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Rehabilitation impact indices and their
independent predictors: a systematic
review
Gerald Choon-Huat Koh,
1
Cynthia Huijun Chen,
1
Robert Petrella,
2,3
Amardeep Thind
2
To cite: Koh GC-H, Chen CH,
Petrella R, et al.
Rehabilitation impact indices
and their independent
predictors: a systematic
review. BMJ Open 2013;3:
e003483. doi:10.1136/
bmjopen-2013-003483
▸Prepublication history and
additional material for this
paper is available online. To
view these files please visit
the journal online
(http://dx.doi.org/10.1136/
bmjopen-2013-003483).
GCK and CHC contributed
equally to this work.
Received 1 July 2013
Revised 13 August 2013
Accepted 15 August 2013
1
Saw Swee Hock School of
Public Health, National
University of Singapore,
National University Health
System, Singapore,
Singapore
2
Department of Family
Medicine, Schulich School of
Medicine & Dentistry,
University of Western
Ontario, London, Ontario,
Canada
3
Lawson Health Research
Institute, London, Ontario,
Canada
Correspondence to
Dr Gerald C Koh;
Gerald_Koh@nuhs.edu.sg
ABSTRACT
Objectives: To (1) identify all available rehabilitation
impact indices (RIIs) based on their mathematical
formula, (2) assess the evidence for independent
predictors of each RII and (3) propose a nomenclature
system to harmonise the names of RIIs.
Design: Systematic review.
Data sources: PubMed and references in primary
articles.
Study selection: First, we identified all available RII
through preliminary literature review. Then, various
names of the same formula were used to identify
studies, limited to articles in English and up to 31
December 2011, including case–control and cohort
studies, and controlled interventional trials where RIIs
were outcome variable and matching or multivariate
analysis was performed.
Results: The five RIIs identified were (1) absolute
functional gain (AFG)/absolute efficacy/total gain,
(2) rehabilitation effectiveness (REs)/Montebello
Rehabilitation Factor Score (MRFS)/relative functional
gain (RFG), (3) rehabilitation efficiency (REy)/length of
stay-efficiency (LOS-EFF)/efficiency, (4) relative
functional efficiency (RFE)/MRFS efficiency and
(5) revised MRFS (MRFS-R). REy/LOS-EFF/efficiency
had the most number of supporting studies, followed
by REs and AFG. Although evidence for different
predictors of RIIs varied according to the RII and study
population, there is good evidence that older age,
lower prerehabilitation functional status and cognitive
impairment are predictive of poorer AFG, REs and REy.
Conclusions: 5 RIIs have been developed in the past
two decades as composite rehabilitation outcome
measures controlling premorbid and prerehabilitation
functional status, rate of functional improvement, each
with varying levels of evidence for its predictors.
To address the issue of multiple names for the same
RII, a new nomenclature system is proposed to
harmonise the names based on common mathematical
formula and a first-named basis.
INTRODUCTION
Little is known about composite indices of
rehabilitation outcomes and the effects of
sociodemographic factors and comorbidities
on these indices. Thus, there is a need to
(1) identify and characterise robust rehabilita-
tion impact indices (RIIs) that can be mea-
sured across sites and settings for comparative
effectiveness research, and (2) determine the
key predictors of these RIIs so that the former
can be adjusted for meaningful evaluation
across sites and settings.
Currently, many studies in rehabilitation
use the final functional status as the outcome
measure after adjusting for the participant’s
initial functional status. However, both were
highly correlated resulting in most variation
in multivariate analysis being accounted by
initial functional status.
1
Moreover, the final
functional status does not consider speed of
functional recovery or achievement of
rehabilitation potential both of which are
important in quality of care.
23
Researchers
have devised several RIIs that account for
baseline functional status. However, these
RIIs have been given different names
although they share the same mathematical
formula, which is inconsistent and confusing.
Moreover, the independent predictors of
RIIs have never been systematically identified
ARTICLE SUMMARY
Strengths and limitations of this study
▪Use of only one citation database for our litera-
ture search. Our literature search was limited to
only articles in English due to the high cost of
technical translations as well as the validity of
how these rehabilitation impact indices (RIIs)
were recorded.
▪It is the first rehabilitation literature to methodic-
ally review all RIIs available based on their
formula for calculation. It proposes a nomencla-
ture system to harmonise the names of RIIs
across the rehabilitation discipline based on a
rational first-named basis.
▪Evidence of independent predictors accessed in
these RIIs were applied over a wide range of
medical conditions and study populations.
Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483 1
Open Access Research
for the wide range of conditions requiring rehabilitation.
Hence, we performed a systematic review to (1) identify
all available RIIs and their synonyms, and categorise
them according to mathematical formula, (2) identify
and assess the evidence for independent predictors of
each RII, and (3) propose a nomenclature system to har-
monise the terminology of RIIs.
