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Time to recovery after general anesthesia at hospitals with and without a phase I post-anesthesia care unit: a historical cohort study

Authors:

Abstract

Purpose There is little knowledge about how hospitals can best handle disruptions that reduce post-anesthesia care unit (PACU) capacity. Few hospitals in Japan have any PACU beds and instead have the anesthesiologists recover their patients in the operating room. We compared postoperative recovery times between a hospital with (University of Iowa) and without (Shin-yurigaoka General Hospital) a PACU. Methods This historical cohort study included 16 successive patients undergoing laparoscopic gynecologic surgery with endotracheal intubation for general anesthesia, at each of the hospitals, and with the hours from OR entrance until the last surgical dressing applied ≥ two hours. Postoperative recovery times, defined as the end of surgery until leaving for the surgical ward, were compared between the hospitals. Results The median [interquartile range] of recovery times was 112 [94-140] min at the University of Iowa and 22 [18-29] min at the Shin-yurigaoka General Hospital. Every studied patient at the University of Iowa had a longer recovery time than every such patient at Shin-yurigaoka General Hospital (Wilcoxon-Mann-Whitney, P < 0.001). The ratio of the mean recovery times was 4.90 (95% confidence interval [CI], 4.05 to 5.91; P < 0.001) and remained comparable after controlling for surgical duration (5.33; 95% CI, 3.66 to 7.76; P < 0.001). The anesthetics used in the Iowa hospital were a volatile agent, hydromorphone, ketorolac, and neostigmine compared with the Japanese hospital where bispectral index monitoring and target-controlled infusions of propofol, remifentanil, acetaminophen, and sugammadex were used. Conclusions This knowledge can be generally applied in situations at hospitals with regular PACU use when there are such large disruptions to PACU capacity that it is known before a case begins that the anesthesiologist likely will need to recover the patient (i.e., when there will not be an available PACU bed and/or nurse). The Japanese anesthesiologists have no PACU labour costs but likely greater anesthesia drug/monitor costs.
REPORTS OF ORIGINAL INVESTIGATIONS
Time to recovery after general anesthesia at hospitals
with and without a phase I post-anesthesia care unit: a historical
cohort study
De
´lai de re
´cupe
´ration apre
`s une anesthe
´sie ge
´ne
´rale dans les
ho
ˆpitaux disposant d’une unite
´de soins postanesthe
´siques de
phase I par rapport a
`des ho
ˆpitaux n’en disposant pas : une e
´tude
de cohorte historique
Kokila N. Thenuwara, MD, MBBS, MME, MHCDS .Tatsuya Yoshimura, MD, MBA .
Yoshinori Nakata, MD, MBA .Franklin Dexter, MD, PhD, FASA
Received: 9 April 2018 / Revised: 30 May 2018 / Accepted: 31 May 2018 / Published online: 12 September 2018
ÓCanadian Anesthesiologists’ Society 2018
Abstract
Purpose There is little knowledge about how hospitals can
best handle disruptions that reduce post-anesthesia care
unit (PACU) capacity. Few hospitals in Japan have any
PACU beds and instead have the anesthesiologists recover
their patients in the operating room. We compared
postoperative recovery times between a hospital with
(University of Iowa) and without (Shin-yurigaoka
General Hospital) a PACU.
Methods This historical cohort study included 16
successive patients undergoing laparoscopic gynecologic
surgery with endotracheal intubation for general
anesthesia, at each of the hospitals, and with the hours
from OR entrance until the last surgical dressing applied
Ctwo hours. Postoperative recovery times, defined as the
end of surgery until leaving for the surgical ward, were
compared between the hospitals.
Results The median [interquartile range] of recovery
times was 112 [94-140] min at the University of Iowa
and 22 [18-29] min at the Shin-yurigaoka General
Hospital. Every studied patient at the University of Iowa
had a longer recovery time than every such patient at Shin-
yurigaoka General Hospital (Wilcoxon-Mann-Whitney, P
\0.001). The ratio of the mean recovery times was 4.90
(95% confidence interval [CI], 4.05 to 5.91; P \0.001)
and remained comparable after controlling for surgical
duration (5.33; 95% CI, 3.66 to 7.76; P \0.001). The
anesthetics used in the Iowa hospital were a volatile agent,
hydromorphone, ketorolac, and neostigmine compared
with the Japanese hospital where bispectral index
monitoring and target-controlled infusions of propofol,
remifentanil, acetaminophen, and sugammadex were used.
Conclusions This knowledge can be generally applied
in situations at hospitals with regular PACU use when
there are such large disruptions to PACU capacity that it is
known before a case begins that the anesthesiologist likely
will need to recover the patient (i.e., when there will not be
an available PACU bed and/or nurse). The Japanese
anesthesiologists have no PACU labour costs but likely
greater anesthesia drug/monitor costs.
Re
´sume
´
Objectif Nous savons peu de choses sur la fac¸on dont les
ho
ˆpitaux peuvent le mieux re´soudre les perturbations qui
Drs. Thenuwara and Yoshimura contributed equally to this research.
K. N. Thenuwara, MD, MBBS, MME, MHCDS
Department of Anesthesia, University of Iowa, Iowa City, IA,
USA
T. Yoshimura, MD, MBA
Department of Anesthesia, Shin-yurigaoka General Hospital,
Kawasaki, Kanagawa, Japan
Y. Nakata, MD, MBA
Teikyo University, Tokyo, Japan
F. Dexter, MD, PhD, FASA (&)
Division of Management Consulting, Department of Anesthesia,
University of Iowa, 200 Hawkins Drive, 6-JCP, Iowa City, IA
52242, USA
e-mail: Franklin-Dexter@UIowa.edu
URL: https://www.FranklinDexter.net
123
Can J Anesth/J Can Anesth (2018) 65:1296–1302
https://doi.org/10.1007/s12630-018-1220-1
re´duisent la capacite´ des unite´s de soins postanesthe´sie
(salle de re´veil). Au Japon, peu d’ho
ˆpitaux disposent de lits
de salle de re´veil et les anesthe´siologistes laissent les
patients re´cupe´rer dans la salle d’ope´ration. Nous avons
compare´lede´lai de re´cupe´ration postope´ratoire entre un
ho
ˆpital disposant d’une salle de re´veil (Universite´de
l’Iowa) et un ho
ˆpital n’en ayant pas (Ho
ˆpital ge´ne´ral Shin-
yurigaoka).
