(PDF) Development of an Acuity-Based Nurse Staffing System for the Post Anesthesia Care Unit

&

- 9

CENTER

FOR

HEALTHCARE

EDUCATION

C)-N

AND

STUDIES

DEVELOPMENT

OF

AN

ACUITY-BASED

NURSE

STAFFING

SYSTEM

FOR

THE

POST

ANESTHESIA

CARE

UNIT

HR

95-001

November

1994

19941214

044

UNITED

STATES

ARMY

MEDICAL

DEPARTMENT

CENTER

AND

SCHOOL

FORT

SAM

HOUSTON,

TEXAS

78234-6000

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Edu-

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U.S.

Army

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cation

&

Studies,

AMEDDC&S

MCCS-HRC

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Nursing

Consultant

(SGPS-CP-N)

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10.

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PROGRAM

PROJECT

TASK

WORK

UNIT

ELEMENT

NO.

ACCESSION

NO.

11.

TITLE

(Include

Security

Classification)

"Development

of

an

Acuity-Based

Nurse

Staffing

System

for

the

Post

Anesthesia

Care

Unit"

(Unclassified)

12.

PERSONAL

AUTHOR(S)

Zadinsky,

Julie

K.

LTC,

AN

13a.

TYPE

OF

REPORT

13b.

TIME

COVERED

14.

DATE

OF

REPORT

(Year,

Month,Day)

15.

PAGE

COUNT

Final

Report

FROM

1992

TOJ__133

1994

November

142

16.

SUPPLEMENTARY

NOTATION

17.

COSATI

CODES

18.

SUBJECT TERMS

(Continue

on

reverse

if

necessary

and

identify

by

block

number)

FIELD

GROUP

SUB-GROUP

Acuity-Based

Staffing;

Nurse

Staffing

System;

Nursing

Research;

Post

Anesthesia

Care

Unit

(PACU);

Statistical

Process

Control

19,

ABSTRACT

(Continue

on

reverse

if

necessary

and

identify

by

block

number)

The

purposes

of

the study

were

(a)

to

provide

an

acuity-based

method

of

determining

nurse

staffing

needs

for'

post

anesthesia

care

units

(PACUs)

in

the

Army

Medical

Department

(AMEDD)

and

(b)

to

provide

a

method

of

analyzing

PACU

workload

variation.

This

method

of

determining

staffing

needs

and

analyzing

workload

variation

is

known

as

the

Post

Anesthesia

Care

Staffing

System

(PACS).

Data

were

collected

using

(a)

the

PACU

acuity

worksheet

(Carty,

Rea,

&

Jennings,

1991)

at

six

study

sites

for

a

16-week

period,

(b)

records

of

nursing

hours

worked

when

the

acuity

information

was

being

collected,

and

(c)

a

survey

of

PACU

characteristics

sent

to

39

Army

PACUs in

the

U.S.

Army

Health

Services

Command

(HSC,

now

the

U.S.

Army

Medical

Command

or

MEDCOM).

The

strong

positive

correlation

(r >

.90)

between

daily

direct

nursing

care

hours

and

patient

volume

supported

the

development

of

a

general

regression

20.

DISTRIBUTION/AVAILABILITY

OF

ABSTRACT

21.

ABSTRACT

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22a.

NAME

OF

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(Include

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Code)

22c.

OFFICE

SYMBOL

JULIE

K.

ZADINSKY,

LTC,

AN

(210)

221-9333

MCCS-HRC

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Form

1473,

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are

obsolete.

SECURITY

CLASSIFICATION

OF

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PAGE

ii

UNCLASSIFIED

19.

ABSTRACT

(Cont.)

model

that

was

used

to

estimate

daily

direct

nursing

care

hours

from

patient

volume

information.

A

method

of

calculating

daily

nursing

care

hours

(NCHs)

was

developed

based

on

the

combination

of

direct

nursing

care

hours

as

calculated

with

the

regression

model

and

the

PACU

indirect

care

multiplier

(Rea,

Jennings,

Carty,

&

Seipp,

1991).

Data

collected

regarding

daily

NCHs

at

the

six

study

sites

were

analyzed.

A

method

was

developed

to

describe

the

typical

workload

of

a

PACU,

to

analyze

the

workload

variation,

and

to

determine

the

appropriate

number

of

nursing

personnel

to

schedule

on

a

daily

basis.

An

expert

panel

of

PACU

head

nurses

recommended

the

distribution

of

skill

mix

for

the

number

of

nursing

personnel

providing

patient

care.

Following

analysis

of

the

distribution

of

daily

workload

at

the

study

sites,

shift

distribution

guidelines

for

nursing

personnel

were

developed.

An

adjustment

method

was

developed

to

adjust

staff

in

response

to

workload

variation

throughout

the

day,

and

an

audit

method

was

developed

to

check

the

accuracy

of

information

collected

for

the

staffing

system.

Accesion

For

7NTIS

CRA&I

DTIC

T/B

F].2

- -

-LIV&

- - ----------

-

J st h

iii

TABLE

OF

CONTENTS

PAGE

DISCLAIM

ER

..............................................

i

REPORT

DOCUMENTATION

PAGE

(DD

FORM

1473)

.....................

ii

TABLE OF

CONTENTS

........................................

iv

LIST OF

TABLES

..........................................

vii

LIST OF FIGURES

..........................................

viii

LIST

OF

APPENDICES

.........................................

ix

SUM M

ARYY

...............................................

x

ACKNOWLEDGEMENTS

.....................................

xii

INTRODUCTION

............................................

1

Background

...........................................

1

Purpose ..............................................

2

Research

Objectives

......................................

3

Assumptions

...........................................

3

D

efinitions

............................................

4

Nursing

Personnel

Category

by

Study Site

....

28

3

Number

of

Patients

Admitted

By

Clinical

Service

at

Each

Study

Site

During

the

Data

Collection

Period

.................................

29

4

Sample

Characteristics

for

Each

Study

Site

..........................

30

5

Number

and

Percent

of

Patients

Who

Were

Defined

as Outliers

in

Each

Anesthesia

Category

at

Study

Sites

..............................

33

6

Direct

Care

Hours

and Patients

Per

Day

With

Their

Correlations

for

Each

Site.

.

36

7 Name

and

Definition

of

Variables

Used

in

Regression

Models

.............

38

8

Regression

of

Daily

Direct

Care

Hours

on

Patient

Volume

for

5

Regression

M

odels

.............................................

40

9

Number

of

Patients

in

the Fitting

and

Validation

Samples

by

Anesthesia

Type

for

Each

Study

Site

......................................

43

10

Recommendations

for

Professional

and

Paraprofessional

Fixed

Staff

Positions

Based

on

the

Average

of

the

Staffing

Range

.........................

61

vii

LIST

OF

FIGURES

FIGURE

PAGE

1

Average

Direct

Care

Time

Per

Patient

by

Anesthesia

Type

for

Each

Study

Site

....

34

2

Correlation

Between Daily

Patient

Volume

and

Daily

Direct

Care

Hours

for

Study

Site

3 . . . . . .

. . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . .

. . . . . . 37

3

Workload

Profile

for

Study

Site

6

With

Only

1

Data

Point

Outside

the

2

SD

Upper

and

Lower Control

Limits

(UCL

&

LCL)

............................

53

4

Workload

Profile

for

Study

Site

6

With

Workload

Differences Between

Tuesdays

and

Wednesdays

Indicated

....................................

55

5

Staffing

Profile

for

Study

Site

2

With

Workload

Differences Between

Wednesdays

and

Thursdays

Indicated

.....................................

59

6

Average

Number

of

Patients

Per

Hour for

Each

Study

Site

................

67

viii

LIST

OF

APPENDICES

APPENDIX

PAGE

A

O'Donnell

and

Seipp's

Nursing

Workload

Model

.....................

85

B

PACU

Acuity

Worksheet

..................................

87

C

Guidelines

for

Using

the

PACU

Acuity

Worksheet

....................

90

D

PACU

Indirect

Care

Multiplier

Formula ..........................

99

E

PACU

Survey

.........................................

103

F

Method

of

Calculating

Nursing

Care

Hours

Per

Day

...................

120

G

PACU

Fixed

Staff

Definition ................................

122

H

Method

of

Recording

Patient

Volume

Information ...................

126

ix

SUMMNARY

The purposes

of

the

study

were

(a)

to

provide

an acuity-based

method

of

determining

nurse

staffing needs

for

post

anesthesia

care

units (PACUs)

in

the

Army

Medical

Department

(AMEDD)

and

(b)

to

provide a

method

of

analyzing

PACU

workload

variation.

This

method

of

determining

staffing

needs

and

analyzing

workload

variation

is known

as

the

Post

Anesthesia

Care

Staffing System

(PACS).

Data

were

collected

using

(a)

the

PACU

acuity

worksheet

(Carty,

Rea,

&

Jennings,

1991)

at

six

study

sites

for

a

16-week

period,

(b)

records

of

nursing

hours

worked

when

the

acuity

information

was

being collected,

and (c)

a survey

of

PACU

characteristics

sent

to

39

Army

PACUs

in

the

U.S.

Army

Health

Services

Command

(-SC,

now

the

U.S.

Army

Medical

Command

or

MEDCOM). The strong

positive

correlation

(r

>

.90)

between

daily

direct

nursing

care hours

and

patient

volume

supported

the

development

of

a

general

regression

model that

was

used

to

estimate

daily direct nursing

care

hours

from

patient

volume

information.

A

method

of

calculating

daily

nursing

care

hours (NCHs)

was

developed

based

on

the combination

of

direct nursing

care

hours

as

calculated

with

the

regression model

and

the

PACU

indirect

care

multiplier

(Rea,

Jennings,

Carty,

&

Seipp,

1991).

Data

collected

regarding

daily

NCHs

at

the

six

study

sites

were

analyzed.

A

method

was

developed

to

describe

the

typical

workload

of

a

PACU, to

analyze

the

workload

variation,

and

to

determine

the

appropriate

number

of

nursing

personnel

to

schedule

on

a

daily

basis.

An

expert

panel

of

PACU

head

nurses

recommended

the

distribution

of

skill

mix for

the

number

of

nursing

personnel providing

patient

care.

Following

analysis

of

the

x

distribution

of

daily

workload

at

the

study

sites,

shift

distribution

guidelines

for

nursing

personnel

were

developed.

An

adjustment

method

was

developed

to

adjust

staff

in

response

to

workload

variation

throughout

the

day, and

an

audit

method

was

developed

to

check

the

accuracy

of

information

collected

for

the

staffing

system.

xi

ACKNOWLEDGEMENTS

Numerous

individuals

made significant contributions

to

the

successful

completion

of

the

study.

A

special

acknowledgement

goes

to

COL

Bonnie

Jennings,

who

served

as

the

study

director

and also

provided the

researchers with numerous

invaluable

consultations

and

reviews

throughout the

research

process.

Also

of

importance

are

COL

Jayne

O'Donnell

and

COL

Karen

Seipp, who developed

the

research

design used

for

both

the Labor

and

Delivery

and

PACU

nurse

staffing

studies.

They

both

provided

numerous

hours

of

consultation

regarding

the

use

of

this

design

in

the PACU

staffing

study.

COL

Jane

Hudak

attended

to

innumerable

administrative

details

throughout

the

course

of

the

study.

Additionally,

she

participated

as

a

researcher

on

the

study

in

such

areas

as

selecting

the

study sites,

training the

data

collectors,

designing

the

PACU

survey,

and

conducting

the

meeting

of

the

expert panel

for

the

skill

mix

recommendation. Other

major

contributors included

the

study

coordinators

at

the

six

study

sites,

who

were

responsible

for

overseeing

data collection

in

their

PACUs.

The

five

PACU

head

nurses

on

the

skill

mix

panel

contributed

their

time to

make

a

skill

mix

recommendation, and

the

head

nurses at

all

PACUs

in

HSC

(now

the MEDCOM)

contributed

to the

study

by

taking

the

time

to

complete

the

lengthy

PACU

survey.

Nursing personnel

at all

study sites

made

the

study

possible

by

collecting

data with

the

PACU

acuity

worksheet.

An

acknowledgement goes

to

COL

Bonnie Jennings;

LTC John

Carty,

retired;

Dr.

Martha

Bramlett;

and

Dr.

Barbara Wojcik

for

helping

to

ensure

a

scholarly technical

report

by

providing

thoughtful

reviews

of

drafts

of

the report.

Additionally,

Dr.

Barbara

Wojcik provided

statistical

consultation

when

she

was

available

throughout

the

course

of

the

xii

study.

Finally,

numerous

individuals

at

the

U.S.

Army

Health

Care

Studies

and Clinical

Investigation

Activity

(HCSCIA;

now

the

Center

for

Healthcare

Education and

Studies,

U.S.

Army

Medical

Department

Center

&

School)--most

notably

Ms.

Patricia Twist

and

Ms.

Janice

Ware--contributed

their

time

and

talents

to the

preparation

of

the

technical

report.

xiii

INTRODUCTION

Background

The

Army

Medical

Department

(AMEDD)

Study

Board

tasked

the

U.S.

Army

Health

Care

Studies

and

Clinical

Investigation

Activity

(HCSCIA)

at

Fort

Sam

Houston,

Texas,

to

extend

the

Workload

Management

System

for

Nursing

(WMSN)

into

the

post

anesthesia

care

unit

(PACU).

(HCSCIA

is

now

reorganized

under

the

Center

for

Healthcare

Education

and

Studies,

AMEDD

Center

&

School.)

WMSN is

an

acuity-based staffing

system

that

was

developed

by

Army

and

Navy

researchers

in

1985

(Department

of

the

Army,

1990;

Misener,

Frelin,

&

Twist,

1983, 1987;

Sherrod,

1984;

Vail,

Morton,

&

Rieder,

1987).

WMSN

consists

of

both

a

patient

classification

system,

which

quantifies

nursing

workload

based

on

patient

acuity,

and

guidelines

for

allocation

of

nursing

personnel.

WMSN

originally

was

developed

for

seven

inpatient

nursing

areas:

critical

care,

medical-surgical,

obstetrics

and

gynecology,

psychiatry,

newborn nursery,

pediatrics,

and

the

neonatal

intensive

care

unit.

Nursing

workload,

commonly

measured

as

nursing

care

hours

(NCHs),

includes

both

direct

and

indirect

care

time.

Direct

care,

which

provides

the

basis

for

classifying

patients

into

acuity

categories,

is

defined

as

nursing

activities

that

take

place

in

the

presence

of

the

patient

(Kay,

Alcock,

Lawrence,

&

Goodman,

1990;

Rea,

Jennings,

Carty,

&

Seipp,

1991).

Indirect

care

is

defined

as

nursing

activities

that

are

performed

away

from

the

patient

in

support

of

patient

care

or

unit

management

(Kay

et

al.,

1990;

Rea

et

al.,

1991).

As

defined

in

this manner,

indirect

care includes

patient care

activities

such

as

preparing

equipment

for

use,

conducting

patient

care

conferences,

and

transporting patients

to

their

receiving units.

1

Indirect

care

also

includes

other

activities

such

as

documenting

patient care,

preparing

time

schedules,

and

cleaning

the

unit.

Extending

WMSN

into

the PACU

necessitated

the

development

of

a

method

to

quantify

PACU

direct and

indirect

care

time.

Catty,

Rea, and Jennings

(1991)

developed

a

patient

classification

system

(PCS)

that

quantifies

the

time nursing

personnel

spend

providing

direct

patient

care

to

PACU

patients.

This

PCS

is

based

on

25

critical

indicators,

which

were

shown

by

the research

to

best

account

for

a

patient's

direct

care

time.

These critical

indicators

are

specific

nursing

tasks.

Nursing personnel

mark

the

frequency with which

the

tasks

are performed

as

care

is

provided.

This is

a

significant

difference

from

WMSN,

which

requires

that

critical

indicators

be

marked

based

on

nursing

activities

that

are

expected

to

be

completed

over

the

period.

Rea

et

al.

(1991)

used

a

stratified

work

sampling

design

to determine

PACU indirect

care time,

which

was

expressed

as

a

percentage

of

the

total

amount

of

time

nursing

personnel are

available

to

provide

patient

care.

Purpose

The main

purpose

of

the

study

was

to

provide

an

acuity-based

method

of

determining

nurse

staffing needs

for

PACUs

in

the

AMEDD.

This

method

is

based

on

the

of

Army

PACU

direct care

(Catty et

al.,

1991)

and

indirect

care

(Rea

et al.,

1991)

nursing

time

components. A

second

purpose

of

the

study

was

to provide

a

method

of

analyzing

the

variation

in PACU

workload.

The method

of

determining

staffing

needs

and

analyzing

the

workload

variation

that

was

developed

in

this

study

is

known

as

the

Post

Anesthesia

Care

Staffing System

(PACS).

2

PACS

provides

a

method

of

using

workload

patterns

to

develop

a

profile

specifying

the

number

of

nursing

personnel

typically

needed

for

patient

care.

Head

nurses

can use

PACS

to

determine

the

number

and

type

of

nursing

personnel

to

schedule

on

a

daily

basis

and

to

analyze

the

variation

in

their

workload.

Research

Objectives

The

following

are

the

research

objectives,

which represent

the

development

of

the

main

components

of

PACS:

1.

Develop

a

method

by which

the

typical

workload

of

a

PACU

can

be

described

and

the variation

in

the

workload

can

be

analyzed.

2.

Develop

a

method

of

determining

the

number

of

nursing

personnel

to

schedule

on

a

daily

basis.

3.

Develop

guidelines

for

the

skill

mix

and

shift

distribution

of

nursing

personnel.

4.

Develop

guidelines

for

adjusting

the

number

of

staff

during

periods

of

the

day when

there

are

changes

in the

typical

daily

workload

pattern.

5.

Develop

a

method

of

checking

the

accuracy

of

information

collected

for

the

staffing

system.

Assumptions

Nursing

workload

in

this

study

was

conceptualized

as

an

ongoing

process

that

varies

over

time.

However,

nursing

workload

was

measured

at

specific

and

limited

periods

of

time

at

the

six

data

collection

sites

in

this

study.

It

was assumed

that

the

measured

nursing

3

workload

accurately

reflects the

ongoing workload

at

the

data

collection

sites.

Additionally,

it

was assumed

that

clinical

responsibilities

of

nursing

personnel

serving

as

data

collectors

did

not

prohibit

them

from

accurately

completing

the PACU

acuity

worksheets.

Defmitions

The

following

definitions

were

used

for

terms

describing

nursing

personnel,

nursing

workload

measurements,

the

staffing system,

and

patient

categorizations:

Nursing

Personnel

categories

of

nursing

activities:

(a)

patient

care

activities

done

away

from

the

patient--such

as

preparing

equipment

for

use

or

ordering

medications;

(b)

patient

care conferences--such

as change

of

shift

report;

(c)

activities

transportation

on

and

off

the

unit--such

as

transporting

patients

to

nursing

units

and

transporting

patient

specimens

to

the

laboratory;

(d) communication

patient

care

or

unit

management--such

as

discussion

of

a

patient's

condition

with

a

physician;

(e)

documentation

of

patient

care

and clerical

support--such

as

reading

patient

records

and

transcribing

orders;

(f)

activities

done

in

support

of

unit

management--such

as

preparing

the time

schedule

and counselling

staff;

(g)

cleaning

on

the

unit--such

as

cleaning

equipment;

and

(h)

inventorying,

ordering,

and

restocking

supplies

and

linen

(Rea

et

al.,

1991).

Nonproductive

time

was

defined

as

activities

that

do

not

contribute

to

workload

productivity

such

as

"activities

of

a

personal

nature

(breaks,

telephone

calls),

fatigue,

unavoidable

delay,

wait/stand-by,

and meals"

(Rea et

al.,

1991,

p.

47).

The

indirect care

time

component

was

measured

by

an

indirect

care

multiplier

that

was

based

on

both

indirect

care

time

and

nonproductive

time

(Rea

et

al.,

1991).

PACU

nursing

workload

referred

to

all

activities

involved

in

providing

nursing

care

to

PACU

patients.

Nursing

workload

was

measured

by

NCHs

per

day

as

plotted

over

a

3-

month

period

of

time

in

a

workload

profile.

NCHs

per

day

were

calculated

by

mathematically combining

direct

care

time

with

the

indirect

care

time

component.

Nursing Workload

Because

one

of

the

purposes

of

the

study

was

to

provide

PACU

nurses

with

a

method of

analyzing

workload

variation,

it

is

especially

important

to recognize factors

that

affect

direct

8

and

indirect

care

time

and

thus

nursing

workload

in

the

PACU.

These

factors

and

the

ways

in

which

they

interact

with

each

other

affect

the

variability

of

nursing

workload.

O'Donnell

and

Seipp

(1992)

developed

a

nursing

workload

model

that

identifies

patients,

health

care

delivered,

and

the

nursing

care

delivery

process

as

major

factors

that

influence

nursing

workload

(see

Appendix

A).

The

application

of

these

factors

to

PACU

workload

will

be

discussed.

Patients

The

volume

of

PACU

patients

and

the

needs

of

these

patients

vary

throughout

the

day

and

from

day

to

day.

This

variation

has

a

major

impact

on

nursing

workload

(Drain

&

Christoph,

1987).

The

number

and

needs

of

patients

who

arrive

in

the

PACU

throughout

the

day

is

determined

by

the

operating

room

(OR)

caseload,

which

varies

due

to

emergency

cases

and

cancellations.

Moreover,

patient

needs

in

the

PACU

vary

in

unpredictable

ways

because

of

postoperative

complications

(Luczun,

1984).

Additionally,

the

number

and

needs

of

patients

arriving

in

the

PACU

may

vary

throughout

the

year

for

reasons

such

as

the timing

of

surgical

residencies

or

school

vacation.

Health

Care

Delivered

Health

care

delivered

by

nursing

and medical

personnel

as

well

as

health-related

disciplines

at

an

MTF

affect

the

type

of

patients

being

seen

at

a

facility

and

thus

their

nursing

care

requirements.

For

example,

the

health

care

delivered

and

thus

the

patient

complexity

at

a

regional

multi-trauma

center

is

very

different

from

the

patient

complexity

at

a

small

community

hospital.

9

Nursing

Care

Delivery

Process

The

staff

delivering

care,

philosophy

of

care,

facility

capacity,

equipment,

and

non-

nursing

support

are

factors

the

nursing

care delivery

process

that

have

been

identified

as

affecting

nursing

workload

(O'Donnell

&

Seipp,

1992).

The

number,

skill

mix,

and

experience

of

PACU

nursing

staff

as

well

as

the

number,

specialty

areas,

and

practice

patterns

of

the

surgical

staff

impact

on

the

care

delivery process.

For

instance,

the

immediate

availability

of

an

experienced

anesthesiologist

or

nurse

anesthetist

in

the

PACU

to

work

with

nursing

personnel

affects

how

nursing

care

is delivered. Differences

in

philosophy

of

care

are

reflected

in

unit

policies

as

well

as

in

the

range

of

nursing

care

provided

by

PACU

nursing

staff

(Andrews,

1987).

For

example,

the

workload varies

according

to

the

extent to

which

nursing personnel

are

involved

in

tasks

such

as

providing

preoperative

teaching

and

preparing

the

patient

for

surgery

(Fraulini,

1987).

Additionally,

facility

capacity

factors

affecting

workload

include

the

number

of

operating

rooms

and

PACU

beds,

the

hours

of

operation

of

the

PACU

and OR,

and

the

existence

of

a

call

system designed

for

nursing

personnel

to

care

for

PACU

patients

after

normal

duty

hours

(Luczun,

1984;

Spadaccia,

1990).

The

accessibility

of

equipment

frequently used

in

patient

care

as

well

as

the

availability

of

the

latest

physiological

monitoring

systems

and

automated

information

systems

at

the

patient's

bedside

influence

the

care

process

(Andrews,

1987;

Luczun,

1984).