METHODS
We conducted this review according to the Preferred
Reporting Items for Systematic Reviews and Meta-Analyses
(PRISMA) statement for reporting systematic reviews.
4
To achieve the first two aims of the study, we con-
ducted the systematic review in two stages. The first stage
was to identify all available RIIs and categorise them
according to the same mathematical formula but under
different names. For example, the difference between
admission and discharge functional scores was termed as
absolute function gain (AFG), absolute efficacy or total gain.
The second stage was to use these different names and
report their independent predictors. For example, we
used the terms ‘absolute function gain’,‘absolute effi-
cacy’and ‘total gain’to identify all articles using differ-
ence between admission and discharge functional
scores. RIIs are prospective as they require functional
status to be measured across two time points. Hence, to
determine the independent predictors of RIIs, we
included case–control and cohort studies, and con-
trolled interventional trials that had RIIs as outcomes,
and excluded descriptive studies that did not examine
factors associated with RIIs. We deemed factors as inde-
pendent predictors if multivariate analysis was per-
formed. In controlled trials, the intervention was
considered a predictive factor.
Studies were identified from PubMed (until 31
December 2011) as the primary citation database to
conduct our literature search and reviewed the articles
referenced in these primary for secondary literature which
may be eligible for our systematic review. Search terms were
specific for each RII. For absolute functional gain, we used
the search terms ‘absolute function gain’,‘absolute effi-
cacy’and ‘total gain’. For rehabilitation effectiveness
(REs), we used the search terms ‘rehabilitation effective-
ness’,‘Montebello Rehabilitation Factor score’and ‘relative
functional gain’. For rehabilitation efficiency (REy), we
used the search terms ‘rehabilitation efficiency’,
‘length-of-stay efficiency’and ‘efficiency’. For relative func-
tional efficiency (RFE), we used the search terms ‘relative
functional efficiency’and ‘MRFS efficiency’.
We limited our search to articles in English as the cost
of technical translations was beyond our budget. Of note,
we did not limit any medical condition (eg, stroke) or
study population (eg, elderly) as rehabilitation is a spe-
cialty defined by treatment and our primary aim was to
study the properties of RIIs in the full range of study
populations. The abstracts of all articles retrieved were
first screened for use of RIIs, subsequently the full articles
were retrieved if they satisfied the criteria described
above. Details of the primary articles eligible for the sys-
tematic review were extracted and tabulated (see online
supplementary tables S1–S3), and their statistically signifi-
cant ( p<0.05) independent predictors were identified.
Evidence for a factor as a predictor of an RII was deemed
to be none if there was no supporting study, weak if there
was only one supporting study, fair if there were two sup-
porting studies, moderate if there were three supporting
studies and good if there were four or more supporting
studies. Similar systems of using number of supporting
studies to weigh scientific evidence have been used by
previous systematic reviews.
56
We did not perform a meta-analysis of pooled data to
generate the overall effect size for each predictor because
of the small number of studies available for each predictor
after stratification by study population, different functional
measures were used across studies which limited pooling of
estimates and important data were missing from primary
articles which precluded pooling of estimates (eg, CIs).
Lastly, we proposed a nomenclature system to harmonise
the terminology of RIIs for future use on the basis that the
name of the RII should (1) follow the name coined by the
first author(s) to define it and (2) be logical and intuitive.
This study was exempted from ethics review because it did
not involve human participants.
RESULTS
From the first stage of our systematic review, we identi-
fied five RIIs used in rehabilitation literature. Figure 1
details the study selection process, including the five
RIIs identified and their synonyms, the number of
potentially relevant articles retrieved from PubMed, the
number of full articles satisfying study eligibility criteria
and the final number of articles accessed. For the
remaining Results section, we will present mathematical
formula for each RII, its synonyms and its independent
predictors.
Absolute functional gain/absolute efficacy/total gain
AFG was first coined by Heruti et al
7
as the difference in
functional measure score before and after rehabilitation.
Mathematically, the formula (FIM, functional independ-
ence measure; DC, discharge; adm, admission) is as
follows:
AFG ¼DC(FIM) adm(FIM)
Other authors have referred to AFG as absolute (FIM)
efficacy or total (FIM) gain.
7–13
After performing a sys-
tematic literature search using these names as search
terms, we found seven studies which studied predictors
for this RII.
7–13
All these studies used FIM as the func-
tional measure. The predictors of poorer AFG/absolute
efficacy/total gain stratified by the study population are
summarised in table 1 and details are found in online
supplementary table S1.
2Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483
Open Access
From table 1, independent predictors of poorer AFG/
absolute efficacy/total gain are older age,
11 13
lower prereh-
abilitation functional status,
11
cognitive impairment,
79–11
non-treatment with thrombolysis
13
and greater neuro-
logical impairment.
13
The independent predictors were
supported by stroke (2 studies), post-hip-fracture arthro-
plasty (2 studies) and the elderly (1 study).
