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Complete the Matrix Template with total of 6 articles include the first article from the attachment then add part 2 requirement in the same document.
Read the instruction for the requirement
APA format, in-text citation, references include.
DHA Practice-based Problem Literature Review Matrix Template
|
Author/
Date |
Theoretical/
Conceptual Framework |
Research Question(s)/ Hypotheses |
Methodology |
Analysis & Results |
Conclusions |
Implications for Future research |
Implications
For practice |
Empirical Research (Yes or No) |
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©2022 Walden Doctor of Healthcare Administration
340 Volume 66, Number 5 • September/October 2021
For more information regarding the concepts in this article, contact Dr. Polanczyk at
cpolanczyk@hcpa.edu.br.
The authors declare no conflicts of interest.
Supplemental digital content is available for this article. Direct URL citations appear in the printed
text and are provided in the HTML and PDF versions of this article on the journal’s website
(www.jhmonline.com).
Value-Based Healthcare Initiatives in Practice:
A Systematic Review
Bruna Stella Zanotto, National Institute of Health Technology Assessment and Graduate
Program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;
Ana Paula Beck da Silva Etges, PhD, National Institute of Health Technology Assessment,
Federal University of Rio Grande do Sul, and Pontifical Catholic University of Rio Grande do Sul
Polytechnic School, Porto Alegre, Brazil; Miriam Allein Zago Marcolino, PT, National Institute
of Health Technology Assessment, Federal University of Rio Grande do Sul and Graduate Program
in Epidemiology, Federal University of Rio Grande do Sul; and Carisi Anne Polanczyk, PhD, MD,
National Institute of Health Technology Assessment, Federal University of Rio Grande do Sul, and
Graduate Programs in Epidemiology and Cardiology and Cardiovascular Sciences, Federal University
of Rio Grande do Sul
Value-based initiatives are growing in importance as strategic models of healthcare man-
agement, prompting the need for an in-depth exploration of their outcome measures. This
systematic review aimed to identify measures that are being used in the application of the
value agenda. Multiple electronic databases (PubMed/MEDLINE, Embase, Scopus, Cochrane
Central Register of Controlled Trials) were searched. Eligible studies reported various imple-
mentations of value-based healthcare initiatives. A qualitative approach was used to analyze
their outcome measurements. Outcomes were classified according to a tier-level hierarchy. In
a radar chart, we compared literature to cases from Harvard Business Publishing. The value
agenda effect reported was described in terms of its impact on each domain of the value
equation. A total of 7,195 records were retrieved; 47 studies were included. Forty studies
used electronic health record systems for data origin. Only 16 used patient-reported outcome
JHM-D-20-00283
Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the
Foundation of the American College of Healthcare Executives. This is an open-access article
distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivitives
4.0 License, where it is permissible to download and share the work provided it is properly cited.
The work cannot be changed in any way or used commercially.
DOI: 10.1097/JHM-D-20-00283
EXECUTIVE SUMMARY
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 341
INTRODUCTION
Healthcare organizations historically have
not connected general business manage-
ment practices to patient requirements.
Healthcare management centered on the
patient—a premise of value-based healthcare
(VBHC)—has been proposed as an innova-
tive way to reform the healthcare system
(Porter & Teisberg, 2006). Measuring out-
comes and costs for each patient is part of the
strategic agenda for moving to a high-value
healthcare delivery system (Porter & Lee,
2013). The applications of VBHC reported
by the Harvard Business School (HBS, where
the VBHC concept originated) deserve
investigation, as they are frequently used in
benchmarking value-based management
models. Many institutions are adopting com-
ponents of VBHC in their clinical practices.
Unfortunately, rigorous scientific reports on
the outcomes of these approaches have been
lacking (van Deen et al., 2017).
The VBHC model suggests that the
health system needs to be managed in terms
of outcomes that matter to patients (Porter,
2010). Still, measuring performance
through generalized outcomes such as
overall hospital mortality, infection rates,
and medication errors is the more common
practice. Those measures represent key roles
in institutional sustainability and care deliv-
ery practice, but they do not capture all the
dimensions that matter most to the patient
(Porter & Lee, 2013; Tseng & Hicks, 2016).
To translate VBHC theory into health
system operations practice, Porter estab-
lished an outcome hierarchy to identify
consensus on what constitutes an out-
come and then applied domains to cover
all phases of the continuum of care. This
outcome measures hierarchy recognizes
that the definition of success for any medi-
cal condition may have a broad variety of
outcomes yet follow a standard 3-tiered
hierarchy—Tier 1, health status achieved;
Tier 2, the process of recovery; and Tier 3,
sustainability of health (Porter, 2010).
Currently, healthcare providers are
well-appointed with metrics and scales
to measure outcomes (both for generic
and particular disease classes). However,
standard and tested measures would
improve validity and enable comparisons
across providers (Porter, 2010; Tsai et al.,
2018; Van Der Wees et al., 2014). The great
barrier to the implementation of outcome
measurement in VBHC initiatives is its
complexity. It requires the strategic
engagement of healthcare managers, data
collection, and technological advances
(Tsai et al., 2018).
Another question that hangs over
VBHC concerns the feasibility of following
the six interdependent and mutually rein-
forcing steps toward a high-value health-
care delivery system (Porter & Lee, 2013;
Porter & Teisberg, 2006; Teisberg et al.,
2020). The six steps are as follows:
surveys to cover outcome tiers that are important to patients, and 3 reported outcomes to all
6 levels of our outcome measures hierarchy. A considerable proportion of the studies (36%)
reported results that contributed to value-based financial outcomes focused on cost savings.
However, a gap remains in measuring outcomes that matter to patients. A more complete
application of the value agenda by health organizations requires advances in technology and
culture change management.
Journal of Healthcare Management
342 Volume 66, Number 5 • September/October 2021
1. Organize integrated practice units.
2. Measure costs and outcomes for
every patient.
3. Move to bundled payment for the
care cycle.
4. Integrate care delivery across sepa-
rate facilities.
5. Expand excellent services across
geography.
6. Enable a suitable information tech-
nology platform.
