Rombeyetal. BMC Medicine (2023) 21:265
https://doi.org/10.1186/s12916-023-02977-6
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BMC Medicine
Cost-effectiveness ofprehabilitation
prior toelective surgery: asystematic review
ofeconomic evaluations
Tanja Rombey1* , Helene Eckhardt1, Jörn Kiselev2,3, Julia Silzle1, Tim Mathes4 and Wilm Quentin1
Abstract
Background Prehabilitation aims at enhancing patients’ functional capacity and overall health status to enable them
to withstand a forthcoming stressor like surgery. Our aim was to synthesise the evidence on the cost-effectiveness
of prehabilitation for patients awaiting elective surgery compared with usual preoperative care.
Methods We searched PubMed, Embase, the CRD database, ClinicalTrials.gov, the WHO ICTRP and the dissertation
databases OADT and DART. Studies comparing prehabilitation for patients with elective surgery to usual preopera-
tive care were included if they reported cost outcomes. All types of economic evaluations (EEs) were included. The
primary outcome of the review was cost-effectiveness based on cost–utility analyses (CUAs).
The risk of bias of trial-based EEs was assessed with the Cochrane risk of bias 2 tool and the ROBINS-I tool
and the credibility of model-based EEs with the ISPOR checklist. Methodological quality of full EEs was assessed using
the CHEC checklist. The EEs’ results were synthesised narratively using vote counting based on direction of effect.
Results We included 45 unique studies: 25 completed EEs and 20 ongoing studies. Of the completed EEs, 22 were
trial-based and three model-based, corresponding to four CUAs, three cost-effectiveness analyses, two cost–benefit
analyses, 12 cost–consequence analyses and four cost-minimization analyses. Three of the four trial-based CUAs (75%)
found prehabilitation cost-effective, i.e. more effective and/or less costly than usual care. Overall, 16/25 (64.0%) EEs
found prehabilitation cost-effective. When excluding studies of insufficient credibility/critical risk of bias, this number
reduced to 14/23 (60.9%). In 8/25 (32.0%), cost-effectiveness was unclear, e.g. because prehabilitation was more effec-
tive and more costly, and in one EE prehabilitation was not cost-effective.
Conclusions We found some evidence that prehabilitation for patients awaiting elective surgery is cost-effective
compared to usual preoperative care. However, we suspect a relevant risk of publication bias, and most EEs were
of high risk of bias and/or low methodological quality. Furthermore, there was relevant heterogeneity depending
on the population, intervention and methods. Future EEs should be performed over a longer time horizon and apply
a more comprehensive perspective.
Trial registration PROSPERO CRD42020182813.
Keywords Prehabilitation, Cost-effectiveness, Health economics, Systematic review, Evidence synthesis
*Correspondence:
Tanja Rombey
Full list of author information is available at the end of the article
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Rombeyetal. BMC Medicine (2023) 21:265
Background
Rationale
Prehabilitation is still a relatively new care concept.
It aims at enhancing patients’ functional capacity and
overall health status through behaviour change [1] to
enable them to withstand a forthcoming stressor [2]. In
the surgical context, prehabilitation complements the
concept of ‘enhanced recovery after surgery’ (ERAS)
and aims to improve surgical outcomes and lower
post-operative complication rates [3]. Prehabilitation
programmes are delivered preoperatively by a multi-
disciplinary team and in various settings (e.g. inpatient,
outpatient, or at home). Typical modalities include
exercise training, promotion of physical activity, nutri-
tional optimisation and psychological support [4],
which are provided in addition to elements of ERAS,
such as medical optimisation and alcohol or smoking
cessation [5].
The potential of prehabilitation is widely recognised.
Nevertheless, prehabilitation has not yet been widely
adopted by health care systems. Current evidence is still
somewhat limited, though much research is still under-
way to determine the optimal programme types and
delivery modalities for different patient populations.
Most research activity seems to be in the field of can-
cer surgery, for example, in an overview of 55 system-
atic reviews on preoperative prehabilitation, 23 reviews
specifically focused on cancer [6]. A likely explanation
for this phenomenon is that there is already a large
body of evidence demonstrating the positive effects of
physical activity on the physical and psychological out-
comes of cancer patients [7]. In addition, little is known
about the cost-effectiveness of prehabilitation, which is
critical for policy-makers considering the implemen-
tation of such programmes. By definition, prehabilita-
tion is an approach to reduce healthcare costs [4] and
a comprehensive analysis of the value of prehabilitation
should incorporate cost outcomes [8].
The aforementioned overview identified only one sys-
tematic review on costs [6], but this review focused on
nutritional support rather than full prehabilitation pro-
grammes [9]. Other reviews that addressed health eco-
nomic outcomes focused on specific populations [10]
or were not systematic reviews [11]. One large system-
atic review including 178 randomised controlled trials
(RCTs) showed that prehabilitation may reduce post-
operative length of stay and complications [12], both of
which would translate into a cost reduction. However,
to our best knowledge, there is currently no compre-
hensive systematic review on the cost-effectiveness of
prehabilitation prior to elective surgery.
Aim andobjectives
The aim of this systematic review was to synthesise
the evidence on the cost-effectiveness of prehabilita-
tion programmes for patients awaiting elective sur-
gery compared with usual preoperative care to inform
decisions about the implementation of prehabilitation
programmes and to guide the design of future rigorous
economic evaluations of prehabilitation programmes.
More specifically, our objectives were to (1) identify
all eligible economic evaluations (EEs), (2) assess their
validity and (3) systematically present their characteris-
tics, methods and findings.
Methods
We followed general methodological guidance on sys-
tematic reviews of interventions [13] as well as guid-
ance specific to systematic reviews of EEs [14–16].
Reporting followed the Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) 2020
statement [17, 18] and guidance for systematic reviews
without meta-analysis [19]. All raw data collected as
part of the review are deposited in the Open Science
Framework (OSF) [20].
Registration andprotocol
The systematic review was prospectively registered in
PROSPERO (CRD42020182813) and we published a
protocol [21]. Important protocol changes are reported
in Additional file1: Appendix1.
Eligibility criteria
The study in- and exclusion criteria are displayed in
Table1 (from the protocol with additional specifica-
tions) [21].
Information sources
We searched PubMed, Embase and the Centre for
Reviews and Dissemination (CRD) Database on
31/08/2021, which are the most efficient combina-
tion of bibliographic databases for systematic reviews
of EEs [22]. Furthermore, we searched OADT.org and
the DART-Europe E-theses Portal for grey literature
and ClinicalTrials.gov and the World Health Organi-
zation (WHO) International Clinical Trials Registry
Platform (ICTRP) for unpublished and ongoing studies
on October 30, 2021. A weekly email alert was created
for the search in PubMed (monitored until August 23,
2022). Additionally, we screened the reference lists of
included EEs and relevant systematic reviews as well as
articles citing the included EEs obtained through Web
of Science and Google Scholar. We also contacted the
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Rombeyetal. BMC Medicine (2023) 21:265
corresponding authors of all included EEs about further
relevant EEs.
Search strategy
The database search strategies consisted of search terms,
relating to the population (e.g. ‘preoperative’), the inter-
vention (e.g. ‘exercise’) and study type, i.e. terms to search
for economic evaluations (e.g. ‘cost’). Full search strate-
gies for all sources can be found in Additional file 1:
Appendix2.
Selection process
Records retrieved from databases were deduplicated,
screened and managed using EndNote 20 (Clarivate Ana-
lytics, Philadelphia (PA), USA). After deduplication, a
randomly selected 10% sample of all unique records was
screened against the eligibility criteria by two review-
ers (TR, HE) independently based on their titles and
abstracts. Disagreement was resolved by consensus.
As agreement was above 80%, the remaining 90% were
screened by one reviewer (TR). We retrieved the full-
text articles for all potentially eligible studies as well as
for relevant systematic reviews, so that their references
could be screened. Each full-text article was screened for
eligibility by two reviewers independently who noted rea-
sons for exclusion. Disagreements were resolved by con-
sensus and by consulting a third reviewer (WQ). Last, all
study reports were mapped to unique studies as the unit
of interest. No automation tools were used in the process.
Data collection process
Data were extracted into a standardised excel sheet that
was piloted by one reviewer (TR). Two reviewers (TR,
HE) independently extracted the data of a randomly
selected 20% sample of the included completed EEs for
calibration. Disagreement was resolved by consensus.
As there were no systematic discrepancies, the remain-
ing records were extracted by one reviewer (TR). All
outcome data was verified by a second person (JS). We
used all documents relevant to the included EEs for data
extraction and contacted the study authors via email in
case of missing or unclear data. Uncertainties about
the methods were only inquired for completed EEs. A
reminder email was sent after 2weeks.
