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For more information regarding the concepts in this article, contact Dr. Polanczyk at [email protected]. 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

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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.

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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

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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;

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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.

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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

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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)

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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)

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Tier Level Measure Healthcare Field Studies References Tier 1: Health Status Achieved

General practice 3 Bernstein et a

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