An in-depth analysis of value-based initia-
tives in terms of outcome measurement
can begin with a subset of medical condi-
tions and then expand over time as infra-
structure and experience grow
(Porter, 2010).
Recognizing the increasing interest
in VBHC as reflected in the amount of
recently published material about it, our
systematic review aimed to identify which
outcomes were considered in studies of the
value agenda, apply them to an outcome
measures hierarchy, and analyze the origin
of the data used to report the outcomes of a
value-based initiative.
Methods
This systematic review followed the
Preferred Reporting Items for Systematic
Reviews and Meta-Analysis (PRISMA)
process proposed by Moher and colleagues
(2009) and is consistent with the methods
of systematic review proposed by Cochrane
(Chalmers et al., 2018).
Literature Search Strategy
The MEDLINE (via PubMed), Embase,
Scopus, and Cochrane Central Register of
Controlled Trials electronic databases were
searched for studies indexed
January 1, 2010–March 4, 2020. Next, the
specific journals and the reference lists of
the retrieved articles were reviewed. The
search strategy combined indexed words
and wildcard terms related to VBHC
(Table S1, provided as Appendix 1 to this
article, published as Supplemental Digital
Content at http://links.lww.com/JHM/A57,
presents the full strategy). The results of
these database searches were cross-checked
to eliminate duplicate entries.
Eligibility Criteria and Study Selection
Two reviewers were responsible for the
independent screening of all titles and
abstracts identified in the electronic search.
Potentially eligible studies were retrieved
for full-text assessments. When a dis-
agreement arose or a consensus was not
reached, a third reviewer made the final
decision. The included studies applied the
VBHC initiative definition established by
Porter (Porter & Lee, 2013). Only studies
in English, Spanish, or Portuguese were
considered. Specific cost analysis stud-
ies, studies of the effectiveness of drugs or
diagnostic tests, and studies from an insur-
ance perspective were excluded. Editorials
and commentaries were considered if they
presented results from a VBHC case study.
Data Extraction Process
Data collection was performed indepen-
dently by the two reviewers; when uncer-
tainty persisted, a third reviewer guided
the decision. Data extraction started with
the general characteristics of the studies:
year of publication, setting, healthcare
field, value initiative, and cost measure-
ment methodology (if applied). To meet
our objectives, we extracted information
on which outcomes the study collected, the
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 343
origin of the data to evaluate these out-
comes, and whether any outcome instru-
ment was used as a collection tool. All data
were consolidated with Microsoft Excel
2010 software.
To classify outcomes used by the studies’
authors to report a value result, we catego-
rized data into the 3-tiered hierarchy defined
earlier (Porter, 2010). Each tier of the hier-
archy contained two broad levels, illustrated
in Figure S1, provided as Appendix 2 to this
article, published as Supplemental Digital
Content at http://links.lww.com/JHM/A61.
Patients’ initial conditions, demographics,
and disease-related factors were considered
to evaluate patient outcomes adjusted to
their risk (Porter, 2010). Therefore, we also
assessed whether baseline characteristics
were a variable considered in the studies’
methods.
Data Analyses
In accordance with the studies’ initial pur-
poses and the elements of the value agenda,
value-added initiatives were distinguished
into three classes:
1. Clinical or surgical pathway
redesign.
2. Computational intelligence platform
development.
3. Clinical, process, and financial
outcomes measurement (i.e., a tradi-
tional VBHC program).
Clinical or surgical pathway redesign calls
for standardized care and a reorganized
healthcare system structure to improve
access and efficiency, which is strongly
related to the value agenda components of
integrated practice units and bundled pay-
ments for care cycle (Porter & Lee, 2013).
The second class, computational intel-
ligence, comprises the information tech-
nology element. It proposes a value-based
implementation using artificial intelligence
to compose the numerator of the value
equation or a shared data platform to
optimize care and access. The third class, a
traditional value program, consists of stud-
ies centered on the foundational premise of
value, the organization of the care pathway
as a function of each patient’s clinical con-
dition, and the ability to measure outcome
and cost for each patient.
The country of the study, year of pub-
lication, healthcare field, and setting were
also assessed. The setting was defined as
system when the study covered a multicen-
tric or national perspective and as hospital
when the scenario featured the provider or
institution level.
For each article, outcome information
was retrieved and classified according to its
corresponding tier level so we could map
the most frequent outcome driver of each
tier in the studies. We also assessed the
data source of each outcome to determine
whether any measurement instruments
were used. The degree of tier-level outcome
reporting was determined by counting how
many levels of the outcome hierarchy in
each study could be mapped. In addition,
we evaluated the differences in outcomes or
costs before and after the implementation
of a value initiative in healthcare. The effect
was described and classified into the fol-
lowing categories mentioned in the litera-
ture as expected results from a value-based
program: financial outcomes, clinical
outcome improvements, patient-reported
outcomes (PROs) improvement, providers’
education, and value culture and manage-
ment (Kaplan & Porter, 2011; Lee, 2010;
Journal of Healthcare Management
344 Volume 66, Number 5 • September/October 2021
Porter, 2010 ; Porter & Lee, 2013 ; Teisberg
et al., 2020; Trimble, 2016 ).
Finally, we created a radar chart
depicting the metrics of outcomes, baseline
characteristics, and costs to illustrate the
balance of outcome measurements in the
literature. To recognize gaps and oppor-
tunities in the evolution of VBHC stud-
ies and the comprehensive defi nition of
value, we retrieved VBHC cases from the
Harvard Business School Case Collection
(2020) . Th ese cases served as a standard
reference for the selected studies in the sys-
tematic review, using the eligibility criteria
described earlier.
RESULTS
Study Selection
Th e literature search found 7,195 records;
105 full-text articles were assessed and
47 fulfi lled the inclusion criteria for the
review. Figure 1 illustrates the PRISMA
diagram, which represents the review
process for this study.