Data items
A list of all data items and detailed descriptions can be
found in Additional file1: Appendix3. For ongoing stud-
ies, we only extracted the study characteristics and, if
published as a protocol, the EE methods. For completed
EEs, we also extracted post-operative results data (per
group and as the difference between groups) on clinical
effectiveness and costs. Costs were reported with their
original year and currency as well as converted to 2020
Table 1 Review in- and exclusion criteria
a As judged by a physiotherapist (JK), based on current evidence on exercise efficacy and duration
b We included trial-based economic evaluations based on randomised controlled trials as well as non-randomised studies of interventions, as we expected that the
latter would provide valuable additional evidence, e.g. from a real-world setting. If a group in a multi-arm study did not meet the inclusion criteria, we included the
study but not the group
c We included ongoing studies, i.e. protocols and registration records, as we were interested in their methods
PICOS Inclusion criteria Exclusion criteria
Population Patients from any country undergoing elective surgery Patients undergoing emergency surgery or non-surgical treatments
(e.g. chemotherapy)
Intervention A preoperative prehabilitation programme (any setting), defined
as a (set of) intervention(s) aimed at optimising function-
ing and reducing disability in individuals awaiting surgery.
The intervention(s) had to include at least one component
of physio- or occupational therapy and at least one in-person
meeting between the patient(s) and health care professional(s).
The ‘dose’, i.e. the programme’s duration (overall and per session)
and frequency, had to be sufficiently longa to have an effect
if the patients fully adhered to it
Purely medical/nutritional interventions, an intervention combined
with additional postoperative rehabilitation, cognitive behaviour
therapy or health counselling/education alone, purely web/app-
based prehabilitation programmes
Control Usual preoperative care as defined by the study authors, i.e.
the routine care that patients with a given condition receive
in the respective hospital (extended only by the baseline measure-
ments performed as part of the trial)
Another prehabilitation intervention; no comparator
Outcome Clinical effectiveness and costs, any timeframe for follow-up Clinical effectiveness only
Study type Full (i.e. cost–benefit, cost-effectiveness and cost–utility analyses)
or partial economic evaluations (i.e. cost-minimization analysis),
trial-basedb or model-based economic evaluations regardless
of their statusc, cost perspective, publication year, language
and type (i.e. full article, conference abstract)
Systematic reviews, simple, non-comparative cost analyses (i.e. stud-
ies that only calculated the costs of the intervention), commentar-
ies/letters, animal studies
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Rombeyetal. BMC Medicine (2023) 21:265
EUR. For conversion, we used the ‘Cochrane Campbell
Economic Methods Group and the Evidence for Policy
and Practice Information and Coordinating Centre Cost
Converter’ (version 1.6) [23]. We only extracted unad-
justed data for the last available follow-up point based on
intention-to-treat analyses.
Risk ofbias andmethodological quality assessment
The risk of bias of trial-based EEs was assessed on out-
come-level using the Cochrane risk of bias tool 2 (RoB 2)
[24] for EEs based on RCTs and the ROBINS-I tool [25]
for EEs based on non-randomised studies of interven-
tions (NRSI). Among other domains, both tools address
the risk of reporting bias. Risk of bias figures were cre-
ated for each outcome domain separately using the rob-
vis application [26]. Methodological quality of trial-based
full EEs was assessed using the Consensus on Health
Economic Criteria (CHEC) checklist [27]. Model-based
EEs were assessed for credibility using the International
Society for Pharmacoeconomics and Outcomes Research
(ISPOR) checklist [28]. Assessments were performed
by two reviewers (TR, HE) independently in a random
20% sample of the included EEs and continued by one
reviewer (TR) as agreement was above 80%.
Effect measures
The review’s primary outcome was the cost-effectiveness
from cost–utility analyses (CUAs) based on direction
of effect (i.e. reduced costs and/or additional quality-
adjusted life year gained). Secondary outcomes were
the cost-effectiveness from cost-effectiveness analyses
(CEAs), cost–benefit analyses (CBAs), cost-minimisa-
tion analyses (CMAs) and cost–consequence analyses
(CCAs) based on direction of effect. We calculated effect
measures when not reported using risk differences for
dichotomous outcomes and mean differences or differ-
ences in medians for continuous outcomes. Confidence
intervals were extracted when reported. All calculated
values are marked as such. All outcomes were reported
in disaggregated form in natural units and combined out-
come measures, e.g. incremental cost-effectiveness ratios
(ICERs), where possible.
Synthesis methods
We were unable to perform a meta-analysis because
the only EEs that were sufficiently homogenous had an
unquantifiable overlap in patient populations [29–34]
or missed crucial information for data transformation
[32, 33]. Therefore, structured narrative synthesis in the
form of vote counting based on direction of effects was
performed [35]. EEs were grouped by design (model-
based vs. trials-based) [16] and analysis type (CUA vs.
CEA, CBA, CCA, CMA) to reflect the prioritisation of
outcomes.
Results were presented graphically in form of a hierar-
chical permutation matrix [36]. There were ten possible
outcomes for incremental costs (which could be higher,
lower or same) and effectiveness (which could be better,
poorer, same or inconsistent) corresponding to five result
categories: cost-effective, neutral, not cost-effective,
unclear; incremental analysis required, and unclear; indi-
vidual decision required). No formal sensitivity analysis
was performed but we discussed the influence of exclud-
ing EEs that were of critical risk of bias or insufficient
credibility. Descriptive post-hoc subgroup analyses were
performed to explore heterogeneity in the EEs’ results
arising from differences in populations, interventions,
methods, funding source and conflict of interest.
Assessment ofpublication bias
To address publication bias, we searched comprehen-
sively for ongoing studies and grey literature and followed
up on their status by searching for related publications
and contacting the named investigators. In addition, we
discussed how the effectiveness results from the included
EEs compare to those of clinical effectiveness studies
on prehabilitation using an overview of 55 systematic
reviews and meta-analyses of RCTs by McIsaac et al.
2022 [6]. Our hypothesis was that the EEs would appear
more beneficial if there truly was a publication bias.
Results
Study selection
The study selection process is presented in Fig. 1. In
total, 45 unique studies were included: 25 completed EEs
[29–34, 37–55] and 20 ongoing studies, of which 11 were
published as protocol articles [56–66] and nine as regis-
tration records [67–75]. Two completed EEs were only
published as conference abstracts [53, 54] and two as
dissertations [37, 49]. A total of 54 email enquiries were
sent to the study authors, of which 23 were answered
(response rate 42.6%). A list of all articles excluded after
full-text screening can be found in Additional file 1:
Appendix 4, with an additional explanation for close
misses and articles excluded post hoc [76–85].
Characteristics ofeconomic evaluations
The characteristics of the 25 completed EEs are dis-
played in Table2. In summary, there were 22 trial-based
EEs (13 RCTs and 9 NRSI), and three model-based EEs
(2 decision trees and 1 financial projection) correspond-
ing to four CUAs, three CEAs, two CBAs, 12 CCAs and
four CMAs. Nine EEs were performed from a mix of a
payer and provider perspective, three EEs each from a
payer or provider perspective, and one EE from a patient
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Rombeyetal. BMC Medicine (2023) 21:265
perspective. The perspective remained unclear in the
remaining nine EEs.
Most EEs were published in the last 10years and came
from Europe (10 EEs), Asia (8 EEs) or North America (7
EEs). The EEs covered a wide range of diseases and sur-
gery types that can be broadly categorised as orthopae-
dic surgery (9 EEs), cancer surgery (8 EEs), mixed major
surgery (6 EEs) and other (2 EEs). In 11 EEs, patients had
an increased perioperative risk (e.g. old age or frailty).
Sample size ranged from 20 to 8830 patients (median
137). The median proportion of women across the EEs
was 53%, and the mean or median age ranged from 59 to
78years, with one outlier (median age 27years).
Characteristics and methods of the 20 ongoing EEs are
reported in Additional file1: Appendix5. All are trial-
based EEs, with the majority based on RCTs (18 EEs).
There were five CUAs, six CEAs, three EEs using both
CUA and CEA, and six EEs with unclear analysis type. In
addition to the above continents, two ongoing EEs were
from Australia and one from South America. The dis-
ease and surgery types were similar to the completed EEs
(9 EEs on cancer, 8 EEs on major mixed or major other
surgeries and 3 EEs on orthopaedics), though there were
slightly more EEs from the field of cardiology and focus-
ing on patients with an increased perioperative risk, and
less EEs from the field of orthopaedics.
Information on the completed and ongoing EEs’
funding and conflict of interest can be found in Addi-
tional file1: Appendix6. Nine EEs did not report any
information, one received parts of its funding from
a commercial funder [57], one from a private donor
[46] and in one, it was unclear [68]. Two EEs declared
a relevant conflict of interest [29, 42], as authors
were related to companies contracted to organise the
prehabilitation.