Rehabilitation effectiveness/Montebello Rehabilitation
Factor Score/
Relative functional gain
REs was a concept first suggested by Heinemann et al.
1
However, it was Shah et al who coined the term rehabili-
tation effectiveness later in 1990.
14
Expressed as a per-
centage reflecting the proportion of potential
improvement actually achieved during rehabilitation, it
can be calculated using the formula (BI, Barthel index;
DC, discharge; adm, admission; max, maximum possible
score):
REs ¼DC(BI or FIM) adm(BI or FIM)
Max(BI or FIM) adm(BI or FIM) 100%
REs are viewed to be superior to AFG/absolute efficacy/
total gain because the latter does not take into account
the potential maximal functional improvement. For
example, patient A improved his BI score from 20 to 60,
whereas patient B improved his BI score from 60 to 100;
although both patients improved by 40 BI units, patient
A has only reached ((60–20)/(100–20))=40/80=50% of
his highest possible level of improvement, whereas
patient B has reached his highest possible level of
improvement (100%) and is now independent.
REs were renamed by other authors as Montebello
Rehabilitation Factor Score (MRFS) in 1994 and relative
functional gain (RFG) in 2007. After performing a
PubMed search, 16 studies were identified.
17914–26
The
predictors of poorer REs/MRFS/RFG stratified by study
population are summarised in table 2 and details are
found in online supplementary table S2.
From table 2, independent predictors of poorer REs/
MRFS/RFG that have been reported are (1) older
age,
114152426
(2) lower prerehabilitation functional
status,
1141517202426
(3) non-acute hospital admis-
sions,
1
(4) cognitive impairment,
79161820232426
Figure 1 Study selection process for the five rehabilitation impact indices (RIIs) identified.
Table 1 Summary of independent factors of poorer absolute functional gain (AFG), absolute efficacy or total gain from
studies by study population*
Sl.
no.
Independent factors of poorer AFG,
absolute efficacy or total gain Stroke
Post-hip-fracture
arthroplasty Elderly
1 Older age
11 13
––
2 Lower prerehabilitation functional
status
11
––
3 Cognitive impairment
11 7 9 10
4 Prior stroke with motor impairment –– –
5 Non-treatment with thrombolysis
13
––
6 Greater neurological impairment
13
––
*Article reference numbers in cells.
Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483 3
Open Access
(5) urinary incontinence,
14 23
(6) myocardial infarction
1
(7) longer ‘stroke onset to admission into rehabilitation
unit’time,
14 26
(8) longer ‘admission to unit to start of
rehabilitation’time,
14
(9) poor adherence to clinical
practice guidelines,
17
(10) territory of stroke,
17
(11)
orthogeriatric setting (as compared with a two-step
model of orthopaedic surgery followed by transfer to a
geriatric rehabilitation facility),
18
(12) users of psych-
ology medications,
19
(13) subcortical vascular lesions,
21
(14) prior episode of stroke,
22
(15) lower body mass
index,
23
(16) unilateral spatial neglect,
25
(17) female
gender,
26
(18) Malay (vs Chinese) ethnicity,
26
(19) care-
giver availability,
26
(20) infarct (vs haemorrhage)
stroke
26
and (21) shorter length of stay (LOS).
23 26
The
independent predictors of REs/MRFS/RFG were sup-
ported by stroke (9 studies), post-hip-fracture arthro-
plasty (5 studies), elderly (1 study) and gait disorders (1
study). Overall, the evidence for older age (5 studies),
lower prerehabilitation functional status (8 studies) and
cognitive impairment (8 studies) as predictors of poorer
REs/MRFS was strong.
Rehabilitation efficiency/Length of stay-efficiency/
efficiency
The concept of REy was also first suggested by
Heinemann et al
1
using the BI. Later, Shah et al
14
renamed this concept to REy. It can be regarded as the
average increase in the score of a functional assessment
tool per day and is calculated using the following
formula (where DC, discharge; adm, admission; date,
date of functional assessment scoring):
REy ¼DC(BI or FIM) adm(BI or FIM)
DateDC dateadm
REy is also known as LOS-efficiency (LOS-EFF) and FIM
efficiency. Compared with REs/MRFS/RFG, there are
many more studies which have used REy/LOS-EFF/effi-
ciency with 63 studies examining predictors of this
RII.
1713–15 25–82
The predictors of poorer REy/LOS-EFF/
efficiency stratified by study population are summarised in
table 3. The details of each study reporting REy/
LOS-EFF/efficiency are found in the online supplemen-
tary table S3. There were four pairs of studies which were
potentially duplicate publications: (Lin
43
and Lin et al
44
;
Yu and Richmond
58
and Yu et al
59
;Vincentet al
64
and
Vincent et al
67
; Vincent et al
65
and Vincent et al
66
;see
online supplementary table S3). Only the last three pairs
of studies reported independent predictors of REy/
LOS-EFF/efficiency (table 3). We chose to treat these
studies as separate original studies as we could not be sure
whether they were duplicate publications.