Also,

non-nursing

services

that

nursing

personnel

must

perform

greatly

impact

on

how

nursing

care

is

delivered

(Andrews,

1987).

This

includes

services

that

could

be provided

by respiratory

therapists,

laboratory

technicians,

pharmacists,

EKG

technicians,

supply

technicians,

and

housekeeping

personnel.

10

Finally,

two

factors

affecting

PACU

workload

that

were

not

specifically addressed

in

the

workload

model

(O'Donnell

&

Seipp,

1992)

are

the

physical

design

of

the

unit

and

the

unit's

location

in relation

to

other

patient

care

areas (Andrews,

1987).

For

example,

the

visibility

of

patients

from

a

centralized

location

in the

PACU

and

the

amount

of

time

it

takes

to transport

a

patient

to

the

surgical wards

affect

how

care

is

delivered.

Review

of

Literature

There

are

very

few

PACU

staff'mg

systems

reported

in

the

literature.

Unpredictable

patient

flow

and

great

fluctuations

in

a

patient's

acuity

during

a

short

length

of

stay

in

the

PACU

were

cited

as

major

obstacles

to

developing

a staffing system

for

this

area

of

practice

(Drain

&

Christoph,

1987).

The

review

of

literature

includes a

brief

examination

of

PACU

staffing

systems

that

are

being

used

in

non-military institutions

and

a

discussion

of

their

limitations.

PACU

Staffing Systems

Most

staffing

systems

are

based

on

a

patient

classification system

(PCS), which

refers

to

"the

identification

and

classification

of

patients

into

care

groups

or

categories,

and

to the

quantification

of

these

categories

as

a

measure

of

the

nursing

effort required"

(Giovannetti,

1979,

p.

4).

Two

common

types

of

PCSs

are

prototype

and

factor

evaluation

systems.

Giovannetti

(1979)

explained

that

a

prototype

system

"describes

the

characteristics

of

patients

typical

to

each

category"

(p.

5);

and

in

a

factor

evaluation

system,

"a number

of

critical

indicators

or

descriptors

of

direct

care requirements

are

separately

rated

and

then

combined

11

to

designate

a

patient's

category"

(p.

5).

Prototype

PCSs

generally

are considered

more

subjective

than factor

evaluation

systems.

At

the

time

of

this

literature

review,

most

PACU

nurses

did

not

use a refined

staffing

system

on

a

routine

basis

to

assess

their

staffing needs.

However,

several

researchers

reported

on

the

development

of

prototype

PCSs

that

were used to

classify

patients

into four

or

six

categories based

on

their

need

for

minimal

to

intensive

nursing care

(Allen,

1990;

Beach,

1985;

Bodenstein

&

DeLozier,

1983;

Shirk

&

Marion,

1986).

These

PCSs

had

guidelines

for

the

nurse-to-patient

ratio

that

should

be

used to

estimate

nursing

care

requirements

for

patients

in

each

category. Each

PCS

organized

and

described

its

patient

categories

differently

and

was

designed

for

use

in

a

specific

PACU.

Other

nurses

reported

on

more

extensive

staffing

systems

that

were

being

developed.

For

example,

Strack

and

Jones

(1983)

reported on

the

development

of

a

staffing

system

based

on a prototype

PCS

that

used

three

levels

of

care

to

classify

patients

and

had

recommended

nurse-to-patient

ratios

that

were

based

on these

levels

of

care.

Management

engineers calculated

the

required

number

of

NCHs

for

the

unit

by

combining

information

obtained

from the

PCS

with

a

fixed quantity

of

hours

representing

indirect

care

time.

They

compared

the required NCHs

per

month

with

the

number

of

hours worked

to

obtain

a

productivity

rating

percentage. Nurses

used the

productivity

rating

to

monitor

changes

made

in

the

unit,

such

as

changes

in the

times

when

staff

were

scheduled

to

arrive

for

work

throughout

the

day.

Smith,

Mackey, and

Markham

(1985)

developed

a

productivity

monitoring

system

that

identified

staffing

requirements

from historical

case load data.

PACU

staff

and management

12

engineers

developed

a

prototype

PCS

by

dividing

patients

into

2

categories based

on

their

required

nursing

care. Data

obtained

from

interviews

and

from

2 weeks

of

observing

PACU

work

were

used

to

compute

patient

care

hours

for

each

patient

category.

One

use

of

this

system

was

that

historical

patient

data

regarding

the

number

of

patients

in

the PACU

throughout the

day

was

combined

with

patient

care

hour

information

to construct

case

load

profile

charts.

The

PACU

head

nurse used

the

case

load

profile

charts

to

match

staffing with

case

load trends.

Two staffing

systems

were

developed

for

pediatric

PACU

patients

(Kay

et

al.,

1990;

Miller,

1986).

The

system

developed

by

Kay

et

al.

(1990)

is

an

adaptation

of

Miller's

(1986)

system.

Both

of

these

staffing

systems

were

based

on

a

factor

evaluation

PCS

that

had

6

classification

categories.

Each

of

the

42

critical

indicators

was

assigned

a

weighted

numerical

value

according

to

the

complexity

of

the

task, and

patients

were

categorized

according

to

the number

of

points

they received

for

the

indicators.

Each classification

category

was

assigned

a

fixed

number

of

NCHs.

Staffing

requirements were

calculated

monthly

using

the

number

of

patients

in

each

category

multiplied by

the assigned

number

of

NCIIs

for

the

category.

Nurses used

these

systems

to

compare

the total

hours

needed

for

patient

care

with

the total number

of

available

nursing

hours.

They

based

their

requests

for

more staff

and

their

staffing

budget on this

information.

Limitations

of

Existing

Staffing

Systems

Two

major

limitations

of

existing

PACU

staffing

systems

were

identified.

First, the

manner

in

which

indirect

care

time

is

accounted

for

in

staffing

systems needs

to

be

refined.

Although nursing

workload

is

comprised

of

both

direct

and

indirect

care

time,

not

all

13

researchers

fully

described

the indirect

care

time

component

of

their

staffing

systems.

For

example,

Shirk

and

Marion

(1986)

allowed

a

fixed

amount

of

indirect care

time

for

their

patient

categories,

and

Strack

and

Jones

(1983)

provided

fixed

monthly

credits

for

indirect

care.

However,

these

researchers

did

not

define

indirect

care

time

or

describe

how

it

was

derived.

Kay

et

al.

(1990)

mentioned

their

self-report

method

of

deriving

indirect

care

time,

but

they

noted

that

this

method

provided

inaccurate

information.

Second, many

of

the

PCSs

suffered

from

a

lack

of

rigorous

development.

Nurses

who

reported on

the

development

of

a

PCS

generally

did

not

address

the

reliability

or

validity

of

the

instrument,

and

most

did

not report

a

method

of

determining

whether

staff

members

consistently

classified

patients

in

the

same

way

when using

the

PCS.

Furthermore,

Kay et

al.

(1990)

reported

that,

in

their

PCS,

some

patients

were

classified

into

a higher

category

than

warranted

due

to the

length

of

stay

indicator.

Other

nurses

used

patient

length

of

stay

in

various

ways

in

their

PCS,

but

its use

deserves

further

investigation

because

a patient's

length

of

stay

is

often

determined

by

such

factors

as

the

availability

of

a

staff

member

to

transport

a

patient to

a

unit

or

the

availability

of

a

bed

on

the

receiving

unit.

In

summary,

the

literature

review

demonstrated

a

lack

of

well-developed

PACU

staffing

systems.

Furthermore,

no

staffing

system

was

found

that

could

be

more

fully

developed

for

use

in

PACUs

within

HSC.

Therefore,

work

proceeded

to

merge

the

prior

studies

of

direct

and

indirect

nursing

care

for

PACU

patients

(Carty

et

al.,

1991;

Rea et

al.,

1991)

into

a

PACU

staffing system.

14

METHODOLOGY

In

the

methodology

section,

selection

of

the data

collection

sites

and

the

study

sample

are

discussed.

Additionally,

the measurement

instruments

and

formula

used

in

the

study

are

described.

The

study

procedures--including

subject

acquisition,

protection

of

human

rights,

and

data

collection--are

explained.

Finally,

methods used

to

manage

the

data

and

analyze

the

research

objectives

are

briefly reviewed.

Study

Sites

and

Sample

Selection

of

Study

Sites

PACUs

were

considered

for

selection

as study

sites

if

they met

five

inclusion

criteria.

First,

a

PACU

had

to

be

a

stand-alone

unit.

That

is,

a

PACU

could

not

coexist

in the

same

location

with

another

unit,

such

as

Same

Day

Surgery

(SDS).

Second,

a PACU

had

to

have

its

own

separate

staffing.

For

example,

the PACU

nursing

staff

could

not

be

responsible

for

providing

patient

care

in

both

the

PACU

and

the

Surgical

Intensive

Care

Unit

(SICU).

Third,

a

PACU

could

not

be

undergoing

any changes

in

its

physical

environment

that

would

influence

its

workload

during

the

planned

period

of

data

collection.

Therefore,

one

PACU

in

a

medical

treatment

facility

(MTF)

that

was

being

moved

to

a

new

physical

location

and

another

PACU

in an MTF

that

was

undergoing

renovation

in the

peri-operative

area

were

not

considered

for

selection

as

study

sites.

Fourth,

a

PACU

could

not

be

located

in

an

MTF

that

was

in

the

process

of

being

closed.

Finally,

a

PACU

had

to

be located

within the

U.S.

Army

Health

Services

Command

(HSC)

in order to

be

considered

for

selection

as

a

data

collection

site. (HSC was

15

reorganized

as

the

U.S.

Army

Medical

Command

or

MEDCOM

in

1994.)

The

workload

at

several

MTFs

outside

of

HSC

was

atypical

at

the

time

of

the

study

because

of

the rapid

reduction

in

military

forces

that

was

occurring

overseas.

Moreover,

there

was

no

reason

to

believe

that

a

difference

existed

between

nursing

care

provided

to patients

in

Army

PACUs

within

and outside

of

HSC.

Data

collection

sites

were

selected

from PACUs

meeting

the initial inclusion

criteria

based on

two

measures

of

workload--patient

volume

and

patient

complexity

(see

Table

1).

Patient

volume

was

measured by

average quarterly minutes

of

service

data

available

for

FY92.

Minutes

of

service

refers

to the

period

of

time

a patient

remains

in the

PACU.

Time

is

counted

from

admission

to

discharge,

plus

10

minutes

for

personnel

to

transport

a

patient

to

a

receiving

unit

and

return

to

the

PACU.

Average

quarterly

minutes

of

service

reflects

more

than

the

average

quarterly

number

of

PACU

patients. However,

workload

data

were

kept

by

minutes

of

service

rather than

by

patient

volume at

the time

of

the

study.

Therefore,

minutes

of

service

was

the

only

indicator

of

patient

volume

readily

available

for

all

PACUs

within

HSC. The

tri-service

PACU

workload

strata

cutpoints

at

quarterly

averages

of

65,000

and

125,000

minutes

of

service

were used

to categorize

PACUs

into

low,

medium,

and

high

workload strata

(Rea

et

al.,

1991).

Patient

complexity

was

measured

by

the

surgical

relative

case

mix index (RCMI)

data

that

were

available

for

FY92

from

the

Patient

Administration

Systems

and Biostatistics

Activity

(PASBA).

The

surgical

RCMI

refers to

an

MTF's

standardized

workload

credit

for

surgical

procedures

based

on

diagnosis

(DRGs), given

that

the

workload

credit

16

Table

1

Characteristics

of

Study

Sites

Average

Quarterly

Surgical

Relative

Workload

Minutes

Case

Mix

Index

Study

Site

Strata

of

Servicea

(RCID

a

lb

Low

62,323

1.72

2b

Low

62,323

1.72

3

Medium

104,130

.83

4

High

177,322

1.35

5

Low

51,333

.82

6

High

267,051

1.67

Notes.

a

Average

Quarterly

Minutes

of

Service

and

Surgical

RCMI

are

based

on

data

from

the

first

6

months

of

FY92.

b

Sites

1

and

2

were

separate

PACUs

at

the

same

MTF.

Because

their

monthly

patient volume

was

almost

identical,

half

of

the

MTF's

Average

Quarterly

Minutes

of

Service

was reported

for

both

PACUs.

Also,

no

data

were

available

that

could

be

used

to

calculate

a Surgical

RCMI

separately

for

both

PACUs

in

this

MTF.

Therefore,

the

MTF's

Surgical

RCMI

was

reported

for

both

PACUs.

17

for

an

average

disposition

across

all

Department

of

Defense

facilities

is

1.00

(Lichtig,

1986;

Moon

&

Jensen,

1990).

An

MTF's

surgical

RCMI

reflects

more

than

the

complexity

of

PACU

patients. However,

it

was

the

best

indicator

of

patient

complexity

available

for

all

PACUs

within

HSC,

and

it

was

an appropriate

indicator

to

use

for

comparing

PACUs

with

each other.

The

variation

in

surgical

RCMI

among the

study sites

is

shown

in

Table

1.

Six

data

collection

sites

that

were

representative

of

all

three

workload strata

and

that

varied

according

to

patient

complexity

were

selected.

Study

site

5

was clearly

in

the

low

workload

stratum,

site

3

was

in

the

high

end

of

the medium

stratum,

and sites

4

and

6

represented

the

low

and

high

ends

of

the

high

stratum. Study

sites

1

and

2

were

separate

PACUs

at

the same

MTF,

and

both

were

at

the

high

extreme

of

the

low

workload

stratum.

Because there

was very

little

difference

between

the

average quarterly

minutes

of

service

at

study

sites

1

and

2

and at PACUs

categorized

in

the

low

extreme

of

the medium

stratum,

sites

1

and

2

were

considered representative

of

PACUs

in

the

high

extreme

of

the

low

workload

stratum

as

well

as

PACUs

in

the

low

extreme

of

the

medium

workload

stratum.

As

would be

expected,

the

two

study

sites

with

a

surgical

RCMI

less

than

one

were

located

in

medical

department

activities

(MEDDACs)

and

were

categorized

in

the

low

and medium

workload

strata.

The four

sites

with

a

surgical

RCMI

greater

than

one

were

located

in

U.S.

Army

Medical Centers

(MEDCENs)

and

were

categorized

in

the high

extreme

of

the

low

workload

stratum

and

in

the high

workload

stratum.

Selection

of

Subjects

The

PACU

patient classification

system

used

in this

study

was

designed

for

use

during

post

anesthesia

Phase

I,

when

nursing

care

focuses

on

"providing

a

transition from

a

totally

18

anesthetized

state

to

one

requiring

less acute

interventions"

(American

Society

of

Post

Anesthesia

Nurses,

1992,

p.

4).

Therefore,

all

patients

who received

Phase

I

post-anesthesia

care

from

PACU nursing

staff

during

the

data

collection period

at

the

study

sites

were

eligible

for

inclusion

in

the

sample. These

patients

were

admitted

to

the

PACU

from

the operating

room,

a clinic,

or

the

same

day

surgery

(SDS)

unit,

and

they

were

discharged from

the

PACU

to

another

unit.

It was planned

that

acuity

data

would

be

obtained

on

a

daily basis

for

a

16-

week period

so

that

workload

and

staffing profiles could

be

developed

for each

site

based

on

3-4

months

of

accurate acuity data.

The

number

of

patients

who could

be

included

in

the

sample

from

the

selected data

collection sites

during

this

period

of

time

was

judged

to

be

adequate

for

data

analysis.

Instrumentation

The

PACU patient

classification

system

(Carty et

al.,

1991)

and

the

PACU

indirect

care

formula (Rea

et

al.,

1991)

served

as

the

basis for

the

measurement

of

NCHs.

Data from

a

PACU

survey also were used

in

the

study.

A

brief

explanation will

be

given

for

these

instruments

and

formula.

PACU Patient Classification

System

The

PACU

patient

classification

system

(PCS)

is

a

factor

evaluative

PCS

that

accounts

for

direct

care

time

(Carty

et

al., 1991).

Direct

care

time

was

defined

as

nursing activities

that

take

place

in

the

presence

of

the

patient.

To

develop

the

PCS,

a

panel

of

clinical

nursing

experts identified

62

direct care

nursing

tasks

that

reflected

the full range

of

PACU

nursing.

The

average time

that

it

took

to

complete

each

of

the

62

direct

care

tasks

was

established

by

19

actual

stopwatch timed

measurements.

A

pilot

test

of

the data

collection instrument

containing

these

62

tasks

demonstrated

a

strong

reliability

(r

=

.93)

and

validity

(r

=

.82).

After

determination

of

the

instrument's reliability

and

validity,

a

study

of

the

62-item

instrument

was

conducted

at

a

sample

of

six

U.S.

Army

medical

treatment

facilities

(MTFs),

and

regression

analysis

identified

25

indicators

that

made

up

the

best parsimonious

set

of

direct

care

predictor

tasks.

In

its final

form,

the

PACU

PCS

consists

of

an

acuity worksheet

containing

these

25

critical

indicators

or

nursing

tasks

(see

Appendix

B).

Pilot testing

of the

final

instrument

demonstrated

a

strong

reliability

(.

=

.98)

as

measured

by comparing

the

direct

care

time

obtained for

a

patient

using

the

final

25-task

instrument

with the

direct

care

time

obtained

using

the

original

62-task

instrument.

Pilot

testing

also

demonstrated

concurrent validity

(r

=

.90) as

measured

by

comparing

the

time

obtained

from the

25-task

instrument

with

the original 62-task

instrument stopwatch time.

Extensive

written

guidelines

are

available

to

ensure

proper

use

of

the acuity worksheet

(see

Appendix

C).

A

separate

acuity

worksheet

is

used

for

each patient to

document

the

frequency

with

which

the

25

nursing

tasks

are

performed.

The worksheet

is

designed

to be

completed

by

nursing

personnel

while patient

care

is

being provided.

After

the

patient

is

discharged

from

the

PACU,

the

frequency

that

each

nursing

task

was

performed

is

totalled.

The

frequencies

are

used

in

the

PCS

regression equation

to

estimate

the total

direct

care

time

for

each

patient.

Indirect

Care

Multiplier

Formula

Rea

et

al.

(1991)

conducted

a

study

to determine

the

PACU

indirect

care

time

component

(which

includes

indirect

care

time

and

nonproductive

time)

expressed

as

a

20

percentage

of

the

total

amount

of

available

time.

As

previously

explained,

available

time

includes

time

associated

with

productive

time

(direct

and

indirect

care

time)

and

nonproductive

time. Rea

et

al.

(1991)

used

a

stratified

work

sampling design

for

their

study

of

indirect

care

and

collected

data

at

a sample

of

PACUs

in

HSC.

Their

research

determined

that

when

using

available

time

and

eliminating

three

fixed

positions

(head

nurse,

wardmaster,

and

ward

clerk),

the

combined

indirect

care

and

nonproductive

proportion

of

76.8%

should

be

used

to

develop

the

PACU

staffing

standard.

Perdue

(1990)

provided

the

following

indirect

care

multiplier

formula

that

should

be

used

together with

the

findings

of

Rea

et al.

(1991):

1 + (%

indirect

/ 1

- %

indirect).

This

formula

has

been

shown

to

accurately

demonstrate

the

relationship between

the

direct

and

indirect

components

of

available

staff time

(see

Appendix

D).

When

this formula was

applied

to

the

findings

of

Rea

et

al.

(1991),

an

indirect

care

multiplier

(ICM)

of

4.31

was

obtained. This

was

the

ICM

that

was

used

in

the

study

and therefore

should

be

used

with

all

applications

of

the

staffing

system

being

developed.

PACU

Survey

The

PACU

survey

is

a

63-item

questionnaire

developed

by

the

researchers

for

the

portion

of

the

study

concerned

with

evaluating

factors

that

impact

on

PACU

workload.

The

questions

were

developed

in

accordance

with the conceptualization

of

nursing

workload used

in

the

study.

A

copy

of

the

survey,

which

was

designed

to

be completed

by

the

head

nurse

of

each

PACU

in

HSC,

can

be

found

in

Appendix

E.

Originally

it

was planned

that

workload

information

from

the

survey

would

be

used

to

group

or

cluster

PACUs

according

to

their

workload.

However,

because

of

the

results

of

the

regression

analysis,

it was

decided

that

21

further

study

with PACU

clusters

would

not

be conducted.

Workload

information

from

the

survey

was

used

for

other

parts

of

the

study,

such

as

the development

of

shift

distribution

and

staffing

adjustment

guidelines.

Procedures

Subject

Acquisition

Permission

to

collect

data

at

the

six study

sites

was

obtained

in

coordination

with

the

Chief,

Nursing

Division,

HSC.

The

chief

nurse

at

each

of

the

data

collection

sites

then

appointed

a

study coordinator

for the

site.

At

all

sites,

the study coordinator

was

the

PACU

head

nurse.

The

researchers

worked closely

with

the

study

coordinators

throughout

the

data

collection process

to

ensure

the

accurate

and

reliable

collection

of

data.

Protection

of

Human

Rights

The

staff

of

the

Clinical

Investigation

Division,

U.S.

Army

Health

Care

Studies

and

Clinical

Investigation Activity,

Fort

Sam

Houston,

Texas, reviewed

the

study

proposal.

They

concluded

that

the

study

was

exempt

from Army

Regulation

40-38,

the

Clinical

Investigation

Program. Furthermore,

it

was

noted that

patient identifiers

were

preserved

on data

collection

forms

only

as

long

as

needed

for

data

analysis

and

that

access

to

these

forms was

strictly

limited to

the

researchers.

Data Collection

Data

were

collected

using

(a)

the PACU acuity

worksheet

at

six

Army

PACUs,

(b)

the

records

of

nursing hours

worked

when

the acuity

information

was

being

collected,

and

(c)

a survey

of

PACU

characteristics

sent

to all

39

PACUs

in

HSC.

The

acuity

worksheet

22

and

time

schedule

data

were collected

for a

16-week

period

from

June

8

through

October

23,

1992.

Surveys were

mailed

to

PACU

head

nurses

in

July

1992.

Direct

Care

Time

Data

Just

prior

to

the

initiation

of

data collection

at

a

site,

training

was

provided for

nursing

personnel

who

would

serve as

data collectors.

To

allow

for individualized

and

intensive

instruction,

personnel

were divided

into

groups

of

3

to

4

individuals

for

a

2-hour

training

session.

The

training

sessions

at

the

study

sites were

identical

in

structure

and

content.

They

were

based

on

the

written guidelines

for

use

of

the

acuity

worksheet,

a

copy

of

which was

given

to

each

data

collector

(see

Appendix

C).

Trainees

practiced using

the

acuity worksheet

with

three

written

case

studies

containing examples

of

the

nursing

tasks

to

be

rated.

The

case

studies

were

corrected

and discussed

during

the

training

session.

To

assess

the

extent

to

which

trainees could

apply

the written

guidelines

to

use

of

the

acuity

worksheet,

criterion-related agreement

between

the

trainee's

score

and the

"correct"

score was assessed

with

a

second

set

of

three

written

case

studies

(Castorr

et

al.,

1990).

Trainees

who

did

not

achieve

at

least

95%

agreement

with

the

correct

rating

of

each

acuity

worksheet

were

evaluated

with

a

different set

of

case

studies after

receiving

individualized

instruction

in

their

problem

areas.

The

passing

percentage

of

agreement was

set

at

a

high

level

(95%)

to

maximize

the

opportunity

to

discover

and clarify

all

portions

of

the rating

guidelines

that

were

not

clear

to

the

trainees.

Only

9

(15%)

of

the

62

trainees required

a

second evaluation.

These

9

personnel,

all

of

whom were

paraprofessionals,

achieved

at

least

95%

agreement

on

subsequent

testings.

23

Nursing

personnel

who

started

working

at

the

study

sites

after

data collection

had

begun

were

trained

in

the data

collection

procedure

by

the

study

coordinator.

