Equity Investment in Physician Practices: What's All This Brouhaha?

There have been two waves of equity-based investment in physician practices. Both used a combination of public and private sources but in different mixes. The first investment wave, in the 1990s, was led by public equity and physician practice management companies, with less involvement by private equity (PE). The second investment wave followed the Affordable Care Act and was led by PE firms. It has generated concerns of wasteful spending, less cost-effective care, and initiatives harmful to patient welfare. This article compares the two waves and asks if they are parallel in important ways. It describes the similarities in the players, driving forces, acquisition dynamics, spurs to consolidation, types of equity involved, models to organize physicians, and levels of market penetration achieved. The article then tackles three unresolved issues: Does PE investment differ from other investment vehicles in concerning ways? Does PE possess capabilities that other investment vehicles lack and confer competitive advantage? Does physician practice investment offer opportunities for supernormal profits? It then discusses ongoing trends that may disrupt PE and curtail its practice investment. It concludes that past may be prologue, that is, what happened during the 1990s may well repeat, suggesting the PE threat is overblown.

Big Med's Spread.

Policy Points Hospital executives posit a number of rationales for system mergers which lack any basis in academic evidence. Decades of academic research question whether system combinations confer public benefits. Antitrust authorities need to continue to closely scrutinize these transactions. Recently, mergers of hospital systems that span different geographic markets are on the rise. Economists have alerted policymakers about the potential impacts such cross-market mergers may have on hospital prices. We suggest there are other reasons for concern that scholars have not often confonted. Cross-market mergers may be conducted for purely self-serving reasons of organizational growth that increases executive compensation. Combinations of sellers should have clear advantages to consumers. System executives and their boards should bear the burden of proof. Federal regulators and state attorney generals should be cognizant that rationales for cross-market systems advanced by merging parties are unlikely to be operative or dominant in merger decision making. Policymakers should be careful about passing legislation that encourages hospitals to consolidate. CONTEXT: There is a growing trend of combinations among hospital systems that operate in different geographic markets known as cross-market mergers. Economists have analyzed these broader systems in terms of their anticompetitive behavior and pricing power over insurers. This paper evaluates the benefits advanced by these new hospital systems that speak to a different set of issues not usually studied: increased efficiencies, new capabilities, operating synergies, and addressing health inequities. The paper thus "looks under the hood" of these emerging, cross-market systems to assess what value they might bestow and upon whom. METHODS: The paper examines recently announced cross-market mergers in terms of their supposed benefits, as expressed by the systems' executives as well as by industry consultants. These presumed benefits are then evaluated against existing evidence regarding hospital system outcomes. FINDINGS: Advocates of cross-market hospital mergers cite a host of benefits. Research suggests these benefits are nonexistent. Additional evidence suggests other motives may be at play in the formation of cross-market mergers that have nothing to do with efficiencies, synergies, or community benefits. Instead these mergers may be self-serving efforts by system chief executive officers (CEOs) to boost their compensation. CONCLUSIONS: Cross-market hospital mergers may yield no benefits to the hospitals involved or the communities in which they operate. The boards of hospital systems that engage in these cross-market mergers need to exercise greater diligence over the actions of their CEOs.

The study protocol to evaluate implementation of the transitional care model in four U.S. healthcare systems during the Covid-19 pandemic.

This study protocol describes the conceptual framework, design, and methods being employed to evaluate the implementation of the Transitional Care Model (TCM) as part of a randomized controlled trial. The trial, designed to examine the health and cost outcomes of at-risk hospitalized older adults, is being conducted in the context of the COVID-19 pandemic. This parallel study is guided by the Practical, Robust, Implementation and Sustainability Model (PRISM) and uses a fixed, mixed methods convergent parallel design to identify challenges encountered by participating hospitals and post-acute and community-based providers that impact the implementation of the TCM with fidelity, strategies implemented to address those challenges and the relationships between challenges, strategies, and rates of fidelity to TCM's core components over time. Prior to the study's launch and throughout its implementation, qualitative and quantitative data related to COVID and non-COVID challenges are being collected via surveys and meetings with healthcare system staff. Strategies implemented to address challenges and fidelity to TCM's core components are also being assessed. Analyses of quantitative (established metrics to evaluate TCM's core components) and qualitative data (barriers and facilitators to implementation) are being conducted independently. These datasets are then merged and interpreted together. General linear and mixed effects modeling using all merged data and patients' socio-demographic and social determinants of health characteristics, will be used to examine relationships between key variables and fidelity rates. Implications of study findings in the context of COVID-19 and future research opportunities are suggested. Trial registration: ClinicalTrials.gov Identifier: NCT04212962.