FIGURE 1
PRISMA Diagram
Records identified through database
searching (N = 7,195)
PubMed (n = 3,322)
Embase (n = 3,268)
Cochrane (n = 191)
Scopus (n = 414)
Sc
re
en
in
g
In
cl
ud
ed
E
lig
ib
ili
ty
Id
en
ti
fi
ca
ti
on
Additional records identified
through other sources
(n = 5)
Records after duplicates removed
(n = 4,931)
Records screened
(n = 4,931)
Records excluded
(n = 4,826)
Full-text articles assessed
for eligibility (n = 105)
Studies included in
qualitative synthesis
(n = 47)
Full-text articles excluded,
with reasons (n = 58)
-Theorical paper and reviews
(n = 22)
-Focus restricted to the
insurance perspective (n = 7)
-Focused on the hospital
performance without explore
patients outcomes (n = 21)
– Costs only (n = 5)
– Cost-efectiveness study
(n = 3)
Note . PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analysis.
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 345
Study Characteristics
The characteristics of each of the 47
included studies are displayed in Table S2,
provided as Appendix 2 to this article, pub-
lished as Supplemental Digital Content at
http://links.lww.com/JHM/A58. The years
of publication ranged from 2010 to early
2020, with 2019 being the year with the
most publications (n = 18). Most selected
studies were performed in the United
States (n = 39). Most (n = 34) focused on
surgical inpatient conditions. We identified
10 studies in which in-hospital medical
(nonsurgical) patients were assessed and
3 studies that involved both medical and
surgical cohorts of patients. We found 15
articles exploring the system setting, espe-
cially multicenter or national studies, and
32 that considered the application at a local
hospital setting. The value programs in the
studies focused on pathway redesign
(n = 21) and traditional VBHC studies
(n = 20). We identified only 6 studies in
which computational intelligence platforms
supported value programs.
Outcomes Measurement
The summary of outcome measures by
tier-level and healthcare field identified in
the studies is presented in Table 1.
In Tier 1, mortality (or survival) was
expressed as 4 different measures across
19 studies. The most-cited measure was
in-hospital death (n = 18), which covered
all healthcare fields among the studies.
Regarding the degree of health or recovery,
5 measures were identified in 31 studies;
the most prominent measure was discharge
related (e.g., discharge disposition, n = 18).
Among the 22 studies that considered
the first level of Tier 2, time to recovery,
4 measures could be assigned according
to the time needed to complete differ-
ent phases of care (expressed as the time
to return to usual activities, time to care
initiation, and operative time/duration of
procedure) and time in the recovery phase.
The second level of Tier 2, the disutility of
the care or treatment process, essentially
comprised measures that providers directly
control or traditionally measured clinical
indicators such as length of stay (n = 33)
and short-term complications (n = 14).
This level was most frequently represented
in the studies, comprising 7 measures for
all healthcare fields. Tier 3, sustainabil-
ity of health, included 4 measures from
35 studies: 30-day readmissions, 90-day
readmissions, additional procedures, and
post-discharge complications. The second
level of Tier 3, long-term consequences of
therapy, was mentioned least in the stud-
ies (n = 15), and when they were reported,
the measures focused on patient-reported
health status that were measured through
PRO surveys.
The tiers measured, financial outcomes,
instruments used to support data collec-
tion, and data origin for all studies are
shown in Table S3, provided as Appendix
3 to this article, published as Supplemental
Digital Content at http://links.lww.com/
JHM/A59. Financial outcomes were evalu-
ated in 37 studies (79%); among them, 13
applied microcosting estimation; time-driven
activity-based costing (TDABC)—the
method recommended in the literature to be
used in VBHC—was used in only 6 studies.
The remaining 24 studies used reimburse-
ment (n = 6), institutional accounting systems
(n = 6), external databases (n = 6), hospital
charges (n = 5), diagnosis-related groups
(n = 2), and cost of implementation (n = 1)
as measures, as displayed in the financial
Journal of Healthcare Management
346 Volume 66, Number 5 • September/October 2021
TABLE 1
Outcome Measures Considered in Each Tier Level and Healthcare Field
Tier Level Measure Healthcare Field Studies References
Tier 1:
Health
Status
Achieved
Survival In-hospital death
Oncological
surgery
2 Bateni et al. (2019),
Khullar et al. (2015)
General practice 2 Bernstein et al.
(2019), Boltz et al.
(2019)
Orthopedic
surgery
4 Colegate-Stone et al.
(2016), DiGioia &
Greenhouse (2012),
Gabriel et al. (2019),
Lee et al. (2016)
Cardiovascular
care
1 Ebinger et al. (2018)
Cardiac surgery 3 Glotzbach et al.
(2018), Kirkpatrick et
al. (2015), van Veghel
et al. (2016)
Bariatric
surgery
1 Goretti et al. (2020)
Obstetrics and
gynecology
1 Van Den Berg et al.
(2020)
Cancer care 2 Thaker et al. (2016),
van Egdom et al.
(2019)
Mixed 2 Chatfield et al.
(2019), Ravikumar et
al. (2010)
Intervention
survival
Oncological
surgery
1 Khullar et al. (2015)
Cancer care 1 Thaker et al. (2016)
Orthopedic
surgery
2 Colegate-Stone et al.
(2016), Gabriel et al.
(2019)
30-day mortality Cardiovascular
care
2 Ebinger et al. (2018),
Glotzbach et al. (2018)
Orthopedic
surgery
1 Lee et al. (2016)
Oncological
surgery
1 Gustafsson et al.
(2016)
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 347
Tier Level Measure Healthcare Field Studies References
Tier 1:
Health
Status
Achieved
1-year mortality Cardiovascular
care
1 Ebinger et al. (2018)
Bariatric
surgery
1 Goretti et al. (2020)
Degree of
health or
recovery
Discharge
disposition (to
home or care
facilities)
Orthopedic
surgery
9 Ahn et al. (2019) ,
Bolz & Iorio
(2016) , DiGioia &
Greenhouse (2012) ,
Dundon et al. (2016) ,
Featherall et al.
(2019), Featherall et
al. (2018) , Gray et al.
(2019) , Iorio et al.
(2016) , Johnson et al.
(2019)
General practice 3 Bernstein et al. (2019),
Hernandez et al.
(2019) , D. V. Williams
et al. (2019 )
Cardiovascular
care
1 Ebinger et al. (2018)
Cardiac surgery 1 Glotzbach et al.
(2018)
Spine surgery 1 Parker et al. (2017)
Cancer care 1 van Egdom et al.