Methods ofeconomic evaluations
Detailed information on the methods can be found
study-by-study in Additional file1: Appendix7 (com-
pleted EEs) and Additional file1: Appendix8 (ongoing
EEs published as protocols). Most completed EEs used
a time horizon for effects and costs of 1month or less
(range: 2weeks to 24months), with various EEs fol-
lowing patients until discharge and using the costs of
hospital stay. No EE discounted effects or costs. Using
bootstrapped precision measures (e.g. 95% confidence
intervals) was the most common method for calculat-
ing uncertainty around the point estimates. Three EEs
applied willingness-to-pay thresholds. In summary,
with two exceptions [40, 42], few EEs applied compre-
hensive economic evaluation methods.
Fig. 1 PRISMA 2020 flow diagram of the search and screening process
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Rombeyetal. BMC Medicine (2023) 21:265
Table 2 Characteristics of the completed economic evaluations
Study ID, main
referenceaType and design of
analysis Perspective Location (city/ cities;
country) Enrolment periodbInclusion criteria
(disease(s); type(s)
of surgery; criteria
for increased
perioperative risk)
Population
demographics Number of patients
randomised (total (IG
vs. CG))
AlShewaier 2016 [37] CUA; trial-based (RCT) Unclear Riyadh; Saudi Arabia 07/2014–01/2015 Isolated ACL injury;
ACL reconstruction Female: 0%, male:
100%
Median age: 27 years
84 (39 vs. 45)
Barberan-Garcia 2019
[38]CCA; trial-based (RCT) Mix of payer/provider
perspective Barcelona; Spain 02/2013–06/2016 Not specified; major
digestive surgery;
age > 70 years and/
or ASA score ≥ III
Female: 25%, male:
75%
Mean age: 71 years
125 (62 vs. 63)
Beaupre 2004 [39] CMA; trial-based (RCT) Payer perspective Edmonton; Canada Not reported Non-inflammatory
arthritis; primary TKA Female: 55%, male:
45%
Mean age: 67 years
131 (65 vs. 66)
Chen 2022 [40] CBA; model-based
(projection) Provider perspective Toronto; Canada Not applicable
(model) Not specified; major
elective intra-cavity
surgery; higher-than-
average risk, limited
physiologic reserve,
frailty, deconditioned
patient, other indica-
tion for prehabilitation
with explanation
Not reported 480 (240 vs. 240)
Dholakia 2021 [41] CEA; model-based
(decision tree) Payer perspective Not reported; USA Not applicable
(model) Epithelial ovarian
cancer; non-emergent
primary debulking
surgery; frailty
Female: 100%, male:
0%
Age not reported
8830 (4415 vs. 4415)
Englesbe 2017 [29] CMA; trial-based (NRSI) Mix of payer/provider
perspective Ann Arbor; USA IG: 06/2014–12/2015c
CG: 07/2006–06/2011 Not specified; major
inpatient abdominal
and thoracic operative
care
Female: 50%, male:
50%
Mean age: 60 years
364 (182 vs. 182)
Fernandes 2017 [42] CUA; trial-based (RCT) Mix of payer/ provider/
patient perspective Svendborg; Denmark 01/2010–03/2011 Symptomatic osteoar-
thritis; TKA, THA Female: 56%, male:
44%
Mean age: 67 years
165 (84 vs. 81)
Gao 2015 [43] CCA; trial-based (NRSI) Unclear Chengdu; China 11/2008–06/2011 Lung cancer; lobec-
tomy; > 800 pack-years,
quitted smok-
ing < 2 weeks ago,
bronchial hyperre-
sponsiveness, impaired
lung function
Female: 59%, male:
41%
Mean age: 66 years
142 (71 vs. 71)
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Rombeyetal. BMC Medicine (2023) 21:265
Table 2 (continued)
Study ID, main
referenceaType and design of
analysis Perspective Location (city/ cities;
country) Enrolment periodbInclusion criteria
(disease(s); type(s)
of surgery; criteria
for increased
perioperative risk)
Population
demographics Number of patients
randomised (total (IG
vs. CG))
Gränicher 2020 [44] CCA; trial-based (RCT) Payer perspective Zürich; Switzerland 07/2016–03/2017 Not specified; TKA Female: 40%, male:
60%
Mean age: 67 years
20 (10 vs. 10)
Howard 2019 [30] CCA; trial-based (NRSI) Mix of payer/ provider
perspective Ann Arbor; USA 01/2012–12/2017cNot specified; major
abdominal surgery Female: 49%, male:
51%
Mean age: 59 years
116 (76 vs. 40)
Huang 2012 [45] CCA; trial-based (RCT) Provider perspective Changhua; Taiwan 01/2008–12/2010 Advanced osteoarthri-
tis; primary TKA Female: 72%, male:
28%
Mean age: 70 years
243 (126 vs. 117)
Koh 2021 [46] CCA; trial-based (NRSI) Patient perspective Singapore; Singapore IG: 02/2017–03/2020
CG: 04/2016–09/2018 Colorectal cancer;
major colectomy;
age ≥ 70 years
Female: 44%, male:
56%
Median age: 78 years
81 (58 vs. 23)
Lai 2017 [32] CCA; trial-based (RCT) Unclear; assumed
provider perspective Chengdu; China 01/2015–12/2015dNon-small cell lung
cancer; lung cancer
surgery; > 20 pack-
years, age > 75 years,
BMI > 30, impaired
predicted lung func-
tion or COPD
Female: 42%, male:
58%
Mean age: 64 years
101 (51 vs. 50)
Lai 2019 [33] CCA; trial-based (RCT) Unclear; assumed
provider perspective Chengdu; China 01/2018-not reported Non-small cell lung
cancer; lobectomy Female: 51%, male:
49%
Mean age: 64 years
68 (34 vs. 34)
McGregor 2004 [47] CEA; trial-based (RCT) Mix of payer/provider
perspective London; UK Not reported Not specified; THA Female: 71%, male:
29%
Mean age: 72 years
39 (19 vs. 20)
Mouch 2019 [31] CMA; trial-based (NRSI) Mix of payer/provider
perspective Multiple cities in Michi-
gan; USA 01/2014–12/2017cNot specified; various
types of surgery; high
risk for complications
(according to surgeon)
Female: 53%, male:
47%
Median age: 70 years
1569 (523 vs. 1046)
Nguyen 2022 [48] CUA; trial-based (RCT) Mix of payer/provider
perspective Paris, Clermont-Fer-
rand; France 10/2012- not reported Knee osteoarthritis;
TKA Female: 68%, male:
32%
Mean age: 69 years
262 (131 vs. 131)
Pham 2016 [49] CMA; trial-based (RCT) Unclear; assumed
provider perspective Sudbury; Canada Not reported Osteoarthritis; TKA,
THA; BMI ≥ 30 Female: 69%, male:
31%
Mean age: 64 years
50 (29 vs. 21)
Ploussard 2020 [50] CCA; trial-based (NRSI) Mix of payer/provider
perspective Quint-Fonsegrives;
France IG: 01/2018–12/2019
CG: 01/2016–12/2017 Not specified; robot-
assisted radical prosta-
tectomy
Female: 0%, male:
100%
Mean age: 66 years
350 (194 vs. 156)
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Rombeyetal. BMC Medicine (2023) 21:265
Table 2 (continued)
Study ID, main
referenceaType and design of
analysis Perspective Location (city/ cities;
country) Enrolment periodbInclusion criteria
(disease(s); type(s)
of surgery; criteria
for increased
perioperative risk)
Population
demographics Number of patients
randomised (total (IG
vs. CG))
Risco 2022 [51] CCA; trial-based (NRSI) Provider perspective Barcelona, Spain 06/2017–12/2019 Not specified; major
digestive, cardiac,
thoracic, gynaecologic
or urologic surgeries;
age > 70 years and/
or ASA score ≥ III and/
or severe decondition-
ing
Female: 69%, male:
31%
Median age 71 years
656 (328 vs. 328)
Tew 2017 [52] CEA; trial-based (RCT) Mix of payer/provider
perspective Middlesbrough, Shef-
field, York; UK 09/2013–07/2015 Abdominal aortic
aneurysms; abdominal
aortic aneurysm repair
Female: 6%, male: 94%
Mean age: 75 years 53 (27 vs. 26)
Tveter 2020 [53] CUA; trial-based (RCT) Unclear; assumed
mix of provider, payer
and patient perspec-
tive
Trondheim, Bergen,
Haugesund; Norway 04/2013–06/2015 Carpometacarpal joint
osteoarthritis; thumb
carpometacarpal joint
surgery
Female: 79%, male:
21%
Mean age: 63 years
180 (90 vs. 90)
Van Wijk 2020 [54] CBA; model-based
(decision tree) Not reported Netherlands (nation-
wide) Not applicable
(model) Not specified;
pancreatic surgery;
low physical fitness,
impaired nutritional
status, the presence
of iron deficiency
anaemia, frailty, and/
or intoxications
Not reported Not reported
Wang 2020 [55] CCA; trial-based (NRSI) Unclear; assumed
provider perspective Singapore; Singapore 02/2016–10/2017 Hepatocellular
carcinoma, colorectal
liver metastases; liver
resection
Female: 26%, male:
74%
Median age: 67 years
104 (70 vs. 34)
Zhou 2017 [34] CCA; trial-based (NRSI) Unclear; assumed
patient perspective Chengdu; China 03/2014–06/2015dPrimary non-small cell
lung cancer; lobec-
tomy; ≥ 20 pack-years,
BMI ≥ 28, impaired
lung function, COPD/
asthma/airway hyper
reactivity
Female: 56%, male:
44%
Mean age: 59 years
939 (197 vs. 742)
ACL anterior cruciate ligament, ASA American Society of Anesthesiologists, BMI body mass index, CBA cost–benefit analysis, CCA cost–consequence analysis, CEA cost-effectiveness analysis, CG control group, CMA
cost-minimisation analysis, COPD chronic obstructive pulmonary disease, CUA cost–utility analysis, IG intervention group, NRSI non-randomised study of interventions, RCT randomised controlled trial, THA total hip
arthroplasty, TJA total joint arthroplasty, TKA total knee arthroplasty, UK United Kingdom, USA United States of America
a Further references relating to the included economic evaluations are cited in Additional file1: Appendix7
b Extracted from article or registration record (in that order)
c Overlapping population (Michigan, United States)
d Overlapping population (Chengdu, China)
Page 9 of 24
Rombeyetal. BMC Medicine (2023) 21:265