Also,

at approximately

monthly

intervals,

the

study

coordinators

independently

rated

a

patient on

an acuity worksheet

with

each

one

of

the

data

collectors.

When

the

data

collector

did

not

reach

95%

agreement

with

the

study

coordinator,

the

areas

of

disagreement

were

discussed,

and

they independently

rated

another

patient

until

this

level

of

percentage

agreement

was

attained.

The

study

coordinator

at each

site

supervised

the collection

of

data

from

the

acuity

worksheets

on

all patients

meeting

the

sample

inclusion

criteria

for

the

16-week

period

of

data

collection.

They

mailed

their

worksheets

to

the

researchers

every

1

to

2

weeks

throughout

the

data

collection

period.

The

researchers

phoned

the

study

coordinators

with

any

questions

they

had regarding

the

acuity worksheet

data.

Time

Schedule

and

Survey

Data

Study

coordinators

mailed

their

corrected

time

schedules

to

the

researchers

every

1

to

2

weeks

throughout

the

16-week

data

collection

period.

Information

on

the

time

schedules

included

the

total

number

of

hours

worked

each

day

for

the

head

nurse,

wardmaster,

ward

clerk,

professional

nursing

staff,

paraprofessional

nursing

staff,

professional

nursing

students,

and

paraprofessional

nursing

students.

The

PACU

survey

was

mailed

to

head

nurses

of

the

39

PACUs

in

HSC

during

July

1992.

Questions

from

head

nurses

regarding

the

completion

of

the

survey

were

answered

by

phone.

There

was a

100%

response

rate.

24

Data

Analysis

Management

of

Data

When the acuity

worksheet

and

time

schedule data

were

received

at

HCSCIA, they were

screened

for

completeness

and

accuracy

of

patient information.

Study

coordinators

were

consulted

regarding

missing,

illegible,

or

illogical

information.

In

most

cases,

the

coordinators

were

able

to

retrieve

the missing

or

illegible

information

from patient

records.

Also,

they

often

were

able

to

explain or

correct

seemingly

illogical

information.

When

a

patient's

acuity

worksheet

remained

illogical

from

a

clinical

perspective

after

consulting

with

the

study

coordinator,

that

patient was

excluded

from

the

study.

As

an additional

assurance

of

the

accuracy

of

the acuity worksheet data,

acuity data were

entered

into a

data

set

by

trained

data

entry

personnel

using

a

double

key

entry

process.

According

to

this

process,

each

data

point

was

verified

by

two

data

entry personnel

before

being

entered

in

the

data

set.

After data

had

been

entered,

the

entire

data

set

was

subjected

to

computer programs

that

used

logical

expressions making

various

assertions

about

the

data.

These

assertions

were

tested

against

each

record,

and a

report

of

the

violations

of

these

expressions

was generated.

Once

again,

any

patient

whose acuity worksheet

was

illogical

from

a

clinical

perspective

was

excluded

from

the

study.

Analysis

of

Objectives

As previously

stated, five

research

objectives

guided

the

development

of

the

staffing

system.

Preliminary

analyses

demonstrated

a strong

positive

correlation

(r

>

.90)

between

daily

patient

volume

and

direct

care

time.

Thus,

regression

analysis

was performed

to

select

a

model

that

would predict

daily

direct care

hours

from

patient volume

information.

The

25

development

of

the

workload

and

staffing

profiles

was

based

on

the

Shewhart

method

of

variance

analysis.

The

shift

distribution

and

staffing

adjustment

guidelines

were

developed

based

on

an

analysis

of

workload

variation

throughout

the

day.

A

panel

of

PACU

head

nurses

was

convened

to

make

skill

mix

recommendations.

Finally,

the

researchers

developed

an

audit

method

that

could

be

used

on

a

continuing

basis

by

PACU

nursing

personnel.

26

FINDINGS

Presentation

of

the

findings

consists

of

a

description

of

sample characteristics,

preliminary

analyses,

analyses

conducted

for

each

research

objective, and additional

analyses.

Statistical

process

control

software (Shewhart,

1992)

was

used

for

development

of

the

workload

profiles,

and

SAS

version

6.07

was

used

for

all

other

data

analyses.

Sample

Characteristics

The

study

sample

consisted

of

7,034

PACU

patients

at

six

study

sites.

Twenty

percent

of

the

entire

sample

received only local

anesthesia

and/or

sedation,

20%

received

regional

and/or

spinal

anesthesia

with

or

without

local

anesthesia

or

sedation, and

60%

received

general

anesthesia

with

or

without another type

of

anesthesia

or

sedation.

The

distribution

of

anesthesia

type

for

each

study

site

is

shown

in

Table

2.

The

sample

represents

patients who

were

cared

for

by

physicians

from a

wide

range

of

clinical

services

as

shown

in

Table

3.

Other

demographic

characteristics

of

the

sample--including

age,

duty

status,

gender,

and

American

Society

of

Anesthesiologists

(ASA)

class--are

presented

in

Table

4. The

majority

of

patients

in

the

sample

were

18

to

59

years

of

age

and were

active

duty soldiers

or

family

members.

There

were almost

an

equal

number

of

male

and

female

patients

in

the

sample.

Also,

most

patients

were

categorized

in

ASA

Class

1

or

2,

indicating

that

they

had

no

organic,

physiologic,

biochemical,

or

psychiatric disturbance

or

had

only

a mild

or

moderate

systemic

disturbance

(Stoelting

&

Miller,

1989).

27

Table

2

Number

and

Percent

of

Patients

in

Each Anesthesia

Category

by Study

Site

Anesthesia Categories'

Siteb

Local

Regional

General

Total

1

145

(17%)

240

(27%)

487

(56%)

872

2

71

(8%)

168

(19%)

631

(73%)

870

3

180

(14%)

257

(20%)

859

(66%)

1296

4

292

(24%)

242

(19%)

698

(57%)

1232

5

98

(13%)

190

(26%)

454

(61%)

742

6

655

(32%)

283

(14%)

1084

(54%)

2022

Total

1441

(20%)

1380

(20%)

4213

(60%)

7034

Notes.

a

Local

Anesthesia refers to patients

who

received

only local

anesthesia and/or

sedation. Regional

Anesthesia

refers

to

patients who received regional

and/or

spinal

anesthesia

with

or

without

local anesthesia

or

sedation.

General

Anesthesia

refers

to

patients

who

received

general

anesthesia

with

or

without

another type

of

anesthesia

or

sedation.

b

Sites

1,

2,

4,

and

6

are U.S.

Army

Medical

Centers

(MEDCENs),

while

sites

3

and

5

are

U.S.

Army medical department activities

(MEDDACs).

28

Table

3

Number

of

Patients

Admitted

By

Clinical

Service

at

Each

Study

Site

During

the

Data

Collection

Period

Study

Site

Clinical

Service

1

2

3

4

5

6

Total

Cardiology

4

0

15

0

72

91

Cardiovascular/Thoracic

Surgery

3

12

0

17

0

35

67

General

Surgery

370

13

331

290

185

323

1512

Gynecology

220

0

269

90

129

162

870

Nephrology

1

2

0

3

0

4

10

Neurosurgery

0

57

0

53

0

93

203

Obstetrics

47

0

50

31

40

68

236

Oncology

8

0

5

0

4

17

Ophthalmology

0

50

28

36

18

102

234

Oral

Surgery

0

102

38

67

53

13

273

Organ

Transplant

0

46

Orthopedics

5

323

251

331

220

305

1435

Otorhinolaryngology

0

183

222

98

58

188

749

Pediatrics

40

52

5

1

2

92

192

Peripheral

Vascular

Surgery

8

0

46

0

59

113

Plastic

Surgery

1

75

0

58

0

102

236

Urology

162

1

102

90

37

347

739

Other

3

0

1

0

7

11

Total

872

870

1296

1232

742

2022

7034

29

Table

4

Sample

Characteristics

for

Each

Study

Site

Study

Site

Characteristics

1

2

3

4

5

6

Total

Age

<

2

24

34

56

15

9

65

203

2-11

48

117

174

53

68

140

600

12-17

24

72

39

29

34

49

247

18-39

327

340

750

519

429

682

3047

40-59

201

167

202

366

144

538

1618

60-79

227

128

73

245

55

512

1240

80-95

21

12

2

5

3

36

79

ASA

Classa

1

278

412

675

419

309

617

2710

2

370

328

577

548

403

962

3188

3

207

118

41

198

27

304

895

4

13

12

2

26

1

15

69

Duty

Statusb

Active

Duty

174

268

423

447

281

556

2149

Retired

176

119

74

271

64

498

1202

Family

Member

506

469

781

508

396

936

3596

Civilian

Emergency

8

11

0

1

2

22

Gender

Female

538

404

697

548

388

917

3492

Male

334

466

599

684

354

1105

3542

Note.

a

172

records

did not

indicate

an

American

Society

of

Anesthesiologists

(ASA)

Class.

b

65

records

did

not

indicate

Duty

Status.

30

Preliminary

Analyses

Preliminary

analyses

include

a

description

of

outliers

for

the variable,

direct

care time

per

patient,

and

an

examination

of

the

stability

of

the

measurement

of

this variable

throughout the

data collection

period at

each study site.

Also,

the

relationship

of

the

variable, direct

care

time

per

patient,

to

the

type

of

anesthesia

and to

patient

volume

per

day

are

described.

Finally, the

development

of

a

regression model to

predict

daily

direct

care

hours

from

patient

volume is

explained.

Direct

Care

Time

Outliers

An

outlier

was

defined

as

"an

observation

(or

subset

of

observations)

which

appears

to

be

inconsistent

with

the remainder

of

that

set

of

data"

(Barnett

&

Lewis,

1978,

p.

4).

Observations

3

standard deviations

(.Ds)

from

the

mean

of

the

variable, direct care

time

per

patient,

were

considered

outliers.

These

observations

were

inconsistent

with the

rest

of

the

data

set

in

that,

for

the

same

procedure,

acuity

worksheets

in

the

outlier

group

either

had

more

indicators

marked

or

had

the

same

indicators

marked more frequently.

Outliers were

calculated

separately

for

the

subsample

of

patients who

had

general

or

regional

anesthesia

and

the

subsample

who had

local

anesthesia

because

in

the final

analysis,

each

subsample

was

used

in

a

separate

regression

model

to

predict

direct

care

time

from

patient

volume.

All

outliers

for

both

subsamples

represented

patient

observations

3

SDs

above

the mean

of

direct

care

time

per

patient.

That is,

there

were

no

data

points

below

3

SDs

from the

mean

of

this

variable.

31

The

entire

sample

had

a

total

of

104

outliers,

which

represented

1.5

%

of

the

data

set.

Outlier

observations

were

found

at

all

six

study sites

(see

Table

5).

Of

the outliers,

83

were

patients

who

had general

or

regional

anesthesia,

and

21

were

patients

who

had

local

anesthesia

or

sedation. Outliers

were

excluded

from

the

preliminary

analyses

development

of

the

regression

model.

Direct

Care

Time

Stability

Preliminary

analyses

were

conducted

to determine

if

direct

care time

per

patient,

as

measured by

the

acuity

worksheet,

varied

systematically

with

the time

during

the

16-week

data collection

period

when

the

acuity worksheet

was

completed.

A

series

of

scatterplots

as

well

as simple

regression

models

were

used

for

these

analyses.

The

scatterplots

and

regression

models

for

each

study

site

with

time

(measured

by

the

day

of

data

collection)

as

the

independent

variable

and

direct

care

time (measured

by

the

acuity

worksheet) as

the

dependent

variable

showed

no significant relationships.

That

is,

there

were

no

detectable

linear

trends

in the

measurement

of

direct

care

time

per

patient

throughout

the

data

collection

period

for

the

study

sites.

Relationship

to

Anesthesia

Type

Analyses

demonstrated

a

significant

difference

in

direct care

time

per

patient

based

on

anesthesia

type.

As

would

be

expected,

the

difference

in

direct care time

based

on

anesthesia

type

was

especially

marked

between

(a)

general and

regional

anesthesia

patients

and

(b)

local anesthesia and

sedation

patients

(see

Figure

1).

This

finding

was

consistent

among

all

study

sites.

32

Table

5

Number

and

Percent

of

Patients

Who

Were Defined

as

Outliers

in

Each

Anesthesia

Category at

Study

Sites

Anesthesia

category

by

study

site.

For

example,

(a)

1

outlier

to

145

patients

with

local anesthesia

at

site

1

means

that

0.7%

of

the

patients

in this

category

were

outliers

and

(b) 104

outliers

to

7034

patients

in

the

entire sample

means

that

1.5%

of

the patients

in

the

sample

were

defined

as

outliers.

33

Direct

Care

Time

in

Minutes

55

50/

45-/

40

"

35

30-

25

20

1

2

3

4

5

6

Study

Site

General

Regional

Local

Figure

1.

Average

direct

care

time

per

patient

by

anesthesia

type

for

each

study site.

34

Relationship

to

Patient

Volume

Preliminary

analyses

demonstrated

a

strong

positive

correlation

between

daily

patient

volume

and

direct

care

hours

per

day

(r

>

.90).

This strong

positive

correlation

was

consistent

among

all

study

sites

for

all

patients

together and

for

patients

by anesthesia type

(see

Table

6).

The

correlation

between

patient

volume

and

direct

care

time

per

day

at

study

site

3

is

illustrated

in

Figure

2.

Development

of

a

Regression

Model

The

strong

correlation

between

daily

direct care

time

and

patient

volume

at

each

study

site supported

the

development

of

a

regression

model

to

predict

direct

care

time

from patient

volume.

It

was

decided

to

explore

the

development

of

one

regression

model

based

on

data

from

all

study

sites.

The

names

and

definitions

of

variables

used

in

the

regression

models

are

listed

in

Table

7.

These

abbreviations

are

used

in

text

and

tables

to describe

the

models.

Criteria

for

Model

Selection

Several

linear regression

models

were

evaluated

to

identify

the

model

with the

best

possible

predictor

variables

for

direct

care

time. The

first criterion

for

model

selection

was

that

the predictor

variables

should

consist

of

data

that

can

be

collected

in

a

reliable

and

valid

manner

and

are

readily available

to

personnel

in

all

PACUs

in

the AMEDD.

That

is,

the

model

should

make

the

staffing

system

reasonably

easy

and

inexpensive

to

use.

Second,

the

final

model

should

accurately

describe and

predict

the

dependent

variable,

daily

direct care

hours.

Regression

models

that

met

the

first

criterion

were

compared

on

the

basis

of

their

coefficient

of

determination

(V),

standard

error

(SE),

E

value,

mean

squared

error

&2),

sum

of

squares

of

prediction

errors

(PRESS

statistic),

and

sum

of

absolute

35

Table

6

Direct

Care

Hours

and

Patients

Per

Day With

Their

Correlations

for

Each

Site

Direct

care

hours

per

day

Patients per

day

Correlation

(DCH)

(PPD)

(DCH:PPD)

Site

Anesthesia

type

M

Range

SD

M

Range

SD

ra

_n

1

Local

1.1

0.3-

3.3

0.7

2.6

1-

7

1.6

.96

55

Regional

2.2

0.4- 5.6

1.3

3.3

1-

8

1.8

.95

72

General

(Gen)

4.4

0.5

- 9.1

2.0

5.9

1

-

11

2.5

.96

82

Gen

&

regional

6.4

0.5

-

13.0

2.6

8.7

1 -

16

3.3

.95

82

All types

7.1

0.5

-

13.7

2.5

10.5

1 -

17

3.3

.91

82

2

Local

0.8 0.3-

2.2

0.5

1.7

1-

5

1.0

.95

43

Regional

1.9

0.5-

4.5

0.9

2.5

1-

6

1.2

.92

65

General

(Gen)

6.2

1.6

-

13.1

2.5

8.0

2

-

17

3.4

.97

78

Gen

&

regional

7.8 2.3

-

14.6

2.5

10.1

3

-

20 3.4

.97

78

All

types

8.2

2.8

-

15.1

2.5

11.0

4

-

21

3.5

.96

78

3

Local

1.3

0.4-

3.3

0.7

2.6

1-

6

1.3

.97

68

Regional

2.5

0.5-

6.5

1.3

3.4

1-

8

1.9

.95

75

General

(Gen)

8.5

0.8 -

17.8

3.6

10.4

1 -

24

4.6

.97

79

Gen

&

regional

10.9 1.6

-

22.2

3.7

13.7

2

-

29

4.7

.97

79

All

types

12.0

1.6

-

23.6

3.8

16.0

2

-

32

5.0

.97

79

4

Local

1.8

0.3- 4.6

1.1

3.9

1-10

2.4

.97

74

Regional

2.1

0.5- 5.2

1.1

3.1

1-

7

1.6

.93

77

General

(Gen)

5.9

0.6

-

10.7

1.9

8.8

1 -

17

2.9

.94 79

Gen

&

regional

7.7

0.6

-

15.4

2.5

11.6

1 -

22

3.8

.94

81

All

types

9.4

0.7

-

15.7

2.7

15.1

1

-

23

4.4

.94

81

5

Local

1.0

0.4- 2.7

0.5

1.9

1-

5

1.0

.96

50

Regional

2.6

0.7-

5.6

1.1

3.0

1-

6

1.4

.95

62

General

(Gen)

4.6

0.8

-

12.4

2.2

6.0

1 -

17

3.0

.98

75

Gen

&

regional

6.7

1.8

-

13.1

2.4

8.5

2

-

17

3.2 .96

75

All

types

7.3

1.1

-

14.2

2.7

10.0

2-

18

3.6

.97

76

6

Local

3.5

0.4-

7.9

1.5

8.3

1-

18

3.5

.98

78

Regional

2.7 0.5-

7.3

1.6

3.8 1

-

11

2.3

.96

74

General

(Gen)

9.0 0.5 -

14.7

3.3

12.9

1 -

22

4.7

.96

83

Gen

&

regional

11.2

0.5

-

19.7

4.4

16.1

1 -

28

6.2

.97

84

All

types

14.5

0.5

-

23.4

4.8

24.0

1 -

37

7.8

.95

84

All

Local

1.7

0.3

-

7.9

1.4

3.9

1 -

18

3.2

.98

368

Sites

Regional

2.3

0.4-

7.3

1.3

3.2

1 -

11

1.8

.94

425

General

(Gen)

6.5

0.5

-

17.8

3.2

8.7

1 -

24

4.4

.96

476

Gen

&

regional

8.5

0.5

-

22.2

3.6

11.5

1 -

29 5.0

.96

479

All

types

9.8

0.5

-

23.6

4.3

14.4

1 -

37

6.9

.95

480

Note.

Outliers

3

SDs

from

the

mean

of

direct

care

time

per

patient

are

not

included

in

calculations.

I

Pearson

correlation

of

DCH

with

PPD.

b

Number

of

days

in

each sample.

36

35

30

25

20

15

10

8

Jun

25

Sep

Days

-Daily

patient

volume

-'Daily

direct

care

hours

Figure

2.

Correlation

between

daily

patient

volume and

daily

direct

care

hours

for study

site

3.

37

Table

7

Name

and

Definition

of

Variables

Used

in

Regression

Modelsa

Variable

Definition

Dependent

Variables

Computed

for

Each

Study

Site

DCHDAYLO

Daily

direct

care

hours

for local

anesthesia

patients

DCHDAYGR

Daily

direct

care

hours

for

general

and

regional

anesthesia

patients

DCHDAYSM

Daily

direct

care

hours

for

patients

with

all

types

of

anesthesia

Independent

Variables

Computed

for

Each

Study

Site

LOCDAYSM

Daily

number

of

local

anesthesia

patients

REGDAYSM

Daily

number

of

regional

anesthesia

patients

GENDAYSM

Daily

number

of

general

anesthesia

patients

COMDAYSM

Daily

number

of

general

and

regional

anesthesia

patients

PTSDAYSM

Daily

number

of

patients

Notes.

'Model

I

DCHDAYSM

=

PTSDAYSM

Model

II

DCHDAYSM

=

GENDAYSM

REGDAYSM

LOCDAYSM

Model

III

DCHDAYSM

=

COMDAYSM

LOCDAYSM

Model

IVa

DCHDAYGR

=

COMDAYSM

Model

IVIb

DCHDAYLO

=

LOCDAYSM

38

prediction

errors.

Finally, the

prediction

reliability

of

the

selected

models

was assessed

with

a

split-sample

analysis.

Evaluation

of

Regression

Models

Model

I

(DCHDAYSM

=

PTSDAYSM)

included

the

total

number

of

patients

per

day

as

the

single

predictor

of

daily direct care

hours.

Although

R

2

was

0.90,

the

PRESS

statistic

and

S'

were

larger

for

Model

I than

for

any

other

models

under

consideration

(see

Table

8).

The

large

PRESS

statistic

and

S'

indicated

that

this

model

would

not

give

an

accurate

prediction

of

direct

care

hours

(Bowerman

&

O'Connell,

1990).

More

specifically,

the

large

S'

indicated

that

there

would

be

wide

prediction

intervals

for

direct

care

hours.

Model

II

included the

number

of

general,

regional,

and

local

anesthesia

patients

per

day

as

separate

predictors

of

daily direct

care

hours

(DCHDAYSM

=

GENDAYSM

+

REGDAYSM

+

LOCDAYSM).

It was reasonable

to

use

the

number

of

patients

by

anesthesia

type as

predictor

variables.

Carty

et al.

(1991)

found

that

direct

care

time

was

related to

type

of

anesthesia,

and

they

varied

the

amount

of

time

given

in

the

PCS

for the PACU

initial

assessment

according

to

the

type

of

anesthesia

used.

Also,

direct

care

time

was

type

of

anesthesia

in

the

present

study

(see

Figure

1).

For

Model

II,

the correlation

of

DCHDAYSM

with

REGDAYSM

(r

=

.44) was

lower

than

the

correlation

of

DCHDAYSM

with

GENDAYSM

(r

=

.87)

or

LOCDAYSM

(r

=

.56).

Also,

this

model

had

slightly

higher

values

for

the

PRESS

statistic

and

S' than

did

some

of

the

other

models

being

considered

(see

Table

8).

At

the

same

time,

there was

little

difference

in

this

model

between

the

regression

coefficients

for

GENDAYSM

(.71)

and

REGDAYSM

(.69).

That

is,

the

amount

of

direct

care

time

given

to

general

anesthesia

patients

(42.6

minutes)

39

Table

8

Regression

of

Daily Direct

Care

Hours

on

Patient

Volume

for

5

Regression

Modelsa

Explanatory

Regression

Coefficientsb

with

ME)

Variable

Model:

I

II

LII

IVa

IVb

INTERCEPT

1.33

0.64

0.63

0.49

0.12

(0.14)

(0.12)

(0.02)

PTSDAYSM

0.59

(0.01)

GENDAYSM

0.71

(0.01)

REGDAYSM

0.69

(0.03)

LOCDAYSM

0.35

0.42

(0.02)

(0.004)

COMDAYSM

0.71 0.69

(0.01)

R

2

0.90

0.94

0.92

0.97

Fc

4,414

2,381

3,575

5,663

10,836

S

2

1.77

1.14

1.04

0.06

PRESSd

856

552

550

498

23

(495)

(404)

(402)

(384)

(71)

Notes.

aModel

I

DCHDAYSM

=

PTSDAYSM

Model

II

DCHDAYSM

=

GENDAYSM

REGDAYSM LOCDAYSM

Model

III

DCHDAYSM

=

COMDAYSM

LOCDAYSM

Model

IVa

DCHDAYGR

-

COMDAYSM

Model

IVb

DCHDAYLO

=

LOCDAYSM

b

p

<

0.0001

C

p

<

0.0001

d

PRESS,

which

is the

sum

of

squares

of

prediction

errors,

is

reported

together

with

the

sum

of

absolute

prediction

errors

in

parentheses.

40

would

not

vary

greatly

with the

direct

care

time

given

to

regional

anesthesia

patients

(41.4

minutes)

when

using

this

regression

model

as part

of

a

staffing

system.