Older Adult and Family Caregiver Perspectives on Engagement in Primary Care.

The purpose of the current in-depth qualitative study was to explore the experiences of older adults and family caregivers in primary care. Twenty patients and caregivers from six Comprehensive Primary Care Plus (CPC+) practices' Patient and Family Advisory Councils within a large academic health system participated in telephone interviews from December 2018 to May 2019. Participants were mostly women (60%), with an average age of 71 years and nine chronic conditions. Transcripts were coded using conventional content analysis. Two key themes emerged related to person-centered care (PCC): Engagement in Health Care and Patient-Provider Relationship. Engagement in health care was defined by participants as: being proactive, centering on patient goals in treatment discussions, adherence, and self-triaging. Approximately all participants discussed the importance of the relationship and interactions with their provider as influencing their engagement. The identified themes offer recommendations for further improvement of primary PCC. [Journal of Gerontological Nursing, 48(11), 7-13.].

Medical Complexity Mediates Healthcare Resource Use in the Socially Vulnerable.

GOAL: The objective of this retrospective, observational study was to assess the mediating effect of medical complexity on the relationship between social vulnerability and four acute care resource use outcomes-number of hospitalizations, emergency department (ED) visits, observation stays, and total visits. Such information may help healthcare managers better anticipate the effects of interventions targeted to the socially vulnerable in their patient population. METHODS: Electronic health records of 147,496 adults served by 27 primary care practices in one large health system from 2015 to 2017 were used. Descriptive statistics were applied to characterize patients and the primary care practices included in the study. Causal mediation analyses using a modified Baron and Kenny approach were performed. PRINCIPAL FINDINGS: Causal mediation analyses demonstrated that increased social vulnerability was associated with increased medical complexity (incidence rate ratio [IRR] = 1.57) and increased numbers of hospitalizations (IRR = 1.63), ED visits (IRR = 2.14), observation stays (IRR = 1.94), and total visits (IRR = 2.04). Effects remained significant, though attenuated, after adjusting for medical complexity (mediator), demographics, and medications (hospitalizations IRR = 1.44, ED visits IRR = 2.02, observation stays IRR = 1.74, total visits IRR = 1.86). Social vulnerability, given medical complexity, explained between 8% (ED visits) and 26% (hospitalizations) of the variation in outcomes. PRACTICAL APPLICATIONS: These findings reinforce the need to modify interventions for medically complex adults to address their social needs and, consequently, reduce costly health services. Health systems seeking to reduce costly care can use these results to estimate savings in the treatment of patients with high social vulnerability-before they get chronic conditions and later as they seek care.

MIRROR-TCM: Multisite Replication of a Randomized Controlled Trial - Transitional Care Model.

In the U.S., older adults hospitalized with acute episodes of chronic conditions often are rehospitalized within 30 days of discharge. Numerous studies reveal that poor management of the complex needs of this population remains the norm. METHODS: This prospective, intent-to-treat, randomized controlled trial (RCT) will assess the effects of replicating the rigorously studied Transitional Care Model (TCM) in four U.S. healthcare systems. The TCM is an advanced practice registered nurse led, team-based, care management intervention that supports older adults throughout vulnerable care episodes that span hospital to home. This RCT will compare health and economic outcomes demonstrated by at-risk older adults hospitalized with heart failure, chronic obstructive pulmonary disease or pneumonia randomized to receive usual discharge planning (control group, N = 800) to those observed by a similar group of older adults randomized to receive the TCM protocol (N = 800). The primary outcome is number of rehospitalizations at 12 months post-discharge, with secondary resource use outcomes measured at multiple intervals. Patient experience with care, health and quality of life outcomes will be assessed at 90 days post-discharge. DISCUSSION: Based on health and economic benefits demonstrated in multiple NIH funded RCTs, the study team hypothesizes that the intervention group, both within and across participating health systems, will have decreased acute care resource use and costs at 12 months and better ratings of the care experience and health and quality of life through 90 days post-discharge compared to the control group. The impact of COVID-19 on implementation of this study also is discussed.