Me
´thodes Cette cohorte historique a inclus 16 patientes
successives subissant une chirurgie gyne´cologique par voie
laparoscopique avec intubation endotrache´ale et
anesthe´sie ge´ne´rale dans chacun des ho
ˆpitaux lorsque le
de´ lai entre l’entre´e au bloc ope´ratoire et le dernier
pansement chirurgical mis e´tait C2 heures. Le temps de
re´ cupe´ration postope´ ratoire, de´fini comme e´ tant le de´lai
e´ coule´ entre la fin de l’intervention et le de´part pour l’unite´
de chirurgie a e´te´ compare´ entre les 2 ho
ˆpitaux.
Re
´sultats La valeur me´diane [plage interquartile] du
temps de re´cupe´ration a e´te´ de 112 [94-140] minutes a`
l’universite´ de l’Iowa et de 22 [18-29] minutes a` l’ho
ˆpital
ge´ne´ral Shin-yurigaoka. Toutes les patientes e´tudie´es a`
l’universite´ de l’Iowa ont eu un temps de re´cupe´ration plus
long que chacune des patientes de l’ho
ˆpital ge´ne´ral Shin-
yurigaoka (test de Wilcoxon-Mann-Whitney, P \0,001). Le
rapport des temps moyens de re´cupe´ration a e´te´ de 4,90
(intervalle de confiance [IC] a` 95 % : 4,05 a` 5,91; P \
0,001) et est reste´ comparable apre`s contro
ˆle pour la dure´e
de l’intervention (5,33; IC a` 95 %, 3,66 a` 7,76;
P\0,001). Les agents anesthe´siques utilise´s a` l’ho
ˆpital
de l’Iowa e´taient un agent volatil, l’hydromorphone, le
ke´ torolac et la ne´ostigmine alors que dans l’ho
ˆpital
japonais le monitorage de l’indice bispectral et des
perfusions contro
ˆle´ es avec cible de propofol et de
re´ mifentanil, de l’ace´taminophe`ne et du sugammadex ont
e´te´ utilise´s.
Conclusions Ces connaissances peuvent eˆtre applique´es
plus ge´ne´ralement aux ho
ˆpitaux disposant de salles de
re´ veil quand on sait a` l’avance que l’anesthe´siologiste
aura probablement besoin de laisser re´cupe´rer le patient
en salle d’ope´ration a` cause de perturbations importantes
des capacite´s de la salle de re´veil (c’est-a`-dire, absence de
lit et/ou d’infirmie`re disponible). Les anesthe´siologistes
japonais n’engendrent pas de frais de personnel en salle de
re´ veil, mais occasionnent probablement des frais plus
e´ leve´s de monitorage et de me´ dicaments anesthe´siques.
Sento et al. recently published their survey of hospitals in
Japan finding that only 16% have any phase I
postanesthesia care unit (PACU) beds.
1
The phase I
discharge-to-ward PACU is differentiated from the
discharge-to-home phase II PACU of outpatient surgical
departments.,
2,A
In Japan, patients are recovered in the
operating room (OR) by the anesthesiologist and then go
directly to the hospital ward. This occurs despite Japanese
hospitals often having a higher postoperative patient-to-
nurse ratio than in the USA (i.e., it is not because the
Japanese wards are functioning like PACUs).
B
Potentially,
in Japan, more expensive devices and drugs are being used,
facilitating fast recovery in the OR, while in the USA
expensive PACU nurse labour is being used instead. We
therefore speculate that there may be useful insights from
the anesthesia techniques used in Japanese hospitals that
recover patients exclusively in their ORs. Anesthesiologists
working at hospitals with regular PACUs can use the
insights when expected to recover the patient (i.e., the
PACU is anticipated to be full).
In this historical cohort study, we compared the surgical
recovery times between the University of Iowa hospital in
Iowa City and the Shin-yurigaoka General Hospital near
Tokyo. Our objective was to test the hypothesis that the
times from end of surgery until the patients left for the
surgical ward (i.e., ‘recovery times’’) would be much
longer at the University of Iowa with a PACU compared
with a Tokyo hospital that does not use a PACU.
Methods
The Institutional Review Boards (IRB) of the University of
Iowa (201801768; 25 January 2018) and of Shin-yurigaoka
General Hospital (20180219-1; 20 February 2018)
approved this historical cohort study and considered it
exempt from the requirement of obtaining written consent
of patients.
The population studied was patients undergoing
laparoscopic gynecologic surgery. We chose this
population because it was the one category with many
patients at both the investigators’ hospitals. No restriction
was placed on whether the patient leaving the PACU
(University of Iowa) or OR (Shin-yurigaoka General
Hospital) was going to a hospital ward or to a phase II
PACU location (see footnote A in the introduction). All
successive patients were studied that met the following
inclusion criteria: i) a laparoscopic gynecologic procedure
was scheduled and performed for at least part of the
A
For the current paper, we consider patients discharged to ward.
Generally, patients may be discharged from the phase I
postanesthesia care unit (PACU) to the phase II PACU, a ward, or
intensive care unit.
B
As reported by the Chief gynecologic nurse, each ward nurse at
Shin-yurigaoka General Hospital cares for an average of seven
gynecologic patients, more than the five or six at the University of
Iowa.
123
Recovery times after anesthesia without PACU 1297
surgical case (i.e., it could have been completed with
laparotomy); ii) endotracheal intubation for general
anesthesia was done; iii) actual hours from OR entrance
until the last surgical dressing was placed on the patient
was Ctwo hours.
Patients were selected in reverse sequence from 31
December 2017. Electronic chart review was performed for
16 successive patients (see the power analysis below). The
requirement was placed on the protocol design that the
study would be reevaluated if 16 such patients were not
identified who had undergone surgery within six months
(i.e., all patients studied had surgery between 1 July 2017
and 31 December 2017). The dates were otherwise not
recorded; only times were recorded, in accordance with the
IRB protocol. This was because as the specific hospitals
were being identified, the combination of procedure
(inherently specifying sex) and date potentially could
lead to identification of the patients.
3,4
The primary endpoint of this study was the ‘recovery
time,’ defined as the time from end of surgery (i.e., final
wound covered)
5
until the patient left for the hospital ward.