This

indicated

that

the

number

of

general

and

regional

anesthesia

patients

could

be

combined

into one

variable

with no negative

practical

impact

on

the

staffing

system.

Model

mII

included

the number

of

general

and

regional

anesthesia

patients combined

together

as

one

predictor

variable

and

the

number

of

local

anesthesia

patients

as

the

second

predictor

variable

(DCHDAYSM

=

COMDAYSM

+

LOCDAYSM).

However,

the

scatterplot

of

DCHIDAYSM

and

LOCDAYSM

produced

an

accordion-like

picture,

demonstrating

a

poor

fit

of

this

predictor

variable

in

the

model

(r

=

.56).

This

model

also

had slightly

higher

values

for

the

PRESS statistic

and

S'

than

did

some

of

the

other

models

being

considered

(see

Table

8).

Model

IV

was

expressed

as

dual

regression

equations

IVa

and

IVb,

which

were

designed

to

be

used

together

as

one model

for

the

staffing

system.

The

part

of

model

IV

that

included

the

number

of

general

and

regional

anesthesia

patients

combined

together

as

a

predictor

of

their

direct care

hours

(DCHDAYGR

=

COMDAYSM)

is

referred

to

as

model

IVa.

The

part

of

model

IV

that

included

the

number

of

local

anesthesia

patients

as

a

predictor

of

their

direct

care

hours

(DCHDAYLO

=

LOCDAYSM)

is

referred

to

as

model

IVb.

Model

IVa

had

a

slightly

lower

W

2

(.92)

than

some

of

the

other

models

examined,

but

the

PRESS statistic

and

S

2

also

were

smaller--indicating

that

this

model

would be

a better

predictor

of

daily

direct

care

hours

(see

Table

8).

Model IVb

had

the largest

R

2

and

smallest

PRESS

statistic

and

S'

of

all

the

models

(see

Table

8).

Also,

models

IVa

and

IVb

showed

fewer

outlying

influential

observations

than

did

other

models

as

noted

by

the

smaller

difference

between

the

PRESS

statistic

and

the

sum

of

absolute

prediction

errors

(Myers,

1990).

Thus,

it

was

determined

41

that

the

dual

regression

equations

IVa

and

IVb used

together

as

one

model

allowed

for

the

best

prediction

of

daily direct

care

hours

from

daily

patient

volume by

anesthesia

type.

Split-Sample Analysis

To assess

the

reliability

of

regression

equations

IVa

and

IVb,

a

split-sample

(cross

validation)

analysis

was

conducted.

Data

collected

for

all

6

sites

(N

=

7,034

patients)

were

randomly

split into

two

subsets:

a "fitting"

or

"training"

sample

and

a

validation

sample

(Huck,

Cormier,

&

Bounds,

1974;

Kleinbaum,

Kupper,

&

Muller,

1988).

The

process

of

random

division

was

performed

for

each

site

separately.

One

subsample

from

each site

was

combined

into

a

fitting

sample

(n

=

3,546),

and

the

other

subsample

from

each

site

was

combined into

a

validation

sample

(g

=

3,488). With

this

method

of

data splitting,

the

fitting

and

validation

samples

had approximately equal representation

from

each

site

(see

Table

9).

According

to

the

split-sample

analysis

technique,

data

from

the

fitting

subset

of

patients

were

used

to build

regression

equations

IVa

and

IVb.

The

coefficient

of

determination

[

2

(1)]

from

each

of

these

models

was

used

in

further

calculations.

Next, the

sample

regression

equations

IVa

and

IVb

were

applied

to

patient

volume

data

from

the

validation

subset

of

patients.

In

this

step,

predicted

direct

care

time

values

were

computed.

Finally,

the

validation

sample was

used

to

perform

a

simple

linear

regression

analysis

independently

for

equations

IVa and

IVb with

predicted

values

of

direct

care

time

as

a

predictor

variable

and

observed

values

of

direct

care

time

as

an

outcome

variable. The

coefficient

of

determination

for

each

of

these

regression

analyses,

referred

to

as

the

"cross-validation

correlation"

[2(2)],

was

used

to

calculate

the

shrinkage

on

cross

validation.

For

regression

42

Table

9

Number

of

Patients

in

the

Fitting

and

Validation

Samples

by

Anesthesia

Type

for

Each

Study

Site

Anesthesia

Type

Sample

Type

by

Site

Local

Regional

General

Total

Site

1

Fitting

90

122

253

465

Validation

55

118

234

407

Site

2

Fitting

36

80

311

427

Validation

35

88

320

443

Site

3

Fitting

90

138

423 651

Validation

90

119

436

645

Site

4

Fitting

150

113

325

588

Validation

142

129 373

644

Site

5

Fitting

43

96

243

382

Validation

55

94

211 360

Site

6

Fitting

320

140

573

1033

Validation

335

143

511

989

Total

Fitting

729

689 2128

3546

Validation

712

691

2085

3488

43

equation

IVa,

the

coefficient

of

determination

[(1)]

was

0.9172.

The

cross-validation

correlation

[W

2

(2)]

was

0.9046.

The

shrinkage

on

cross-validation

[defined

as

W

2

(1) - V

2

(2)]

was

0.9172

-

0.9046

=

0.0126.

For

regression

equation

IVb,

the

shrinkage

was

the

difference

between

12(1)

=

0.9425

and

W

2

(2)

=

0.9313

or

0.9425

- 0.9313

=

0.0112.

Both

equations

were

determined

to

be

reliable

based

on

the

fact

that

shrinkage

values

less

than

0.10

indicate

a

high

reliability

of

estimation

(Kleinbaum

et

al.,

1988).

Furthermore,

the

small

shrinkage

values

supported

the

decision

to use

pooled

data

from

all

study

sites

to

estimate

the

regression

coefficients

in

the

dual

regression

equations.

Analyses

of

Research Objectives

Objective

One

The

first

research

objective

was

to

develop

a

method by which

the typical

workload

of

a

PACU

could

be

described

and

the

variation

in

the

workload

could

be

analyzed.

The

calculation

of

nursing

care

hours

(NCHs)

as

well

as

the

development

of

the

workload

profile

and

the

analysis

of

workload

variation

will

be

explained.

Calculation

of

Nursing

Care

Hours

NCHs

per

day

were

calculated

for

each

study site

by

combining

the

daily direct

nursing

care

hours

obtained

from the

regression

model

with

the

PACU

indirect care

multiplier

(ICM). As

previously

discussed,

direct

care

time

was

measured

using

the

PACU

PCS

(Carty

et

al.,

1991),

and

the

ICM

was

derived

from

a study

of

the

indirect

care

time

component

(Rea

et

al., 1991).

The

calculations

for

using

the

regression model

and

the

indirect

care

multiplier

to

obtain

NCHs

per

day

from

patient

volume

information

are included

in

Appendix

44

F.

To evaluate

the

accuracy

of

this

method

of

calculating daily

NCHs,

these

"actual"

NCHs

per

day

for

each

study site

were

plotted

over

time

to

provide

a

graphical

display

of

each

site's

workload

over

the

entire

period

of

data

collection.

Additionally,

NCHs

per

day

that

nursing personnel

were

"available"

for

patient

care

for

each

day

of

data

collection

were calculated

using

the time

schedule

information.

Professional

and

paraprofessional

nursing

personnel

who

were

assigned

to

the

unit in

patient

care

positions

were

included

in

these

calculations.

Their

available

time

was

considered

to

be the

number

of

hours

they

spent

in

direct

and

indirect

care activities

as

well

as

time

spent

in

personal

activities, unavoidable delay,

wait/stand-by,

and

meals

(Rea

et

al.,

1991).

The

number

of

hours

per

day

that

these

personnel

were

available

for

care

on

the

unit

was

totalled

to

equal

the

"available"

NCHs.

Actual

and

available NCHs

were

plotted

separately

over the

entire

period

of

data

collection

and were

compared

by

visual

inspection

of

the

graphs.

When the

two

graphs

were

viewed

with

a

consideration

of

the

practice

patterns

and skill

mix

of

nursing personnel

at

each

site,

it

could

be

seen

that

there

generally

were

an adequate

number

of

available

NCHs

to

cover the

workload

as

measured

by

the

actual

NCHs.

Assuming

that

PACU

head

nurses

would

schedule

enough

staff

to

provide

adequate

nursing

care,

it

was

determined

that

this

method

of

calculating

NCHs

provided

a

reasonable estimation

of

nursing

workload.

Development

of

the

Workload

Profile

The

Shewhart

method

of

variance

analysis

as

outlined

in

statistical

process control

(SPC)

methodology

was

used to

develop

a

control chart

that

could

be

adapted

for

use

as

a

workload

profile

(Shewhart,

1931).

A

typical control

chart

displays

a

process

characteristic

of

interest,

45

such

as

nursing workload,

that

has

been

measured

or

computed

from

a

sample

over

time.

For

example,

PACU

nursing

workload

was

measured

in

this

study

by

NCHs

per

day

over

a

period

of

several

weeks.

As previously

discussed,

NCHs

per

day

were

calculated

for

each

study

site

by

combining

the

daily

direct nursing

care

hours

obtained

from

the

regression

model

with

the

PACU

indirect

care

multiplier (ICM).

The

control chart is characterized

by

several statistical

properties

(McNeese

&

Klein,

1991;

Wadsworth,

Stephens,

&

Godfrey,

1986).

The chart

contains

a center

line

that

represents

the

mean

of

the

process

characteristic.

The

researcher

draws two horizontal

lines,

referred

to

as

the

upper control

limit (UCL)

and

the

lower

control

limit

(LCL),

so

that

most

of

the

sample

points fall

between

them

when

the

process

is

stable

or

in

control.

If

the

process

is

in

control,

the

plotted points

have

an essentially

random

pattern

reflecting

the

natural

variability

due

to

common

causes

of

variation

within

the

process

itself.

Sample

points

that

plot

outside

the

control limits

are

interpreted

as

being

due

to

assignable

or

special

causes

of

variation

that

are

unusual.

Eliminating

the

underlying

cause

of

sample

points being

outside

the control

limits

makes

the

process

more

stable.

To

develop

the workload

profile,

the

type

of

control chart

and

unit

of

measurement

that

were

to

be

used

had to

be

determined.

Because

each

subgroup

should

be

as

homogeneous

as

possible

with

respect

to

the

variability

of

the

process

under

consideration,

NCHs

per

day

was

selected

as

the

rational subgroup

or

unit

of

measurement

(Wadsworth

et

al.,

1986).

Several

days

of

the week

could

not

be

combined into

one

subgroup because

of

variability

in

the

workload

between

days

of

the

week.

Also,

there

was

no

subgroup

smaller than

the

day

that

would be

logical

to use

for

monitoring PACU

workload.

46

Because

the

day

was

selected as

the

unit

of

measurement,

the

control chart

for

individual

measurements--referred to

as

the

individuals

or

X

chart--was

used

for

the

development

of

the

workload

profile

(Pyzdek,

1990;

Wadsworth

et

al.,

1986).

Individuals

control

charts

are

designed

for

the

normally

distributed

population

(Pyzdek,

1990;

Wadsworth

et

al.,

1986).

If

the

process

shows

evidence

of

a

serious

departure

from

normality,

the

control limits

may

not

be

meaningful.

Therefore, the

distribution

of

NCHs

per

day

within

the

entire

16-week

period

of

data collection

was

examined

for

each

study

site.

No

marked departure

from

normality

was

observed.

Another

consideration

in

developing

the

control

chart

was

the

frequency

of

data

collection.

For

the

workload

profile,

the

data

needed

were the

number

of

patients

recovered

in

the PACU

per

day

in

two

categories

of

anesthesia.

PACU

head nurses

at

the

six

study

sites

concurred

that

collecting

patient

volume

information

every day

they

were

open

to

recover

patients

would

be

a

minimal

amount

of

work

and would

be

much

simpler

and easier

to

remember

than

recording

the information

less

frequently,

such

as

every

other

week.

Furthermore,

head

nurses

of

all

PACUs

in

HSC

reported

on

the

PACU

survey

that

they

had

a

routine

operating

schedule

of

Monday

through

Friday,

except

for

being

closed

on

holidays.

Thus,

it

was

decided

that

data would

be

collected

for

the

workload

profile

on

each

day

the

PACU

was

open

to

recover

patients

from

a

routine

operating

schedule

(usually

Monday

through

Friday).

It

was

noted

that,

at

the

time

of

the

study,

there were

two

PACUs

in

HSC

that

had a

practice

of

staying

open Monday

through

Friday

on

a

24-hour

basis to

provide

care

for

a

limited

number

of

remain

overnight

patients

(RONs).

As

will become

evident

in

47

the

section

on

additional

analyses,

the

presence

of

RONs

in

a

unit

would

not

influence

the

frequency

of

data collection

for

the

staffing system.

Additionally,

it

was

decided

to

develop

a

workload

profile

with

3

months

of

NCH

data.

When

reporting

workload

data

5

days

a

week,

a

quarterly workload

profile

would

have

50-60

data

points plotted

over

time.

This

is

a

sufficient

number

of

data

points

on

which

to

base

a

control chart (Grant

&

Leavenworth,

1988;

Pyzdek,

1990).

Moreover,

3

months

is

a

reasonable

period

of

time

on

which

to

base

a

workload

profile,

given

that

no

data

are

available

regarding the

variability

of

workload

patterns

over

time.

Also,

a

quarterly

workload

profile

could

be

generated

along

with

other

administrative reports

that

commonly

are

generated

on

a

quarterly

basis.

Thus,

the

original data

collected

for

the

study

were

decreased

to

a

12-week

data

set

to

develop

a

workload

profile

for

each

study

site.

The

first

and last

2

weeks

of

data

were

removed

to

obtain

12

consecutive

weeks

of

workload

data.

After

developing

the

workload

and

staffing

profiles

with

this

12-week

data

set,

the

results

were

compared

with workload and

staffing

profiles

developed

with

the

entire

16-week

period

of

data.

There were

no

differences

in

the

decisions

that

would

have

been

made

regarding the

development

of

workload

or

staffing

profiles

using

the

12-week

or

16-week

data

set.

This

was

further

evidence

that led

to

the

decision

to

develop

the

workload

profile

with

3

months

of

NCH

data.

Before

establishing

control

limits

for

the

individuals

control

chart,

the

variability

of

the

workload

process

had

to

be

examined

(Pyzdek,

1990).

First,

the

moving

range control

chart

with

3

SD

control

limits

was used

to

estimate

the

process

dispersion

or

variability

of

two

successive

observations

of

NCHs

per

day

for

each

study

site (McNeese

&

Klein,

1991;

48

Pyzdek,

1990).

The

moving

range refers

to

the

absolute values

of

differences

between

successive

observations

on

the

individuals

chart, and

these

values

are

plotted

as

data

points

on

a

moving

range

chart.

A

moving range

chart

was

made

for

each

site

with

the

center

line

equal

to

the

mean

of

the

moving

range

(MR),

the

lower

control

limit

equal

to 0,

and

the

3

SD

upper

control

limit

equal to

3.267

MR

(where

3.267

is

a

constant

used

for

the

3 SD

upper

control limit

when

a

moving

range

of

2

observations

is used) (Pyzdek,

1990;

Wadsworth

et

al.,

1986).

Initial

calculations

for

the center line

and

3

SD

control limits

revealed

that

study

sites

3

and

4

each

had

one data

point

outside

the

upper

control

limit

on

their

moving

range

charts,

and

the

other four

study sites

had

no

data

points

outside

the

control

limits.

According

to

the

procedure

for

constructing

a

moving

range

control

chart,

the

data

points

outside

the

control

limits

for

study

sites

3

and

4

were

removed

from

their

respective

data

sets,

and

the

standard deviations

and means

were calculated

again.

The new

moving

range

charts

showed

that

study

site

3

had

1

data

point

outside

the

3

SD control limits

and

study site

4

had

no data

points

outside the

3

SD

control

limits.

Because

the

moving

range

charts

were

in

statistical

control, an

individuals

control

chart

could be

constructed

for

each

study

site

using

an

estimate

of

the

process

standard

deviation

computed

from

the moving

range

chart

(where

SD

=

MR/d2,

with

d2

=

a

constant

of

1.128

when

a

moving range

of

2

observations

is

used)

(Pyzdek,

1990).

Four

study

sites

had

no

data

points

outside

the

3

SD control

limits,

while

study

sites

3

and

4

each

had

1

data

point

outside

the control

limits.

When

data

points

outside

the

3

SD control

limits

were

removed

from the

data

sets

of

study

sites

3

and 4

and

the

standard deviations

and

means

were

calculated

again,

the

new

individuals

charts had

no

data

points

outside

the

3

SD

control

49

limits.

It

was

concluded

that

most

of

the

variability

of

NCHs

per

day

for

each

study

site

was

due

to

natural

or

common

causes,

and

therefore

the process

was

in

statistical

control

as

evaluated

by

the

3

SD

control limits.

That

is,

the process

of

providing

nursing

care

to

patients

as

measured

by nursing

workload

at

the

study

sites

was

interpreted

as

a

stable

process.

When

a

process

is

in

statistical

control,

the

two

estimates

of

process

standard

deviation--

one computed

using

the

moving

range

chart

(where

SD

=

MR/d2, with

d2

=

a

constant

of

1.128

when

a

moving

range

of

2

observations is

used)

and

the other

using

the

"standard"

method

of

calculating

a

standard

deviation--are

very

close

(Pyzdek,

1990;

Wadsworth

et

al.,

1986).

Because

the

moving range and individuals

charts

demonstrated

statistical

control

and

because

the

standard

method

of

calculating

a

standard

deviation

would

be

easier

for

nursing

personnel

to

use

when

constructing

workload

profiles,

the

standard

method

was

adopted

for

use

in

setting

the

control

limits

for

the workload

profile.

Moreover,

after

further

analysis

of

the

data,

it

was

decided

that

2

SD control

limits

for

the

individuals

charts

would

be

used

for

the

workload

profiles

(instead

of

the

3

SD

control

limits more

commonly

used

in manufacturing

industries).

Setting

the

control limits

based

on

an

analysis

of

the

data

is

entirely

appropriate

in that

Shewhart conceived

of

the control

chart

as

an

empirical

tool

that

should

be

relevant

to

the

data

being

analyzed

(Mandel,

1991).

It

was

decided

to

use

the

2

SD

control

limits

for

two

reasons.

First,

most

of

the variability

of

NCHs

per

day

for

the

study

sites

fell

within

2

SDs

from the

mean

of

NCHs

per

day

as

demonstrated

by

the

individuals

control

charts

that

were

developed

using the

standard

method

of

calculating

the

standard deviation.

Four

of

the

study

sites

each

had

only

2

data

points

50

greater

or

less

than

2

SDs

from

the

mean

of

NCHs

per

day

for

the

3-month

period

of

time

used to

create

the

individuals

charts,

while

study

site

1

had

3

data

points

and

study

site

3

had

4

data

points

greater

or

less

than

2

SDs

from

the

mean

of

NCHs

per

day

for

this

3-month

period

of

time.

When

data

points

outside

the

2

SD

control

limits

were

removed

from

their

respective

data

sets

and

the

standard

deviations

and

means

were

calculated

again,

study

sites

2,

5,

and

6

each

had

1

data

point

outside

the

2

SD

control

limits,

while

study

sites

1

and

3

each

had

2

data

points

and

study site

4

had

4

data

points

outside

the

2

SD

control

limits.

The

total

number

of

data

points

outside

the

final

2

SD

control

limits

of

the

3-month

workload

profiles

ranged

from

3

data

points

for

study sites

2,

5,

and

6

(which

represented

5

%

of

the

data

points

for

each

of

these

sites)

to

6

data

points

for

study

sites

3

and

4

(which

represented

10

%

of

the

data

points

for

each

of

these

sites).

The

second

reason

for

selecting

2

SD

control

limits

was

that

individuals

control

charts

are

not

as

sensitive

to

change

as

are

some

other

types

of

control

charts,

but

using

2

SD

instead

of

3

SD

control

limits

would give the

charts

a higher

sensitivity

to

an

out-of-control

process

(Shainin

&

Shainin,

1988;

Wadsworth

et

al.,

1986).

It

was

noted

that

setting

the

control

limits

at

2

SDs instead

of

3

SDs

from the

mean

increases

the

likelihood

of

a

Type

I

error,

or

the

error

involved

in

calling

a

data

point

out-of-control

when

it

is

not

(Shainin

&

Shainin,

1988;

Wadsworth

et

al.,

1986).

However,

the

cost

of

a Type

I

error,

or

searching

for

reasons

why

a

data

point

is

out-of-control

when

it

is

not,

is

low.

Nursing

personnel

can

quickly

and

inexpensively

search

for

possible

reasons why

there

are

an

increased

or

decreased

number

of

patients

on

days

representing

data

points

outside

the

control

limits.

51

The

method

of

developing

a

quarterly

workload

profile

described

in

the

preceding

paragraphs

was

used

to construct

a

separate

profile

for

each

study

site.

First,

the

arithmetic

mean

and

standard

deviation

of

NCHs

per

day

were

computed

for

Mondays

through

Fridays

(excluding

holidays)

for

the

entire 3-month

period

of

time.

The

mean served

as

the

center

line

for

the

chart, and

the

upper

and

lower

control

limits were

placed

at

2

SDs

above and

below

the

mean

(as

computed

by

the

standard

method

of

calculating

the

standard

deviation).

NCHs

per

day

for

the

3-month

period

of

time were plotted

on

the

chart, and

data

points

outside

the control limits were

removed. The

mean

and

standard

deviation

were

computed

on

the

new

data

set

without

the

outlying

data

points,

and a

chart

representing

the

workload

profile

with its mean

and

2

SD

control

limits

was

made

for

each

study

site.

The

workload

profile

that

has

been

developed based

on

the

individuals

control

chart is

a

pattern

of

a

unit's

nursing

workload

over

a

specified

period

of

time

as

expressed

in

NCHs

per

day. A

workload

profile

developed

in

this

manner

for

study

site

6

can

be

found

in

Figure

3.

The

profile

demonstrates

that

nurses

in

this

PACU together

typically

worked

a

total

of

52

to

95

NCHs

per

day

and

that

one

data

point

fell

outside the

2

SD

control

limits

on

the

workload

profile

during

this

3-month

period

of

time.

Analysis

of

Variation

in

Workload

The

workload

profile

is

designed

to be

used

for

analyzing

variation

in

workload.

As

has

been

discussed,

there

are

many factors

that

affect

PACU

workload.

These

factors

should

be

kept

in

mind

when

searching

for

the

cause

of

workload

variation.

However,

it

should

be

remembered

that NCHs

per

day

are

calculated

using

a

regression model

that

assigns

a

fixed

amount

of

direct

care time

to

patients

based

on

the

type

of

anesthesia

they

received.

52

Nursing

Care

Hours

Per

Day

100

]

UCL

93

NCHs

90

A

80

70

v

60

50

-LOL

50

NCHs

.......................

M

ean

NCHs

6

Jul

25

Sep

Days

Figure

3.

Workload profile

for

study

site

6

with

only

1

data

point

outside

the

2

SD

upper

and

lower

control limits

(UCL

&

LCL).

53

Therefore,

variation

in

NCHs

per

day

on

the

workload

profile

largely

will

be

due

to

differences

in

the

number

of

patients

seen

per

day

in

each

of

the

two

anesthesia

groups.

Given

this

understanding

of

the

NCH

data,

there

are

two

ways

in

which

head

nurses

can

use

their

workload

profile

to

analyze

variation

in

workload.

The

variation

in

workload

profiles

for

the

six

study sites

was

analyzed

in

these

ways.

First,

the

profiles

were

examined

for

data

points

that

fell

outside

the

control

limits.

Even

after

talking

with

the

study

coordinators,

no

consistent

underlying

cause

was

found

for

the

change

in

patient

volume

that

led

to

the high

and

low

workload

days

outside

the

control

limits.