(2019)
Pediatric care 1 Weiss et al. (2019)
Oncological
surgery
1 Gustafsson et al.
(2016)
Physical function-
related
Orthopedic
surgery
7 Ahn et al. (2019) ,
Berglund et al.
(2019) , DiGioia &
Greenhouse (2012) ,
Gabriel et al. (2019) ,
Johnson et al. (2019) ,
McCreary et al.
(2019) , Pelt et al.
(2016)
TABLE 1
(Continued)
Journal of Healthcare Management
348 Volume 66, Number 5 • September/October 2021
Tier Level Measure Healthcare Field Studies References
Tier 1:
Health
Status
Achieved
General practice 3 Bernstein et al.
(2019), Hernandez
et al. (2019) , D. V.
Williams et al. (2019)
Bariatric
surgery
1 Goretti et al. (2020)
Spine surgery 1 Parker et al. (2017)
Cancer care 2 Th aker et al. (2016) ,
van Egdom et al.
(2019)
Cardiac surgery 1 van Veghel et al.
(2016)
Pain-level achieved Oncological
surgery
1 Ackerman et al.
(2019)
Orthopedic
surgery
2 Berglund et al.
(2019) , Gabriel et al.
(2019)
Cardiac surgery 1 van Veghel et al.
(2016)
Diagnoses-related
(freedom from
disease)
Cancer care 2 Th aker et al. (2016) ,
van Egdom et al.
(2019)
Surgical outcomes * Obstetrics and
gynecology
2 Danilyants et al.
(2019) , Van Den
Berg et al. (2020)
Bariatric
surgery
1 Goretti et al. (2020)
Orthopedic
surgery
2 McCreary et al.
(2019) , Pelt et al.
(2016)
Oncological
surgery
1 Peard et al. (2019)
Cardiac surgery 1 J. B. Williams et al.
(2019)
Tier 2:
Process of
Recovery
Time to
recovery
Time to return to
usual activities
Orthopedic
surgery
2 Berglund et al.
(2019) , Gabriel et al.
(2019)
Bariatric
surgery
2 Goretti et al. (2020) ,
Noria et al. (2015)
Mixed 1 Makdisse et al. (2018)
TABLE 1
(Continued)
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 349
Tier Level Measure Healthcare Field Studies References
Tier 2:
Process of
Recovery
Spine surgery 1 Parker et al. (2017)
Cancer care 2 Th aker et al. (2016) ,
van Egdom et al.
(2019)
Time to care
initiation
Orthopedic
surgery
4 Colegate-Stone et al.
(2016) , DiGioia &
Greenhouse (2012) ,
Lee et al. (2016) ,
McCreary et al. (2019)
Cardiac surgery 1 Glotzbach et al. (2018)
Obstetrics and
gynecology
1 Van Den Berg et al.
(2020)
General practice 1 D. V. Williams et al.
(2019)
Operative time
(duration of
procedure)
Orthopedic
surgery
2 DiGioia &
Greenhouse (2012) ,
McCreary et al.
(2019)
Oncological
surgery
1 Ackerman et al.
(2019)
Time in the
recovery phase
General practice 2 Bernstein et al.
(2019), Hernandez et
al. (2019)
Orthopedic
surgery
4 DiGioia &
Greenhouse (2012) ,
Gray et al. (2019) ,
Johnson et al. (2019) ,
Pelt et al. (2016)
Cardiac surgery 1 Glotzbach et al.
(2018)
Disutility of
the care or
treatment
process
Length of inpatient
stay
Oncological
surgery
6 Ackerman et al.
(2019) ; Bateni et al.,
2019 ; Gustafsson et
al., 2016 ; Khullar et al.,
2015 ; Kulkarni et al.,
2011 ; Peard et al., 2019
General practice 3 Bernstein et al.
(2019), Boltz et al.
(2019) , D. V. Williams
et al. (2019)
TABLE 1
(Continued)
Journal of Healthcare Management
350 Volume 66, Number 5 • September/October 2021
Tier Level Measure Healthcare Field Studies References
Tier 2:
Process of
Recovery
Orthopedic
surgery
12 Bolz & Iorio (2016) ,
Colegate-Stone et al.
(2016) , DiGioia &
Greenhouse (2012) ,
Dundon et al. (2016) ,
Featherall et al.
(2019), Featherall et
al. (2018) , Gray et al.
(2019) , Iorio et al.
(2016) , Johnson et al.
(2019) , McCreary et
al. (2019) , Navarro et
al. (2018), Pelt et al.
(2016)
Mixed 2 Chatfi eld et al.
(2019) , Ravikumar et
al. (2010)
Obstetrics and
gynecology
2 Danilyants et al.
(2019) , Van Den
Berg et al. (2020)
Cardiovascular
care
1 Ebinger et al. (2018)
Cardiac surgery 3 Glotzbach et al.
(2018) , Kirkpatrick
et al. (2015) , J. B.
Williams et al. (2019)
Bariatric
surgery
2 Goretti et al. (2020) ,
Noria et al. (2015)
Spine surgery 1 Parker et al. (2017)
Pediatric care 1 Weiss et al. (2019)
Short-term
complications
Oncological
surgery
5 Bateni et al. (2019) ,
Khullar et al. (2015) ,
Kulkarni et al.
(2011) , Peard et al.
(2019) , Smith et al.
(2016)
Obstetrics and
gynecology
1 Danilyants et al.
(2019)
Cardiovascular
care
2 Ebinger et al. (2018) ,
Golas et al. (2018)
TABLE 1
(Continued)
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 351
Tier Level Measure Healthcare Field Studies References
Tier 2:
Process of
Recovery
Cardiac surgery 1 Kirkpatrick et al.
(2015)
Mixed 1 Makdisse et al.
(2018)
Orthopedic
surgery
1 Rosner et al. (2018)
Cancer care 2 Th aker et al. (2016) ,
van Egdom et al.
(2019)
Bariatric
surgery
1 Noria et al. (2015)
Intensive care unit
days
Oncological
surgery
3 Ackerman et al.
(2019) , Khullar et al.
(2015) , Kulkarni et
al. (2011)
General practice 1 Bernstein et al.