If there were differences in recovery times, the anesthetic
monitors and drugs used would be of interest and were
therefore also recorded.
Statistical methods
The primary method of statistical analysis was chosen a
priori. The Wilcoxon-Mann-Whitney test was used to
estimate the probability (p00) that a randomly selected case
at the University of Iowa had a longer time to recovery than
did a randomly selected case at the Shin-yurigaoka General
Hospital.
The secondary methods of analysis used generalized
linear modeling, a log link function, and heteroscedastic-
robust standard error. This analysis was performed while
controlling for covariates, including the time from OR
entrance to end of surgery. We expected this variable to be
a significant covariate that could cause bias because of its
positive correlation among all types of procedures with the
time from end of surgery to extubation.
6
The following power analysis, as reported to the IRBs,
was used to determine the sample size. Because of the
multiple planned analyses, a type I two-sided error rate
(alpha) of 0.01 was used: Z
alpha/2
=Z
0.005
= 2.58. In
addition, a 90% statistical power to detect a difference
between hospitals was planned: Z
beta
=Z
0.10
= 1.28.
Assuming equal sample sizes at each of the two hospitals,
equation A3.2 in Divine et al. was applied to our problem
7
;
accordingly, each group’s N= 2.48/(p00 -0.5)
2
. From
preliminary discussions about respective patients’ typical
recovery times, we expected no overlap of recovery time
between the US and Japanese hospitals, but also recognized
that there may be some overlap due to uncommon patient
or operational conditions. We used p00 = 0.90 (i.e., at most
10% overlap between groups) and thus obtained data on 16
consecutive patients meeting the inclusion criteria at each
hospital.
Results
All 16 of the patients at the Shin-yurigaoka General
Hospital Tokyo went to the hospital ward directly from the
OR. None of the 16 University of Iowa patients needed to
wait in the PACU because a ward bed was unavailable (i.e.,
none of the measured recovery times was prolonged for
such non-clinical reasons). All the data elements recorded
about each patient are listed in Table 1along with the
summary measures.
The median [interquartile range] of recovery times was
112 [94-140] min at the University of Iowa and 22 [18-29]
min at the Shin-yurigaoka General Hospital (Figure). Every
studied patient at the University of Iowa had a longer
recovery time than every such patient at Shin-yurigaoka
General Hospital (Wilcoxon-Mann-Whitney, P\0.001)
(Figure). The ratio of the mean recovery times was 4.90
(95% confidence interval [CI], 4.05 to 5.91; P\0.001),
which remained comparable while controlling for the
duration of surgery (5.33; 95% CI, 3.66 to 7.76; P\
0.001). Thus, the estimated mean recovery time at Shin-
yurigaoka General Hospital was approximately 80% [i.e., 1
-(1/4.90) = 79.6% and 1 -(1/5.33) = 81.2%] faster than
that of the University of Iowa Hospital.
Covariates that could not be studied were those that
differed uniformly between the hospitals (Table 1). None
of the patients at the University of Iowa had BIS
TM
(Medtronic; Minneapolis, MN, USA) monitoring vs all the
patients at Shin-yurigaoka General Hospital. In addition,
all the patients at the University of Iowa had anesthetic
maintenance with a volatile agent, whereas all the patients
at Shin-yurigaoka General Hospital received target-
controlled infusions of propofol. Analgesics, in addition
to fentanyl, were hydromorphone and/or ketorolac at the
University of Iowa compared with remifentanil and
acetaminophen at Shin-yurigaoka General Hospital.
Reversal of neuromuscular blockade was done with
neostigmine at the University of Iowa vs sugammadex at
Shin-yurigaoka General Hospital.
Discussion
At a Japanese hospital with no PACU, where
anesthesiologists recover their patients in the OR, mean
recovery times after general anesthesia for laparoscopic
123
1298 K. N. Thenuwara et al.
Table 1 Comparisons of patients and anesthetics at University of Iowa and Shin-yurigaoka General Hospital in Tokyo
Variable University of Iowa Shin-yurigaoka General Hospital
(Tokyo)
Pvalue
BIS monitor Used 0
Not used 16
Used 16
Not used 0
\0.001
Maintenance hypnotic Propofol target- controlled infusion
0
Sevoflurane 9
Isoflurane 6
Desflurane 1
Propofol target-controlled infusion 16
Sevoflurane 0
Isoflurane 0
Desflurane 0
\0.001
Additional analgesics Remifentanil and acetaminophen 0
Hydromorphone and ketorolac 7
Hydromorphone 7
Ketorolac 2
None 0
Remifentanil and acetaminophen 15
Hydromorphone and ketorolac 0
Hydromorphone 0
Ketorolac 0
None 1
\0.001
Reversal of neuromuscular blockade Sugammadex 0
Neostigmine 14
None 2
Sugammadex 15
Neostigmine 1
None 0
\0.001
Time from OR entrance to end of surgery (hr) Median 4.72
25th percentile 4.02
75th percentile 5.51
Mean 4.91
Median 2.70
25th percentile 2.39
75th percentile 3.41
Mean 2.99
0.001
Procedure Hysterectomy 13
Myomectomy 1
Cystectomy 0
Sacral colpopexy 2
Hysterectomy 7
Myomectomy 6
Cystectomy 3
Sacral colpopexy 0
0.011
Decade of age (years) Median 45
25th percentile 40
75th percentile 55
Median 40
25th percentile 30
75th percentile 45
0.35
Time from end of surgery to tracheal extubation (min) Median 11.0
25th percentile 7.5
75th percentile 19.5
Mean 13.9
Median 9.0
25th percentile 6.5
75th percentile 11.0
Mean 8.9
0.36
ASA physical status 1-2 13
33
1-2 16
30
0.23
Fentanyl before tracheal extubation Used 14
Not used 2
Used 16
Not used 0
0.48
Time of day of end of surgery Median 3:05 PM
25th percentile 12:22 PM
75th percentile 5:16 PM
Median 3:52 PM
25th percentile 1:38 PM
75th percentile 4:44 PM
0.55
Another case performed in the OR after the current
case
Yes 10
No 6
Yes 9
No 7
0.99
Another case performed in the OR after the current
case and by the same surgeon
Yes 9
No 7
Yes 8
No 8
0.99
Rocuronium Used 16
Not used 0
Used 16
Not used 0
1.00
Elective procedure Elective 16
Urgent 0
Elective 16
Urgent 0
1.00
Categories were compared using Fisher’s exact test. Continuous and ordered variables were compared using the Wilcoxon-Mann-Whitney test.