From table 3, the independent predictors of REy/
LOS-EFF/efficiency that have been reported are
(1) admissions from sources other than home,
1
(2) older
age,
14 15 33 58 59 74 80
(3) lower prerehabilitation
Table 2 Summary of independent factors of poorer rehabilitation effectiveness (REs) or Montebello Rehabilitation Factor
Score (MRFS) or relative functional gain (RFG) from studies by study population*
Sl.
no.
Independent factors of poorer
REs/MRFS/RFG Stroke
Post-hip-fracture
arthroplasty Elderly
Gait
disorders
1 Older age
114152426
––
2 Lower prerehabilitation functional status
11415172426 2022
––
3 Non-acute hospital admissions
1
–––
4 Cognitive impairment
16 24 26 7 9 18 20 23
–
5 Urinary incontinence
14
–
23
–
6 Myocardial infarction
1
–––
7 Longer ‘stroke onset to admission into
rehabilitation unit’time
14 26
–––
8 Longer ‘admission to unit to start of
rehabilitation’time
14
–––
9 Poor adherence to clinical practice guidelines
17
–––
10 Orthogeriatric setting –
18
––
11 Subcortical vascular lesions –– –
21
12 Shorter length of stay
26
–
23
–
13 Lower body mass index ––
23
–
14 Unilateral spatial neglect
25
–––
15 Female gender
26
–––
16 Malay (vs Chinese) ethnicity
26
–––
17 Caregiver availability
26
–––
18 Ischaemic (vs haemorrhagic) stroke
26
–––
19 Users of psychotropic medication
19
–––
20 Territory of stroke
17
–––
21 Prior stroke –
22
––
*Article reference numbers in cells.
4Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483
Open Access
Table 3. Summary of independent factors of poorer rehabilitation efficiency (REy) or length-of-stay efficiency (LOS-EFF) or Functional Independence Measure (FIM)
Efficiency by study population*
S/No.
Independent factors of poorer
REy/LOS Efficiency/FIM
Efficiency Stroke
Post hip
fracture
arthroplasty Elderly Heterogeneous
Brain
tumor
Brain
injury
Spinal
cord
injury Encephalitis
Hemo
dialysis
Knee
arthroplasty
1. Admissions from sources other than
home
1
−−− −−−−−−
2. Older age
14 15 80 74 58†59†
−−−
33
−−−
3. Lower pre-rehabilitation functional status
14 15 80 74 47 58†
59†
−−−−−−−
4. Ischemic (vs. hemorrhagic) stroke
26 28
−−− −−−−−−
5. Depression
34 42 54
−− −−−− − −
6. Cognitive impairment
26 7 54
−− −−−− − −
7. Poorer balance −− −
30
−−−− − −
8. Heterotopic ossification on triple-phase
bone scan (vs. none)
−− − − −
35
−− − −
9. Non-traumatic (vs. traumatic) spinal cord
injury
−− − − − −
38
−−−
10. Encephalitis (vs. traumatic brain injury or
stroke)
−− − − − −−
39
−−
11. Longer length of stay
15 26
−−− −−−−−−
12. Direct admission from emergency ward
(vs. indirect admission via general
medical ward)
41
−−− −−−−−−
13. Not receiving radiation therapy during
rehabilitation (vs. receiving) in brain
tumor patients
−− − −
45
−− − − −
14. Recurrent (vs. first diagnosis) in brain
tumor patients
−− − −
45
−− − − −
15. Greater co-morbidity burden −
71 47
−−−−−−−
16. Spinal stenosis-induced (vs. traumatic)
spinal cord injury
−− − − − −
49
−−−
17. Japan (vs. USA)
50
−−− −−−−−−
18. Right hemispheric stroke
51
−−− −−−−−−
19. Greater neurological impairment
51 79
−−− −−−−−−
20. Dialysis (vs. non-dialysis) patients −− − − − −− −
53
−
21. Program to reduce conflicts between
hemodialysis and therapy sessions
−− − − − −− −
56
−
22. Extremes of dependency
57 58
−−− −
63
−− − −
23. Discharge to nursing facility (vs. home)
60 61
−−− −−−−−−
24. Lower haemoglobin levels −− − − − −− − −
61
Continued
Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483 5
Open Access
Table 3. Continued
S/No.