Second,

the

profiles

were

analyzed

for

patterns

in

the

distribution

of

the

data

points.

For

all

study

sites,

a

pattern

of

differences

in

workload

by

day

of

the

week

was

evident.

In

fact,

much

of

the

workload

variation

could

be

explained

by

day

of

the

week

differences

in

workload.

Furthermore,

these

workload

differences

seemed

to

be

explained

by

the

practices

of

the

clinical

services

that

were

allocated

operating

room

(OR)

time

by

day

of

the

week.

For

example,

a

busy

orthopedic

service

that

always

maximized

its

OR

time

on

Wednesdays

with

a

heavy

case

load

would be

a factor

that

contributes

to

Wednesdays

being

a

high

workload

day.

Figure

4

shows

that

for

study

site

6,

for

instance,

Wednesday

generally

was

a high

workload

day

and

Tuesday

was

a

low

workload

day.

There

was

some

variation

within

Tuesdays

and

Wednesdays.

However,

generally

speaking,

the

workload

at

study

site

6

required

more

staff

on

Wednesdays

than

on

Tuesdays

during

the

period

of

data

collection

because

of

the

consistent

variation

in

workload

between

these

two

days

of

the

week.

54

Nursing

Care

Hours

Per

Day

100

-

90

80

-

X

70

-V

60

50

0

Tuesdays

X

Wednesdays

40

6

Jul

25

Sep

Days

Figure

4. Workload

profile

for

study

site

6

with

workload

differences

between

Tuesdays

and

Wednesdays

indicated.

55

Workload

profiles

were

not

created

for

each

day

of

the

week

with data

from

the

study

sites

because

there

were not

enough

available

data

points.

Only

up

to

16

data

points

from

the

entire

period

of

data collection

were

available

for

each

day

of

the

week

at

a

study

site,

but

at

least

25

to

30

data points

are

needed

to

create

a

control

chart

(Grant

&

Leavenworth,

1988;

Pyzdek,

1990).

However,

the

quarterly

workload

profile

that

is

developed

with

3

months

of

consecutive

workdays

can

be

used

to

look

for

patterns

due

to

variation

in

workload

by

day

of

the

week.

As

demonstrated

in

Figure

4,

a

pattern

of

variation

in

workload

by

day

of

the

week

is evident

when

the

day

of

week

for

each

data

point

is

marked

on

the

quarterly

workload

profile.

Objective

Two

The

second

research

objective

was

to

develop

a

method

of

determining

the number

of

nursing

personnel

to

schedule

on

a

daily

basis

to

accomplish

a

unit's

workload.

This

number

of

nursing

personnel,

which

is

reported

as

a

staffing

range,

refers

to

variable

staff.

Variable

staff

are

those

whose

primary

role

is

to

provide

nursing

care

to

patients

(Rea

et

al.,

1991).

Fixed

staff

have

an

administrative

role

in

addition

to

their

clinical

responsibilities

(Rea

et

al.,

1991).

Recommendations

regarding

the

number

of

fixed

staff

that

a

PACU

needs

will

be

discussed

after

development

of

the

staffing

range

is

explained.

Finally,

recommendations

for

managing

days

at

the

extremes

of

workload

will be

discussed.

Staffing

Range

The

staffing

needs

of

a

unit

are best

described

as

a

range

of

personnel,

not

an

absolute

value.

The

upper

end

of

the

staffing

range

indicates

the

number

of

nursing

personnel

to

schedule

for

patient

care

on

higher

workload

days

and

the

lower

end indicates

the

number

to

56

schedule

on

lower

workload

days.

The

number

of

nursing

personnel

reported

in

the

staffing

range

is

expressed

as

full

time

equivalents

(FTEs)

rounded

to

the

nearest

tenth

of

an

FTE.

Reporting

fractions

of

an

FIE

gives

head nurses

the

justification

to

hire

part-time

staff

to

work

a specified

number

of

hours

per

pay

period.

For

instance,

a

staffing

range

upper

limit

of

7.5

FTEs

indicates

the

need on

high

workload

days

for

7

variable

staff

to

work

full-time

(8

hours

per

day)

and

1

variable

staff

member

to

work

on

a part-time

basis

for

50%

of

the

work

day

(4

hours

per

day).

The

criterion

used

to

develop

the

staff'mg

range

was

that

it

should

represent

the

number

of

FTEs

needed

to

accommodate

most

expected

variation

in

workload.

As

has

been

discussed,

much

of

the

variation

in

the workload

profiles

occurred

due

to

workload

differences

by

day

of

the

week.

To

determine

the

staffing

range

that

accommodated

most

expected

variation

in

workload,

the

number

of

NCHs

at

the

mean

and

at

1/½,

1,

and

2

SDs

above

and

below

the

mean

of

each

site's

workload

profile

was

computed.

The

NCHs

for

each

of

these

workload

levels

was

converted

to

FTEs

by

dividing

the

NCHs

by

8

and

rounding

to

the

nearest

whole

number.

Also,

the

mean

NCHs

for

each

weekday

(Monday

through

Friday)

were

calculated

and

converted

to

FTEs

for

each

study

site.

The

mean

FMTs

for

each

weekday

in

the

majority

of

cases

fell within

a

range

of

+0.5

SD

from

the

mean

of

each

site's

workload

profile.

Furthermore,

there

was no

case

in

which

the

mean weekday

FTEs

exceeded

the

+0.5

SD

range

of

the

workload

profile

by

1.0

or

more

FM~s.

Additionally,

it

was

noted

that

in

most

cases

setting

the

staffing

range

at

+1.0

SD

instead

of

+0.5

SD

from

the

mean

of

the

workload

profile

would

result

in

a

difference

of

requiring

1½

more

FTE

at the

upper

end

of

the

staffing

range.

A

staffing

range

this

wide

57

would

not

be

justified,

especially

when

the

staffing

system allows

for

two

fixed

staff

positions

in

addition

to

the

number

of

variable staff

recommended

by

the

staffing

range.

As

will

be

explained, fixed

staff

can

help

provide

direct

patient

care

on

high

workload

days.

Therefore,

it

was

recommended

that

the

staffing

range

be

set

at 0.5

SD

above

and below

the

mean

NCHs

in

a

3-month workload

profile.

The

staffing

profile

for

study site

2

can

be found

in

Figure

5.

The

staffing

range

of

3.9-

5.1

FTEs

per

day

is

set

at

+0.5

SD

from

the

mean

value

of

NCHs

per

day

for

the

workload

profile.

The

workload

for

Wednesdays

and

Thursdays is

indicated

on

the chart

to

demonstrate

that

much

of

the

variability

in

the workload

profile

was

due

to

differences

in

workload

between

these

2

days

of

the

week.

Based

on

the

workload

during

the

data

collection

period,

study

site

2

would

schedule

4

variable

staff

for

low

workload

days

such

as

Wednesdays

and

5

variable

staff

for

high

workload days

such

as

Thursdays.

Allocation

of

Fixed

Staff

The

need

for

fixed

nursing

staff

is

recognized

regardless

of

variation

in

workload.

In

the

PACU

staffing

system,

the

head

nurse,

wardmaster,

and

ward

clerk

are recognized

as

fixed staff

positions

(see

Appendix

G).

It

is

important

to

emphasize

that

the

staffing

range

indicates

the

number

of

variable

staff

who

are

needed

on

the

unit

in

addition to

the

fixed

staff.

It

was

stated

that

the primary

role

of

the

variable staff

is to

provide

nursing

care

to

patients.

Therefore, the

number

of

variable staff

needed

depends

on

the

workload,

and

the

staffing

range

has been

developed

so

that

it

varies

according

to

workload.

The

general

guideline

for

the

allocation

of

fixed

staff

is

that

a

PACU

should

have

a

baseline

of

one head

nurse

and one

wardmaster

as

fixed staff positions.

There is

an

58

Nursing

Care

Hours

Per

Day

60-

50

-

x

X

40

,

Mea

NCs0Wdedy

20

-

________X

Thursdays

Staffing

range

of

3.9

-

5.1

FTEs

per

day

22

Jun

11

Sep

Days

Figure

5.

Staffing

profile

for

study

site

2

with

workload

differences

between

Wednesdays

and

Thursdays

indicated.

59

exception

to

this

general

guideline

that

applies

to

PACUs

with

low

workload.

When

the

staffing

range

indicates

that

there

is

sufficient

workload

to

justify

no

more

than the

two

nursing personnel

necessary

for

minimum

staffing,

these

personnel

must

serve

as

both

the

fixed

staff

(i.e.,

head

nurse

and

wardmaster)

and

variable

staff

for

the

unit.

The

workload

in

these

PACUs

does

not

justify

the

addition

of

fixed

staff

positions

to

the

staffing

range.

The

addition

of

one

paraprofessional

fixed

staff

position

is

justified

when

the

staffing

range

indicates

a need

for

approximately

three

variable staff,

and

the addition

of

both

one

paraprofessional

and one

professional fixed

staff

positions

are

justified

when

the

staffing

range

indicates

a

need

for

approximately

four

or

more variable

staff.

Specific

guidelines

were

developed

to

use

for

allocation

of

fixed staff

to

the

PACU

(see

Table

10).

These

guidelines follow

the

principle

of

having enough

workload

to

justify

separate

fixed

staff positions

as

outlined

above,

but

they

use

the

average

of

the

staffing

range

as

specific

cut-off points

for

the

allocation

of

fixed

staff.

Also,

a

ward

clerk

was

recommended

when

the

workload is

sufficient

to

generate

a

need

for

approximately

seven

or

more variable

nursing

staff

per

day. This

is

in

accordance

with

the

PACU

Joint

Healthcare

Manpower

Standards

(Joint

Healthcare Management Engineering

Team,

1991,

1992).

For

example,

the

staffing

range

calculated

for

study site

2

was

3.9

to

5.1 FTEs

(see

Figure

5).

The

average

of

the

staffing

range

for

this

PACU

was

4.5

FTEs

[(3.9

+

5.1)/2].

According

to

the

fixed

staff

recommendations

outlined

in

Table

10,

the

workload

during

the

data

collection

period

justified

staffing

this

unit with

one

professional

and

one

paraprofessional

staff member

to

serve

as

a

head

nurse

and

wardmaster

in

addition

to

the

3.9

60

Table

10

Recommendations for Professional

and

Paraprofessional

Fixed

Staff

Positions

Based

on

the

Average

of

the

Staffing Range

Average

of

Staffing Range

Additional

Staff

Positions

<_2.4

2.5

-

3.4

3.5

-

6.4

26.5

Paraprofessional

staff position

0

1 1 1

Professional

staff

position

0

1 1

Clerk

0 0 0

1

to

5.1

FTEs

to

serve

as

the

variable

staff. However,

the

workload

did

not

justify

staffing

this

unit

with

a

ward

clerk.

Managing

Days

at

the

Extremes

of

Workload

As

has

been

explained,

the

staffing

range

was

designed

to

accommodate

most

expected

variation

in

workload.

However,

there

will

be

some

days

at

the

high

and

low extremes

of

workload when

the

number

of

personnel

recommended

by

the

staffing

range

will

not

be the

ideal number

for

accomplishing

the

workload

as

calculated

by

NCHs

per

day.

There

are

two

ways

by

which

the number

of

personnel

recommended

in

the

staffing

range

can

accomplish

the

required

nursing

care

more

efficiently

on

very

high

and

very

low

workload

days.

First,

it

should

be

emphasized

that

workload

is

measured

as

NCHs, which are

comprised

of

direct

care

and

indirect

care

time.

Part

of

the

workload

that

is

generated

by

indirect

care

activities,

such

as

restocking

supplies,

can

be

shifted

from

high

to

low

workload

days.

Expert

PACU

61

head

nurses who

participated

in

the

study

reported

this

was

a

common

way

they

managed

their

days

at

both

extremes

of

workload.

Second,

the fixed

staff

(i.e.,

the

head

nurse

and/or

wardmaster)

can

help

accomplish

the

workload

on

high

workload

days

by

working

as

one

of

the variable staff

members

in

providing direct

patient

care.

PACU

nurses

who

participated

in

the

study

noted

that

PACU

head

nurses and

wardmasters

in

the

AMEDD

commonly

provide

patient

care

as

part

of

their

duties.

According

to the PACU

survey,

the

average

percentage

of

time

that

head

nurses

of

PACUs

in

each

of

the

3

workload

strata

provided patient

care

was

as follows:

(a)

86

%

of

the

time

for

head

nurses

of

PACUs

categorized

in

the

low

workload

stratum,

(b)

80

%

of

the

time

for

head

nurses

of

medium

workload PACUs,

and

(c)

63

%

of

the time

for

head

nurses

of

high

workload

PACUs.

All

except

4

head

nurses

provided patient

care

at

least

50%

of

the

time,

and

a

few

head

nurses

noted

that

they

provided

patient

care

at

the expense

of

completing

their

administrative

duties

on

their

off-duty

time.

It

was

noted

that

in

very

small

PACUs,

the variable staff

also

serve

as

the

head nurse

and

wardmaster,

so

there

are

no

separate

fixed

staff

to

provide

additional

direct

patient

care

when needed.

However,

small

PACUs with

very

low

workload

are

less

likely

than

larger

PACUs

to

have

days

with

high

workload

that

cannot

be

managed

by

the

number

of

personnel

recommended

in

the

staffing

range.

The variability

in the

number

of

patients

seen

per

day at

small

PACUs

generally

is limited by

the

small

number

of

operating

rooms

at

the

MTF.

62

Objective

Three

The

third

research

objective

was

to

develop

guidelines

for

the

skill

mix

and

shift

distribution

of

nursing

personnel.

Together

with

the

staffing

range,

the

skill

mix

and

shift

distribution

make

up

the

staffing

profile.

Skill Mix

Skill

mix

refers

to

the

recommended

proportion

of

different

types

of

nursing personnel

to

provide

patient

care

on

a

nursing

unit.

The

professional:paraprofessional

skill

mix

refers

to

the

proportion

of

professional

to

paraprofessional

nursing

personnel

scheduled

to

work

in

the

unit

for

the

day.

Professional

nurses

include

civilian

and military registered

nurses.

Paraprofessional

nursing

personnel

include

civilian

licensed

practical

nurses

(LPNs),

military

practical

nurses

(91Cs),

civilian nurse

assistants

(NAs),

and military medical

specialists

(9lBs).

The

LPN:NA

skill

mix

refers to

the

proportion

of

military

and/or

civilian

practical

nurses

to nurse

assistants

and/or

medical

specialists.

Because

there were

no

empirically

based

skill

mix

standards

in

existence,

five

PACU

head

nurses were

selected

to

serve

on

a

panel

to

make

skill

mix

recommendations

for

the

staffing system.

Criteria

for

selection

of

the

panel

members

were

that

each

individual

had

to

be

a

registered

nurse with

a

minimum

of

one

year's

experience

as

a

head

nurse

in

a

PACU

in

the

AMEDD.

From

among

those

personnel

who

met

the

selection

criteria

for

the panel,

two

individuals

were head

nurses

at

U.S.

Army

Medical

Centers

(MEDCENs)

and

three

were

head

nurses at

medical

department

activities

(MEDDACs).

Four

panel

members

were

Army

Nurse

Corps officers,

and

one

was a

civilian

nurse.

The

panel

members

had

1

to

11

63

years

experience

in the

PACU

and

1

to

3

years

experience

as

a

PACU

head

nurse.

Two

panel

members

were

already

involved in

the

study

as study

coordinators

at

data

collection

sites.

A

packet

of

information

was

mailed

to

each

panel

member.

The

packet

consisted

of

(a)

the

American

Society

of

Post

Anesthesia

Nurses (ASPAN)

staffing

standards,

(b)

current

skill

mix recommendations

for

the

seven

inpatient

clinical areas

using

WMSN,

and

(c)

the

skill

mix

that

head

nurses

in

the PACUs

in

HSC reported

in

the

PACU

survey

as

using

and

as

recommending

for

use

in

their

unit.

After

studying

the

packet

of

information,

panel

members

mailed

their

skill mix

recommendations

with

their

rationale

for

their

recommendations

to

the

researchers.

The researchers

met

with panel

members

by

way

of

a

2-hour

conference

call

to

reach

group

consensus

on

the

skill

mix

recommendation.

Panelists

reached

a

group

consensus

that

the

ideal

professional:paraprofessional

skill mix

should

be

60:40,

although

some

panelists

initially

recommended

a

skill

mix

of

50:50.

Panelists

commented

that

the

PACU

is

a

critical

care

unit,

and a 60:40

skill

mix

is

consistent

with

the

WMSN

skill

mix

for

intensive

care

areas.

Also,

all

panelists

agreed

that the

potential

for

complications

anesthesia

or

the

surgical

procedure

during

the

immediate

post-operative

period

necessitates

having

at

least

as

many

professional

as

paraprofessional

nursing

staff

to

provide

patient

care.

The

panel

recommended

a

LPN:NA

skill

mix

of

60:40.

This

differs from

the

WMSN

intensive care

skill

mix

because

nursing

assistants

can

do

more

tasks--such

as

patient

transport--in

the

PACU

than

in

the

ICU.

The

larger proportion

of

LPNs

to

NAs

is

64

appropriate

for

the

immediate postoperative

period

because

of

requirements

for

continuous

patient

assessment

and

monitoring.

The

expert

panel's

recommendations

were

considered

by

the

researchers

together with

data

on

current

authorizations

of

nursing personnel

in

PACUs within

HSC.

It

was

noted

that

current

authorizations

for

PACUs

did

not

support

the

panel's

ideal professional:

paraprofessional

skill

mix.

The

average

authorization

professional:paraprofessional

skill

mix

was 45:55,

and

the average

authorization

LPN:NA

skill

mix

was

73:27

at

the

time

of

the

study.

Therefore,

the

final

recommendation

for

the

staffing system

was

that

a

minimum

of

50

%

of

the variable

staff

scheduled

daily

should

be

registered nurses.

That

is,

the

recommended

professional:paraprofessional

skill

mix

was

50:50.

The

recommended

LPN:NA

skill

mix

was

60:40.

Given

the LPN:NA

skill

mix

of

60:40, the

researchers

judged

a

professional:

paraprofessional

skill

mix

of

50:50

to

be

a

practical

and

sound

recommendation.

Shift Distribution

Shift

distribution

refers

to

the

allocation

of

nursing

personnel

to

work

in

turn

with

each

other

during

different

periods

of

time throughout

the

hours

of

operation

of

a

unit

(Bell

et

al.,

1985;

Luczun,

1984).

A shift

refers

to

a

group

of

nursing

personnel

who

are

assigned

to

work

during

a

particular

period

of

time,

such

as

0730

to

1600

or

0900 to

1730.

The

traditional

system

of

3

shifts

per

day

with

a

short

period

of

overlap

at

the

time

of

change

of

shifts

is

not

appropriate

for

a

PACU.

Instead,

PACU

nursing

staff

are

best

allocated

to

different

shifts

according

to

the

typical

variation

in

workload

throughout

the

day,

with

the

greatest

number

of

nursing personnel

scheduled

to

work

during

times

of

greatest

workload

65

(Bell

et

al.,

1985;

Luczun,

1984).

Therefore,

shift

distribution

guidelines

were

developed

based

on

an

indicator

of

workload

variation

for

the

six

study

sites.

Because

PACU

workload--as

measured

by

NCHs

per

day--has

been

shown

to

be

patient

volume

per

day,

the

hourly

patient

load

in

the

PACU

was

used

as

an indicator

of

workload.

That

is,

the

average

number

of

patients

in

the

PACU

for

each

hour

of

the

day

was

used

to

represent

the

typical

daily workload

pattern.

For

each

study site,

a

histogram

was

used

to

display

the

average

number

of

patients

for

each

hour

the

PACU

was

open

during

the

period

of

data

collection.

The

pattern

of

workload

throughout

the

day

for

all

study

sites

was

determined

by

a

visual

interpretation

of

the

data

displayed

in

Figure

6.

For

all

study

sites,

the

number

of

patients

(and

therefore

the

workload)

in

the

PACU

gradually

increased

over a

period

of

2

to

4

hours,

stayed

at a

relatively

high

level

for

4

to

5

hours,

and

then

gradually decreased

over

a

period

of

6

to

7

hours.

Data

obtained

from

the

PACU

survey

verified

that

this

pattern

of

workload

distribution

shown

throughout

the

day

at

the

study

sites

was

typical

for

all

PACUs

in

HSC.

This

pattern

of

workload

distribution

reflected

that

(a)

routine

operating

room

schedules

started

in

the

early

morning

and finished

by late

afternoon

or

early

evening

in

all

MTFs

within

HSC

at

the

time

of

the

study

and

(b)

the

average

workload

extended

later

in the

day

for

PACUs

that

had

a policy

of

opening

to

recover

emergency

cases

after

the

PACU's

normal

hours

of

operation

and/or

a

policy

of

providing

care

for

remain

overnight

patients

(RONs).

As

demonstrated

in

Figure

6,

the

average

workload

remained

higher

in

the

evening

for

study

site

6,

which

was

the

only

study

site

that

had

a

policy

of

providing

care

for

emergency

cases

throughout

the

night

and

also

a

policy

of

providing

care

for

RONs.

66

Average

Number

of

Patients

Per

Hour

7

6

5-

4

3

2

11

0

700 900

1100 1300

1500 1700

1900

2100

lime

of

Day

-*Site

1

ESite

2

-e-Site

3

--

Site

4 -*-Site

5

-*-Site

6

Figure

6.

Average

number

of

patients

per

hour

for

each

study

site.

67

The

pattern

of

gradually

increasing

and

then

decreasing

workload

in

the

PACU

throughout

the

day

supports

the

use

of

staggered

shifts

that

enable

nursing

personnel

to

be

distributed

according

to

each

PACU's

typical

variation

in

workload

throughout

the

day.

This

allows

for

most

nursing

personnel

to

be

scheduled

when

the

workload

is

expected

to

be

greatest.

It

also

allows

for

minimal

coverage

with

at

least

one

professional

and one

paraprofessional

staff

member

on

duty

during

periods

of

the

day

with the

lowest

expected

workload.

For

example,

the

average

shift

distribution

reported

on

the

survey

for

study

site

4

was

as

follows:

(a)

1

RN

or

1

91C/LPN

on

the

0730-1600

shift,

(b)

1-2

RNs and

2-3

9lCs/LPNs

on

the

0800-1630

shift,

(c)

1

RN

and

1-2

9lCs/LPNs

on

the

0930-1800

shift,

and

(d)

1

RN

and

1

91C/LPN

on

the

1100-1930

shift.

At

the

time

of

the

survey,

this

PACU

did not

have

any

nurse

assistants

(NAs)

assigned

to

the

unit.

Objective

Four

The

fourth

research

objective

was

to

develop

guidelines

for

adjusting

the

number

of

staff

during

periods

of

the

day

when

there

are

changes

in

the

typical

daily

workload

pattern.

The

staffing

adjustment

method

should

not

be

confused

with the

method

of

shift

distribution.

As

previously

stated,

shift

distribution

refers

to

the

allocation

of

nursing

personnel

to work

in

turn

with

each

other

during

different

periods

of

time

throughout

the

hours

of

operation

of a

unit

(Bell

et

al.,

1985;

Luczun,

1984).

The

staffing

adjustment

method

refers

to

a

procedure

used

to

increase

or

decrease

the

number

of

staff

during

periods

of

the

day

when

there

are

changes

in the

typical

daily

workload

pattern.

Conditions

that

occur throughout

the

day

resulting

in

changes

in the

typical

daily

workload

pattern

demand

a

temporary

reallocation

of

staff.

68

The

adjustment method is

based

on

the

fact

that

the

distribution

of

workload

throughout

the

day

varies

according

to

the

number

of

patients

to

be

taken

care

of

at

a

time.

Therefore,

PACU

nurses

need to

look

for

possible

changes

in

their

usual

number

of

patients

to

recover

at

the

same

time

in

the

PACU

when

they update

their

operating

room

schedule

throughout

the

day.