Cost-Effectiveness Analysis of Branded Drugs With Market Demand and Insurance.

OBJECTIVES: Cost-effectiveness analysis of branded pharmaceuticals presumes that both cost (or price) and marginal effectiveness levels are exogenous. This assumption underlies most judgments of the cost-effectiveness of specific drugs. In this study, we show the theoretical implications of letting both factors be endogenous by modeling pharmaceutical price setting with and without health insurance, along with patient response to the prices that depend on marginal effectiveness. We then explore the implications of these models for cost-effectiveness ratios. METHODS: We used simple textbook models of patient demand and pricing behavior of drug firms to predict market equilibria in the drug and insurance markets and to generate calculations of the cost-effectiveness ratios in those settings. RESULTS: We found that ratios in market settings can be much different from those calculated in cost-effectiveness studies based on exogenous prices and treatment of all patients at risk rather than those who would demand treatment in a market setting. We also found that there may be considerable similarity in these market cost-effectiveness ratios across different products because drug firms with market power set profit-maximizing prices. CONCLUSIONS: We found that market cost-effectiveness ratios will always indicate an excess of benefits over cost. Insurance will lead to less favorable ratios than without insurance, but when insurers bargain with drug firms, rather than taking their prices as given, cost-effectiveness ratios will be more favorable.

When Should Medicare Mandate Participation In Alternative Payment Models?

The Centers for Medicare and Medicaid Services continues to propose and implement alternative payment models (APMs) to shift Medicare payment away from fee-for-service and toward approaches that emphasize health care value. As APMs expand in scope, one critical question is whether they should engage providers on a voluntary or a mandatory basis. Clinicians and policy makers may view the benefits and drawbacks of these two modes of participation differently. In this Analysis we compare the benefits and drawbacks of mandatory and voluntary participation, based on clinical versus policy perspectives, and we argue that both modes are necessary for APMs to achieve the goal of improving value. Policy makers should match the mode of participation and related financial incentives to each clinical scenario in which an APM is implemented. We propose ways to coordinate mandatory and voluntary APMs based on clinical scenarios.

Policy Flight Simulators: Accelerating Decisions to Adopt Evidence-Based Health Interventions.

EXECUTIVE SUMMARY: In this study, the authors used simulation to explore factors that might influence hospitals' decisions to adopt evidence-based interventions. Specifically, they developed a simulation model to examine the extent to which hospitals would benefit economically from the transitional care model (TCM). The TCM is designed to transition high-risk older adults from hospitals back to communities using interventions focused on preventing readmissions.The authors used qualitative methods to identify and validate simulation facets. Four simulation experiments explored the economic impact of the TCM on more than 3,000 U.S. hospitals: (1) magnitude of readmission penalty, (2) application to specific diagnosis-related groups, (3) level of cost sharing between payer and provider, and (4) capitated versus fee-for-service payments. The simulator projected hospital-specific economic effects. The authors used Monte Carlo methods for the simulations, which were parameterized with public data sets from the Centers for Medicare & Medicaid Services (CMS) and TCM data from randomized controlled trials and comparative effectiveness studies.Under current conditions, the simulation indicated that only 10 of more than 3,000 Medicare-certified hospitals would benefit financially from the TCM. If current readmission penalties were doubled, the number of hospitals projected to benefit would increase to 300. Targeting selected diagnosis cohorts would also increase the number of hospitals to 300. If payers reimbursed providers for 100% of the TCM costs, 2,000 hospitals would benefit financially. Under a capitated payment model, 1,500 hospitals would benefit from the TCM.Current CMS penalties-or reasonable increases-have little economic effect on the TCM. In the current environment, two strategies are likely to facilitate adoption: (1) persuading payers to reimburse TCM costs and (2) focusing on hospitals with higher bed occupancies and higher revenue patients.

Cost impact of the transitional care model for hospitalized cognitively impaired older adults.