(2019)
Orthopedic
surgery
1 Johnson et al. (2019)
Cardiac surgery 2 Kirkpatrick et
al. (2015) , D. V.
Williams et al. (2019)
Infection rate Oncological
surgery
1 Smith et al. (2016)
Orthopedic
surgery
2 DiGioia &
Greenhouse (2012) ,
Lee et al. (2016)
Target medication
usage
Oncological
surgery
2 Ackerman et al.
(2019) , Kulkarni et
al. (2011)
Orthopedic
surgery
2 Berglund et al.
(2019) , Gray et al.
(2019)
General practice 3 Bernstein et al.
(2019), Hernandez et
al. (2019) , van Deen
et al. (2017)
Cardiac surgery 2 Glotzbach et al.
(2018) , J. B. Williams
et al. (2019)
TABLE 1
(Continued)
Journal of Healthcare Management
352 Volume 66, Number 5 • September/October 2021
Tier Level Measure Healthcare Field Studies References
Tier 2:
Process of
Recovery
Cardiovascular
care
1 Golas et al. (2018)
Patient satisfaction Orthopedic
surgery
4 Berglund et al. (2019) ,
Colegate-Stone et al.
(2016) , DiGioia &
Greenhouse (2012) ,
Featherall et al. (2019)
General practice 3 Boltz et al. (2019) ,
Hernandez et al.
(2019) , D. V. Williams
et al. (2019)
Mixed 1 Chatfi eld et al. (2019)
Obstetrics and
gynecology
1 Danilyants et al.
(2019)
Bariatric
surgery
2 Goretti et al. (2020) ,
Noria et al. (2015)
Cancer care 1 van Egdom et al. (2019)
Cardiac surgery 1 J. B. Williams et al.
(2019)
Psychological
markers †
Orthopedic
surgery
2 Gabriel et al. (2019) ,
Lee et al. (2016)
Bariatric
surgery
1 Goretti et al. (2020)
General practice 2 Hernandez et
al. (2019) , D. V.
Williams et al. (2019)
Spine surgery 1 Parker et al. (2017)
Cancer care 2 Th aker et al. (2016) ,
van Egdom et al.
(2019)
Tier 3:
Sustain-
ability of
Health
Sustainability
of health
30-day
readmissions
Oncological
surgery
3 Bateni et al. (2019) ,
Gustafsson et al.
(2016) , Khullar et al.
(2015)
General practice 5 Bernstein et al.
(2019), Boltz et al.
(2019) , Hernandez et
al. (2019) , van Deen
et al. (2017) , J. B.
Williams et al. (2019)
TABLE 1
(Continued)
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 353
Tier Level Measure Healthcare Field Studies References
Tier 3:
Sustain-
ability
of
Health
Mixed 2 Chatfi eld et al.
(2019) ; Ravikumar et
al. (2010)
Orthopedic
surgery
3 Dundon et al. (2016) ,
Iorio et al. (2016) ,
Lee et al. (2016)
Cardiovascular
care
1 Golas et al. (2018)
Bariatric
surgery
2 Goretti et al. (2020) ,
Noria et al. (2015)
Cardiac surgery 3 Kirkpatrick et al.
(2015) , van Veghel
et al. (2016) , D. V.
Williams et al. (2019)
Pediatric care 1 Weiss et al. (2019)
90-day
readmissions
Oncological
surgery
1 Khullar et al. (2015)
Orthopedic
surgery
5 Ahn et al. (2019) ,
Bolz & Iorio (2016) ,
Dundon et al. (2016) ,
Gray et al. (2019) ,
Rosner et al. (2018)
Need for revision/
reoperation
Oncological
surgery
2 Abdulla et al. (2012) ,
Smith et al. (2016)
Bariatric
surgery
1 Goretti et al. (2020)
Mixed 1 Makdisse et al.
(2018)
General practice 1 van Deen et al.
(2017)
Cardiac surgery 1 J. B. Williams et al.
(2019)
Aft er-discharge
complications
Orthopedic
surgery
4 Ahn et al. (2019) ,
Featherall et al.
(2019), Featherall et
al. (2018) , Rosner et
al. (2018)
Spine surgery 1 Parker et al. (2017)
Oncological
surgery
1 Smith et al. (2016)
TABLE 1
(Continued)
Journal of Healthcare Management
354 Volume 66, Number 5 • September/October 2021
Tier Level Measure Healthcare Field Studies References
Tier 3:
Sustain-
ability
of
Health
Long-term
consequences
Health-reported
status
Orthopedic
surgery
5 Ahn et al. (2019) ,
Berglund et al.
(2019) , Gabriel et al.
(2019) , Johnson et
al. (2019) , Lee et al.
(2016)
Obstetrics and
gynecology
1 Danilyants et al.
(2019)
Bariatric
surgery
1 Goretti et al. (2020)
General practice 3 Hernandez et al.
(2019) , van Deen
et al. (2017) , D. V.
Williams et al. (2019)
Mixed 1 Makdisse et al.
(2018)
Spine surgery 1 Parker et al. (2017)
Cancer care 2 Th aker et al. (2016) ,
van Egdom et al.
(2019)
Cardiac surgery 1 van Veghel et al.
(2016)
* Surgical outcomes related to organ function preservation, method of tissue extraction, and estimated blood loss.
† Psychological markers are defi ned as measures of anxiety, discomfort, and ability to work or function normally while
undergoing treatment.
TABLE 1
(Continued)
outcome information in Table S3
(http://links.lww.com/JHM/A59).
Th e main data source in the studies
was the electronic health record (EHR),
including medical and hospital records
(85%) or an external database (15%). Only
16 studies (34%) used PRO surveys as
instruments to cover outcome tiers (see
Table S3 http://links.lww.com/JHM/A59 ).
Among those, generic metrics of mul-
tiple conditions appeared in 8 studies
(e.g., EQ-5D); metrics tailored to disease
classes were reported in 12 studies (e.g.,
International Consortium for Health Out-
comes Measurement [ICHOM] specifi c
surveys). Other surveys relating to patient
experience were conducted in nine stud-
ies (e.g., Hospital Consumer Assessment
of Healthcare Providers and Systems), and
scales completed by professionals (e.g.,
Activity Measure in Post-Acute Care) were
used in three studies.