For

example,

if

several operating

rooms

have

more than

the

usual

number

of

short

cases scheduled

first

on

their

list,

there

will

be

an

increased

number

of

patients

to recover

in

the PACU

during

a

short period

of

time

in

the

morning.

Also,

there

may

be

several

emergency cases

added

at

midday

to

an

already

full

operating

room

schedule

resulting

in

more

than

the

usual

number

of

patients

to

recover

at

the

same

time in

the

afternoon.

Furthermore,

PACU

nurses

need

to use

their

clinical

judgment

to determine

the

point

at

which

the

number

and

type

of

increased

or

decreased

patients

expected

in

the

unit

represents

a

significant change

in the

typical

daily

workload pattern

such

that

a

temporary

adjustment

of

the

number

of

staff

to

provide

patient care

is

needed.

The staffing

adjustment

method

refers to two

simple

procedures that

head

nurses

can

use

to

increase

or

decrease

the number

of

staff

during periods

of

the

day

when

there

are

changes

in the

typical

daily

workload

pattern.

First,

a

shift

may

be

changed

to

start

earlier

or

later

so

that

more

staff

are

present

during the

time

of

increased

workload

and/or

fewer staff

are

present

during

the

time

of

decreased

workload. When

shifts

are

adjusted,

the

desired

skill

mix

needs

to

be

maintained.

Also,

a

minimum

of

one

professional

and one paraprofessional

staff

member

should

be

on

duty

whenever

patients

are

in

the

unit.

Second,

the

head

nurse

and

wardmaster

can

help

with

patient

care

during

periods

of

increased

workload and

perform

their

administrative

duties

during

periods

of

decreased

69

workload.

This is

a

reasonable

procedure

to

suggest

for

the

staffing

adjustment

method.

As

previously

discussed,

the

PACU

survey

revealed

that

head

nurses

of

PACUs

in

HSC

commonly

provided patient

care during

times

of

increased workload.

Also,

PACU

nurses

who

participated

in

the

study

indicated

that

it

was

common

practice

for

wardmasters

of

PACUs

in

HSC

to

provide patient

care

during times

of

increased

workload.

Objective

Five

The

fifth

research

objective

was

to

develop

a

method

of

checking

the

accuracy

of

information

collected

for

the

staffimg

system.

The procedure

that

was

developed to check

the

accuracy

of

information

collected

for

the

staffing

system

is

referred

to

as

the

audit

method.

The

reported

information

consists

of

the number

of

PACU

patients recovered

per

day

by

type

of

anesthesia received.

First,

the information

to be

audited

needs

to

be

collected.

All

nursing

personnel

should

be

instructed

in

the

procedure

for

recording

the

number

of

PACU

patients

seen

per

day

by

type

of

anesthesia

received.

Written

instructions

for

recording

this

information

and

a

sample

patient

volume

worksheet can

be

found

in

Appendix

H.

Personnel

need

to record

the

number

of

PACU

patients

seen

per

day

by

anesthesia

type.

All nursing

personnel

can

identify

patients

on

the

operating

room

schedule

who

are admitted to

the

PACU

and

record

the

type

of

anesthesia they

had.

Because

patients

who actually

arrive

in the

PACU

and

the

type

of

anesthesia they

had

often

differ

from

what

is

written

on

the

operating

room

schedule,

nursing staff

need to

be careful

to make

the

necessary

corrections

on

the

schedule

so

that

accurate

patient

volume

by anesthesia

type

can

be

recorded.

70

To

provide

consistency

in

the

data

collection

procedure,

it

is recommended

that

one

person

in

each

PACU

be

designated

as

the

unit

recorder.

The

recorder

should

be

able

to

interpret

the type

of

anesthesia

written

on

the corrected operating

room

schedule

and

accurately

record

numerical information.

The

recorder

is

responsible

for

recording patient

volume

by

anesthesia

type

on

a

patient

volume

worksheet and

for

entering this

information

into

an automated

system

that

will

be

used to

compute

daily

nursing

care

hours

(NCHs).

As

explained

in

greater

detail

in

Appendix

H,

the patient

volume worksheet

should

provide

space

for

recording

the number

of

patients

recovered

by

PACU nursing staff

for

each

day

by

the type

of

anesthesia received.

The

patient information that

has

been

collected

should

be

audited

at

least

once each

3

months. Thus,

there

would

be

at

least

one

audit on

data

submitted

for

each

quarterly

workload

profile.

Additionally,

an audit

should

be

performed whenever there

seems

to

be

a

discrepancy

between

the

number

and type

of

patients

who

are

being

cared

for

in

the

PACU

and

who

are being

reported

in the patient

volume information.

According

to

the audit

method,

the

head

nurse--or

another

registered

nurse

who

the

head

nurse

designates

as an

auditor--should

check one

day's

records

of

patients

recovered

in

the

PACU.

The

auditor

identifies

the

accuracy

of

the

patient

volume

and

type

of

anesthesia

for

each patient

by comparing

for

that

day (a)

the operating

room

schedule

that

has

been

corrected

by

the nursing staff

to

reflect

the

patients

who

were

admitted to

the

PACU

and

the

type

of

anesthesia they

received,

(b)

the

PACU's

patient

volume

worksheet,

and

(c)

the

standard

operating

room

form

(DA

Form

4107)

that

identifies

the

patient

and

the type

of

anesthesia

received.

71

Because

of

the

relative

simplicity

of

obtaining the

patient

volume

information,

100%

agreement

between

the operating

room

schedule,

the patient

volume

worksheet, and

DA

Form

4107

for

one

day's

records

of

patients

is

expected.

If

100%

agreement is

not

attained,

the reason

for

the

inconsistent

information

should

be

identified,

and

nursing

staff

should

be

given instructions

regarding any

problems

that have

been

identified

in

collecting

the

patient

volume

information.

Inconsistent

information may

be

caused

by inaccurate

recording

of

the

number

and/or

type

of

anesthesia

on

the

operating

room

schedule

or

patient

volume

worksheet

or

by

inaccurate

completion

and/or

interpretation

of

DA Form

4107.

It

may

be

the

PACU

or

operating

room

staff

or

the

auditor

who

did

not

record

or

interpret

the

information correctly.

After

the

PACU

head

nurse

or

another

designated

person has

provided

the

staff

with

the necessary

training,

the

audit

should

be

repeated

until

100%

agreement

between

the corrected

operating

room

schedule,

the

patient

volume

worksheet,

and

DA Form

4107 is

attained

for

one

day's

records

of

patients

recovered

in

the

PACU.

Additional

Analyses

Acuity

data

also

were

collected

for

153

remain

overnight

patients

(RONs),

who

were not

part

of

the

study sample

that

has

been

described

in

this

report.

RONs

were patients

who

remain

for

postoperative

care

in

the

PACU

from the

day

of

their

surgery

until the

following

morning.

All

RONs

were

at

study

site

6,

which

was

the

only

study

site

that

had

a

policy

of

staying

open

24 hours

to

provide

care

for

up

to

3

RONs

in

addition

to

patients

having

emergency surgery

during

the

night.

RONs

at this

site

were

described

as

patients

who

did

not

require

an

intensive

care

unit,

but

needed

closer

monitoring

than patients

on a

surgical

72

ward.

There

were

128

RONs

who

had

general

anesthesia,

22 RONs

who

had

regional

anesthesia,

and

3

RONs

who

had

local

anesthesia

over

the

16-week

data collection

period.

The

development

of

a

regression

model

to

predict

direct

care

time

from

patient volume

for

RONs

was

not

pursued

for

several

reasons.

First,

a

moderate

correlation

was

found

between

daily patient volume and

direct

care

hours

per

day

for

RONs

(r

=

.77)

as

opposed

to

the high

correlation

(Q

>

.90)

for

all

other

patients

in the

study.

Also,

there

were

only

a

small

number

of

RONs

in

the

study

(_n

=

153),

and all

RONs

were

from

one

study

site.

It

should

be

noted

that

the

workload

and

staffing

profiles

were

not

designed

to

account

for

nursing

staff

needed

to

care

for

RONs

throughout

the

duration

of

their

stay

in PACU.

At

the

time

of

the

study,

there

were

two PACUs

in

HSC

that

had

a

policy

of

staying

open

24

hours

to

provide

care

for

up

to

3

RONs

at a

time.

In

these

cases,

minimum

staffing

of

one

professional

and

one

paraprofessional

nursing

personnel

would

be needed

to

provide

care

for

RONs

during the

hours when

the

PACU

was

not

receiving

routine

post-anesthesia

patients.

For

example,

for

study

site

6,

it

was

estimated

that

additional

minimal

staff

would

be

needed

from

2000

in

the

evening

until

0700

the

to

provide

nursing

care

for

RONs

throughout

the

night. The

high

cost

of

staffing

a PACU

throughout the

evening

and night

hours

highlights

the

need

to

examine

the

policy

of

keeping

the

PACU

open

on

a

24-hour

basis

to

provide

care

for

a

few

RONs

throughout the night.

73

DISCUSSION

The

purposes

of

this

study

were

to

provide

an

acuity-based

method

of

determining

nurse

staffing

needs

for

PACUs

in the

AMEDD

and

to provide

a

method

of

analyzing

PACU

workload

variation.

In

this

section,

findings

the

research

objectives

are

discussed.

Objective

One

The

first

research

objective

was

to

develop

a

method

by

which

the

typical

workload

of

a

PACU

could

be

described

and

the

variation

in

workload

could

be

analyzed.

Because

of

the

strong

positive

relationship

between

patient

volume

and

direct

care

time

at

all

study sites,

a

regression

model

was

developed

to

predict

direct

care

time

from patient

volume.

Predictor

variables

were selected

that

yielded

the

simplest

adequate

model

to

predict

daily

direct

care

hours

from

patient

volume

information.

Using

patient

volume

to account

for

acuity

eliminated

use

of

the

acuity

worksheet

for

the

staffing

system.

PACU

nurses

will

spend

much

less

time

collecting

daily

patient

volume

information

for

their

staffing

system

than

they

would have

spent

completing

acuity worksheets.

Yet

the

staffing

system

is

still

based

on

a

sound

method

of

capturing acuity-based

workload

information

because

of

the

high

correlation

between

daily

direct

care

time

and patient

volume.

The

workload

profile

was

developed

to

be

used

with

NCH

data

over

a

3-month

period

of

time

using

2

SD

control

limits.

These

decisions

were

based

on workload

data

collected

from

six

study

sites

for

a

16-week

period

of

time.

Once

the

staffing

system

is

implemented

and

patient

volume

data

are

collected

over a

one-year

period

of

time,

the

variability

of

the

PACU

74

workload

should

be

examined

again

to

determine whether

there are

any

indications

for

changing

the

3-month

reporting

period

or

the

2

SD

control limits.

Head

nurses

can

use

the

workload

profile

to

help

them

monitor,

evaluate,

and

improve

the

workload

process

on

an

ongoing basis.

When

the

evaluation

of

the

workload

process

identifies opportunities

for

improvement,

head

nurses

can

make recommendations

for

change

based

on

their

workload

data.

Evaluation

of

the

effectiveness

of

any

changes

can

be

done

by

continuously

monitoring

the

workload

process.

Use

of

the

workload

profile

in

this

manner

will

enhance

the

head

nurse's

overall

program

to

continuously

assess

and improve

the

quality

of

care

in

the PACU

(Flarey,

1993;

Levin,

1993).

Head

nurses

should

not

view

the

workload

in

the PACU

in

isolation from

the

workload

in

other

units

in the MTF.

For

example,

the

OR's

workload

directly

influences

the

PACU's

workload,

and

the

PACU's

workload

directly

influences

the

workload

of

the

surgical

wards.

If

a

PACU's

workload

varies by

the

day

of

the

week

and

the high

workload

day

is Thursday

or

Friday,

this

pattern

of

workload

affects

the

surgical

wards

in that the

wards

may

have

to

increase

their

staffing

on

the

weekends

to meet

the patient

care

needs

of

the

increased

number

of

postoperative

patients

on

the

weekends.

Objectives

Two

and

Three

The

second

and

third

research

objectives

were

to

develop

methods

for

determining

the

number

of

nursing personnel

to schedule

on

a

daily

basis

and

to

develop guidelines

for

the

skill

mix

and shift

distribution

of

nursing

personnel.

The

staffing

range

that

is

provided

for

the

PACU

head

nurse on

a

quarterly basis

together

with

the

skill

mix

and

shift

distribution

75

guidelines

are

referred

to

as

the

staffing

profile,

which

represents

a

pattern

of

the

unit's

typical

staffing

needs.

The

staffing

range

refers

to

the range

of

nursing

personnel

to

schedule

on

a

daily basis

to

accomplish

a

unit's

workload.

This

number

of

nursing

personnel

is

reported

as

a range

so

that

head

nurses

can

schedule

their staff

according

to

expected

differences

in

workload.

Moreover,

head

nurses

should

use

the

workload

profile

to

analyze

variation

in their

workload

patterns

so

they

can

staff

their

units

more

efficiently.

For

example,

nurses

can

examine

why

certain

days

of

the

week

have

a

much

heavier

workload

and

require

more

nursing

personnel.

This

is

an important

consideration

in

that

head

nurses

could

more

easily

staff

all

days

with

their

staffing

range

if

they

had

a

more

consistent

workload

of

regularly

scheduled

surgeries

throughout

the

week.

Skill

mix

refers

to

the

recommended

proportion

of

different

types

of

nursing

personnel

to

provide

patient

care

on

a

nursing

unit.

A

50:50

professional:paraprofessional

skill

mix

and

a

60:40

LPN:NA

skill

mix

were

recommended

for

the

staffing

system

after

consideration

of

the

expert

panel's

recommendation

and

the

current

authorization

skill mix.

Head

nurses

using

the

staffing

system

should

note

the

skill

mix that

they

are

able

to

use

in

the

PACU

and

the

influence

that

this

skill

mix

seems

to

have

on

nursing

care

that

is

provided.

This

information

could

be

used

to

re-evaluate

the

recommended

skill

mix

after

the

staffing

system

has

been

used

for

one

year.

Shift

distribution

refers

to

the

allocation

of

nursing

personnel

to

work

in

turn

with

each

other

during

different

periods

of

time

throughout

the

hours

of

operation

of

a

unit

(Bell

et

al.,

1985;

Luczun,

1984).

Although

the

analysis

of

workload

data

collected

in

this

study

76

supported

the

use

of

staggered

shifts

in

the

PACU,

a system

of

staggered

shifts

is

not a

new

concept.

Most

head

nurses

reported

in

the

PACU

survey

that

they

were using

a

system

of

staggered

shifts

for

their unit.

Moreover,

experienced

head

nurses

who

participated

in

the

study

reported

that

they

were monitoring

their

typical

daily

workload

pattern

and

staggering

their

shifts

accordingly.

Head

nurses

can

determine

how

best to stagger

their

shifts

by determining

the

typical

distribution

of

their

workload

throughout

the

day.

The

average

number

of

patients

in

the

unit

for

each

hour

of

the

day can

be

estimated

by

using

an

hourly

count

of

the

number

of

patients

in the

PACU

for

each

hour

the

PACU

is

open.

The number

of

patients

in

the

unit

is

counted

once

each

hour

(e.g.,

at

0730, 0830,

0930,

1030,

etc.)

for

3

to

4

weeks.

At

the

end

of

this

period

of

time,

the

average

of

each

hourly

count

is

calculated. The

average

number

of

patients

for

each

hour

of

the

day

can

be

graphed

to

obtain

the

unit's

typical

distribution

of

workload

throughout

the

day.

Objective

Four

The

fourth

research

objective

was

to

develop guidelines

for

adjusting

the

number

of

staff

during

periods

of

the

day

when

there

are

changes

in

the

typical

daily

workload

pattern.

These

guidelines

are

referred

to

as

the

adjustment

method.

Again,

the

adjustment

method

is

not

a

new

concept

for

the

PACU.

Experienced

head

nurses

reported

that they

had

used

this

method

to

provide

adequate

patient

care during

times

of

increased

workload.

However,

the

findings

in

this

study

regarding

the

relationship

of

direct

care

time

to

patient

volume

support

the

use

of

a

staffing

adjustment

method that is

based

on

the

number

of

patients

needing

77

nursing

care

at

any

given

time.

Moreover,

a

formalized

method

of

staff adjustment

becomes

another

tool

that

nurses

can

use

to

manage

their

unit.

This

is

especially

important

during

the

present

time

of

cost

constraints when

there

is no

pool

of

personnel

available

to

work

in

the

PACU

during

short

periods

of

increased

workload.

Objective Five

The fifth

research

objective

was

concerned

with

developing

an

audit

method,

which

consists

of

a

simple

procedure

for

checking

the

accuracy

of

information

collected

for

the

staffing system.

The

information

needed

for

the

staffing system

consists

of

the

number

of

PACU

patients

recovered

per

day

by

type

of

anesthesia

received.

All

staff members

should

be

educated

in the

procedure

used

for

collecting

the

necessary

patient

information

for

the

staffing

system

so

they

can

plan

and

conduct

their

own

audits.

Providing

nurses

with

a

simple

method

of

conducting

their

own audit

at

least

once

each

quarter

and

more

frequently

at

their

own

discretion

helps

them

manage

their

staffing system

at

the

unit

level.

78

CONCLUSIONS

A

scientifically

sound

but

clinically

practical

approach

was

used

in

this

study

to

develop

a

Post

Anesthesia

Care

Staffing

System (PACS)

for

PACUs

in

the

AMEDD.

PACU

head

nurses

in

the

AMED

can

use

the

staffing

profile

together

with

the

skill

mix

and

shift

distribution

guidelines

to

determine

the

number

and type

of

nursing

personnel

needed

to

meet

their

unit's

patient

care

needs

on a

day-to-day

and

shift-by-shift

basis.

Also,

the

staffing

adjustment

guidelines

can

be

used

as

a

practical

measure

to

maximize

existing

nursing

resources

during

times

of

unexpected

variation

in

workload

throughout

the

day.

Because

nursing

services

are

the largest

consumer

of

personnel

in

medical

treatment

facilities

(MTFs),

section

supervisors

and

chief

nurses

of

MTFs must be

able

to

justify

nursing

staff

expenses

and maximize

existing

nursing resources

with

a

staffing

system

such

as PACS.

Additionally,

head

nurses

can

use

the

workload

profile

to

continually

monitor

and

improve

their

workload

process.

Nursing

personnel

at

the

unit

level

are most

familiar

with

the

intricacies

of

the

workload

process

in their

PACU.

Thus,

they

are

in

the

best

position

to

interpret

the

workload

profile

and

search

for

ways

to

improve

the

workload

process.

79

RECOMMENDATIONS

First,

it

is recommended

that

the

nurse

staffing

system

outlined

in this

study

be

accepted

as

the

Post

Anesthesia

Care

Staffing

System

(PACS)

and

be

implemented

in

all

PACUs

in

the

AMEDD.

PACU

personnel

can

record

the

number

of

patients

recovered

in

their

unit

per

day

by

anesthesia

type

and

enter

this

information

into

an

automated

system,

which

can

be

used

to

calculate

NCHs

per

day.

An

individual

at

HSC

(now

reorganized

as

the

U.S.

Army

Medical

Command

or

MEDCOM)

who

is

designated

to

manage

the

staffing

system

can

use

statistical

process

control

software

to

create

the workload

and staffing

profiles.

This

system

manager

can

use

the

workload

profiles

to compare

the

workload

of

different

groups

of

PACUs,

such

as

all

low

workload

sites.

However,

it

is

important

that the

workload

and

staffing

profiles

be

sent

back

to

the

head

nurses

in

a

timely

fashion

so

they

can

evaluate

their

staffing

needs.

Additionally,

head

nurses

can

use

the

workload

and

staffing

profiles

to

monitor

and

evaluate

their

workload

process

on

an

ongoing

basis.

Second,

it

is recommended

that

a

follow-up

study

be

conducted

after

nursing

workload

data

have

been

collected

with

the

PACS

for

one

year.

The

system

manager

at

HSC

could

be

the person

to

conduct

the

study.

One

purpose

of

the

study

would

be

to

determine

whether

workload

data

obtained

over

a

one-year

period

of

time

would

indicate

a

need

to

adjust

the

method

used

to

develop

the

workload

and

staffing

profiles. Another

purpose

would

be

to

determine

if

there

are

trends

in

the

workload

data

based on

events

such

as

the timing

of

surgical

residencies.

Results

of

the

study

would

be used

to adjust

the

staffing

system

methodology

as needed

and

to

estimate

future

PACU

workload

for

purposes

of

planning

long-term

staffing

and

budget

needs.

80

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84

"APENDIX

A

O'Donnell

and

Seipp's

Nursing

Workload

Model

85

LuO~

0

iiCO

-J:

U~Uj

oL

COa

1:

1

z

-LJ

co.

CD-JW

J

4

30)

...............

'5Li

CF

j.C

OC

LCu

Lu

L

0L

LI

CO

0

LU

C0

0)

86

APPENDIX

B

PACU

Acuity

Worksheet*

*Typographical

errors

were

found

in

three

critical

indicators

on

the

PACU

acuity

worksheet

as

it

was

published

in

the

original

PACU

technical

report

(Catty

et

al.,

1991).

The

following

corrections

were

made

before

the

acuity

worksheet

was

used

in

this

study:

(a)

"Suctioning--all

types"

was

corrected

to

"Suctioning--oral";

(b)

"Dressing

change,

small

(•54"

by

8")"

was

corrected

to

"Dressing

change,

small

(<4"

by

8")";

and

(c)

"Dressing

change,

large

(>4"

by

8")"

was

corrected

to

"Dressing

change,

large

(>

4"

by

8")."

87

0

6

z

-

I

u(U

-

I

o

c

LU

f

'U

t

0

C-

B

4ý

4;c

II

4m_

0

c c

E

-

- -

-

LU

c

o

t

S-~

-C

-

00

E

EV

TD

LUJ

-0

EU

-E

~

'

co

4)

0

4

)

0

D--

Ix~

0i~

>

ix-

.E

ox

k'

a'

tA

IL

o

LU

6.E~.

0

.

~

E

~

-

1=

FAU

0

>>-

-

-1

1

rI

?-,

Lz

0

_0

u

z

I I Iell

01

0 -C

0

U-

c..

ui

LU

C

3

C

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EE

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z

L0

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c

m C

w CE

03-

LU

m~

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--

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u

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0

W

CU

uoc

CU

.!

0

4A~

0

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%n

4Az

CO'M

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A C89

APPENDIX

C

Guidelines

for

Using

the

PACU Acuity

Worksheet

90

WORKLOAD

MANAGEMENT

SYSTEM

FOR

NURSING-

POST

ANESTHESIA

CARE

UNIT

ACUITY

WORKSHEET:

GUIDELINES

FOR

USE

1.

Introduction:

The WMSN-PACU

worksheet

is

used

to

document

how

frequently

certain

direct

nursing

care

activities

occur.

The

nursing

activities

listed on

the

worksheet

do

not

cover

all

the nursing

activities

that PACU

nurses

do

for

their

patients.

Rather, the

activities

listed

are

those

that

best

account

for

the

total

direct

nursing

time

spent caring

for

PACU

patients.

This

information

is

used

to

classify

patients

according

to

their

acuity.

The

worksheet

has

three

sections

to

complete.

a.

Section

I

(General

Information)

contains

general

information

such

as

the

date

and

time

of

admission

and

discharge/transfer.

b.

Section

II

(Initial

Assessment)

refers to

a series

of

nursing

care

activities

that

are

done

for

patients

as

soon

as

they

enter

the

PACU.