Table 3 Characteristics of the prehabilitation programmes evaluated in the completed economic evaluations
Study ID, main
reference Type and modalities Involved health care
professionals Setting Overall duration,
frequency and duration
per sessiona
Intensity of exercise
trainingbEvidence-
based
programme
Programme
costs in EUR
(2020)
AlShewaier 2016 [37] Unimodal: exercise (resist-
ance, proprioception
and balance)
Physiotherapists Outpatient—hospital 4 weeks, 3x/week,
for 45 min High Yes 838
Barberan-Garcia 2019 [38] Multimodal: counsel-
ling/education, exercise
(endurance), promotion
of physical activity
Specialised physiothera-
pist Outpatient—hospital Individual, but min
4 weeks, 1–3x/week, indi-
vidual session duration
High Yes 457
Beaupre 2004 [39] Multimodal: counsel-
ling/education, exercise
(resistance)
Physiotherapists Outpatient—community 4 weeks, 3x/week, indi-
vidual and progressing
session duration
High No 225
Chen 2022 [40] Multimodal: exercise
(endurance, resist-
ance, disease-specific),
nutrition (counselling,
supplements), psychoso-
cial (stress management),
smoking cessation
Kinesiologist or certified
exercise physiologist,
dietitian, psychologist
Outpatient—hospital
(FBP group), home (HBP
group)
Individual; min 2 weeks,
2x/week (FBP), 3–5x/
week (HBP), for 60 min
Moderate Yes 798
Dholakia 2021 [41] Various (model): smoking
cessation, stabilising
diseases, nutrition (coun-
selling, supplements),
exercise (endurance,
resistance, inspiratory
muscles), psychosocial
(stress management),
counselling/education,
other (social/financial
support)
Variable (model) Variable (model) Variable (model) Not applicable No Variable (model)
Englesbe 2017 [29] Multimodal: promotion
of physical activity, exer-
cise (inspiratory muscles),
nutrition (counselling),
psychosocial (stress
management), planning
of care, smoking cessa-
tion
Not reported Home Individual; min 2 weeks,
3-7x/week, individual
session duration
Not reported No 80
Page 10 of 24
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Table 3 (continued)
Study ID, main
reference Type and modalities Involved health care
professionals Setting Overall duration,
frequency and duration
per sessiona
Intensity of exercise
trainingbEvidence-
based
programme
Programme
costs in EUR
(2020)
Fernandes 2017 [42] Multimodal: exercise
(resistance, propriocep-
tion and balance)
Physiotherapists Outpatient—hospital Not reported but ‘An
attendance of 12 sessions
or more was considered
good compliance’, imply-
ing ≥ 6 weeks, 2x/week,
for 60 min
Not reported No 351 (824
when includ-
ing patient
expenses)
Gao 2015 [43] Multimodal: exercise
(inspiratory muscles,
endurance)
Professional therapists Inpatient 3–7 days, 2x/day,
for 50–60 min Not reported No 246
Gränicher 2020 [44] Multimodal: exercise
(endurance, stretching
and flexibility, resistance;
individual exercises
when indicated), counsel-
ling/education
Physiotherapists Outpatient—hospital 3–4 weeks, 1.25–3x/
week, individual session
duration
Low to moderate No 283
Howard 2019 [30] Multimodal: promotion
of physical activity, exer-
cise (inspiratory muscles),
nutrition (counselling),
psychosocial (stress
management), planning
of care, smoking cessa-
tion
Not reported Home Individual; min 2 weeks,
3–7x/week, individual
session duration
Not reported No 80
Huang 2012 [45] Multimodal: exercise
(resistance), counselling/
education
Physiotherapists Home 4 weeks, 7x/week,
for 40 min (first session);
remaining sessions
individual
Not reported No 20
Koh 2021 [46] Multimodal: nutrition
(supplements), exercise
(resistance), counselling/
education, drug evalua-
tion, stabilising diseases
Dieticians, physiothera-
pists Outpatient—community,
hospitalc3 weeks, frequency
not reported, individual
session duration
Not reported No Not calculable
Lai 2017 [32] Multimodal: exercise
(inspiratory muscles,
endurance)
Inpatient 1 week, 3 + 2 + 1/
day, for 45–60 min
plus breathing exercises
Not reported No Not calculable
Lai 2019 [33] Multimodal: exercise
(inspiratory muscles,
endurance)
Specialised nurses, physi-
cal therapists Inpatient 1 week, 3 + 1/day,
for 30 min plus breathing
exercises
Not reported No Not calculable
McGregor 2004 [47] Unimodal: counselling/
education, exercise (not
specified)
Not reported Home 1–3 weeksc, unclear
frequency, individual ses-
sion duration
Not reported No 22
Page 11 of 24
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Table 3 (continued)
Study ID, main
reference Type and modalities Involved health care
professionals Setting Overall duration,
frequency and duration
per sessiona
Intensity of exercise
trainingbEvidence-
based
programme
Programme
costs in EUR
(2020)
Mouch 2019 [31] Multimodal: promotion
of physical activity, exer-
cise (inspiratory muscles),
nutrition (counselling),
psychosocial (stress
management), planning
of care, smoking cessa-
tion
Not reported Home Individual; min 2 weeks,
3-7x/week, individual
session duration
Not reported No 54
Nguyen 2022 [48] Multimodal: counsel-
ling/education, nutrition
(counselling), psycho-
social (stress manage-
ment, anxiety reduction),
exercise (resistance,
stretching and flexibility,
endurance, propriocep-
tion and balance)
Physiotherapist, instruc-
tor in physical activity,
social worker, dietician,
psychologist, occupa-
tional therapist
Outpatient—hospital,
home 8 weeks, 2x/week,
for 60 min Low Yes 60
Pham 2016 [49] Multimodal: exercise
(stretching and flexibility,
resistance, endurance,
proprioception and bal-
ance), counselling/
education
Kinesiologist and/
or Human Kinetics gradu-
ate student
Outpatient—community 12 weeks, 3x/week,
for 40–60 min Moderate to high Yes 103
Ploussard 2020 [50] Multimodal: counselling/
education, planning
of care, exercise (disease-
specific), promotion
of physical activity,
stabilising diseases,
psychological (other),
nutrition (counselling,
supplements)
Urology nurse, physi-
otherapist, nurse anaes-
thetist, oncology nurse
specialist, cardiologist (if
needed), pneumologist
(if needed), psychologist,
dietician, urologist
Home 2 weeksc, 2–3x/day, for 1
full day, then individual
session duration
Not reported No 231
Risco 2022 [51] Multimodal: counselling/
education, promotion
of physical activity,
exercise (endurance,
resistance), nutrition
(counselling, supple-
ments), psychosocial
(anxiety reduction, stress
management, other)
Anaesthesiologists, physi-
otherapists, dietitians,
psychologists and nurses
Outpatient—hospital Min 4 weeks, 2-3x/week,
for 47 min (endurance)
and individual session
duration (strength, physi-
cal activity)
High (endurance), mod-
erate (strength) Yes 445
Page 12 of 24
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Table 3 (continued)
Study ID, main
reference Type and modalities Involved health care
professionals Setting Overall duration,
frequency and duration
per sessiona
Intensity of exercise
trainingbEvidence-
based
programme
Programme
costs in EUR
(2020)
Tew 2017 [52] Unimodal: exercise
(endurance) Research nurse, physi-
otherapist Outpatient—hospital 4 weeks, 3x/week,
for 45 min (after first 3
sessions option to do it
in 37 min)
High Yes 1341
Tveter 2020 [53] Multimodal: counselling/
education, other (assistive
devices, orthoses), exer-
cise (stretching and flex-
ibility, resistance)
Occupational therapist Home 12 weeks, 3x/week, indi-
vidual session duration Moderate to high Yes Not reported
Van Wijk 2020 [54] Various (model):
not reported, but assum-
edly: exercisec, promotion
of physical activity, nutri-
tion, stabilizing diseases,
alcohol cessation, smok-
ing cessation
Variable (model) Not reported Variable (model) Not reported No information 1446
Wang 2020 [55] Multimodal: exercise
(inspiratory muscles),
nutrition (counselling,
supplements), counsel-
ling/education, planning
of care, other (financial/
social support)
Physiotherapist, dietician,
case manager Not reported 2–4 weeks, 5x/week,
for 30 min plus breathing
exercises
Not reported No Not reported
Zhou 2017 [34] Multimodal: exercise
(inspiratory muscles,
endurance)
Lung cancer nurse spe-
cialists, physiotherapists Inpatient 1 week, 2 + 3 + 1x/day,
for 65–70 min Not reported No Not calculable
FBP facility-based prehabilitation, HBP home-based prehabilitation
a Referring to exercise element if multiple modalities
b As judged by an experienced physiotherapist
c Information obtained through author contact
Page 13 of 24
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Description ofprehabilitation programmes
Characteristics of the completed EEs’ prehabilitation
programmes can be found in Table3. Briefly, in most
EEs, the prehabilitation programme was multimodal. All
25 programmes included an exercise element, though the
type of training and use of unsupervised sessions var-
ied. Additionally, many included an element of counsel-
ling or education (13 EEs) or an element addressing the
patients’ nutritional status (11 EEs). The programmes
involved various groups of health care professionals, the
most common group being physiotherapists (14 EEs).