Pvalues are two-sided. ASA = American Society of Anesthesiologists; OR = operating room
At the University of Iowa, propofol was used for induction and not maintenance, and none of the analgesics was infused
123
Recovery times after anesthesia without PACU 1299
gynecologic surgery were 80% faster than those of a US
hospital that uses a PACU.
Our results have economic implications. An anesthetic
with BIS monitoring, propofol target-controlled infusion,
remifentanil, acetaminophen, and sugammadex will have a
greater device and drug cost than one with sevoflurane,
hydromorphone, ketorolac, and neostigmine. Nevertheless,
if an anesthesiologist is going to recover the patient 1:1
rather than a nurse caring for two patients in a PACU
2
(with anesthesiologist backup), the labour costs per hour
will be greater.
8,9
Thus, the Japanese anesthesiologists
substitute more expensive supplies/drug costs for less of
their time (i.e., labour costs). The approach of using the
BIS monitor and drugs with fast recovery time is sustained,
in part, by the Japanese’ Diagnostic Procedure
Combination hospital payment system that excludes
anesthesia drugs, making them fee-for-service, paid by
the patient’s insurance; thus, the hospital lacks incentive
for lesser cost. This approach not to reduce the time spent
in the PACU but to facilitate its bypass altogether matches
the findings of the pharmacoeconomics of anesthetic drugs
and techniques for outpatient surgery.
10-12
For outpatient
surgery, this strategy lowers costs especially for facilities
with many patients per day, an eight-hour (vs a longer ten-
hour) OR workday, and PACU nurses who either are
salaried or work full-time hourly and frequently have
overtime.
13,14
Our results are potentially useful at hospitals with
regular PACU use when it is known before a case begins
that the anesthesiologist likely will need to recover the
patient in the OR (i.e., there will not be an available PACU
bed and/or nurse). An example of such events is when there
is damage to portions of the PACU (e.g., flooding).
15
Other
situations where this event might occur include when
patients from another location (e.g., non-OR anesthetizing
locations) are being recovered temporarily in the surgical
PACU (e.g., the other location’s PACU is temporarily
closed for renovations). Nevertheless, our findings that
different anesthetics can, in combination, result in recovery
times that are only 20% as long were for gynecologic
surgery (Table 2). Knowing before the case begins that the
patient has a substantial chance of needing recovery in the
OR generally would depend on there being PACU staffing
shifts and start times chosen based on matching the
expected peak number of PACU patients by time of
day.
16-20
Even then, when there is a large variability among
days in the peak numbers of patients, predicting for the
individual case is challenging.
21
Nevertheless, this is not so
when a disruption is so large that there will inevitably be
cases every day with recovery in the OR.
15
For example, if
a 12-bed PACU only has eight beds available for surgical
patients for a week (e.g., from renovation), and the other
patients recover in the ORs, there will be negligible
variability in the peak number of patients in the PACU
(i.e., it will be eight patients for most of the workday).
Planning can be done in this circumstance.
22
Study limitations
We did not collect safety data and do not have the timing
on when each patient met each of the multiple criteria for
Figure Recovery time at the University of Iowa and at Shin-
yurigaoka General Hospital after general anesthesia for laparoscopic
gynecologic surgery. The recovery time was the time from final
wound covering until the patient left for the hospital ward. A potential
independent variable that differed between hospitals was the time
from operating room (OR) entrance to the final dressing on the patient
(Tables 1and 2)
Table 2 Ratio of mean recovery times between University of Iowa and Shin-yurigaoka General Hospital in Tokyo
Variable from Table 1that differs significantly but not completely
between hospitals
Mean (95% confidence
interval)
Pvalue for ratio
of recovery times
Pvalue for
covariate
None 4.90 (4.05 to 5.91) \0.001
Time from OR entrance to end of surgery 5.33 (3.66 to 7.76) \0.001 0.49
Hysterectomy 4.92 (4.11 to 5.90) \0.001 0.91
Recovery time was measured as the period from end of surgery until the patient was ready to leave for the hospital ward. The non-significant
effect of surgical time had a narrow confidence interval, with a 0.997 to 1.001-fold longer recovery time for each additional one minute of
surgical time (i.e., 0.9995 to 1.0000 per hour). The generalized linear modeling also was performed using the sequence of the patients at each
hospital as a continuous variable: 4.89 (4.10 to 5.83), P\0.0001, and sequence P= 0.15. OR = operating room
123
1300 K. N. Thenuwara et al.
discharge to the ward.
C,23
However, the hospital in Tokyo
does not have a PACU for any of its patients (i.e., it was
not just unavailable for the study patients); only 16% of
hospitals in Japan have any PACU beds.
1
Thus, the
relevant issue is not whether patients can safely undergo
surgery and then go directly to a hospital ward with no
greater numbers of nurses there than in North America. The
question is how long patients routinely wait in the ORs
recovering. The answer is vastly less time (20%) than that
spent routinely in a phase I PACU. Nevertheless, while
achieving this reduction in labour costs, the anesthetics
were different and generally more expensive (i.e.,
substitution of drug/supply for labour costs). As referred
to in the last paragraph of the results, from the data, we are
unable to know which of the differences in drugs/supplies
contribute to the briefer recovery times. We also cannot
quantify whether recovery time is saved by not having a
handoff of care or from heterogeneity in the use of
discharge criteria.
C
We limited the procedure category to laparoscopic
gynecologic surgery, though this was unlikely to have
influenced our conclusions. The principal covariates for
recovery time after general anesthesia are not surgical
procedure or patient sex, but availability of
anesthesiologists, transport personnel, or ward beds, as
well as patient pain.
24,25
We did not have a way to collect patients’ initial
postoperative pain scores, because the data were collected
retrospectively. However, it is unlikely that differences in
acute pain during the first couple of hours after surgery
account for the 4.9-fold differences in recovery times.
However, our conclusions are limited to the fact that the
recovery times differ markedly between hospitals; we do
not have a way to know how the differences were achieved.