Th e reported saturation of tier-level
outcomes showed limited coverage for
value assessments in the literature report-
ing VBHC initiatives. Only three studies
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 355
( Gray et al., 2019 ; Noria et al., 2015 ; Th aker
et al., 2016 ) reported outcomes to all levels
of the tier hierarchy. Studies covered three
levels of the outcome hierarchy ( n = 24,
51%) most frequently, followed by
four levels (19%) and fi ve levels (15%).
Value Effect Reported by Studies
Th e reported results that triggered a value
increase in each case studied are con-
solidated in Table 2 , which also shows
whether the contribution was observed in
the fi nancial outcome, clinical outcome
improvement, PRO improvement, provider
education and value culture, or hospital
management.
A considerable proportion of the stud-
ies (36%) achieved results that contributed
to value-based fi nancial outcomes focused
on cost savings. An important common
fi nding was that the calculated savings
were derived from reductions in readmis-
sions and inpatient stays, and the savings
are accounted for as an indirect fi nancial
impact. However, these opportunities for
future cost savings are not measured by
accurate costs and economical methods
( Etges et al., 2020 ). Two studies ( Johnson
TABLE 2
A Summary of Value Effect and Domains Reported in Real-World Settings
Value Eff ect Domain Reported
t t
t t
Value
Outcomes( 1) Outcomes( 0)
Costs( 1) Costs( 0)
=
= − =
= − =
Where:
Outcomes include measures
stratifi ed in Tiers 1, 2, and 3.
Costs may consider costs over
the complete pathway;
t = time
Financial outcome Direct cost savings ( Ackerman et al., 2019 ;
Bernstein et al., 2019; Boltz et al., 2019 ;
Bolz & Iorio, 2016 ; Chatfi eld et al., 2019 ;
Dundon et al., 2016 ; Ebinger et al., 2018 ;
Featherall et al., 2019; Glotzbach et al., 2018 ;
Goretti et al., 2020 ; Gray et al., 2019 ; Iorio et al.,
2016 ; Lee et al., 2016 ; Pelt et al., 2016 )
Indirect cost savings ( DiGioia &
Greenhouse, 2012 ; Weiss et al., 2019 )
Reduced variance in cost ( Ackerman et al., 2019 )
Sustainable ( Goretti et al., 2020 )
Clinical outcome
improvement
Reduced complications ( Danilyants et al.,
2019 ; Goretti et al., 2020 ; Rosner et al., 2018 )
Reduced mortality ( Colegate-Stone et al., 2016 ;
DiGioia & Greenhouse, 2012 ; Iorio et al., 2016 )
Improved laboratories and recovered from
comorbidities ( Abdulla et al., 2012 ;
Goretti et al., 2020 ; Iorio et al., 2016 ;
D. V. Williams et al., 2019 )
Perioperative outcomes ( J. B. Williams et al.,
2019 )
Reduced pharmacological treatment time
( Hernandez et al., 2019 ; Kirkpatrick et al.,
2015 ; Lee et al., 2016 )
Journal of Healthcare Management
356 Volume 66, Number 5 • September/October 2021
Value Eff ect Domain Reported
Patient-reported
outcome
improvement
Patient satisfaction with service
( Colegate-Stone et al., 2016 ; DiGioia &
Greenhouse, 2012 ; Noria et al., 2015 ;
van Egdom et al., 2019 )
Improved work and function relationships
( Hernandez et al., 2019 ; Ahn et al., 2019 ;
Goretti et al., 2020 ; Parker et al., 2017 ;
Weiss et al., 2019 )
Improved/favorable quality of life scores
( Ahn et al., 2019 ; Iorio et al., 2016 ; Parker et
al., 2017 ; J. B. Williams et al., 2019)
Improved well-being ( Hernandez et al.,
2019 ; Bateni et al., 2019 ; Goretti et al., 2020 )
Provider
education and
value culture
Support for innovative implementations
( Boltz et al., 2019 )
Value consciousness and engagement
( Ackerman et al., 2019 ; Chatfi eld et al., 2019 ;
Gustafsson et al., 2016 ; Navarro et al., 2018;
Noria et al., 2015 ; Ravikumar et al., 2010 )
Replicable ( Goretti et al., 2020 )
Hospital
management
Increased hospital capacity ( Abdulla et al.,
2012 ; Ackerman et al., 2019 ; Bolz & Iorio,
2016 ; Chatfi eld et al., 2019 ; Dundon et al.,
2016 ; Featherall et al., 2019; Gabriel et al.,
2019 ; Gray et al., 2019 ; Johnson et al., 2019 ;
Kirkpatrick et al., 2015 ; Kulkarni et al., 2011 ;
Noria et al., 2015 ; Pelt et al., 2016 ; Weiss et al.,
2019 ; D. V. Williams et al., 2019 )
Improved discharge effi ciency ( Bolz &
Iorio, 2016 ; ( DiGioia & Greenhouse, 2012 ;
Dundon et al., 2016 ; Ebinger et al., 2018 ;
Featherall et al., 2019; Featherall et al., 2018 )
Better resource and capacity allocating
( Colegate-Stone et al., 2016 ; Gustafsson et al.,
2016 ; Van Den Berg et al., 2020 )
Value-offi ce ( Hernandez et al., 2019 ;
Makdisse et al., 2018 )
Improved quality through risk adjustment
(Bernstein et al., 2019; Golas et al., 2018 ;
Khullar et al., 2015 ; Smith et al., 2016 ;
D. V. Williams et al., 2019 )
Benchmarking ( Van Den Berg et al., 2020 ;
van Veghel et al., 2016 )
TABLE 2
(Continued)
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 357
et al., 2019; van Deen et al., 2017) identi-
fied neutral effects or were not able to
consistently observe improved results even
though they showed these effects as poten-
tial improvements.
Regarding PRO improvement, 25% of
the studies reported improved PROs; how-
ever, of the studies that used PRO measure-
ment instruments (n = 16), 11 achieved
positive results. Management effects were
mainly related to hospital capacity (n = 15),
improved quality through risk adjustments
(n = 5), and better resource allocation
(n = 3).