Most programmes were performed in an outpatient (11
EEs) or home setting (8 EEs). The programmes’ overall
duration ranged from 3days to 3months, with most pro-
grammes lasting between 2 and 4weeks. The frequency
of supervised sessions ranged from daily to once per
week, with session durations being individual or rang-
ing from 30 to 70min. Where intensity was reported,
we mostly classified it as high, e.g. an 80% of peak work
rate for endurance training. Many programmes were not
evidence-based. They costed between 100 and 1000 EUR
(2020) per patient. Characteristics of the programmes
evaluated in the ongoing studies can be found in Addi-
tional file1: Appendix9.
Risk ofbias andmethodological quality
The results of the assessment of risk of bias and meth-
odological quality of the included studies can be found
in Additional file1: Appendix10. The majority of RCT-
based EEs were judged to be of high risk of bias with the
RoB 2 tool. Only one RCT had a moderate risk of bias
in all domains [42], and none had a low risk of bias. The
main reason for high risk of bias was the absence of a
prospective study protocol/registration record. All NRSI-
based EE had at least a high, one even a critical risk of
bias [34], the main reason being that most EEs did not
adequately control for confounding when selecting or
analysing patients.
The methodological quality of full trial-based EEs as
judged with the CHEC-checklist ranged from 8 to 15
fulfilled items (of 18 to 19 applicable items) and thus
can be considered moderate to low. The credibility of
model-based EEs as judged with the ISPOR checklist was
acceptable in one EE [40], insufficient in another EE [41]
and could not be determined due to lack of information
in one EE published as a conference abstract [54].
Results ofindividual economic evaluations
Table 4 provides an overview of the results of the
completed EEs. Smaller values represent a higher
benefit unless indicated otherwise. Morbidity refers
to the rate of postoperative complications unless
indicated otherwise. Detailed cost results can be found
in Additional file1: Appendix11 including quantities
of resource use, unit costs, total costs, incremental
cost-effectiveness ratio (ICER) in the original currency
and year, and the study authors’ conclusion. Further-
more, adherence and safety/feasibility outcomes can be
found in Additional file1: Appendix12. Two EEs had
adherence rates of less than 35% [48, 51] and in three
EEs, drop-out and/or adverse event rates were notably
higher in the prehabilitation groups [47, 48, 53].
Results ofsynthesis
Four trial-based EEs [37, 42, 48, 53] reported data on
the primary outcome, i.e. cost-effectiveness based on
CUA (Fig.2, thick bordered column). Based on direc-
tion of effects, three CUAs (75%) fell into the cost-effec-
tive category, and one fell into the category ‘unclear;
incremental analysis required’. The ICER of the latter
study was 7906 EUR (2020) per quality-adjusted life
year (QALY) gained, which is likely acceptable under
common willingness-to-pay (WTP) thresholds [37].
Three model-based and 18 trial-based EEs reported
on the secondary outcomes (Fig.2), i.e. cost-effective-
ness based on other types of EEs, respectively. Based
on direction of effects, two model-based EEs fell into
the cost-effective category [40, 41], but one was judged
insufficiently credible [41]. The remaining model-based
EE fell into the category ‘unclear; individual decision
required’ [54]. Of the trial-based EEs, 11 fell into the
cost-effective category [29, 31–34, 38, 46, 47, 49, 50,
55], one of which was judged to be of critical risk of
bias [34], three into the category ‘unclear; incremental
analysis required’ [43, 51, 52], three into the category
‘unclear; individual decision required’ [30, 44, 45], and
one, a CMA with a difference in total costs of + 2 EUR
(2020), into the not cost-effective category [39].
Overall, 16/25 (64.0%) EEs found prehabilitation
cost-effective based on direction of effects, (14/23;
60.9% when excluding the EEs of insufficient cred-
ibility/critical risk of bias [34, 41]), in 8/25 (32.0%) it
was unclear, and one EE (4.0%) found prehabilitation
not cost-effective [39]. Descriptive post hoc subgroup
analyses revealed heterogeneity in the cost-effective-
ness results depending on the population, intervention
and methods, but not on conflict of interest and fund-
ing source (Additional file 1: Appendix 13). Briefly,
cost-effectiveness was more frequently observed in
EEs of cancer patients, patients with a high periop-
erative risk, multimodal programmes, home-based or
inpatient prehabilitation, shorter programmes, low-
cost programmes and EEs taking a mix of payer/pro-
vider perspective.
Page 14 of 24
Rombeyetal. BMC Medicine (2023) 21:265
Table 4 Results of completed economic evaluations
Study ID, main reference Clinical effectiveness (IG vs. CG) Total costs in EUR (2020) (IG vs. CG) Cost-effectiveness based on
direction of effectsaRisk of bias/quality
Results from model-based economic evaluations
Results from CEAs
Dholakia 2021 [41] Mortality: 397/4415 (9.0%) vs. 441/4415
(10.0%); RDb -1.0% Mean 59,849 vs. 65,304; MDb -5455 Cost-effective ISPOR-Q: Insufficiently credible
Results from CBAs
Chen 2022 [40] Morbidity: 24/240 (10.0%) vs. 16/240
(6.7%); RDb -3.3% Meanb 3292 vs. 3742; MDb -450 Cost-effective; total cost–benefit:
108,022 EUR (2020) ISPOR-Q: Sufficiently credible
Van Wijk 2020 [54] Morbidity: not reported 28,001 vs. 30,242; difference -2,241cUnclear (effectiveness not reported);
return of investment: 1.55 ISPOR-Q: Insufficient information
Results from trial-based economic evaluations
Results from CUAs
AlShewaier 2016 [37]QALYsd: Median 0.679 (IQR 0.10) vs.
0.573 (0.05); Difference in mediansb
0.106
Median 20,790 vs. 19,952; difference
in mediansb 838 Unclear; incremental analysis required:
ICER: 7906 EUR (2020) per QALY gained,
but no WTP reported
RoB 2: High
CHEC: 13/19 items
Fernandes 2017 [42]QALYsd: Mean 0.66 ± BS SE 0.04 vs.
0.61 ± 0.04e; MD 0.04 (95% CI 0.01
to 0.07)
Mean 17,432 ± BS SE 1265 vs.