Some

patients will

require

all

of

the

following

nursing

activities

when they

enter

the

PACU,

whereas

other patients

will

require

only

a few

of

them:

*

Insure

airway

patency,

assess

respiratory

status,

initiate

oxygen

therapy

and stir-up

routine

as

needed,

and

orient

to

unit;

*

Check

and

record blood

pressure,

pulse, respirations,

temperature,

and

neurological

and/or

motor-sensory

responses;

"*

Connect

the patient

to

the pulse

oximeter and

cardiac

monitor

and

record

observations;

"*

Assess

integrity

of

IV/central/arterial

lines,

place

IV

fluids/blood

products

on

IV pole,

check

amount

of

fluids

in bag(s), and

check

flow

rate;

*

Assess

patient's

total

condition,

inspect

dressings and

drains,

assess

patient's

body

position,

and

reposition

if

necessary;

*

Receive

report

from

anesthesia

personnel,

report

baseline measurements

(PARS)

to

anesthesia

personnel,

and

record

initial

assessments

on

flow

sheet

or

appropriate

form.

91

The

amount

of

nursing

time

for

the

initial

assessment

has

been found

to

vary

according

to

the

type

of

anesthesia

used

(e.g.,

it

takes

longer

to

do

the

initial

assessment

of

a

patient

receiving

a

general anesthesia

than

a

patient

receiving local

anesthesia).

Therefore,

check

the

type

of

anesthesia

used (general,

spinal/regional,

or

local)

to

account

for

the

appropriate amount

of

nursing time

for

the

initial

assessment.

c.

Section

MI

(Multiple

Occurring

Activities)

lists

nursing

care activities

that

you

do

for

your

PACU

patients

throughout

their

stay

in

PACU.

Each

time

you

complete

one

of

these

activities,

place

a

tick

mark

in the

appropriate

space.

The tick

marks

will

be

added

up

when

a patient

is

discharged

or

transferred.

2.

Starting

the

Worksheet:

Start

a

separate

worksheet

for

each

patient

admitted to

PACU.

It

is

important

to

keep

the

worksheet

near

the

patient

while

in

the

PACU

so

all

nursing

personnel

can use

it

to

mark

completed

nursing

activities.

a.

Stamp

the

worksheet

with the

patient's

identification

plate

in the

bottom

left

hand

corner.

Make

sure

all information

on

the

stamp

plate

is legible.

b.

Write the

date

and

time

of

admission

in

Section

I.

Use military

time.

c.

Mark

only

ONE

block

in

Section

H.

1)

Mark

General

anesthesia for

the

patient

who

received

general

anesthesia

OR

general

anesthesia

piu

spinal/regional

anesthesia

OR general

anesthesia plus

local

anesthesia

and/or

sedation.

2)

Mark

Spinal

or

regional

anesthesia for

the

patient

who

received

spinal

or

regional

anesthesia

OR

spinal/regional

anesthesia plus

local

anesthesia

and/or

sedation.

3)

Mark

Local

anesthesia

and/or

sedation

for

the

patient

who received

local

anesthesia

and/or

sedation.

3.

Using

the

Worksheet:

In

Section

II,

mark

all nursing

care activities completed

during

the

patient's

stay

in

PACU.

Place

one

tick

mark

in

the

area

labeled

"Counting

Area"

each

time

you

complete

one

of

the

identified

nursing

activities.

a.

Keep

the

worksheet

near

the

patient

so

you

can

mark

activities

as

they occur.

All

nursing staff

providing

care

for

the

patient

are

responsible

for

marking

completed activities.

b.

Record

the

mark

in

the block

labeled

for

the

appropriate

shift.

Use

the

night

shift

block

for

all

activities

completed

from

2300

until

0700

hours,

the

day

shift

block

for

all

activities

completed

from

0700

until

1500

hours,

and

the

evening

shift

block

for

all

activities completed

from

1500

until

2300

hours.

For

example,

if

you

admit

a patient

to PACU

at

1400

92

hours,

mark

activities completed

before

1500

hours

in

the

day

shift

block,

and

mark

activities

completed

at

or

after

1500

hours

in

the

evening shift

block.

c.

It

will

be

easier

to

total the

marks

if

you

avoid

stray

marks and

record

the tick

marks

in

groups

of

five.

Review

the

worksheet at the end

of

your

shift

or

when

the

patient

has

been

discharged/transferred

to

assure

that

all

completed

nursing

activities

have

been marked.

4.

Continuing

the

Worksheet:

Start

a

new

worksheet

for

patients

who

remain

in

the

PACU

after

2400

hours.

a.

Stamp

a new

worksheet

using the

patient's

identification

plate.

b. Write

the

new

date

in Section

I.

c.

Leave

the

time

of

admission

blank.

(The

patient

has already

been

admitted).

d.

Check the

"yes"

box

for

"Continuation

Sheet"

located

in

Section

I.

e.

Do

not

complete

Section

II

on

the

new

worksheet. (The

initial

assessment

was

already

done

on

admission

to

PACU).

5.

Finishing

the

Worksheet:

a. When a

patient

is

discharged

or

transferred:

1)

Write

the time

of

discharge/transfer

from the

PACU

in

Section

I.

2)

Total

the

tick

marks

for

each

nursing

care

activity

in the

counting

area

in

Section

M

and

write

the

total in the

"Total No."

column

for

each

nursing activity.

3)

Remove

the

worksheet

from

the

patient's

record before

transferring

or

discharging

the

patient.

4)

Give

the

worksheet

to

the

charge

nurse

to

review

for

legibility

and

completeness.

b.

When a

patient

remains

in

PACU

after

2400

hours:

1)

Add

the

marks

in

each counting

area

in

Section

MI"

and

write

the total

in the

"Total

No."

column

for

each

nursing

activity.

2)

Give

the totaled

worksheet to

the

charge

nurse

to

review

for

legibility

and

completeness.

3)

Start

a

new

worksheet.

Refer

to

the

section,

"Continuing

the

Worksheet."

93

6.

Reviewing

Finished

Worksheets:

The

charge

nurse

reviews

completed

worksheets

to

assure

that:

a.

each

worksheet

is

stamped

with

the

patient's

identification

plate

and

all

information

is

legible;

b.

each

worksheet

has

the

correct

date,

time

of

admission

and discharge

or

transfer,

and

marking

of

continuation

sheet

in

Section

I

as

appropriate;

c.

only

one

block

is

marked

in

Section

II

to

indicate

type

of

anesthesia

used;

d.

tick

marks

in

Section

MI

are

accurately

totaled.

The

charge

nurse

on

each

shift

verifies

that

the

worksheets

are

legible

and

complete

by

initialling

the

appropriate

space

in

the

bottom

right

hand

corner

of

the

sheets.

Store

completed

worksheets

in

a

safe

location

designated

by

the

PACU

Head

Nurse.

94

WORKLOAD

MANAGEMENT

SYSTEM

FOR

NURSING-

POST

ANESTHESIA

CARE

UNIT

ACUITY

WORKSHEET:

OPERATIONAL

DEFINITIONS

Section

II:

Initial

Assessment

Initial

assessment

refers

to

a

series

of

continuous

nursing

activities

that

are

done

for

patients

as

soon

as

they

enter

the

PACU. The

assessment

begins

when

a

nursing

staff

member

starts

any

one

of

the nursing

care

activities

listed

below

and

ends

when

the

continuous

nursing

activities

stop.

Some

patients

will require

all

of

the

following

nursing

activities

when

they

enter the PACU,

whereas

other patients

will

require

only

a

few

of

them:

*

Insure

airway

patency,

assess

respiratory

status,

initiate

oxygen

therapy and

stir-up

routine

as needed,

and

orient

to unit;

*

Check

and

record blood

pressure,

pulse,

respirations, temperature,

and

neurological

and/or

motor-sensory

responses;

"*

Connect

the

patient

to

the

pulse

oximeter

and

cardiac

monitor

and

record

observations;

"*

Assess

integrity

of

IV/centrallarterial

lines,

place

IV

fluids/blood

products

on IV

pole,

check amount

of

fluids

in

bag(s),

and check

flow

rate;

*

Assess

patient's

total

condition,

inspect

dressings

and

drains, assess

patient's

body

position,

and

reposition

if

necessary;

*

Receive

report

from

anesthesia

personnel,

report

baseline

measurements

(PARS)

to

anesthesia

personnel,

and

record

initial

assessments

on

flow

sheet

or

appropriate

form.

1.

General

anesthesia:

Mark

if

the

nursing

activities are

performed

for

a

patient

who

received

general

anesthesia

OR

general

anesthesia

plus

spinal/regional

anesthesia

OR

general

anesthesia

plus

local

anesthesia

and/or

sedation.

2.

Spinal

or

regional

anesthesia:

Mark

if

the

nursing

activities

are performed

for

a

patient

who

received

spinal

or

regional

anesthesia

OR

spinal/regional

anesthesia

plus

local

anesthesia

and/or

sedation.

3.

Local anesthesia

and/or

sedation:

Mark

if

the

nursing

activities

are

performed

for

a

patient

who

received local anesthesia

and/or

sedation.

95

Section

III:

Multiple

Occurring

Activities

A.

PACU

Parameters

1.

Stir-up

routine:

Includes

time

to

instruct

patient

to

cough

and

deep

breathe,

answer

questions

about

surgery,

re-orient

to

place

and

time,

assess

level

of

comfort,

determine

if

patient

can

be

medicated

for

pain,

give

fluids

if

permitted,

and leave

the

area.

2.

Vital

signs:

T,

P,

R,

and

B/P:

Includes

time

to

place

equipment

at

bedside;

obtain

temperature,

pulse

rate,

respiratory

rate,

blood

pressure, and

02

saturation;

record

results

of

measurements;

and

remove

equipment

from

area.

OR

P,

R,

and

B/P:

Includes

time

to

place

equipment

at

bedside;

obtain

pulse rate,

respiratory

rate,

blood

pressure,

and

02

saturation;

record results

of

measurements;

and

remove

equipment

from

area.

3.

Motor/sensory

testing:

Includes

time

to

assess

extremities

for

sensation

awareness

and

muscle strength,

record

results,

and leave

the

area.

4.

Neuro

assessment:

Includes

time to

adjust

room

lights and

check

pupillary

reflexes

with

flashlight;

make

inquires within

the

framework

of

interviewing that

will

give

information

about

the

patient's

orientation,

memory,

intellectual

performance,

and

judgment;

assess

extremities

for

sensation

awareness

and

muscle strength;

record

results;

and

leave

the

area.

5.

Circulation/pulse

checks:

Includes

time

to

check

extremity

for

pulse (rate

and

strength),

swelling,

numbness,

and

tingling;

evaluate

temperature

and

color

of

the

skin;

assess

the

patient's

ability

to

move

the part;

record

results;

and

leave

the area.

6.

Monitor

adjustments:

Includes

time

to

attach

monitor

(e.g.,

cardiac

monitor

or

pulse

oximeter)

to

patient

and

set

or

change

alarm

settings;

readjust

devices attached

to

patient

(not

just

turning

off

alarm);

and

leave

the

area.

7.

Measure

output:

Includes

time

to place

calibrated

cylinder

or

container

at

bedside;

measure

and

record

output

of

urine,

emesis,

or

any

type

of

drainage;

and

remove

equipment

from

area.

8.

Nausea/emesis

care:

Includes

time

to

position

patient

to

protect

airway

and/or

hold

emesis

basin

for

those

patients

experiencing

nausea,

retching

and/or

vomiting;

provide

oral

care

when

necessary

(cleanse

mouth

with appropriate

agent);

and

remove

equipment

from area.

[Also

mark

"Measure

output"

for

measuring

and

recording

emesis

at

bedside.]

96

B.

IV

Therapy

1.

IV

bottle

change

with

flow

rate

adjustment:

Includes

time

to

place

equipment

at

bedside,

remove

used

IV

container and

replace

with

new

container,

calculate

and adjust

flow

rate,

and

remove

equipment

from area.

2.

IV

medication:

Intravenous-IV

push:

Includes

time

to

place equipment

at

bedside,

select

site

for

injection of

medication

utilizing

existing

system,

administer

medication,

record

in chart, and remove

equipment

from

area;

OR

Intravenous piggy-back:

Includes

time

to

place

equipment

at

bedside,

select

site

for

administration

of

solution

utilizing existing

system,

hang medication and adjust flow

rate,

record

on

Intake

and

Output Record, and

remove

equipment

from

area.

3.

IV

insertion:

Includes

time

to

place

equipment

at

bedside;

apply

tourniquet

to

extremity;

cleanse

site;

perform

venipuncture; connect

IV

tubing;

apply

ointment

and

dressing

and tape

securely;

time,

date and

initial

dressing; calculate

and

regulate

flow

rate;

record

on

Intake

and

Output

Record;

and remove

equipment

from

area.

4.

IV/arterial

line

blood

sample:

Includes

time

to

place

equipment

at

bedside,

clear

system,

obtain blood

sample

through

stopcock,

flush

system,

label

samples,

and

remove

equipment

from

area.

C.

Procedures

1. Oxygen

administration

(Initial

and/or

adjustment): Includes

time

to

place

equipment

at

bedside,

turn

on

oxygen,

fit

the

mask over

the

mouth

and

nose

or

fit

nasal

prongs,

adjust

headband,

regulate

oxygen

flow

rate,

evaluate

fit

and

patient's

response

to

oxygen

and

equipment, and

leave

the

area.

[Does

not

include

oxygen administration

during

the initial

assessment.]

2.

Suctioning

-

oral:

Includes

time

to

place

or

set

up

equipment

at bedside,

suction

oral

cavity

with suction

catheter/oral

suction

tip, flush

catheter

before

and

after

each aspiration,

and

replace

or

remove

used

equipment

from

area.

3.

Urinary

catheterization:

Indwelling-catheterization: Includes

time

to

place

equipment

at

bedside,

prepare patient,

insert

indwelling

catheter,

inflate balloon, tape catheter

in

place,

connect

to

urinary

drainage

bag,

and

remove used

equipment

from area.

[Also

mark

"Measure

output"

when

measuring

and

recording

urinary

output

at

bedside.]

97

OR

Straight-catheterization:

Includes

time

to

place

equipment

at

bedside,

prepare

patient,

insert

catheter,

empty

bladder,

remove

straight

catheter,

and

remove

used

equipment

from

area.

[Also

mark

"Measure

output"

when

measuring

and

recording

urinary

output

at

bedside].

4.

Venipuncture

-

blood

sample:

Includes

time

to place

equipment

at

bedside,

apply

tourniquet

to

extremity,

cleanse

site,

perform

venipuncture,

withdraw

blood

sample,

apply

pressure

to

puncture

site,

apply

labels

on

blood

tubes,

and

remove

equipment

from

area.

5.

Dressing

change,

small

(less

than

4"

by

8"): Includes

time to

place equipment

at

bedside,

remove

soiled

dressing,

cleanse

skin,

apply

dressing

to

site,

and

remove

equipment

from

area.

6.

Dressing

change,

large

(equal

to

or

larger

than

4"

by

8"):

Includes

time

to

place

equipment

at

bedside,

remove

soiled

dressing,

cleanse

skin,

apply

dressing

to

site,

and

remove

equipment

from

area.

7.

EKG

-

rhythm

strip

or

12-lead:

Includes

time

to

place

equipment

at

bedside;

prepare

equipment

for

use;

apply

leads;

obtain

rhythm

strip

or

12-lead

EKG;

remove

leads;

record

name,

date

and

time;

and

remove

equipment

from

area.

D.

Support

Activities

1.

Patient

position

change:

Includes

time

to

a)

remove

support

pillows,

reposition

patient,

and

apply

support

pillows

for

reasons

of

comfort

and/or

b)

assist

with

positioning

and

removal

of

x-ray

film

and leave

the

area.

2.

Incontinent

care:

Includes

time

to

place

equipment

at

patient's

bedside,

bathe

buttocks,

perineum,

and

thighs;

change

bedding;

and

remove

equipment

and

soiled

linen

from

area.

3.

Occupied

bed

change:

Includes

time

to place

linen

at

bedside,

turn

patient

on

side,

roll

linen

to

one

side

of

bed,

replace

with

clean

linen,

turn

patient

to freshly

made

side

of

bed,

remove

soiled

linen,

complete

bed

making,

and

remove

soiled

linen

from

area.

98

APPENDIX

D

PACU

Indirect

Care

Multiplier

Formula

99

HSHN-H

(5-5c)

4

June

1993

MEMORANDUM

FOR

HQDA

(DASG-CN),

5109

Leesburg

Pike,

Falls

Church,

VA

22041-3258

SUBJECT:

Indirect

Care

Multiplier

Formula

for

Post

Anesthesia

Care

Units

1.

This

is a

decision

paper.

2.

PURPOSE.

Provide

approval

of

the

method

used

to

calculate

the

indirect

care

multiplier

(ICM)

in

the

Post

Anesthesia

Care

Unit

(PACU)

staffing

system.

3.

DISCUSSION.

a.

The

ICM

and

direct

care

time

are

used

to

calculate

total

nursing

care

hours

and

staffing

levels.

The

Perdue

report

(1990)

"Evaluation

of

the

Methodological

Issues

of

the

Major

Studies

in

the

Development

of

the

WMSN

Patient

Classification

System"

provided

the

recommended

ICM

formula.

It

is

derived

correctly

and

accurately

demonstrates

the

relationship

between

the

direct

and

indirect

components

of

available

staff

time.

It is

the

appropriate

formula

to

apply

to variable

nursing

care.

b.

This

diverges

from

the

formula

used

in

the

Workload

Management

System

for

Nursing

(WMSN).

That

formula

is

more

appropriately

applied to

regularly

occurring

activities,

such

as

time

schedule

preparation.

Use

of

the

current

WMSN

ICM

formula

in

the

PACU

staffing

system

would

underrepresent

the

number

of

recommended

staff

(TAB

B).

4.

RECOMMENDATION.

Recommend

that

Brigadier

General

Adams

sign

proposed

Ist

Endorsement

at

TAB

A.

ORIGINAL

SIGNED

2

Encls

WILLIAM

B.

YORK,

JR.

1.

TAB

A

(Proposed

1st

End)

Colonel,

MC

2.

TAB

B

(ICM

Formula)

Director,

HCSCI

100

DASG-CN

(HSHN-H/4

Jun

93)

(5-5c)

1st

End

LTC

Zadinsky/er/AV

471-0278

SUBJECT:

Indirect

Care

Multiplier

Formula

for

Post

Anesthesia

Care

Units

Office

of

the

Chief,

Army

Nurse

Corps,

Room

623,

Skyline

Five,

5109

Leesburg

Pike,

Falls

Church,

VA

22041-3258

FOR

Director,

Directorate

of

Health

Care

Studies

and

Clinical

Investigation,

Building

2268,

Fort

Sam

Houston,

TX

78234-

6100

This

action

has

been

Approved/Disapproved

OBI[MiNAL

SIGNED

Encl

NANCY R.

ADAMS

nc

Brigadier

General,

AN

Assistant

Surgeon

General/

Chief,

Army

Nurse

Corps

101

PACU

Indirect

Care

Multiplier

Formula

1.

The

WMSN

ICM

formula

is:

1

+ %

indirect

time.

The

Perdue

formula

is:

1

+ (%

indirect

/

1

%

indirect).

2.

The

table

demonstrates

that

for

12

hours

of

direct

care,

the

WMSN

formula

produces

less

than

half

the

number

of

staff

produced

by

using

the

Perdue

formula.

Formula

ICM

Nursing

Care

Recommended

Hours

Staff

Perdue

4.31

51.72

6.5

WMSN

1.77

21.24

2.7

102

APPENDIX

E

PACU

Survey

103

MTF

July

1992

Development

of

an

Acuity-Based

Nurse

Staffing

System

for

Post Anesthesia

Care

Unit

(PACU)

Instructions:

Please

answer

the following

questions

by

filling

in

the

blank

or

circling

the

answer

that

applies

to

you

and

your

PACU.

Please

answer

every

question.

If

the

question

is

not

applicable

to

your

PACU,

please

state

NA.

If

you

need

more

room

for

your

responses,

use

the

reverse

side

of

the

paper.

In

addition

to

returning

your

survey,

please

send

us

copies

of

your

monthly

MEPERS

reports

for

the

last

year

(the

report

that

lists

the

number

of

patients

recovered

per

month

in

your

PACU

for

each

clinical

service).

Medical

Treatment

Facility

1.

How

many

Operating

Rooms

does

your

facility

have?

2.

What

are

the

normal

working

hours

of

the

Operating

Room?

a.

Monday

through

Friday

to

b.

Saturday

to

c.

Sunday

to

3.

How

many

operational

beds does

your

PACU

have?

4.

What

are

the

normal

hours

of

operation

for

your

PACU?

a.

Monday

through

Friday

to

b.

Saturday

to

c.

Sunday

to

5.

Who

recovers

your

PACU

patients

after

normal

duty

hours?

(Circle

all

that

apply

and

explain.)

a.

SICU/critical

care

staff

in

their

unit

b.

On-call

PACU

staff

in

the

PACU

c.

On-call

PACU

staff

in

SICU/critical

care

unit

d.

Other

(please

specify)

104

6.

Which

best

describes

the

physical

lay-out

of

your

PACU?

a.

Separate

unit;

have

beds

designated

solely

for

PACU

patients

b.

Combined

unit;

share

beds

for

PACU

patients

with

another

unit

(specify

type

of

unit__

c.

Other

(please

specify)

7.

Is

your

PACU

used

as

overflow

for

critical

care

patients

(e.g.,

patients

may

be

scheduled

to

be

recovered

in

SICU

but

are

cared

for

in

PACU

because

there

are

no

available

beds

in

SICU,

etc.)?

If

so,

what

is

your

estimate

of

how

many

overflow

patients

you

have

per

month

in

your

PACU?

How

does

this

influence

your

nursing

workload?

8.

Which

clinical

areas

other

than

the Operating

Room

use

the

PACU

for

recovery

of

patients

(e.g.,

special

procedures

done

in

a

clinic,

surgeries

done

somewhere

other

than

the

Operating

Room,

etc.)?

Clinical

area

Type

of

procedure

AveraQe

#

patients/month

a.

b.

c.

d.

e.

105

9.

Where

is

your

PACU

located

in

relation

to

the

Operating

Room

and

the

SICU?

Please

explain

how

this

location

influences

your

ability

to

obtain

help

from

anesthesia

and

nursing

staff

in

special

situations.

10.

Does

your

facility

have

a Same

Day

Surgery

or

Ambulatory

Surgery

Center?

If

so,

about

how

many

Same

Day

Surgery

patients

do

you

recover

in

your

PACU

per

month?

Do

these

patients

present

any

special

problems

that

influence

your

nursing

workload

(e.g.,

Do

you

ever

have

to

discharge

Same

Day

Surgery

patients

to

home)?

If

you

don't

have

a

Same

Day

Surgery

unit

now,

do

you

anticipate

one

in

the

near

future?

Anesthesia

Personnel

1.

How

many

anesthesiologists

and

nurse

anesthetists

are assigned

to

your

facility

(not

including

those

in

training)?

2.

Does

your

facility

have

a

training

program

for

anesthesiologists

or

nurse

anesthetists?

3.

What

Medical

Officer

is in

charge

of your

PACU?

How

does

he/she

influence

your

PACU

and

your

nursing

workload?

Please

explain.

106

Nursing

Staff

1.

Who

is

your

immediate

first-line

supervisor/rater

(e.g.,

Head

Nurse,

SICU;

Chief,

Surgical

Nursing

Section,

etc.)?

2.

Within

the

Department

of

Nursing's

organizational

structure,

which

clinical

nursing

section

does

your

PACU

belong

to?

3.

How

many

nursing

personnel

do

you

have

for

your

PACU

(including

Head

Nurse

and

NCOIC

but

excluding

Agency/Contract

nurses)?

Authorized

Assicrned

ANC

Other

RNs

91C

LPN

91A

91B

Nursing

Assistant

4.

Does

your

unit

share

staffing

with

another

nursing

unit?

If

so,

which

unit?

5.

List

the

number

of

Agency/Contract

nurses

you

routinely

use

each

week

and

the

number

of

hours

each

nurse

works

per

week.