On the Radar: Literature and
HBS Cases
Twelve HBS cases were selected for value
initiatives in the fields of prostate cancer
(Porter, Deerberg-Wittram, et al., 2014),
orthopedic surgeries (Kaplan et al., 2012;
Porter, Marks, et al., 2014), pediatric care
(Porter, Bachmann et al., 2014; Porter et al.,
2016), and primary general practice
(Kaplan et al., 2018; Porter, Landman,
et al., 2014; Porter & Teisberg, 2009 ;
Porter et al., 2017) (see Table S4, which
summarizes the main characteristics of
these cases, provided as Appendix 4 to this
article, published as Supplemental Digital
Content at http://links.lww.com/JHM/
A60). In all HBS cases, the PRO measures
were used. Figure 2 presents the compari-
son of the outcome tier coverage profiles of
the included studies from the literature and
the selected HBS cases. Of note, one initia-
tive was reported in both metrics: the HBS
and literature search (Hernandez
et al., 2019).
The most conflicting information
concerns tier levels that are more depen-
dent on PRO measures such as Tier 2’s
time to recovery and Tier 3’s long-term
consequences, which are expressed less
frequently in the literature (47% and 32%,
respectively); in contrast, the same levels
were more commonly considered in HBS
cases (75% and 92%, respectively). This
was not surprising, as predicted by the
number of studies using PRO measures
earlier in the results. Regarding micro-
costing or TDABC methods, the stud-
ies showed similarly low prevalence in
both the literature (27%) and HBS cases
(28%) as revealed by the dotted lines in
Figure 2. Studies that used methods other
than microcosting to measure financial
information had a greater proportion of
both the literature and HBS cases (79%
and 92%, respectively). Tier 1’s mortal-
ity survival-related metrics were also not
widely computed in the selected studies
(40% in the literature and 60% in HBS
cases). Regarding the literature, two studies
(Abdulla et al., 2012; Ahn et al., 2019) did
not measure Tier 2’s disutility of the care
process or treatment process level, and six
did not measure baseline characteristics
for risk-adjustment data, making these two
tiers the most prevalent in the literature
(96% and 87%, respectively), This pattern
was also verified for HBS cases, because
those two levels were reported in all cases.
DISCUSSION
This systematic review was intended to
map how outcomes are being measured in
the studies of the value agenda. We identi-
fied a significant imbalance of outcome
measurements in many aspects, such as the
configuration of tier levels chosen in value
initiatives, instruments applied to sup-
port data, and the rare use of microcosting
methods to determine financial outcomes.
Journal of Healthcare Management
358 Volume 66, Number 5 • September/October 2021
Tier 3, especially long-term consequences,
was the least explored, whereas traditional
clinical and process outcomes such as
length of stay and infections were still the
most frequent measures considered in the
literature.
VBHC was introduced to reduce waste
and increase the quality of care ( Porter &
Lee, 2013 ). As shown in this review, the
increase in the quality of care is usually
measured by the hospital and clini-
cal outcomes, not necessarily by patient
perceptions, and the fi nancial results are
not being reported with highly precise
accounting methods. PRO measures play
a central role in the value agenda model.
Nevertheless, studies evaluating long-term
consequences and new conditions are rare
( Halpern et al., 2020 ). However, these fac-
tors received the most attention when we
FIGURE 2
Radar Chart of Literature and Cases Profi le in Outcome Information Coverage
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Note. Th e black line inside the circle represents the proportion of Harvard Business School cases in each tier; the gray line
demonstrates the same profi le for the systematic review studies. Th e dotted line represents the studies within the fi nancial
result category that used microcosting methods or time-driven activity-based costing (TDABC).
Value-Based Healthcare in Practice Initiatives
www.ache.org/journals 359
looked at the applied cases of VBHC in the
HBS Case Collection (Kaplan et al., 2012,
2018; Porter, Bachmann, et al., 2014 Porter,
Deerberg-Wittram, et al., 2014; Porter,
Landman, et al., 2014; Porter, Marks, et al.,
2014; Porter & Teisberg, 2009; Porter et al.,
2007; Porter et al., 2016).
We found that widespread and consis-
tent use of PRO measurements has proven
to be ambiguous for a range of reasons,
including the complexity of the measures
tracked and the fluctuating reliability of
patient assessments on many measures
(Schupbach et al., 2016), which may
explain the gap seen in the radar chart
regarding the comprehensiveness of the
value definition.
In agreement with the factors listed
by Martin and colleagues (2019), our
results demonstrate that measuring out-
comes in healthcare has been difficult for
three reasons: (1) current outcome mea-
surements consist of nonstructured and
condition-related data that are difficult to
access, (2) adherence to evidence-based
processes rather than clinically and
patient-reported driven results is limiting,
and (3) the healthcare provider seldom
incorporates an integrated view of the
patient’s outcomes over the full cycle of care.
The evolution to electronic registries
that provide practicable patient-centered
care could take two main routes: (1) the
education and dissemination of a value
culture, which can instantly reinforce staff
to register important outcomes about the
patient either through validated question-
naires or more effective multidisciplinary
meetings, and (2) the creation of an EHR
system-integrated real-time outcome
measurement platform. This reflection
leads us to surmise that VBHC is not
feasible without investment in information
technology (Boscolo et al., 2020). Once
a functionally integrated EHR system is
implemented, it must be validated to ensure
that it provides quality measurements
—an essential component of quality
improvement (Etges et al., 2020). Address-
ing suboptimal outcomes and compar-
ing cost data for treatment options will
facilitate process improvement and value
(Thaker et al., 2016).
Academics and consultants created the
ICHOM in 2012 to address the shortcom-
ings of outcome measurement. Today, the
ICHOM working group stipulates that the
intention of such parameterization is not to
devise new measures of results but rather
to agree on a well-assessed outcome mea-
sure indicator that everyone should use
to cover a much broader spectrum of the
outcome hierarchy for a health condition
(ICHOM, n.d.). The use of the ICHOM
questionnaires in the literature is still
restricted to a few studies concentrated in
the fields of orthopedic surgery (Berglund
et al., 2019; Glotzbach et al., 2018; Pelt et al.,
2016), general practice (Hernandez et al.,
2019; Kulkarni et al., 2011), bariatric
surgery (Noria et al., 2015), obstetrics (Van
Den Berg et al., 2020), breast cancer (van
Egdom et al., 2019), and prostate cancer
(Thaker et al., 2016).