17,574 ± 1480; MD -142 (95% CI -3952
to 3668) (331b when including patient
expenses)
Cost-effective (unclear when includ-
ing patient expenses); Probability
of CEA at a WTP of 40,000 EUR: 84%
(approx. 79% when including patient
expenses)
RoB 2: Some concerns
CHEC: 16/19 items
Nguyen 2022 QALYsd: Mean 0.7 ± SD 0.3 vs. 0.6 ± 0.3;
MDb 0.1 Mean 15,071 ± SD 7014 vs.
15,472 ± 6309; MD -401 Cost-effective RoB: Some concerns (QALY), high (costs)
CHEC: 9/19 items
Tveter 2020 [53]QALYsd: Not reported per group; differ-
ence 0.07cNot reported per group; difference
-508cCost-effective RoB 2: Some concerns (QALY), high
(costs)
CHEC: 11/19 items
Results from CEAs
McGregor 2004 [47] HrQoL: EQ-5D-3L VAS (0–100%)d: mean
75.80 ± SD 14.86 vs. 72.15 ± 22.20f;
MDb 3.65%, EQ-5D-3L utilitiesd: mean
0.72 ± SD 0.13 vs. 0.60 ± SD 0.31f; MDb
0.12
Mean 4148 vs. 5005; MDb -856 Cost-effective RoB 2: High
CHEC: 8/19 items
Tew 2017 [52] HrQoL: EQ-5D-5L utilitiesd: mean 0.837
vs. 0.760; MD 0.077 (95% CI 0.005
to 0.148)
BS mean 14,269 ± SD 3542 vs.
13,688 ± 3542; BS MD 582 (95% CI -1588
to 2848)
Unclear; incremental analysis required,
but ICER not reported RoB 2: High
CHEC: 14/19 items
Page 15 of 24
Rombeyetal. BMC Medicine (2023) 21:265
Table 4 (continued)
Study ID, main reference Clinical effectiveness (IG vs. CG) Total costs in EUR (2020) (IG vs. CG) Cost-effectiveness based on
direction of effectsaRisk of bias/quality
Results from CCAs
Barberan-Garcia 2019 [38] HrQoL:
SF-36 PCSd: mean 47 ± SD 7 vs. 44 ± 8;
MDb 3
SF-36 MCS scored: mean 51 ± SD 9 vs.
50 ± 9; MDb 1
Morbidity: 19/62 (30.6%) vs. 39/63
(61.9%); RDb -31.3%
Mortality: 1/62 (1.6%) vs. 4/63 (6.3%);
RDb -4.7%
PROMs:
YPAS scored: mean 46 ± SD 13 vs.
39 ± 15; MDb 7
HAD total score: mean 6 ± SD 5 vs. 8 ± 6;
MDb -2
Mean 5428 (range 1792 to 30,532) vs.
6416 (1587 to 34,521); BS MD -955 (95%
CI -3109 to 1033)
Cost-effective RoB 2: Some concerns (morbidity, mor-
tality), high (PROMs, costs)
CHEC: not applicable
Gao 2015 [43] Morbidity: 12/71 (16.9%) vs. 59/71
(83.3%); RDb -66.4% Mean 9728 ± SD 1130 vs. 8955 ± 888;
MDb 773 Unclear; incremental analysis required,
but ICER not applicable for CCA ROBINS-I: Serious
CHEC: not applicable
Gränicher 2020 [44] PROMs:
Lysholm Scored: mean 87.1 ± SD 9.0 vs.
69.1 ± 14.9; MDb 18
Lysholm Score pain itemd: mean
25.0 ± SD 0.0 vs. 16.5 ± 9.1; MDb 8.5
Tegner Activity Scaled: mean 3.8 ± SD
0.8 vs. 2.5 ± 0.9; MDb 1.3
Physical function:
Stair climbing test, time in seconds:
mean 12.58 ± SD 4.64 vs. 13.59 ± 5.30;
MDb -1.01
Knee ROM (degrees)d: mean 100.5 ± SD
18.7 vs. 103.5 13.7; MDb -3
Mean 3187 vs. 4052; MDb -865 Unclear (inconsistent effectiveness);
individual decision required RoB 2: Some concerns (PROMs, physical
function), high (costs)
CHEC: not applicable
Howard 2019 [30] Morbidity: 12/40 (30.0%) vs. 29/75
(38.7%); RDb -8.7%
Mortality: 1/40 (2.5%) vs. 1/75 (1.3%);
RDb 1.2%
Mean 58,300 ± SD 42,590 vs.
75,248 ± 77,516; MDb (incorporating
prehabilitation costs) -16,870
Unclear (inconsistent effectiveness);
individual decision required ROBINS-I: Serious
CHEC: not applicable
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Table 4 (continued)
Study ID, main reference Clinical effectiveness (IG vs. CG) Total costs in EUR (2020) (IG vs. CG) Cost-effectiveness based on
direction of effectsaRisk of bias/quality
Huang 2012 [45] Morbidity:
Infection rate: 2/126 (1.6%) vs. 1/117
(0.9%); RDb 0.7%
Rate of deep vein thrombosis: 5/126
(4.0%) vs. 3/117 (2.6%); RDb 1.4%
PROMs: Pain (VAS): mean 2.4 ± SD 0.7 vs.
2.5 ± 0.6; MDb -0.1
Physical function:
Knee ROM (degrees)d: mean 76 ± SD 22
vs. 74 ± 20; MDb 2
Ambulation statusd: 108/126 (85.7%) vs.
95/117 (81.2%); RDb 4.5%
Mean 6726 ± SD 283 vs. 6841 ± SD 241;
MDb (incorporating prehabilitation
costs) -95
Unclear (inconsistent effectiveness);
individual decision required RoB 2: High
CHEC: not applicable
Koh 2021 [46, 86] Morbidity: 24/58 (41.4%) vs. 11/23
(47.8%); RDb -6.4%
Mortalityg: 0/58 (0%) vs. 0/23 (0%); RDb
0%
Not reported per group; MD -2584 Cost-effective ROBINS-I: Serious
CHEC: not applicable
Lai 2017 [32] Morbidity: 5/51 (9.8%) vs. 14/50 (28.0%);
RDb -18.2% Mean 7677 ± SD 1374 vs. 8608 ± 2482;
MDb -931 Cost-effective RoB 2: High
CHEC: not applicable
Lai 2019 [33] Morbidity: 4/34 (11.8%) vs. 12/34
(35.3%); RDb -23.5% Median 10,456 (IQR 9683 to 11,339) vs.
11,285 (10,544 to 13,340); Difference
in mediansb -830
Cost-effective RoB 2: High
CHEC: not applicable
Ploussard 2020 [50] Mortality: 0/194 (0%) vs. 1/156 (0.6%);
RDb -0.6% Mean 2904 vs. 3282; MDb -379 Cost-effective ROBINS-I: Serious
CHEC: not applicable
Risco 2022 [51] Morbidity: Comprehensive complica-
tions index: mean 15.1 ± SD 17.1 vs.
16.6 ± 16.9; MDb: -1.5
Mean 7288 vs. 7142; MD 145 Unclear; incremental analysis required,
but ICER not applicable for CCA ROBINS-I: Serious
CHEC: not applicable
Wang 2020 [55] Morbidity: 21/70 (30.0%) vs. 18/34
(52.9%); RD -22.9%
Mortality: 1/70 (1.4%) vs. 1/34 (2.9%);
RDb -1.5%
PROMs (in subsample of n = 33 vs.
n = 24):
FACT-Hep scored: median 152 (range
102 to 179) vs. 148 (66 to 175); differ-
ences in mediansb 4
Median 6138 (IQR 4590 to 8833) vs.
7349 (5328 to 11,026); difference
in medians -1210
Cost-effective ROBINS-I: Serious
CHEC: not applicable
Zhou 2017 [34] Morbidity: 36/197 (18.3%) vs. 194/742
(26.1%); RDb: -7.8% Not calculable in EUR (2020) as origi-
nal currency not reported; original
values: mean 7131.8 ± SD 2316.6 vs.
77,266.4 ± 1615.0; MDb -134.60
Cost-effective ROBINS-I: Critical
CHEC: not applicable
Page 17 of 24
Rombeyetal. BMC Medicine (2023) 21:265
Table 4 (continued)
Study ID, main reference Clinical effectiveness (IG vs. CG) Total costs in EUR (2020) (IG vs. CG) Cost-effectiveness based on
direction of effectsaRisk of bias/quality
Results from CMAs
Beaupre 2004 [39] Not applicable Mean 1285 ± SD 1196 vs. 1283 ± 1329;
MD 2 Not cost-effective RoB 2: High
CHEC: not applicable
Englesbe 2017 [29] Not applicable Provider perspective: median 16,900
(IQR 10,162 to 30,365) vs. 23,091 (14,993
to 39,017); difference in mediansb -6191
Payer perspective: median 19,216 (IQR
12,122 to 33,840) vs. 24,519 (17,057
to 37,243); difference in mediansb -5303
Cost-effective ROBINS-I: Serious
CHEC: not applicable
Mouch 2019 [31] Not applicable Mean 24,435 ± SD 20,024 vs.