The application of our study was in the consideration of
using different anesthetic techniques to reduce recovery
times when the PACU is full. An alternative strategy may
be to revise case sequencing to reduce the peak necessary
number of PACU nurses and beds.
26
When there are
sufficient nurses and beds to prevent delays from the OR
into the PACU, case sequencing does not significantly
reduce the necessary PACU nursing hours.
27
Nevertheless,
that may not be so under the conditions in the present
study. This would not change the results of our study about
recovery times, but would reduce their usefulness, since if
it were known ahead which patients likely will recovery in
the ORs, the less expensive intervention would be case
sequencing rather than using more expensive anesthetic
drugs and supplies.
Conflicts of interest The Division of Management Consulting,
Department of Anesthesia, University of Iowa, performs some of the
calculations described in this article. Franklin Dexter receives no
funds personally other than his salary and allowable expense
reimbursements from the University of Iowa and has tenure with no
incentive program. He and his family have no financial holdings in
any company related to his work other than indirectly through mutual
funds for retirement. Income from the Division’s consulting work is
used to fund Division research.
Editorial responsibility This submission was handled by Dr.
Hilary P. Grocott, Editor-in-Chief, Canadian Journal of Anesthesia.
Author contributions Kokila N. Thenuwara and Tatsuya
Yoshimura helped design and conduct the study. Yoshinori Nakata
helped design the study. Franklin Dexter helped design and conduct
the study, analyze the data, and write the manuscript.
Funding Departmental funding.
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C
At the University of Iowa, the postanesthesia care unit (PACU)
discharge policy has three criteria in addition to those of the modified
Aldrete score:
23
normothermia, no indication of urinary retention or
oliguria, and a minimum PACU time of 30 min. The latter had no
influence on results as every patient had a PACU time [30 min
(PACU minimum 36 min and recovery time minimum 58 min). At
Shin-yurigaoka General Hospital, discharge to the ward was left to the
judgment of the anesthesiologist; the electronic anesthesia chart has a
built-in checklist, which is the same as the modified Aldrete score.
23
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hospital admissions but more phase II nursing interventions.
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to decrease the time for emergence or increase the phase I
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ambulatory surgery center. Anesth Analg 1999; 88: 1053-63.
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1302 K. N. Thenuwara et al.
... The definition of a PACU is not uniform, which hinders comparison between different studies. For example, the PACU described by Thenuwara et al. may be seen as a regular recovery room for direct postoperative care [19], whereas the PACU as described in other studies provides prolonged specialized postoperative care-including possible mechanical ventilation-and is similar to the PACU in the current study [12][13][14]20]. A recent systematic review investigating the organization of postoperative care on patient outcome concluded that postoperative care at the PACU was not associated with worse outcomes compared to ICU care [21]. ...
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Background: A post-anaesthesia care unit (PACU) may improve postoperative care compared with intermediate care units (IMCU) due to its dedication to operative care and an individualized duration of postoperative stay. The effects of transition from IMCU to PACU for postoperative care following intermediate to high-risk noncardiac surgery on length of hospital stay, intensive care unit (ICU) utilization, and postoperative complications were investigated. Methods: This single-centre interrupted time series analysis included patients undergoing eleven different noncardiac surgical procedures associated with frequent postoperative admissions to an IMCU or PACU between January 2018 and March 2019 (IMCU episode) and between October 2019 and December 2020 (PACU episode). Primary outcome was hospital length of stay, secondary outcomes included postoperative complications and ICU admissions. Results: In total, 3300 patients were included. The hospital length of stay was lower following PACU admission compared to IMCU admission (IMCU 7.2 days [4.2–12.0] vs. PACU 6.0 days [3.6–9.1]; p < 0.001). Segmented regression analysis demonstrated that the introduction of the PACU was associated with a decrease in hospital length of stay (GMR 0.77 [95% CI 0.66–0.91]; p = 0.002). No differences between episodes were detected in the number of postoperative complications or postoperative ICU admissions. Conclusions: The introduction of a PACU for postoperative care of patients undergoing intermediate to high-risk noncardiac surgery was associated with a reduction in the length of stay at the hospital, without increasing postoperative complications.
... Pavyzdžiui, Japonijoje tik 16 proc. ligoninių taiko pirmąją fazę, kadangi dauguma neturi PAPP, o prabudęs pacientas, susinormalizavus gyvybiniams parametrams, tiesiai iš operacinės perkeliamas į atitinkamą ligoninės skyrių [15]. Slaugytojų pareigos gali būti perimtos kito personalo, pavyzdžiui, slaugytojų padėjėjų ar gydytojų rezidentų, todėl jų skaičius gali kisti. ...
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Poanestezinės priežiūros palatos yra skirtos pacientų prie­žiūrai po anestezijos. Šiose palatose stebimi pacientai, siekiant išvengti su anestezija ar chirurgine intervencija susijusių komplikacijų, laiku jas pastebėti ir gydyti. Slau­gytojų lovų santykis yra svarbus rodiklis vertinant poa­nestezinės priežiūros kokybę. Efektyvų darbą užtikrina reglamentuotos ligoninės ar šalies gairės.
... This study has some limitations. Firstly, residual anesthetic drugs may affect respiration and cause postoperative pulmonary atelectasis 25 . We did not perform postoperative anesthetic drug residue monitoring and cannot exclude the possible effects of anesthetic drug residue on OI and postoperative pulmonary atelectasis. ...