AIM: The goal of this study was to compare postacute care costs of three care management interventions. MATERIALS & METHODS: A total of 202 hospitalized older adults with cognitive impairment received either Augmented Standard Care, Resource Nurse Care or the Transitional Care Model. The Lin method was used to estimate costs at 30 and 180 days postindex hospital discharge. RESULTS: The Transitional Care Model had significantly lower costs than the Augmented Standard Care group at both 30 (p < 0.001) and 180 days (p = 0.03) and significantly lower costs than Resource Nurse Care at 30 days (p = 0.02). CONCLUSION: These findings suggest that the Transitional Care Model can reduce both the amount of other postacute care and the total cost of care compared with alternative services for cognitively impaired older adults. Clinicaltrials.gov : NCT00294307.

Adaptations of the evidence-based Transitional Care Model in the U.S.

Despite a growing body of evidence that adaptations of evidence-based interventions (EBI) are ubiquitous, few studies have examined the nature and rationale for modifications to the components of these interventions. The primary aim of this study was to describe and classify common local adaptations of the Transitional Care Model (TCM), an EBI comprised of 10 components that has been proven in multiple clinical trials to improve the care and outcomes of chronically ill older adults transitioning from hospitals to home. Guided by Stirman's System of Classifying Adaptations, 582 transitional care clinicians in health systems and community-based organizations throughout the U.S. completed a survey between September 2014 and January 2015; interviews were then conducted with a subset of survey respondents (N = 24) between April and December 2015. A total of 342 survey respondents (59%) reported implementation of the TCM in distinct organizations. Of this group, 96% reported a mean of 4.4 adaptations to the 10 TCM components (40%, one to three; 43%, four to six; and 17%, seven to nine). Nine of ten respondents (94%) reported contextual adaptations while content adaptations were less frequently reported (58%). The top three reported adaptations all related to context (i.e., delivering services from hospital to home, relying on advance practice nurses, and fostering care continuity); interviews clarified a diverse set of reasons for such modifications. Findings reinforce the need for investment in adaptation science and suggest hypotheses to guide rigorous examination of the association between adaptations of TCM components and desired outcomes.

Developing a Policy Flight Simulator to Facilitate the Adoption of an Evidence-Based Intervention.

While the use of evidence-based interventions (EBIs) has been advocated by the medical research community for quite some time, uptake of these interventions by healthcare providers has been slow. One possible explanation is that it is challenging for providers to estimate impacts of a specific EBI on their particular organization. To address that concern, we developed and evaluated a type of simulation called a policy flight simulator to determine if it could improve the adoption decision about a specific EBI, the transitional care model (TCM). The TCM uses an advanced practice nurse-led model of care to transition older adults with multiple chronic conditions from a hospitalization to home. An evaluation by a National Advisory Committee, made up of senior representatives from various stakeholders in the U.S. healthcare system, found the policy flight simulator to be a useful tool that has the potential to better inform adoption decisions. This paper describes the simulation development effort and documents lessons learned that may be useful to the healthcare modeling community and those interested in using simulation to support decisions based on EBIs.

Transformation of the Health Care Industry: Curb Your Enthusiasm?

Policy Points: Policymakers seek to transform the US health care system along two dimensions simultaneously: alternative payment models and new models of provider organization. This transformation is supposed to transfer risk to providers and make them more accountable for health care costs and quality. The transformation in payment and provider organization is neither happening quickly nor shifting risk to providers. The impact on health care cost and quality is also weak or nonexistent. In the longer run, decision makers should be prepared to accept the limits on transformation and carefully consider whether to advocate solutions not yet supported by evidence. CONTEXT: There is a widespread belief that the US health care system needs to move "from volume to value." This transformation to value (eg, quality divided by cost) is conceptualized as a two-fold movement: (1) from fee-for-service to alternative payment models; and (2) from solo practice and freestanding hospitals to medical homes, accountable care organizations, large hospital systems, and organized clinics like Kaiser Permanente. METHODS: We evaluate whether this transformation is happening quickly, shifting risk to providers, lowering costs, and improving quality. We draw on recent evidence on provider payment and organization and their effects on cost and quality. FINDINGS: Data suggest a low prevalence of provider risk payment models and slow movement toward new payment and organizational models. Evidence suggests the impact of both on cost and quality is weak. CONCLUSIONS: We need to be patient in expecting system improvements from ongoing changes in provider payment and organization. We also may need to look for improvements in other areas of the economy or to accept and accommodate prospects of modest improvements over time.