26,903 ± 24,935; MDb -2468 Cost-effective ROBINS-I: Moderate
CHEC: not applicable
Pham 2016 [49] Not applicable Reported only for a subset of patients
(5/29 vs. 11/21): mean 5081 ± SD 298 vs.
5152 ± 656; MDb -71
Cost-effective RoB 2: High
CHEC: not applicable
BS bootstrapped, CBA cost–benefit analysis, CCA cost–consequence analysis, CEA cost-effectiveness analysis, CG control group, CHEC Consensus on Health Economic Criteria, CMA cost-minimisation analysis, CUA cost–
utility analysis, EQ-5D-3L EuroQoL 5 dimensions 3 levels, EQ-5D-5L EuroQoL 5 dimensions 5 levels, FACT-Hep Functional Assessment of Cancer Therapy—Hepatobiliary, HAD Hospital Anxiety and Depression Scale, IG
intervention group, ICER incremental cost-effectiveness ratio, ISPOR-Q International Society for Pharmacoeconomics and Outcomes Research Questionnaire, IQR interquartile range, MD mean difference, PROMs patient-
reported outcome measures, QALY quality-adjusted life-year, HrQoL health-related quality of life, RD relative difference, RoB 2 revised Cochrane risk-of-bias tool for randomised trials, ROBINS-I tool for assessing risk of bias
in non-randomised studies of interventions, ROM range of motion, SD standard deviation, SF-36 Short Form 36, VAS visual analogue scale, YPAS Yale Physical Activity Scale
a ‘Cost-effective’ if better effectiveness and same/lower costs, or same effectiveness and lower costs; ‘unclear’ if better effectiveness and higher costs, or same effectiveness and same costs, or inconsistent/poorer
effectiveness and lower costs; ‘not cost-effective’ if same effectiveness and higher costs, or poorer effectiveness and same/higher costs
b Calculated by review authors
c Measure of central tendency (mean, median) not reported
d Higher values indicating higher benefit
e When missing values were imputed by linear trend at point and adjusted for baseline EQ-5D-3 L scores
f Values were obtained through author contact
g Survival was also calculated but not mentioned in the methods as an outcome
Page 18 of 24
Rombeyetal. BMC Medicine (2023) 21:265
Publication bias
There was a relevant risk of publication bias regarding
the included completed EEs. Firstly, the review had ini-
tially included 74 study reports belonging to 54 unique
studies. However, ten reports referring to nine unique
studies were excluded post hoc [76–85] (see Additional
file1: Appendix4), of which four protocols [77–80], one
registration record [85] and a conference abstract [81]
referred to studies that no longer reported on costs in
the study publication [87–95]. The authors of two studies
confirmed that no economic evaluation was performed
[78, 80]. The remaining authors did not respond.
In comparison to the results of the overview by
McIsaac etal. 2022 [6], the included EEs on cancer sur-
gery showed more beneficial results regarding morbid-
ity [32–34, 43, 46, 55] and mortality [41, 50, 55], and the
included EEs on orthopaedic surgery showed more bene-
ficial results on health-related quality of life (HrQoL) [37,
42, 47, 48, 53]. Apart from that, results were comparable
but, overall, the included EEs’ results appear more ben-
eficial suggesting a risk of publication bias.
Discussion
This is the first comprehensive systematic review on the
cost-effectiveness of prehabilitation prior to elective sur-
gery including 25 completed and 20 ongoing EEs. Using
vote-counting based on direction of effects, the major-
ity of completed EEs found prehabilitation cost-effective,
including three CUAs, and only one EE favoured usual
care. However, most EEs were of high risk of bias and/or
low methodological quality, and we identified a relevant
risk of publication bias. Furthermore, the included EEs
were heterogeneous in their population, intervention and
methods. Therefore, our results should be interpreted
with caution. An update of this review might lead to
more definite evidence, as it should include at least eight
more completed CUAs [58, 59, 62–66].
Cost-effectiveness depended on the population and
intervention, with certain groups (e.g. cancer- or high-
risk patients) and programmes (e.g. shorter, home-based
prehabilitation) resulting more frequently in benefit.
Among the included EEs, there was a high variability
in populations, whose underlying diseases and surger-
ies differed in concept (e.g. restoration in orthopaedic
surgery and cure in cancer surgery). It is possible that
for orthopaedic patients, the restoring character of the
surgery might be the crucial element in the recovery of
both groups, although the modalities of prehabilitation
may also serve as a conservative therapy option for cer-
tain orthopaedic patients, delaying or even eliminating
the need for surgery [49, 53]. Of course, for other patient
groups, cure through prehabilitation is not possible, e.g.
for cancer patients whose disease cannot be improved in
itself by prehabilitation. Lastly, it might be more (cost-)
effective to focus on patients with low functional capac-
ity [96] who are at high-risk for adverse perioperative
outcomes because of factors such as old age, relevant co-
morbidities [4] and frailty [97], as these patients much
room for preoperative improvement.
Our review also showed great variability in the pro-
gramme modalities, ‘dose’ (i.e. frequency, intensity and
duration) and delivery settings. As a result, the pro-
gramme costs ranged from below 100 EUR (2020) per
patient in six (mainly home-based) EEs [29–31, 45,
47, 48] to above 1000 EUR (2020) in two EEs [52, 54].
Although prehabilitation is usually defined as a multi-
modal approach, it is not yet clear what intervention
designs are most effective and whether they in fact need
Fig. 2 Hierarchical permutation matrix presenting the results vote counting based on direction of effects
Page 19 of 24
Rombeyetal. BMC Medicine (2023) 21:265
to be multimodal [6]. For example, in certain indications,
a unimodal intervention, such as preoperative breathing
exercises, would likely be less costly and hence could turn
out to be more cost-effective.
The dose–response relationship of prehabilitation pro-
grammes is a crucial aspect for programme effectiveness
and depends largely on the length of the preoperative
period available for prehabilitation. This again depends
on the underlying diseases and how fast these are pro-
gressing, i.e. patients with slowly progressing diseases,
such as osteoarthritis, can generally wait longer than
those with more rapidly progressing diseases, such as
most cancer types, who should often be operated within
a few weeks following diagnosis [98]. However, cancer
patients undergoing neoadjuvant treatment before sur-
gery may be ideal candidates for prehabilitation [99, 100].
Similarly, the waiting period for patients on organ trans-
plant lists may present a window of opportunity to imple-
ment a prehabilitation programme [101], and waiting
lists in general may aid the early identification of eligible
patients [102].
The dose of prehabilitation is also determined by the
intensity of individual sessions which must be sufficiently
high to have an effect while being tolerable for the target
population [103]. Although there were few adverse events
directly related to prehabilitation, some EEs reported that
patients from the intervention group dropped out due to
high-intensity [32–34]. Programmes must be designed
in a way to facilitate high adherence rates and thus cost-
effectiveness [104]. For instance, offering home-based
options may reduce issues regarding transportation,
which was found to be a central barrier to adherence to
prehabilitation [105]. Though not considered specifically
in this review, telemedicine is likely to play an important
role in the provision of prehabilitation as well.
Limitations
Some limitations on review and study level apply. First,
we could not perform a meta-analysis but had to resort
to narrative synthesis in the form of vote counting based
on direction of effects. This synthesis method does not
provide any information on the magnitude of effects, nor
does it account for the EEs’ sample sizes [106]. Second,
the review’s broad inclusion criteria led to a large number
of included articles that we coined ‘EEs’ for the purpose
of the review. However, most of them were trial reports
including cost outcomes which understood themselves
as pilot and/or feasibility trials and thus did not apply
comprehensive EE methods. Third, as there currently
is no universally recognised definition of prehabilita-
tion [6] nor common concepts, procedures or measure-
ments [4], the definition of the prehabilitation elements
varied between the EEs. The definition of usual care also
varied across EEs. For instance, advice on physical activ-
ity and smoking cessation were included as standard
care in some EEs [38, 50, 51], while those aspects were
part of prehabilitation in other EEs [29–31, 40, 41, 54].
Lastly, characteristics of health systems, such as the type
of financing (public vs. private) and organisation of care
(centralised vs. decentralised), play a crucial role in pro-
gramme delivery and cost justification. As we did not for-
mally assess the generalisability and transferability of our
results to different health systems, we recommend pol-
icy-makers interested in implementing prehabilitation to
conduct a health technology assessment (HTA) for their
government.