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Objective: This study aimed to evaluate the lung protection effect of an individualized protective ventilation strategy based on lung impedance tomography (EIT) technology in patients with partial pulmonary resection. Patients and methods: Eighty patients of any gender, American Society of Anesthesiologists (ASA) classification I-II, age 30-64 years and body mass index (BMI) 18-28 kg/m2 who underwent elective thoracoscopic partial lung resection were selected and divided into 2 groups (n=40) using the random number table method: [positive end-expiratory pressure (PEEP) by electrical impedance tomography (EIT)] PEEPEIT group (experimental group) and control group. The PEEPEIT group used volume-controlled ventilation after one-lung ventilation, setting a tidal volume of 6 ml/kg and titrating the optimal PEEP value by EIT. Group C used volume-controlled ventilation after one-lung ventilation, setting a tidal volume of 6 ml/kg and a PEEP of 5 cm H2O. Clinical data were collected and recorded at 5 min after double lung ventilation (T0), single lung ventilation, 30 min after PEEP setting (T1), 60 min after PEEP setting (T2), the end of surgery, 10 min after resumption of double lung ventilation (T3) and 10 min after removal of the tracheal tube (T4), and serum surface active substance-associated protein-A (SP-A) concentrations were measured at T0, T3 and 1 d after surgery (T5). Results: PEEP values were higher in the PEEPEIT group than in the control group at T1 and T2 (p-value <0.05); oxygenation index (OI) was higher in the PEEPEIT group compared to the control group at T2 and T3 (p-value <0.05); pulmonary dynamic compliance (Cdyn) was higher in the PEEPEIT group compared to the control group at T1 and T2 (p-value <0.05); intrapulmonary shunt rate (Qs/Qt) was lower in the PEEPEIT group compared to the control group at T1, T2 and at T3, the intrapulmonary shunt rate (Qs/Qt) was reduced in the PEEPEIT group compared to group C (p-value <0.05); at T5, the SP-A protein was reduced in the PEEPEIT group compared to group C. There was no statistically significant difference in the incidence of postoperative pulmonary complications between the two groups (p-value >0.05). Conclusions: The EIT-guided individualized protective ventilation strategy has a lung-protective effect in patients undergoing thoracoscopic partial lung resection.
... Proses pulih sadar dari anestesi harus diawasi seksama dan kondisi pasien harus dinilai ulang sebelum pasien bisa dipindahkan ke ruang perawatan (Permatasari et al., 2017). Rerata waktu pemulihan dilakukan University of Iowa, USA 112 menit dan di Rumah Sakit Umum Shin-yurigaoka, Kawasaki, Jepang 22 menit (Thenuwara et al., 2018). ...
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This study aims to analyze the dominant factors associated with the time to recover consciousness of patients with laparotomy, general anesthesia in the Recovery Room of Bhayangkara Hospital Tk I Jakarta. The research method used is analytical research with a cross-sectional approach. The results showed a relationship between age and recovery time after general anesthesia post-laparotomy (p = 0.028). There was a difference between the sexes and the time to recover consciousness of the laparotomy patients with general anesthesia (p = 0.04). There was a difference between ASA and recovery time of conscious laparotomy patients with general anesthesia (p = 0.01). There was a correlation between BMI and awake in patients with available anesthesia laparotomy (p = 0.0005). There was no relationship between body temperature, fasting time, and duration of operation with p values (0.59, 0.6, and 0.94), respectively. In conclusion, the dominant factor that affects the recovery time of consciousness in post-laparotomy general anesthesia patients is body temperature, namely hypothermia. Keywords: Anesthesia, Laparotomy, Conscious Recovery, Thermoregulation
... All these recommendations significantly increase the costs of management of the operating rooms, the wards, and the health workers, in violation of the main principle, under which outpatient surgery is a low-cost procedure [50][51][52]. ...
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The spread of the COVID-19 disease substantially influenced the International Healthcare system, and the national governments worldwide had before long to decide how to manage the available resources, giving priority to the treatment of the COVID-infected patients. Then, in many countries, it was decided to limit the elective procedures to surgical oncology and emergency procedures. In fact, most of the routine, middle-low complexity surgical interventions were reduced, and the day surgery (DS) activities were almost totally interrupted. As a result of this approach, the waiting list of these patients has significantly increased. In the current phase, with a significant decrease in the incidence of COVID-19 cases, the surgical daily activity can be safely and effectively restarted. Adjustments are mandatory to resume the DS activity. The whole separation of pathways with respect to the long-stay and emergency surgery, an accurate preoperative protocol of patient management, with a proper selection and screening of all-day cases, careful scheduling of surgical organization in the operating room, and planning of the postoperative pathway are the goals for a feasible, safe, and effective resumption of DS activity.
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Background Suppose that before surgery starts predictions of cases’ operating room (OR) times are biased. Summing among cases in ORs, bias causes over-utilized or under-utilized time, reducing the efficiency of use of OR time and labor productivity. Correcting for such bias requires just arithmetic. We focus on benefits of improving the accuracy of unbiased predictors of OR times. Globally, for small or large surgical suites, can machine learning and other computational (e.g., Markov-Chain Monte-Carlo) methods for predicting OR times increase labor productivity? Methods Discrete-event simulations were performed using a realistic but inherently non-explanatory OR model. Then an analytical model of one OR was used with normally distributed times per case. Results Discrete-event simulation results were consistent quantitatively with the several earlier empirical studies. When mean absolute predictive errors of cases’ OR times were decreased while retaining no bias, there was a negligible but significant reduction in productivity. The analytical model showed that there could equally have been negligible but significant increases in productivity. Managers and clinicians should have no expectation that implementing machine learning software to decrease mean absolute predictive errors will increase productivity if without increases to allocated times (i.e., longer durations of the workday into which cases are scheduled). Suppose that allocated times are increased while maintaining the same (longer) staff shift length (e.g., increasing the hours into which cases are scheduled from 10.5 hours to 11.5 hours while staff continue to work 12 hour shifts with <10% risk working late). Then, increasing the accuracy of estimates of cases’ OR times can achieve large (≈6%) increases in productivity, but less so (≈4%) for facilities already (appropriately) using case resequencing decisions to increase productivity. Conclusions Earlier empirical studies of reductions in predictive error have shown small benefit to unbiased estimators because they used current cases and allocated time. Organizations cannot benefit from modern predictive methods unless allocated times are adjusted statistically, differentiated from the longer hours for staff scheduling. Surgical suites in provinces, organizations, etc., with labor contracts based on coverage of allocated hours (e.g., two 4-hour sessions) should not expect benefit, from a labor costs perspective, from investing in newer methods for predicting average operating room time.
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This study aimed to identify the effect of training sessions on Iraqi nurses' practice concerning patients in phase post-anesthesia care. Methodology: There were 50 participants in this cross-sectional study. from April 5th through June 6th, 2021. a sample of nurses from two Parts a First, gender, training session. Second part: It had (20) items on Patients in Phase Post-anesthesia Care. Results: The results of the study showed that all Iraqi nurses who participated (50 nurses) for the practice of nurses about the Patients in Phase Post-anesthesia Care had a low level of practice and there is relationship with training session, and their demographic data and nurses' practice. Conclusions: The finding of the study reported that there weresignificant differences between effect of thetraining sessiononIraqi nurses' practice toward patients in phase post-anaesthesia care. Recommendation: Based on the result finding, the researcher recommended that the implement of the monthly trainingprogramsfor all nurses in Iraq Hospitals.