Independent factors of poorer
REy/LOS Efficiency/FIM
Efficiency Stroke
Post hip
fracture
arthroplasty Elderly Heterogeneous
Brain
tumor
Brain
injury
Spinal
cord
injury Encephalitis
Hemo
dialysis
Knee
arthroplasty
25. Longer ‘stroke onset to admission into
rehabilitation unit’time
26 51 62
−−− −−−−−−
26. Revision (vs. primary) total hip
arthroplasty
−
64†
−− −−−− − −
27. Revision (vs. primary) total knee
arthroplasty
−− − − − −− − −
65†66†72
28. Female gender −
67†
−− −−−− −
65†
29. Aortic aneurysm repair induced (vs.
traumatic) spinal cord injury
−− − − − −
68
−−−
30. Principal disability diagnosis (in order of
decreasing FIM efficiency: traumatic
brain injury, stroke, spinal cord injury,
amputations and pulmonary conditions)
−− −
70
−−−− − −
31. Extremes of body-mass index −
71
−− −−−− − −
32. Primary (vs. co-morbid) debility
diagnosis
−−
73
−−−−−−−
33. Hispanic and black (vs. white) ethnicity
74
−−− −−−−−−
34. Lower staff to patient ratio
76
−−− −−−−−−
35. Neglect
25 79
−−− −−−−−−
36. Non-treatment with thrombolysis
13
−−− −−−−−−
37. Diabetes mellitus −
80
−− −−−− − −
38. Medications that predispose to falls −
80
−− −−−− − −
39. Malay (vs. Chinese) ethnicity
26
−−− −−−−−−
40. Caregiver availability (vs. no caregiver)
26
−−− −−−−−−
41. Higher pre-rehabilitation functional status
26
−−− −−−−−−
42. Peptic ulcer disease
26
−−− −−−−−−
* Paper reference numbers in cells
†The following pairs of reference numbers are potentially duplicate publications: [58 & 59], [64 & 67] and [65& 66]
6Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483
Open Access
functional status,
14 15 47 58 59 74 80
(4) non-haemorrhagic
(vs haemorrhagic) stroke,
26 28
(5) depression,
34 42 54
(6)
cognitive impairment,
72654
(7) poorer balance,
30
(8)
heterotopic ossification on triple-phase bone scan (vs
none),
35
(9) non-traumatic (vs traumatic) spinal cord
injury,
38
(10) encephalitis (vs traumatic brain injury or
stroke),
39
(11) longer LOS,
15 26
(12) direct admission
from emergency ward (vs indirect admission via general
medical ward),
41
(13) not receiving radiation therapy
during rehabilitation (vs receiving) in patients with brain
tumour,
45
(14) recurrent (vs first diagnosis) in patients
with brain tumour,
45
(15) greater comorbidity
burden,
47 71
(16) spinal stenosis-induced (vs traumatic)
spinal cord injury,
49
(17) Japan (vs USA),
50
(18) right
hemispheric stroke,
51 79
(19) greater neurological impair-
ment,
51
(20) patients undergoing dialysis (vs non-
dialysis),
53
(21) programme to reduce conflicts between
haemodialysis and therapy sessions,
56
(22) extremes of
dependency,
57 58 63
(23) discharge to nursing facility (vs
home),
60 61
(24) lower haemoglobin levels,
61
(25) longer
‘stroke onset to admission into rehabilitation unit’
time,
26 51 62
(26) revision (vs primary) total hip arthro-
plasty,
64
(27) revision (vs primary) total knee arthro-
plasty,
65 66 72
(28) female gender,
65 67
(29) aortic
aneurysm repair induced (vs traumatic) spinal cord
injury,
68
(30) principal disability diagnosis (in order of
decreasing FIM efficiency: traumatic brain injury, stroke,
spinal cord injury, amputations and pulmonary condi-
tions),
70
(31) extremes of body mass index,
71
(32) primary
(vs comorbid) debility diagnosis,
73
(33) Hispanic and
African-American (vs white) ethnicity,
74
(34) lower
staff-to-patient ratio,
76
(35) neglect,
25 79
(36) non-
treatment with thrombolysis,
13
(37) diabetes mellitus,
80
(38) medications that predispose to falls,
80
(39) Malay (vs
Chinese) ethnicity,
26
(40) caregiver availability (vs no care-
giver),
26
(41) higher prerehabilitation functional status
26
and (42) peptic ulcer disease.
26
The medical conditions
and study populations from which independent predictors
of REy/LOS-EFF/efficiency were derived included strokes
(21 studies), post-hip-fracture arthroplasty (7 studies),
elderly (4 studies), heterogeneous (2 studies), brain
tumour (1 study), brain injury (2 studies), spinal cord
injury (4 studies), encephalitis (1 study), haemodialysis
(2 studies) and knee arthroplasty (4 studies). Overall, the
evidence for older age and lower prerehabilitation func-
tional status as predictive of poorer REy/LOS-EFF/effi-
ciency were good with seven (6 if 1 considers Yu and
Richmond
58
and Yu et al
59
as duplicate publications)
studies each reporting this association respectively
with most of the studies based on stroke and elderly
rehabilitation, a situation similar with REs/MRFS/
RFG. The evidence for cognitive impairment being pre-
dictive of poorer REy/LOS-EFF/efficiency was weaker
when compared with REs/MRFS/RFG (3 vs 8 studies,
respectively). Of note, unlike with REs/MRFS/RFG, the
evidence for depression being predictive of poorer REy/
LOS-EFF/ efficiency was stronger (none vs 3 studies,
respectively).