Limitations on the study level included the high risk of
bias and low methodological quality of the included EEs.
However, the exclusion of the two EEs judged to be insuf-
ficiently credible/of critical risk of bias only had a small
effect on the results. Furthermore, there was a high risk
of publication bias associated with trial-based EEs. Trial-
based EEs are by nature prone to a specific form of publi-
cation bias, namely conduct bias [107], meaning they are
not published because they were never performed in the
first place, e.g. when the underlying trial was ‘inconclu-
sive’ or had negative results. Although an intervention
that is less effective but cheaper than the control may
still be cost-effective, it is generally not acceptable from
an ethical and quality of care perspective to replace usual
care with a less-effective intervention.
Implications forpractice andpolicy
Owing to the limitations described above, our results
should be interpreted with caution. As many EEs were
based on prospective trials, decision-makers must also
consider the possibility that there was a motivational
bias among the participants and that the cost-effective-
ness of prehabilitation may be lower under ‘real world’
circumstances. Before implementing prehabilitation
into routine care, decision-makers should assess poten-
tial barriers and facilitators [108, 109], which may dif-
fer between health systems and stakeholders, or even
individuals. For example, qualitative studies found that
group prehabilitation was perceived both as a barrier and
facilitator [110, 111]. In their framework for prehabilita-
tion services, Bates etal. 2020 list several considerations
for the implementation of prehabilitation, including to
involve patients when designing the prehabilitation pro-
gramme [112].
Finally, decision-makers must determine which patient
population(s) should receive prehabilitation and estab-
lish screening pathways, accessibility to the programme
and strategies to ensure sustainability [113]. This involves
performing a budget impact analysis, including the one-
time investments into infrastructure (e.g. prehabilitation
Page 20 of 24
Rombeyetal. BMC Medicine (2023) 21:265
centres) as well as the running costs for the provision of
prehabilitation and maintenance of the infrastructure.
Although many EEs found that prehabilitation paid off
during the index hospitalisation, the pervasive shortage
of health care professionals [114] may hinder implemen-
tation of prehabilitation.
Implications forfuture research
First, future research should address the knowledge gaps
discussed above, i.e. which populations benefit most
and what the optimal prehabilitation programme for
those populations is. If a broadly defined population is
included in a clinical trial, it is recommended to consider
pre-specified subgroup analyses for economic evalua-
tion [115]. To ensure added value, new clinical research
should consider the existing evidence [116] as well as
involve patients and stakeholders in all phases of research
[117], e.g. when designing the prehabilitation programme
[118]. Ideally, these efforts would result in a clinical prac-
tice guideline for prehabilitation, the first step of which
was taken by Tew etal. 2018 with a guideline on preop-
erative exercise training in patients awaiting major non-
cardiac surgery [119].
Second, future research should address the shortcom-
ings of existing EEs. Common issues included inadequate
reporting, short time horizons, and the use of limited
perspectives. Reporting guidelines are intended to sup-
port authors and increase the accuracy and transparency
of reporting, but they are frequently used inappropri-
ately, including those for EEs [120]. In our review, report-
ing guidelines for EEs seemed to have been under-used,
as none of the full EEs published as full-text articles after
2013 [37, 40–42, 48, 52] reported following the Consoli-
dated Health Economic Evaluation Reporting Standards
(CHEERS) [121], which is applicable to both trial- and
model-based EEs. A possible reason is that only two trial-
based EEs were published as separate full-text articles
[38, 42]. Hence, we recommend that authors publish full
EEs as separate articles and follow the latest version of
the CHEERS checklist [122].
Many EEs had a short time horizon of 1month or less.
However, as argued by Grocott and Ludbrook 2019, ‘it
is plausible that improved fitness arising from preha-
bilitation might have a further lingering positive impact
on the need for later care’ [123]. Such an impact can
only be detected using a longer time horizon but, in our
review, only five EEs [39, 41, 42, 48, 53] had a time hori-
zon of 12months or more. To determine an adequately
long-time horizon, we recommend authors to consult
guidelines from their national HTA institutes and by
the ISPOR [115]. On a closely-related matter, many EEs
applied limited perspectives, such as the provider per-
spective, with the hospital being the provider, and there-
fore did not consider post-discharge or out-of-hospital
resource use. None of the included EEs applied a full
societal perspective including costs from other sectors,
e.g. productivity loss. When this is not feasible, we sug-
gest that authors adopt a comprehensive health sector
perspective including all relevant payers and providers.
For example, EEs may consider improved access for other
patients through freed-up capacity, e.g. due to earlier
discharge of prehabilitated patients [124]. In summary,
future EEs should be performed over a longer time hori-
zon and apply a more comprehensive perspective.
Update ofthereview
We plan to update the review upon publication of our
own economic evaluation [59] in 2025/26 by re-running
the search strategies modified only by adding the MeSH/
Emtree term ‘Preoperative Exercise’.
Conclusions
We found some evidence that prehabilitation for patients
awaiting elective surgery is cost-effective compared to
usual preoperative care. Cost-effectiveness based on
direction of effect was more frequently observed for
cancer patients, patients with a high perioperative risk
and for low-cost (shorter or home-based) programmes.
However, the results should be interpreted with caution
as most EEs were of high risk of bias and/or low meth-
odological quality, and we suspect a relevant risk of
publication bias. Future research should address clinical
knowledge gaps surrounding prehabilitation, e.g. which
populations benefit most, as well as the shortcomings of
existing EEs, e.g. by adopting a societal perspective.
Abbreviations
CBA Cost-benefit analysis
CCA Cost-consequence analysis
CEA Cost-effectiveness analysis
CHEC Consensus on Health Economic Criteria
CHEERS Consolidated Health Economic Evaluation Reporting Standards
CMA Cost-minimisation analysis
CRD Centre for Reviews and Dissemination
CUA Cost-utility analysis
EE Economic evaluation
ERAS Enhanced recovery after surgery
HrQoL Health-related quality of life
HTA Health technology assessment
ICER Incremental cost-effectiveness ratio
ICTRP International Clinical Trials Registry Platform
ISPOR International Society for Pharmacoeconomics and Outcomes
Research
NRSI Non-randomised study of an intervention
PRISMA Preferred Reporting Items for Systematic Reviews and
Meta-Analyses
Page 21 of 24
Rombeyetal. BMC Medicine (2023) 21:265
QALY Quality-adjusted life year
RCT Randomised controlled trial
ROB Risk of bias
ROBINS-I Risk of bias in non-randomised studies of interventions
WHO World Health Organization
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12916- 023- 02977-6.
Additional file1: App1. Important changes made to the protocol. App2.
Search strategies. App3. Data items. App4. List of excluded studies. App5.
Characteristics of ongoing economic evaluations. App6. Funding and
competing interest of included economic evaluations. App7.Methods of
completed economic evaluations. App8. Methods of ongoing economic
evaluations with a published protocol. App9.Description of prehabilita-
tion programmes in ongoing studies. App10.Risk of bias and methodo-
logical quality of included economic evaluations. App11.Detailed costs
results of included economic evaluations. App12.Results of adherence
and safety outcomes. App13.Results of descriptive post-hoc subgroup
analyses to explore heterogeneity in cost-effectiveness results.
Acknowledgements
Not applicable.
Authors’ contributions
TR, HE and JS collected and analysed the data. All authors interpreted the
data. JK performed content assessments of the prehabilitation programmes.
TM provided specific methodological expertise regarding systematic reviews
on economic evaluations. WQ supervised the review process. TR was a major
contributor in writing the manuscript draft. All authors edited the manuscript
draft and have read and approved the final manuscript.
Funding
Open Access funding enabled and organized by Projekt DEAL. The systematic
review is part of a larger project which is supported by the Innovation Fund
coordinated by the Innovation Committee of the Federal Joint Committee
in Germany (Innovationsausschuss beim Gemeinsamen Bundesausschuss
(G-BA)), grant number 01NVF18024. The funders had no role in planning or
conduct of the review nor in the decision to submit the results for publication.
Availability of data and materials
All raw data collected as part of the review are deposited in the Open Science
Framework (OSF) [20].
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
TR, HE, JS, JK and WQ are involved in one of the included ongoing economic
evaluations [59]. TM declares to have no competing interests.
Author details
1 Department of Health Care Management, Technische Universität Berlin,
Straße des 17. Juni 135, Berlin 10623, Germany. 2 Department of Anesthesiol-
ogy and Operative Intensive Care Medicine, Charité – Universitätsmedizin
Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität
zu Berlin, Berlin, Germany. 3 Department of Health Sciences, Fulda University
of Applied Sciences, Fulda, Germany. 4 Department for Medical Statistics,
University Medical Centre Goettingen, Goettingen, Germany.
Received: 17 May 2023 Accepted: 11 July 2023
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