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A deficiency of the postanesthesia care unit (PACU) beds or nurses may cause delays in the operating rooms (ORs) and increase the number of cancellations. Some disruptions like the COVID-19 pandemic may cause this deficiency. This paper investigates two integrated OR and PACU scheduling problems; one with few PACU beds, and the other with few PACU nurses. For each problem, a mathematical model and a matheuristic are proposed for minimising the number of cancellations. To the best of our knowledge, it is the first study that investigates the implications of a severe lack of the PACU beds or nurses on the number of cancellations. The matheuristics hybridise the decomposition of each instance into some small-sized sub-instances with a variable neighbourhood search algorithm. The main advantages of these methods are their flexibility to incorporate many problem details (such as a step-wise demand for the PACU nurses) and to solve any large-scale problem. Numerical results for a data set with 22 ORs show that with an increasingly severe lack of PACU capacity there is progressively greater benefit of the matheuristics than their initial solutions. Moreover, these results show the influence of the overtime and the recovery in ORs on improving the situation.
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Study Objective. Recently, there has been interest in activity-based cost accounting for inpatient surgical procedures to facilitate “value based” analyses. Research 10-20 years ago, performed using data from 3 large teaching hospitals, found that activity-based cost accounting was practical and useful for modeling surgeons and subspecialties, but inaccurate for individual procedures. We hypothesized that these older results would apply to hundreds of hospitals, currently evaluable using administrative databases. Design. Observational study Setting. State of Texas hospital discharge abstract data for 1st quarter of 2016, 4th quarter of 2015, 1st quarter of 2015, and 4th quarter of 2014 Patients. Discharged from an acute care hospital in Texas with at least 1 major therapeutic (“operative”) procedure Measurements. Counts of discharges for each procedure or combination of procedures, classified by ICD-10-PCS or ICD-9-CM Main Results. At the average hospital, most surgical discharges were for procedures performed at most once a month at the hospital (54%, 95% confidence interval [CI] 51% to 55%). At the average hospital, approximately 90% of procedures were performed at most once a month at the hospital (93%, CI 93% to 94%). The percentages were insensitive to the quarter of the year. The percentages were 3% to 6% greater with ICD-10-PCS than for the superseded ICD 9 CM. Conclusions. There are many different procedure codes, and many different combinations of codes, relative to the number of different hospital discharges. Since most procedures at most hospitals are performed no more than once a month, activity-based cost accounting with a sample size sufficient to be useful is impractical for the vast majority of procedures, in contrast to analysis by surgeon and/or subspecialty.
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The postanesthesia care unit (PACU), which is run and coordinated by anesthesiologists, delivers general medical supervision as well as close and constant care to patients who have just undergone a surgical procedure under anesthesia. Although PACU management has been considered a standard procedure in many developed countries since the 1940s, Japanese hospitals have tended to cease their management, and only 16.1% of hospitals in Japan currently have PACUs. In today's efficiency-required atmosphere in Japan, we need to consider a better postoperative management method, including facilities similar to the PACU, to prevent serious adverse events and improve the postoperative outcomes and quality of life. Nevertheless, the way postoperative patients are treated and cared for, and the location in which they receive such attention, will likely need to be modified to fit the Japanese style due to Japan's unique medical systems and traditions. Here, we describe the past, present and future of the PACU and postanesthesia care in Japan compared with other countries.
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Ambulatory surgery centers (ASC) are implementing new anesthetic techniques and rapid recovery protocols in the postanesthesia care unit (PACU) to achieve earlier discharge after general anesthesia.Using computer simulation, we addressed two questions. First, what is the decrease in an ASC's operating room (OR) staff if the time from which the surgery is finished to the time the patient leaves the OR is decreased? Second, what is the decrease in PACU nursing staffing if patients bypass phase I PACU (i.e., proceed from the OR directly to the phase II PACU)? The decrease in labor costs from rapid emergence or fast-tracking depends on how staff are compensated, how many ORs routinely run concurrently, and what percentage of patients undergo general anesthesia. The results show potential decreases in ASCs' labor costs ($7.39 per case) from technologies (e.g., new anesthetics or Bispectral Index[trade mark sign] [Aspect Medical Systems, Natick, MA] monitoring) to decrease emergence times or increase the phase I bypass rates. Implications: Decreases in operating room and postanesthesia care unit labor costs resulting from faster emergence and phase I postanesthesia care unit bypass vary depending on the amount of routine overtime, how the staff are compensated, and how many patients are routinely anesthetized each day. (Anesth Analg 1999;88:1053-63)
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In this article, we consider the privacy implications of posting data from small, randomized trials, observational studies, or case series in anesthesia from a few (e.g., 1-3) hospitals. Prior to publishing such data as supplemental digital content, the authors remove attributes that could be used to re-identify individuals, a process known as "anonymization." Posting health information that has been properly "de-identified" is assumed to pose no risks to patient privacy. Yet, computer scientists have demonstrated that this assumption is flawed. We consider various realistic scenarios of how the publication of such data could lead to breaches of patient privacy. Several examples of successful privacy attacks are reviewed, as well as the methods used. We survey the latest models and methods from computer science for protecting health information and their application to posting data from small anesthesia studies. To illustrate the vulnerability of such published data, we calculate the "population uniqueness" for patients undergoing one or more surgical procedures using data from the State of Texas. For a patient selected uniformly at random, the probability that an adversary could match this patient's record to a unique record in the state external database was 42.8% (SE < 0.1%). Despite the 42.8% being an unacceptably high level of risk, it underestimates the risk for patients from smaller states or provinces. We propose an editorial policy that greatly reduces the likelihood of a privacy breach, while supporting the goal of transparency of the research process.