Relative functional efficiency/MRFS efficiency
Heruti et al
16
defined RFE in 2002 as REs/MRFS/RFG
divided by LOS. In the same year, Zwecker et al
83
used
the term MRFS efficiency to describe the same formula.
The formula for RFE/MRFS efficiency using FIM as the
functional assessment tool (where DC, discharge; adm,
admission; max, maximum possible score) is as follows:
RFE ¼DC(BI or FIM) adm(BI or FIM)
Max(BI or FIM) adm(BI or FIM) 1
LOS ¼REs
LOS
¼AFG
(Max(BI or FIM) adm(BI or FIM)) LOS
Heruti et al
16
demonstrated that the RFE/MRFS effi-
ciency was higher in cognitively intact elderly partici-
pants (n=79) compared to cognitively impaired elderly
participants (n=65) admitted into a geriatric rehabilita-
tion unit but Zwecker et al
83
found no associations
between RFE/MRFS efficiency and cognitive function.
Recently, Toglia et al
84
found that the Montreal
Cognitive Assessment (MoCA) was predictive of RFE/
MRFS efficiency in 72 patients with mild subacute
stroke. To date, these are the only three articles so far
that have used the RFE/MRFS efficiency index. Further
studies are needed to increase the evidence base for pre-
dictors of this relatively new RII.
Revised MRFS
In 2007, Press et al
85
proposed a new RII: the revised
MRFS (MRFS-R). They proposed that the highest pos-
sible functional status should not be the maximum score
of the functional assessment tool used but the premor-
bid functional score instead. For example, hypothetical
patient A was quite functional with a premorbid func-
tional score (premorbidFIM) of 120 before a fracture;
after fracture repair, on admission to the rehabilitation
department, patient A’s admFIM score dropped to 60.
After rehabilitation, patient A’s DCFIM rose to 80. In
this case, patient A’s MRFS was 0.33, as follows:
MRFS ¼DCFIM admFIM
PremorbidFIM admFIM ¼80 60
120 60 ¼20
60
¼0:33
Patient B who was much more dependent before suffer-
ing a hip fracture had premorbid functional score
(premorbidFIM) of 80. Patient B’s admFIM score
dropped to 20 after hip fracture and after rehabilitation,
patient B’s DCFIM score rose to 40. In patient B’s case,
the MRFS score was also 0.33:
MRFS ¼DCFIM admFIM
PremorbidFIM admFIM ¼40 20
80 20 ¼20
60
¼0:33
As such, according to the MRFS formula, these two
patients enjoyed an equal level of rehabilitation success.
Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483 7
Open Access
However, these two patients are different as patient B
started with a poorer premorbid functional status than
patient A. As such, Press et al proposed a revised MRFS
which adjusts the MRFS to make it more relevant to clin-
ical practice by changing the calculation from an abso-
lute to a relative one and using the premorbid
functional score as the highest possible functional status
attainable, as follows:
MRFSR¼ðDCFIMadmFIMÞ=DCFIM
ðPremorbidFIMadmFIMÞ=premorbidFIM
¼MRFS=DCFIM
premorbidFIM
Using this new index, patient A’s MRFS-R would be 0.5,
as follows:
MRFSR¼ðDCFIMadmFIMÞ=DCFIM
ðPremorbidFIMadmFIMÞ=premorbidFIM
¼(8060)=80
(12060)=120¼20=80
60=120¼0:25
0:5¼0:5
Patient B’s MRFS-R score would be higher at 0.67, as
follows:
MRFSR¼(DCFIMadmFIM)=DCFIM
ðPremorbidFIMadmFIMÞ=premorbidFIM
¼(4020)=40
(8020)=80¼20=40
60=80¼0:5
0:75¼0:67
Press et al assert that patient B realised his/her rehabili-
tation potential more than patient A and that the
MRFS-R is a more useful way to quantify the differences.
In the same article, Press et al
85
compared the MRFS-R
with MRFS and found that they were very highly corre-
lated (r = 0.99, p<0.01). Nevertheless, in a linear regres-
sion model with MMSE, LOS and Severity Index of
Cumulative Illness Rating Scale for Geriatrics as inde-
pendent factors, they found the adjusted R
2
for MRFS-R
was higher than with MRFS as the dependent variable
(0.16 vs 0.12), suggesting that the MRFS-R accounted for
more variance in the similar model than MRFS. As this
is the first and currently only article that has used
MRFS-R, more studies are needed to increase the evi-
dence base for predictors of this new RII as well.