Do

the

contract/agency

nurses

present

any

special

problems

for

you

in

regard

to

your

workload

and/or

staffing

(e.g.,

how

much

advance

notice

do

you have

to

give

in

order

to

use

them)?

6.

What

is

the

average

percentage

of

time

you,

as

the

Head

Nurse,

devote

to

clinical

care

of

PACU

patients?

Please

explain.

107

7.

What

is

the

educational

background

for

all

RNs

assigned

to

your

unit,

including

yourself?

Fill

in

the

number

of

RNs

for

each

educational

level,

and

identify

your

education

by

placing

an

asterisk

(*)

beside

your

educational

level.

Educational

Background

Number

of

RNs

Diploma

Associate

degree

BSN

MSN

Doctorate

Other

8.

What

is

the

PACU

and

critical

care

nursing

experience

of

your

assigned

PACU

nursing

staff?

Circle

the

skill

level

of

each

staff

member

(e.g.,

ANC

or

RN)

and

fill

in

total

number

of

years

of

PACU

and

critical

care

experience.

Years

of

Years

of

PACU

Critical

Care

Experience

a.

ANC

or

RN:

1.

Head

Nurse

(ANC

or

RN)

2.

ANC

or

RN

#2

3.

ANC

or

RN

#3

4.

ANC

or

RN

#4

5.

ANC

or

RN

#5

6.

ANC

or

RN

#6

b.

91C

or

LPN:

I.

NCOIC

(91C

or

LPN)

2.

91C

or

LPN

#2

3.

91C

or

LPN

#3

4.

91C

or

LPN

#4

5.

91C

or

LPN

#5

c.

91A/91B/Nursing

Assistant

(NA):

1.

91A

or

91B

or

NA

#1

2.

91A

or

91B

or

NA

#2

3.

91A

or

91B

or

NA

#3

4.

91A

or

91B

or

NA

#4

5.

91A

or

91B

or

NA

#5

108

9.

How

many

of

the

RNs

have

certification

from

professional

nursing

organizations,

including

yourself?

Fill

in

the

number

of

RNs

who

are

certified

and

list

the

type of

certification

held.

Please

place

an

asterisk

(*)

beside

your

certification.

Certification

Number

of

RNs

10.

What

types

of

students

do

you

have

assigned

to

your

PACU

(e.g.,

91C

students,

91B

Medical

Proficiency

Training

Students,

etc.)?

How

many

students

do

you

have,

how

frequently

do

they

rotate

through your

unit,

and

how

long

does

each

student

stay

on

your

unit?

How

does

having

the

students

impact

on

your

nursing

workload?

Please

explain.

11.

Do

you

have

a

problem

with

rapid

turnover

of

nursing

personnel

assigned

to

your

PACU?

Please

comment.

12.

What

shifts

do

you

have

for

your

PACU

and

what

is

the

average

number

of

nursing

personnel

assigned

to

each

shift?

Shift

Times

ANC/N

91C/LPN

91A/91B/NA

109

13.

Do

you

think

the

number

of

nursing

personnel

(for

each

skill

level)

currently

assigned

to

the

PACU

is

adequate?

ANC/

91C/LPN

91A/91B/

a.

Less

than

adequate

b.

Adequate

c.

More

than

adequate

Please

explain

your

answer:

14.

What

type

of

staffing

do

you

recommend

for

your

PACU?

(Please

indicate

the

number

of

staff

for

each

skill

level

that

you

consider

ideal

for

your

unit.)

Shift

Times

ANC/

91C/LPN

91A/91B/

Please

explain

your

answer:

15.

Please

state

any

specific

staffing

assignment

policies/guidelines

you

have

in

your

PACU

(e.g.,

1

staff

member

per

child

under

_

years,

1

staff

member

per

ventilator

patient).

110

16.

How

do

you

get

more

staff

when

your

PACU

gets

busier

than

anticipated?

(Circle

all

that

apply

and

indicate

how

frequently

you

use

each

strategy.)

a.

Request

staff

be

pulled

from

another

unit

b.

Staff

from

another

unit

help

out

informally

c.

Request

agency

or

float

pool

staff

d.

Request

PACU

staff

work

overtime

e.

Call

in

off-duty

PACU

staff

f.

Other

(please

specify)

17.

If

you

use

an

"on

call"

system,

approximately

how

many

times

a

month

are

PACU

staff

members

called

in

to

recover

patients?

What

are

the

days and

the

hours

that

are

covered

"on

call"?

18.

What

would

you

like

to

change

about

the

way

that

you

adjust

your

staffing

to

accommodate

unanticipated

fluctuations

in

nursing

workload?

Please

explain.

19.

When

do

you

receive

the

Operating

Room

schedule

and

what

information

do

you

use

from

it

to

adjust

your

staffing?

20.

What

information

from

the

Operating

Room

schedule

would

you

like

to

have

for

adjusting

the

number

of

staff

you

have

assigned

to

your

unit

for

a

particular

day?

1i1

21.

Which

types

of

patients

on

your

Operating

Room

schedule

do

you

know

with

fair

accuracy

will

not

be

recovered

in

your

PACU?

Where

will

they

go

from

the

OR

instead

of

PACU

(e.g.,

SICU,

Same

Day

Surgery,

Ward)?

OR

Patients

NOT

Recovered

in

PACU

Place

of

Recovery

22.

What

are

the

average

number

of

add-ons

and

cancellations

to

the

daily

OR

schedule?

PACU

Patients

1.

What

is

the

average

number

of

patients

recovered

in

your

PACU

per

month?

2.

Which

months

do

you

have

the

heaviest

workload

and

why?

3.

Which

months

do

you

have

the

lightest

workload

and

why?

4.

Which

days

of

the

week do

you

have

the

heaviest

workload

and

why?

5.

Which

days

of

the

week

do

you

have

the

lightest

workload

and

why?

112

6.

Which

hours

of

the

day

do

you have

the

heaviest

workload

and

why?

7.

Which

hours

of

the

day

do

you have

the

lightest

workload

and

why?

8.

What

is

your

best

estimate

of

the percentage

of

patients

recovered

in

your

PACU

who

have

received

the

following

anesthesia?

Type

of

Anesthesia

Percentage

of

Patients

a.

General

anesthesia

b.

Spinal

or

regional anesthesia

c.

Local

anesthesia

and/or

sedation

9.

What

is

your

best

estimate

of

the percentage

of

patients

recovered

in

your

PACU

who

have

the

following

ASAs?

ASA

Category

Percentage of

Patients

a.

ASA

1

b.

ASA

2

c.

ASA

3

d.

ASA

4

e.

ASA

5

10.

What

is

the usual

or

typical

PARS

score

of

patients

on

admission

to

your

PACU?

11.

List

the types

of

operative

or

diagnostic

procedures

you

recover

that

require

the

most

nursing

care

time

at

the

bedside

and

why?

Approximately

how

many

cases

per

month

of

each

of

these

procedures

do

you

recover?

113

12.

Describe

the

nursing

care

activities

you

do

for

your

PACU

patients

that

require

the

most

nursing

care

time

at

the

bedside.

How

frequently

or

routinely

do

you

do

these

activities?

13.

What

is

the

average

number

of

C-section

patients

you

recover

per

month?

Does

the

Labor

&

Delivery

Unit

at

your

facility

also

recover

C-section

patients?

If

so,

please

explain

(e.g.,

L&D

may

only

recover

C-section

patients

during

certain

hours).

14.

Describe

the

nursing

workload

of

the

average

C-section

patient

(e.g.,

does

their

nursing

care

require

more

or

less

time

than

your

average

PACU

patient,

etc.).

15.

Which

age

categories

of

your

PACU

patients

require

the

most

nursing

care

time

and

why?

16.

Describe

any

new

nursing

practices

you

are

doing

now

that

you

were

not

doing

several

years

ago.

114

17.

How

else

would you

describe

your

PACU

patients

and

the

nursing

care

that

you

provide

for

them?

a.

Are

most

of your

patients

active

duty

or

retired?

b.

Do

you

have

a

large

number

of

pediatric

or

elderly

patients?

c.

How

often

do

you

have

patients

who

require

a

ventilator?

d.

How

often

do

you

use

Patient

Controlled

Analgesia

(PCA)

pumps?

e.

Describe

other

characteristics

of

your

PACU

patients

that

influence

your

nursing

workload

and

your

staffing.

PACU

Policies

1.

Do

you

have

a

Standard Operating

Procedure

(SOP)

for

routine

vital

signs

or

for

any

other

nursing

practices

that

influence

your

nursing

workload?

If

so,

please

explain

and/or

send

us

a

copy

of

the

SOPs

with

your survey.

115

2.

What

guidelines

do

you

have

for

differentiating

what

nursing

care

must

be

given

by

an

RN

versus

a

91C/LPN

versus

a

91A,

91B,

or

Nursing

Assistant?

Please

explain

and/or

return

with

your

completed

survey

a

copy

of

your

SOPs

describing

these

guidelines.

3.

How

many

and

what

type

of

nursing

personnel

are

required

to

be

in

your

PACU

at

all

times

(e.g.,

at

least

1

RN

and

1

LPN/91C)?

4.

what

is

the

required

minimum

length

of

stay

in

your

PACU

for

the

following

types

of

patients:

a.

for

patients

recovering

from

general

anesthesia?

b.

for

patients

recovering

from

spinal

anesthesia?

c.

for

patients

recovering

from

local

anesthesia

and/or

sedation?

d.

for

any

other

categories

of

patients?

116

5.

Does

your

PACU

have

a

required

minimum

number

of

personnel

to

transport

patients

back

to

their

unit

and

a

required

skill

level?

a.

Number

of

nursing

personnel:

b.

Skill

level

of

nursing

personnel:

6.

What

is

the

average

amount

of

time

required

for

staff

to

transport

patients

to

their

unit

and

return

to

the

PACU?

7.

What

is

your

visitation

policy

and

how

does

it

influence

your

nursing

workload?

a.

No

visitors

allowed

b.

1

parent

may

visit

child

(age

of

child:__

(duration

of

visit:__

c.

Spouse/significant

other

may

visit

(duration

of

visit:_ _

d.

Other

(please

specify)

8.

Do

you

have

standing

orders

for

patient

care

on

issues

such

as

medications

and

discharge

criteria?

a.

If

yes,

do

you

like

your

standing

orders?

Why

or

why

not?

b.

If

no,

do

you

want

standing

orders?

Why?

117

General

Information

1.

Describe

and

discuss

any

new

or

anticipated

changes

in

your

facility,

your

PACU,

or

the

patient

population

served

by

your

facility

that

may

influence

the

nursing

workload

in

your

PACU.

2.

Does

your

PACU

have

a

computer(s)?

If

yes,

how

do

you

use

the

computer(s)?

(Circle

all

that

apply.)

a.

Patient

monitoring

b.

Admission/disposition

c.

Lab/x-ray

results

reporting

d.

Order

entry

e.

Nursing

care

plans/documentation

f.

Other

(please

describe)

3.

Which

of

the

following

non-nursing

support

does

your

PACU

receive?

(Fill

in

the

blanks

as

appropriate.)

Type

of

Support

JHours

per

Day

Type

of

Tasks

Ward

Clerk

Housekeeping

Laboratory

Supply

Pharmacy

Respiratory

Therapy

Transport/Escort

EKG

Other

(please

list)

118

Thank

you

very

much

for

the

time

and

effort

you

have

taken

to

complete

this

survey

and

to

send

us

copies

of

your

MEPERS

reports

for

the

last

year!

Comment

on

anything

about

your

PACU

that

we

may

have

overlooked.

Your

input

will

help

us

develop

a

useful

nurse

staffing

system

for

your

PACU.

Also,

please

feel

free

to

contact

us

with

any

comments

or

suggestions.

COL

Jane

Hudak

or

LTC

Julie

Zadinsky

Nursing

Studies

Branch

(HSHN-H)

U.S.

Army

Health

Care

Studies

and

Clinical Investigation

Activity

Building

2268

Fort

Sam

Houston,

TX

78234-6060

DSN:471-1880/0278

COMM:(512)221-1880

FAX:(512)554-4745

We

would

like

to

share

the

results

of

the

survey

with

you.

Due

to

the

demands

of

the

PACU

staffing

study,

we

do

not

expect

to

have

the

final

survey

results

in

the

near

future.

However,

if

you would

like

to

receive

a

summary

of

the

major

findings

of

the

survey,

please

indicate

below:

Yes,

I

would

like

to

receive

a

summary

of

the

major

findings

of

the

survey.

Please

mail

the

summary

to

me

at

the

PACU

at

this

MTF.

I

will

notify

you

by

phone

or

mail

if

my

duty

position

and

address

change.

119

APPENDIX

F

Method

of

Calculating

Nursing

Care

Hours

Per

Day

120

Method of

Calculating Nursing

Care

Hours

Per

Day

Patient

volume

information

is

entered

into

a

data

set

in

such

a way

that

each

day

has

two

observations.

The

first

observation

is

the

total

number

of

patients

seen

by

PACU

nursing

personnel

for

one

day

in the

General

and/or

Regional/Spinal anesthesia

category.

The

second

observation

is

the

total

number

of

patients

seen

for

one

day

in

the

Local

anesthesia

and/or

Sedation category.

Calculations

are

done

for

each

observation

in

the

data

set. Note

that

each observation

is

by

day.

Also,

the

data

set

should

consist

of

daily

observations

for

a

3-month

period

of

time

because

this

is

the

amount

of

data

needed

to

develop

one

quarterly

workload

profile.

1.

Patient volume

will

be

reported

by number

of

patients

per

day

in

2

different

anesthesia

categories:

(a)

patients who had

General

anesthesia

and/or

Regional/Spinal

anesthesia

and

(b)

patients

who

had

Local

anesthesia

and/or

Sedation.

2.

The

number

of

patients

per

day

who

had

General anesthesia

and/or

Regional/Spinal

anesthesia

is

put

into

the

following

formula

as

Xl.

Y1

is

the

direct care

hours

per

day

for

these

patients.

Y1

=

0.485687

+

[0.694732

(Xl)]

3.

The

number

of

patients

per

day

who

had

Local

anesthesia

and/or

Sedation

is

put

into

the

following

formula

as X2.

Y2

is

the

direct

care

hours

per

day

for

these

patients.

Y2

=

0.124070

+

[0.419431

(X2)]

4.

To

obtain

the total

direct

care

hours

per

day

for

all patients

(Y3):

Add

Yl

and

Y2.

Y3

=

Y1

+

Y2

5.

To

obtain

the

total nursing

care

hours (NCHs)

per

day

for

all patients:

Multiply

total

direct

care

hours

per

day

(Y3)

by

4.31

(the

Indirect

Care

Multiplier

or

ICM).

NCHs

per

day

=

Y3

* 4.31

121

APPENDIX

G

PACU

Fixed

Staff

Definition

122

HSHN-H

(5-5c)

4

June

1993

MEMORANDUM

FOR

HQDA

(DASG-CN),

5109

Leesburg

Pike,

Falls

Church,

VA

22041-3258

SUBJECT:

Post

Anesthesia

Care

Unit

Fixed

Staff

Definition

1.

This

is

a

decision

paper.

2.

PURPOSE.

Provide

approval

of

the

definition

of

fixed

staff

used

by

the

Post

Anesthesia

Care

Unit

(PACU)

staffing

system

to

calculate

nursing

care

hours.

3.

DISCUSSION.

a.

Fixed

staff

positions

are

recognized

regardless

of

variation

in

workload

and

include

those

that are

primarily

administrative

in

nature:

(head

nurse

[HN],

wardmaster

[WM],

and

ward

clerk

[WC]).

The

PACU

staffing

system

identifies

the

recommended

number

of

variable

nursing

staff

(registered

nurses,

licensed

practical

nurses

and

nursing

assistants)

based

on

variation

in

patient

workload. Medical

treatment

facilities

and

other

agencies

will

be

required

to

use

the

same

definition

of

fixed

staff

for

development

of

future

manpower

standards

if

they

utilize

PACU

acuity

data.

b.

The

PACU

indirect

care

study

(Rea,

Jennings,

Carty,

&

Seipp,

1991)

also

recommended

the

HN,

WM,

and

WC

as

fixed

staff.

This

diverges

from

the

Workload

Management

System

for

Nursing

(WMSN)

definition

of

fixed

staff

as only

the

HN

and

WM.

Identifying

the

WC

as

variable

staff

limits

the

flexibility

of

the

large

PACUs

that

may

need

a

WC

because

their

duties

include

only

secretarial

functions.

Also,

identifying

the

WC

as

variable

staff

slightly

increases

the

number

of

recommended

variable

staff

per

day

(TAB

B).

4.

RECOMMENDATION.

Recommend

that

Brigadier

General

Adams

sign

the

proposed

1st

Endorsement

at

TAB

A.

ORIGINAL

SIGNED

2

Encls

WILLIAM

B.

YORK,

JR.

1.

TAB

A

(proposed

1st

End)

Colonel,

MC

2.

TAB

B

(NCH

Calculation)

Director,

HCSCI

123

DASG-CN

(HSHN-H/4

Jun

93)

(5-5c)

1st

End

LTC

Zadinsky/er/AV

471-0278

SUBJECT:

Post

Anesthesia

Care

Unit

Fixed

Staff

Definition

Office

of

the

Chief,

Army

Nurse

Corps,

Room

623,

Skyline

Five,

5109

Leesburg

Pike,

Falls

Church,

VA

22041-3258

FOR

Director,

Directorate

of

Health

Care

Studies

and

Clinical

Investigation,

Building

2268,

Fort

Sam

Houston,

TX

78234-

6100

This

action

has

been

Approved/Disapproved

ORIGINAL

SIGNED

Encl

NANCY

R.

ADAMS

nc

Brigadier

General,

AN

Assistant

Surgeon

General/

Chief,

Army

Nurse

Corps

124

Calculation

of

Nursing

Care

Hours

1.

Nursing

care

hours

(NCH)

and

the

number

of

recommended

variable

nursing

staff

are

calculated

from

direct

care

time

and

the

indirect

care

multiplier

(ICM).

The

higher

the

ICM,

the

higher

the

number

of

recommended

staff.

2.

Rea

et

al.

(1991)

determined

in

their

study

that

defining

fixed

staff

as

the

HN,

WM,

and

WC

produced

a

slightly

lower

ICM

than

defining

only

the

HN

and

WM

as

fixed

staff.

The

difference

in

the

two

ICMs

is

small

because

only

the

high

workload

PACUs

in

the

study

had

a

WC.

The

following

table

demonstrates

this

point

using

20

hours

of

direct

care

time.

When

fixed

staff

is

defined

as

the

HN,

WM

and

WC,

the

recommended

number

of

staff

is

10.8.

If

fixed

staff

is

only

the

HN

and

WM,

the

recommended

number

of

staff

is

11.0.

Fixed

Staff

Nursing

Care

Recommended

Hours

Staff

mN,

WM,

WC

86.20

10.8

EM,

WM

87.80

11.0

125

APPENDIX

H

Method

of

Recording

Patient

Volume

Information

126

Method

of

Recording

Patient

Volume

Information

1.

Record

the

number

of

patients

who

receive

routine post-anesthesia

care

from

PACU

nursing

staff.

These

patients

may

be

recovered

(a)

during

normal

hours

of

operation

by

PACU

nursing

staff

or

(b)

after

normal hours

of

operation

by

on-call

PACU

nursing

staff.

2.

Record

the number

of

patients

recovered

per

day

in

2

different

anesthesia

categories.

(a)

In

the

first

category,

record

the

number

of

patients

who

had general

AND/OR

regional/spinal

anesthesia.

Also

record

here

the

number

of

patients

who

received

one

of

these

anesthesias

PLUS

local

anesthesia

and/or

sedation.

(b)

In

the

second

category,

record

the

number

of

patients

who

received

ONLY

local

anesthesia

and/or

sedation.

3.

For

recording

purposes,

each

day

begins

at

0001

hours

and

ends

at

2400

hours.

Record

each

patient

visit

in

the

PACU

only once,

even

if

the

visit

extends

past

midnight.

A

patient

visit

is

defined

as

an

episode

of

care

that

includes admission

to the

PACU,

an

initial

assessment,

routine

post-anesthesia

care,

and

discharge

to

another

unit.

4.

Patients

who are

in the PACU

for

other

than

routine

post-anesthesia

care generate

workload

that

is not captured by

the

staffing

system.

Head

nurses

who

have

patients

of

this

type

should

consider

ways

to capture

the

workload

generated

by

these patients

so

that they

can

justify

the

need

for

extra

staff

in

addition

to

the number

of

staff

indicated

in

the

staffing

profile.

Two

categories

of

patients in

the

PACU

for

other than routine

post-anesthesia

care

are

as

follows:

(a)

Remain

Overnight

patients

(RONs)

are

those patients

who

are identified

to

remain

overnight

for

postoperative

care

in

the

PACU

from

the

day

of

their

surgery

until the

following

morning. These

patients

may

be

counted

once

on

the

patient

volume

worksheet

to

account

for

the

workload

involving

their

phase

I

post-anesthesia care.

However,

the

workload

resulting

from

their

extended

post-operative

care

in the

PACU

is

NOT

captured

by

the

staffing

system.

(b)

Same

Day Surgery

(SDS)

patients

are

counted

once on

the

patient

volume

worksheet

to

account

for

the

workload resulting

from

their

routine post-anesthesia

nursing

care.

However,

workload

generated

by

SDS

preadmission,

preoperative,

or

extended

postoperative

care

is

NOT

captured

by

the

staffing

system.

127

Patient

Volume

Worksheet

Example

Record

the

number

of

patients

recovered

by

PACU

nursing

staff

for

each

day

by

the

type

of

anesthesia

the patient

received.

Month/Year

Date

General

&

Local/

Date

General

&

Local/

Regional/

Sedation

Regional/

Sedation

Spinal

Patients

Spinal

Patients

1

17

2

18

3

19

4

20

5

21

6

22

7

23

8

24

9

25

10

26

11

27

12

28

13

29

14

30

15

31

16

128

DISTRIBUTION

LIST

Defense

Technical

Information

Center,

ATIN:

DTIC-OCC,

Cameron

Station,

Alexandria,

VA

22304-6145

(2)

Defense Logistics

Information

Exchange,

U.S.

Army

Logistics

Management

College,

ATTN:

ATSZ-DL,

Fort

Lee,

VA

23801-6043

(1)

Director,

Joint Medical

Library,

ATTN:

DASG-AAFJML,

Offices

of

the

Surgeons

General,

Army/Air

Force,

Rm

670,

5109

Leesburg Pike,

Falls

Church,

VA

22041-3258

(1)

HQDA

(DASG-CN),

ATIN:

COL

Terris

Kennedy,

Room

623,

Skyline

Five,

5111

Leesburg

Pike,

Falls

Church,

VA

22041-3258

(1)

Department

of

Nursing,

Madigan

Army

Medical

Center,

ATTN:

COL

Bonnie

Jennings,

Tacoma,

WA

98431-5000

(1)

Commander,

U.S.

Army

Medical

Command, ATTN:

MCHO-CL (COL

Simmons),

2050

Worth

Road,

Fort

Sam

Houston,

TX

78234-6000

(1)

Commander,

U.S.

Army Medical

Command,

ATTN: MCRM-MD-EOB

(MAJ

Harper),

2050

Worth

Road,

Fort

Sam

Houston,

TX

78234-6000

(1)

Chief,

Functional

Branch, WMSN

Project

Officer,

ATTN:

MAJ

Hickey,

2455

NE

Loop

410,

Suite

150,

San

Antonio,

TX

78217-5607

(1)

Stimson

Library,

Academy

of

Health

Sciences,

ATTN: MCCS-HSL,

Fort

Sam

Houston,

TX

78234-6060

(1)

129

Development of an Acuity-Based Nurse Staffing System for the Post Anesthesia Care Unit

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