Joseph P. Newhouse is the principal investigator on this project. Vanessa Azzone is the project contact: 617-432-2981.

The Role of Private Plans in Medicare, funded by the National Institute on Aging, is undertaking an examination of the underpinnings of Medicare Advantage from a framework grounded in economic theory. The study consists of five projects plus an administrative core and a data and measures core.

The overarching purpose of this project is to improve the design of the Medicare Advantage program and to advance the economic, clinical, and policy literatures relating to the regulation, payment, and performance of health plans. An innovative and cost-effective Medicare Advantage program is essential for US health policy. This program has a direct effect on Medicare beneficiaries through their health insurance choices and indirect effects on the entire US health care system. With the Medicare Modernization Act of 2003, the emergence of new data sources, and evolving ideas in economics about consumer behavior and industrial organization, now is an important time to establish a new standard of empirical and theoretical research on Medicare Advantage. A redesigned Medicare Advantage program could enable Medicare to become a leader in health care reform, with major benefits for the elderly, the federal government, and the US health care system.

This project is done in collaboration with Kaiser Permanente of Northern California and the National Committee for Quality Assurance. Additional co-investigators or consultants on this project are Nolan Miller (University of Illinois), Eric Schneider (RAND), Bob Town (University of Minnesota) and Jacob Glazer (Boston University).

For more information, see the project summaries below:

The Role of Private Plans in Medicare - Specific Aims of the Cores and Projects

Administrative Core – Joseph P. Newhouse, PhD, Principal Investigator, Thomas G. McGuire, PhD, Associate Director, Vanessa Azzone, PhD, Project Manager

The mission of the Administrative Core (AC) is to maximize the project leaders’ focus on scientific work while providing a structure for ongoing evaluation and critique of the program's project. The AC will accomplish this through the pursuit of two specific aims. The first aim is to coordinate and continually evaluate the oversight and support provided by the Core for the benefit of the project.  The second aim is to charter and organize the two main scientific oversight groups built into the project leadership structure: the Steering Committee and the Scientific Advisory Board.

Data and Measures Core –John Z. Ayanian, MD, MPP, Principal Investigator

The Data & Measures Core will provide the personnel, expertise, and computational resources needed for effective utilization of the data to be acquired and analyzed by the investigators in the Program Project. This Core involves three main components. First, the Core will be responsible for all data management and oversight activities including dataset acquisition, preparation, integration, management, quality control, security and archiving. Second, the Core will offer and coordinate clinical expertise in measurement, specification of key analytic variables, and interpretation across the projects.  Almost all aims in the projects involve some clinical or health data. The explicit clinical linkage will help ensure cross-project learning about fruitful approaches and maximize consistency in approaches across projects. Third, the Core will offer and coordinate expertise on statistical model building and other data analysis methods across projects.  A coordinated approach is particularly important given the common data elements and interrelated research questions. The Data & Measures Core is staffed by senior researchers with extensive experience with the data and methods involved in the component projects. The Core’s primary function will be an integrative one. This Core has the following specific aims:

Aim 1: Acquire necessary data and create, integrate, and manage data for projects. The Core is responsible for preparing data use applications and obtaining and preparing the following major datasets to be used in one or more P01 projects: Medicare Denominator file; Medicare Part A and Part B claims for traditional Medicare (TM) enrollees, Healthcare Effectiveness Data and Information Set (HEDIS®) measures of quality and utilization for Medicare Advantage (MA) plans; Consumer Assessment of Health Plans Survey (CAHPS) measures of patient experiences for both MA and TM enrollees; Health and Retirement Study (HRS) including restricted geographic identifiers and linked Medicare claims; Medicare Current Beneficiary Survey (MCBS); Medical Expenditure Panel Survey (MEPS); Community Tracking Survey (CTS) contextual information; area level information from the Area Resource File (ARF) and the US Census; and the Nationwide Inpatient Sample (NIS) and State Inpatient Datasets (SID) from the Healthcare Cost and Utilization Project (HCUP). The Core will monitor the progress of assembling these key datasets, assist in the analysis, and advise each project on data use and quality issues. The Core will construct program-wide datasets in a common format on a regular basis, along with related documentation and other tools to facilitate data use among the research projects. These activities will promote integration of information across projects and efficient use of large datasets. 

Aim 2: Coordinate and provide expert clinical input to all projects. Senior clinical health services researchers will advise research project leaders on the specification of clinical and health status measures across the wide range of datasets to be employed in the program project.  Expertise will be provided related to the use of diagnostic and procedure codes and functional status data for risk adjustment in all projects, specification of clinical quality and utilization measures in Medicare claims data, and the specification of clinically relevant subgroups of Medicare enrollees with specific health conditions.