DISCUSSION
Increasingly complex RIIs have been developed in the
past decade in response to the need to create composite
summative measures that control for premorbid and pre-
rehabilitation functional status, and rate of functional
improvement. The current RIIs available in increasing
complexity are: (1) AFG, (2) REs, (3) REy, (4) relative
rehabilitation efficiency (RREy) and (5) relative rehabili-
tation effectiveness (RREs). On the basis of current lit-
erature, more studies have used REy than REs, and even
fewer have used AFG, RREy or RREs. Thus, the number
of known predictors is highest for REy than the other
RIIs. Although the evidence varies, there is consistent
evidence that older age, lower prerehabilitation func-
tional status and cognitive impairment are predictive of
poorer AFG, REs and REy, particularly in stroke and
post-hip-fracture arthroplasty rehabilitation.
One of the possible reasons why few studies have used
AFG as an RII could be that AFG does not take into
account the potential maximal functional improvement
like REs and RREs. Another reason could be that AFG
does not consider the rate of functional improvement
per unit time like REy and RREy. It is also worthwhile to
note that although Heruti et al’s
7
study found associa-
tions between cognitive impairment and REs, it did not
find any such association with AFG, supporting the
superiority of REs as an RII over AFG.
Most researchers use LOS for a hospital stay as the
denominator for REy and RREy instead of the number
of days between first and final functional assessment
scoring. This is acceptable provided the functional
scoring is performed close to the date of admission and
discharge. However, if the first functional measurement
was performed many days after admission or the last
functional assessment was performed many days before
date of discharge, REy and RREy may be spuriously high
if LOS was used in the denominator. Hence, it may be
more accurate to use the number of days between the
date of first and last functional measurement as the
denominator for REy instead of LOS, as conducted by
Koh et al
26
In fact, it was because Koh et al used time
between first and last functional assessment in their
study that they were able to demonstrate that LOS was
an independent predictor of REy and not the result of
statistical singularity arising from LOS being the denom-
inator of REy.
Three RIIs use the variable ‘maximal score attainable’
(ie, max (BI or FIM)): REs, RREs and RREy. Some
studies use the maximum score of the functional meas-
urement tool (eg, 100 for BI and 126 for FIM), whereas
other studies use the premorbid functional level of the
patient (ie, prior to disabling event that necessitated
rehabilitation, like stroke or hip fracture). The propo-
nents for the latter argue that premorbid functional
status is more appropriate because it is more meaningful
to the patient and a person’s function rarely improves
beyond their premorbid functional status. However,
there are disadvantages in using premorbid functional
status as the ‘maximal score attainable’. First, premorbid
functional data are often not available as patients often
present in acute settings already disabled from a stroke
or hip fracture. Hence, premorbid functional data are
often collected retrospectively from patient or caregiver
and is vulnerable to recall bias. Second, studies have
shown that persons can still improve their functional
status months to years after their acute disabling event
with rehabilitation, suggesting that one’s premorbid
functional status is not necessarily their maximal
8Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483
Open Access
functional status attainable.
86–88
Lastly, by fixing max (BI
or FIM) as the maximum score of activities of daily
living measure used, rehabilitation indices become stan-
dardised which is important when comparing across
studies, sites or time. We recommend that users of RIIs
that contain the variable max (BI or FIM) clearly state
in their publications which ‘maximal score attainable’
they used (ie, maximum score of functional measure or
premorbid functional status).
It is also noteworthy that there may be trade-off rela-
tionships between RIIs with respect to certain independ-
ent predictors. Koh et al
26
found that a shorter LOS and
poorer prerehabilitation functional status was predictive
of poorer REs, but longer LOS and better prerehabilita-
tion functional status was predictive of poorer REy. The
authors also demonstrated a trade-off relationship
between REs and REy with respect to LOS and prereh-
abilitation functional status, and identified the ideal
range of LOS and prerehabilitation functional status
which optimised REs and REy.
Having the same RII with different synonyms is confus-
ing and limits dissemination of results in the inter-
national research community, especially within the
multidisciplinary field of rehabilitation. To standardise
the terminology of RIIs with the same mathematical
formula, we propose a harmonised nomenclature system
for RIIs on the basis that the name for the RII should
follow the name coined by the first author(s) to define
it, and be logical and intuitive, as detailed in table 4.
While subject to international acceptance, we feel that
our harmonised nomenclature system for RIIs is fairer to
the authors who first named it and more easily
understood.
A limitation in our study was the use of only one cit-
ation database for our literature search. However, we felt
that this was sufficient as a high percentage of health-
care, medical and rehabilitation articles would be
archived in this database. Another limitation of our
qualitative systematic review was that it would under-
identify predictors of RIIs compared to a quantitative
one (ie, a meta-analysis) as the latter would have greater
power to achieve statistical significance due to larger
sample sizes from pooling of studies. Another limitation
was that our literature search was limited to only articles
in English due to the high cost of technical translations.