An Overview of Value, Perspective, and Decision Context-A Health Economics Approach: An ISPOR Special Task Force Report [2].

The second section of our Special Task Force builds on the discussion of value and perspective in the previous article of the report by 1) defining a health economics approach to the concept of value in health care systems; 2) discussing the relationship of value to perspective and decision context, that is, how recently proposed value frameworks vary by the types of decisions being made and by the stakeholders involved; 3) describing the patient perspective on value because the patient is a key stakeholder, but one also wearing the hat of a health insurance purchaser; and 4) discussing how value is relevant in the market-based US system of mixed private and public insurance, and differs from its use in single-payer systems. The five recent value frameworks that motivated this report vary in the types of decisions they intend to inform, ranging from coverage, access, and pricing decisions to those defining appropriate clinical pathways and to supporting provider-clinician shared decision making. Each of these value frameworks must be evaluated in its own decision context for its own objectives. Existing guidelines for cost-effectiveness analysis emphasize the importance of clearly specifying the perspective from which the analysis is undertaken. Relevant perspectives may include, among others, 1) the health plan enrollee, 2) the patient, 3) the health plan manager, 4) the provider, 5) the technology manufacturer, 6) the specialty society, 7) government regulators, or 8) society as a whole. A valid and informative cost-effectiveness analysis could be conducted from the perspective of any of these stakeholders, depending on the decision context.

Objectives, Budgets, Thresholds, and Opportunity Costs-A Health Economics Approach: An ISPOR Special Task Force Report [4].

The fourth section of our Special Task Force report focuses on a health plan or payer's technology adoption or reimbursement decision, given the array of technologies, on the basis of their different values and costs. We discuss the role of budgets, thresholds, opportunity costs, and affordability in making decisions. First, we discuss the use of budgets and thresholds in private and public health plans, their interdependence, and connection to opportunity cost. Essentially, each payer should adopt a decision rule about what is good value for money given their budget; consistent use of a cost-per-quality-adjusted life-year threshold will ensure the maximum health gain for the budget. In the United States, different public and private insurance programs could use different thresholds, reflecting the differing generosity of their budgets and implying different levels of access to technologies. In addition, different insurance plans could consider different additional elements to the quality-adjusted life-year metric discussed elsewhere in our Special Task Force report. We then define affordability and discuss approaches to deal with it, including consideration of disinvestment and related adjustment costs, the impact of delaying new technologies, and comparative cost effectiveness of technologies. Over time, the availability of new technologies may increase the amount that populations want to spend on health care. We then discuss potential modifiers to thresholds, including uncertainty about the evidence used in the decision-making process. This article concludes by discussing the application of these concepts in the context of the pluralistic US health care system, as well as the "excess burden" of tax-financed public programs versus private programs.

A Health Economics Approach to US Value Assessment Frameworks-Summary and Recommendations of the ISPOR Special Task Force Report [7].

This summary section first lists key points from each of the six sections of the report, followed by six key recommendations. The Special Task Force chose to take a health economics approach to the question of whether a health plan should cover and reimburse a specific technology, beginning with the view that the conventional cost-per-quality-adjusted life-year metric has both strengths as a starting point and recognized limitations. This report calls for the development of a more comprehensive economic evaluation that could include novel elements of value (e.g., insurance value and equity) as part of either an "augmented" cost-effectiveness analysis or a multicriteria decision analysis. Given an aggregation of elements to a measure of value, consistent use of a cost-effectiveness threshold can help ensure the maximization of health gain and well-being for a given budget. These decisions can benefit from the use of deliberative processes. The six recommendations are to: 1) be explicit about decision context and perspective in value assessment frameworks; 2) base health plan coverage and reimbursement decisions on an evaluation of the incremental costs and benefits of health care technologies as is provided by cost-effectiveness analysis; 3) develop value thresholds to serve as one important input to help guide coverage and reimbursement decisions; 4) manage budget constraints and affordability on the basis of cost-effectiveness principles; 5) test and consider using structured deliberative processes for health plan coverage and reimbursement decisions; and 6) explore and test novel elements of benefit to improve value measures that reflect the perspectives of both plan members and patients.