In addition to the ICHOM, however,
some processual measures are still needed to
add all the tiers of value (Thaker et al., 2016).
It is evident in the HBS cases that measur-
ing outcomes—clinical, processual, finan-
cial, and PRO—is a valuable tool that helps
healthcare providers to be more intentional
about quality, efficiency, and (especially)
patient outcomes (Porter, 2010; Schupbach
et al., 2016), and this model of measuring
Journal of Healthcare Management
360 Volume 66, Number 5 • September/October 2021
outcomes has been demonstrated to have a
higher success rate and permanence (Porter,
2010; Thaker et al., 2016).
Regarding financial outcomes, we
note that cost studies were not part of our
main scope. Nevertheless, in the spec-
trum of value initiatives, we would expect
an exploration of both numerators and
denominators to compose the value equa-
tion. Because we could identify only 13
studies and 3 cases that applied advanced
methods to evaluate real costs, we suggest
that scaled VBHC adoption would require
more methodological rigor in the evalu-
ation of financial outcomes (Etges et al.,
2020; Tsai et al., 2018).
Developments in the EHR are mak-
ing outcomes far less costly to measure
(Porter & Teisberg, 2006). The majority
of VBHC studies used medical records to
collect data to evaluate the value of health-
care. However, as verified from the studies
that covered the full range of the outcome
hierarchy (Noria et al., 2015), the EHR
does not uniformly capture the three tiers
of outcomes we described, requiring addi-
tional staff to manually maintain parallel
control of the data and update the research
databases (Noria et al., 2015).
Study Limitations
There are both weaknesses and strengths
to consider in our work. To the best
of our knowledge, this is the first sys-
tematic review to perform a broad lit-
erature search of VBHC initiative studies
with a priori–defined methods and
well-established methodological guide-
lines. However, as there is not a valid
instrument to assess the methodological
quality of VBHC initiative studies, the
methodological quality of these studies
could not be determined. We also did not
identify studies with negative results asso-
ciated with the outcome measurement in
the VBHC initiative; thus, there is poten-
tial publication bias toward those only
reporting successful results in this field. In
addition, the searches were conducted in
early March 2020, so this study does not
include or reflect the possible movement in
VBHC initiatives driven by the COVID-19
pandemic. Thus, we should stress that this
was a prepandemic systematic review of
VBHC initiatives.
CONCLUSION
Our systematic review suggests that, in
a real-world setting, there is still a gap
between measuring outcomes that matter
to patients and measuring financial out-
comes through rigorous methodological
methods. Advances in technology capac-
ity and a culture of change in manage-
ment appear to be the main barriers to
making the value agenda more easily
reproducible.
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The author declares no conflicts of interest.
PRACTITIONER APPLICATION:
Value-Based Healthcare Initiatives in Practice:
A Systematic Review
Pradipta Komanduri, FACHE, vice president, clinical support services, Seattle Children’s, Seattle,
Washington
Zanotto and colleagues provide a unique assessment of value-based outcome mea-
surements to-date, noting that while there have been reported benefits from such
initiatives, there are gaps in accurate measurement of costs and long-term out-
comes at the patient level. Their research aggregated improvement efforts into three main
categories: standardizing care through pathways; developing technology; and improving
traditional measures tied to clinical, process, and financial outcomes at the facility level.
The authors suggest that the true impact of value-based measures can only be under-
stood through a more consistent approach to outcome measurement at the patient level.
While value-based care models thus far have been necessary experiments to transform
© 2021 Foundation of the American College of Healthcare Executives
DOI: 10.1097/JHM-D-21-00175
Consider the following scenario:
Value-based care is a healthcare delivery model that pays providers based on patient health outcomes. Some Central Healthcare System (CHS) administrators have heard that this model provides patients with lower costs, higher satisfaction scores, and reduced risks and have suggested that CHS implement it across their facilities. However, several CHS leaders have expressed concern that the costs associated with implementing this new model may outweigh the potential benefits. CHS administrators have determined that reviewing the literature around value-based care and associated costs will help inform their decision and reach consensus about how to proceed.
What do you think CHS leaders hope to gain from a literature review on the costs associated with value-based care? Any major change to a healthcare delivery model carries risks, and learning about the successes and failures of other organizations may help CHS leaders better understand how those risks might manifest and identify strategies to mitigate them. Consulting the literature will also help CHS administrators draw comparisons between their organization and those examined in studies to better understand specific adaptations that might be most appropriate in their setting and plan for contingencies. In this Assignment, you will analyze a systematic review on value-based care and search the literature for empirical studies on the costs associated with value-based healthcare models. You will use a Literature Review Matrix to organize each study’s conclusions and then synthesize your findings to inform decision-making and priority action steps related to the adoption of a value-based care model.
Articles:
1. See attachment as article 1
2. Focus particularly on value-based healthcare and cost implications and assumptions.
3. Search the literature for 5–7 additional empirical studies on the topic of value-based healthcare and the costs associated.
a. Each article should be no more than 5 years old and should be from a peer-reviewed journal.
b. The articles selected should be empirical studies that include data on cost and value-based care.
i. Reviews (systematic, integrative, meta-analysis, etc.) are not appropriate selections for this assignment.
c. Your selected articles should flow from the content in the initial article provided (Zanotto et al., 2021). You may want to consider searching the articles that are referenced within the initial article.
DO:
Part 1: Literature Review Matrix
· Using the matrix template provided, break down the information in each of your selected articles, including the initial article on value-based healthcare.
· Within the matrix, you should include your initial article (Zanotto et al., 2021) and at least 5 additional articles.
Part 2: Synthesis of Findings
· Synthesize the findings and conclusions from the articles.
· Note that this is not a
summary of the articles, but, rather, a
synthesis of the findings of all of the articles.
· Analyze any additional information that would be useful in making the decision and justify the need for the additional information.
· Explain how this synthesis can help inform the decision-making process around implementing value-based healthcare.