Another limitation is the validity of how these rehabilita-
tion indices were recorded. As the FIM and the Barthel
index generate ordinal data, it should not be treated as
interval numbers and factor analysis should be used to
group related measures together. Factor analyses have
consistently shown that the FIM comprises two separate
factors (a motor and a cognitive factor),
87
and Rasch
analysis had suggested that FIM scores should use a
transformation to convert ordinal data into interval
data.
88 89
Thus, the raw ordinal scores should not be
summed into a single total, and the above mathematical
manipulations (subtraction or division) of rehabilitation
indices (table 4) may not be valid. In addition, although
FIM and BI have recognised floor/ceiling effects,
89–93
only three studies specifically reported extremes of
Table 4. Proposed harmonized nomenclature system for rehabilitation indices
S/No. Current Names Formula* Proposed Standard Name
1. ▸Absolute Functional Gain
(AFG)
▸Absolute (FIM) Efficacy
▸Total (FIM) Gain
FIMDC FIMAdm Absolute Functional Gain (AFG)
2. ▸Rehabilitation Effectiveness
(REs)
▸Montebello Rehabilitation
Factor Score (MRFS)
▸Relative Functional Gain
(RFG)
FIMDC FIMAdm
FIMMaxFIMAdm
Rehabilitation Effectiveness (REs), prefixed by
functional measure used (e.g. FIM effectiveness, BI
effectiveness)
3. ▸Rehabilitation Efficiency
(REy)
▸Length-of-Stay Efficiency
(LOS-EFF)
▸(FIM) Efficiency
FIMDC FIMAdm
LOS
Rehabilitation Efficiency (REy), prefixed by functional
measure used (e.g. FIM efficiency, BI efficiency)
4. ▸Relative Functional
Efficiency (RFE)
▸MRFS Efficiency
FIMDC FIMAdm
ðFIMMax FIMAdmÞX LOS
MRFS Efficiency
5. Revised MRFS (MRFS-R) (FIMDC FIMAdmÞ=FIMDC
ðFIMMax FIMAdmÞ=FIMMax
Revised MRFS (MRFS-R)
* FIM=Functional Independence Measure; DC=Discharge; Adm=Admission; Max=Maximum possible score, LOS=Length of Stay
Koh GC-H, Chen CH, Petrella R, et al.BMJ Open 2013;3:e003483. doi:10.1136/bmjopen-2013-003483 9
Open Access
dependency predicting FIM efficiency (Gagnon et al,
57
Yu et al
59
and Turner-Strokes et al
63
;table 3), which may
suggest reporting bias. However, we feel that it could be
because most of the studies have either not reached
extremes of dependency or authors may not have
checked for extremes in the first place. For example, in
Turner-Strokes et al’s article, the study population was
patients with severe acquired brain injury which ranged
from the severely functionally impaired to those who
recovered well. The literature search was also only con-
ducted by one author (GCK) although the data extrac-
tion and analysis were verified by the other three
authors, independently. We also acknowledge that our
system of weighing the level of evidence for predictors
of RIIs based on number of supporting articles was
qualitative and arbitrary. Despite these study limitations,
this systematic review is the first in rehabilitation litera-
ture to methodically review all RIIs available based on
their common formula for calculation, assess the evi-
dence for independent predictors of these RIIs applied
over a wide range of medical conditions and study popu-
lations, and propose a nomenclature system to harmon-
ise the names of RIIs across the rehabilitation discipline
based on a rational first-named basis.
CONCLUSIONS
In conclusion, there are many RIIs reported in the lit-
erature and they include AFG, REs, REy, RREy and
RREs, with REy having the most number of studies using
it as an outcome measure and hence, having the stron-
gest evidence for its predictors. Although the evidence
for different predictors of RIIs varies according to the
RII, medical condition and study population, there is
good evidence that older age, lower prerehabilitation
functional status and cognitive impairment are predict-
ive of poorer AFG, REs and REy. A new nomenclature
system is proposed to harmonise the names of RIIs
based on a common mathematical formula and a first-
named basis.
Acknowledgements The authors would like to thank the libraries of National
University of Singapore and University of Western Ontario for support in
article retrieval.
Contributors The literature search, initial study data extraction and tabulation
of results were performed by GCK and CHC, and verification of data extracted
and results tabulated were subsequently performed by CHC, RP and AT
independently.
Funding Ministry of Health (Singapore) Health Services Research Competitive
Research Grant Number HSRG/0006/2013.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement No additional data are available.
Open Access This is an Open Access article distributed in accordance with
the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license,
which permits others to distribute, remix, adapt, build upon this work non-
commercially, and license their derivative works on different terms, provided
the original work is properly cited and the use is non-commercial. See: http://
creativecommons.org/licenses/by-nc/3.0/
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