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The post-anesthesia care unit (PACU) is a major contributor to the operating room (OR) process flow and efficiency. A sudden failure of hospital facility infrastructure due to a burst pipe resulted in the complete loss of a 66-bed combined preoperative and PACU facility of a major academic medical center. The OR suites were undamaged. The clinical and administrative challenges of caring for surgical patients without the usual preoperative and postoperative care areas are discussed. Our strategy for maintaining OR functions and management of patient flow, OR personnel, case prioritization, and equipment needs are detailed from the time of initial crisis until restoration of these clinical care areas. Utilization of the hospital disaster Incident Command Structure and the activation and decision support provided by the hospital Emergency Operations Center (EOC) for the week immediately following the crisis, helped maintain OR functionality.
Article
Background: Hypoxemia, as measured by pulse oximetry (SpO2), is common in postanesthesia care unit (PACU) patients. The temporal distribution of desaturation has managerial implications because treatment may necessitate the presence of an anesthesiologist. Methods: We retrieved SpO2 values recorded electronically every 30 to 60 seconds from 137,757 PACU patients over n = 80 four-week periods at an academic medical center. Batch mean methods of analysis were used. Onset times of hypoxemic episodes (defined, on the basis of previous studies, as SpO2 <90% lasting at least 2 minutes) were determined and resolution at 3, 5, and 10 minutes was assessed. Episodes beginning <30 minutes and ≥30 minutes after PACU admission were compared. Patients undergoing intubation in the PACU were identified by doing a free text search of electronically recorded nursing notes for phrases suggesting intubation, followed by a confirmatory manual chart review. Intervals from PACU admission to intubation were determined. Results: Fewer than half (31.2% ± 0.05%) of episodes of PACU hypoxemia lasting ≥2 minutes occurred <30 minutes after PACU admission. Most (i.e., >50%) occurred ≥30 minutes after admission (P < 0.0001). Few (<1%) anesthesia providers transporting patients to the PACU were still present in the PACU 30 minutes after arrival in the PACU. Fewer than half (37%; 95% confidence interval, 27.4% to 48.8%) of PACU intubations occurred <30 minutes after PACU admission. Most (i.e., >50%) occurred ≥30 minutes after admission (P = 0.029). Hypoxemic episodes in the PACU resolved more slowly than episodes in operating rooms (P < 0.0001). After 3 minutes, 40.9% ± 0.6% were unresolved in the PACU versus 23% (99% upper confidence limit) in operating rooms, and 32.6% ± 0.5% vs 9% (99% upper confidence limit) after 5 minutes. Conclusions: Because most (68.8%) hypoxemic episodes in the PACU occur ≥30 minutes after admission, a time by which the anesthesia provider who transported the patient usually would no longer be present (>99% of cases), the PACU needs to be considered when anesthesiologist operating room staffing and assignment decisions are made.
Article
Prolonged time to extubation has been defined as the occurrence of a ≥ 15-minute interval from the end of surgery to removal of the tracheal tube. We quantified the increases in the mean times from end of surgery to exit from the OR associated with prolonged extubations and tested whether the increases were economically important (≥ 5 minutes). Anesthesia information management system data from 1 tertiary hospital were collected from November 2005 through December 2012 (i.e., sample sizes were N = 22 sequential quarters). Cases were excluded in which the patient's trachea was not intubated or extubated while physically in the operating room (OR). For each combination of stratification variable (below) and quarter, the mean time from end of surgery to OR exit was calculated for the extubations that were not prolonged and for those that were prolonged. Results are reported as mean ± SEM, with "at least" denoting the lower 95% confidence interval. The mean times from end of surgery to OR exit were at least 12.6 minutes longer for prolonged extubations when calculated with stratification by duration of surgery and prone or other positioning (13.0 ± 0.1 minutes), P < 0.0001 compared to 5 minutes (i.e., times were substantively long economically). The mean times were at least 11.7 minutes longer when calculated stratified by anesthesia procedure code (12.4 ± 0.4, P < 0.0001) and at least 11.3 minutes longer when calculated stratified by surgeon (12.4 ± 0.6, P < 0.0001). We recommend that anesthesia providers document the times of extubations and monitor the incidence of prolonged extubations as an economic measure. This would be especially important for providers at facilities with many ORs that have at least 8 hours of cases and turnovers.
Article
When the phase I postanesthesia care unit (PACU) is at capacity, completed cases need to be held in the operating room (OR), causing a "PACU delay." Statistical methods based on historical data can optimize PACU staffing to achieve the least possible labor cost at a given service level. A decision support process to alert PACU charge nurses that the PACU is at or near maximum census might be effective in lessening the incidence of delays and reducing over-utilized OR time, but only if alerts are timely (i.e., neither too late nor too early to act upon) and the PACU slot can be cleared quickly. We evaluated the maximum potential benefit of such a system, using assumptions deliberately biased toward showing utility. We extracted 3 years of electronic PACU data from a tertiary care medical center. At this hospital, PACU admissions were limited by neither inadequate PACU staffing nor insufficient PACU beds. We developed a model decision support system that simulated alerts to the PACU charge nurse. PACU census levels were reconstructed from the data at a 1-minute level of resolution and used to evaluate if subsequent delays would have been prevented by such alerts. The model assumed there was always a patient ready for discharge and an available hospital bed. The time from each alert until the maximum census was exceeded ("alert lead time") was determined. Alerts were judged to have utility if the alert lead time fell between various intervals from 15 or 30 minutes to 60, 75, or 90 minutes after triggering. In addition, utility for reducing over-utilized OR time was assessed using the model by determining if 2 patients arrived from 5 to 15 minutes of each other when the PACU census was at 1 patient less than the maximum census. At most, 23% of alerts arrived 30 to 60 minutes prior to the admission that resulted in the PACU exceeding the specified maximum capacity. When the notification window was extended to 15 to 90 minutes, the maximum utility was <50%. At most, 45% of alerts potentially would have resulted in reassigning the last available PACU slot to 1 OR versus another within 15 minutes of the original assignment. Despite multiple biases that favored effectiveness, the maximum potential benefit of a decision support system to mitigate PACU delays on the day on the surgery was below the 70% minimum threshold for utility of automated decision support messages, previously established via meta-analysis. Neither reduction in PACU delays nor reassigning promised PACU slots based on reducing over-utilized OR time were realized sufficiently to warrant further development of the system. Based on these results, the only evidence-based method of reducing PACU delays is to adjust PACU staffing and staff scheduling using computational algorithms to match the historical workload (e.g., as developed in 2001).