Aim 3: Coordinate and provide expert statistical input to all projects.  Statisticians from the Core will advise project leaders on both standard and innovative analytic techniques relevant to Medicare and managed care data. Core statisticians will provide expertise in the creation of composite quality measures, hierarchical modeling and causal inference. A key focus of this effort will be to direct empirical analyses and methodologic development related to creating composite quality scores based on HEDIS and CAHPS data for both MA and TM patients. The Core statisticians also have extensive experience in developing geographically based hierarchical models that will be crucial to the appropriate analyses of these complex datasets.

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Project 1 – Beneficiary Choice and Medicare Advantage - Richard G. Frank,PhD, Principal Investigator

Consumers must choose health insurance effectively if Medicare Advantage (MA) is to succeed. MA is premised on the assumption that offering beneficiaries a broad choice of health plans promotes both beneficiary and social welfare. The Congress, in the Balanced Budget Act (BBA) of 1997 and more recently in the Medicare Modernization Act (MMA) of 2003, expanded the types of plans that could participate in MA and raised payment rates dramatically. In response, plans entered and in many regions of the country beneficiaries can now choose from among more than 20 plans. We know little, however, about how beneficiaries choose among the menu of plans, whether beneficiary choices effect good matches, or whether the policy of maximizing the range of choices serves beneficiaries or the Medicare program.

Aim 1: To use Medicare administrative data to examine the impact of plan attributes (e.g. extent of network), market conditions (e.g., presence of a Part D choice) and personal characteristics (e.g. provider attachment) on a Medicare beneficiary’s decision to enroll in MA.  Test the effect of the number and diversity of choices on the decision to enroll in MA.

Aim 2: Conditional on joining MA, use Medicare administrative data to examine the impact of plan attributes, market conditions, and personal characteristics on a beneficiary’s choice of a specific type of MA plan (HMO, PPO, and Private Fee for Service [PFFS]) and a specific plan. Use the choice between PFFS and TM in “floor counties” to examine which beneficiaries tend to forgo choosing “dominant” health plans.

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Project 2 – Health Plan Responses to Changes in Medicare Advantage Payment Rates – Michael E. Chernew, PhD, Principal Investigator

The Medicare Advantage (MA) program reflects the belief that a system of private, integrated health plans will expand the diversity of plan offerings, an objective valued by many, and result in more generous benefits, lower premiums, and higher quality of care than the traditional Medicare (TM) program. Payment rates for MA plans are a primary tool used to influence these outcomes and are an important topic of debate. 

In regulated markets the price set by the government significantly affects market outcomes. In the presence of regulated prices, firms compete through improved quality or entry, driving at least the marginal firm’s average cost to the administered price. In MA, the firms are insurers, and the relevant payment variable for policy makers is the “benchmark” payment rate set by Medicare.  Medicare policy is premised on a competitive response to benchmark rates. The generosity of payment may affect the number and type of plans that participate in the MA program, the set of benefits they offer, and perhaps the quality of care delivered. Distinct from other price regulated industries, however, MA plans can charge Medicare beneficiaries a price (premium) above the premium set by the government. Thus, in addition to competing by offering more generous benefits or better quality, plans can also compete by lowering this premium.  Plan decisions about premiums, benefits and quality will, in turn, influence the number of Medicare beneficiaries that enroll in MA plans and their economic and perhaps their health outcomes. 

This project will examine the impact of Medicare payment policy on plan behavior in the environment after the Medicare Modernization Act (MMA) of 2003. We will focus on the benchmark payment rates Medicare assigns to each county. These payment rates define the level of reimbursement a plan receives from the government for a beneficiary of average risk in each county. Medicare has frequently changed the rules governing how these benchmark payment rates are set and continues to do so. 

The MMA restructured the policy environment for MA plans, rendering past research of questionable relevance to this new setting. Specifically, the MMA expanded the number of plan options, altered the payment rates, and changed the algorithms for setting those rates. It expanded the standard benefit package to include prescription drugs, which may alter the way MA plans respond to payment changes. Furthermore, the overall rates are simply higher than in the past, which may change the nature of competition with TM or with other MA plans. Our research is intended to contribute to the general understanding of the effect of payment policy in health care, as well as, more directly, to quantify the effects of Medicare payment rates on the number and attributes of MA plans, particularly supplemental benefits and quality. 

The specific Aims of the project are to:

Aim 1:  Assess how benchmark payment rates affect insurer participation, plans offered, and enrollment in the MA program.

Aim 2:  Assess how benchmark payment rates affect the benefits offered by MA plans.

Aim 3:  Assess how benchmark payment rates affect MA plan performance on standard quality measures.

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Project 3 – Integration of Care and Selection: Medicare Advantage Compared with Traditional Medicare – Joseph P. Newhouse, PhD, Principal Investigator

Relative to traditional Medicare (TM), clinically integrated health plans that participate in Medicare Advantage (MA) may be able to treat a given patient more efficiently, using fewer resources and delivering care of equal or superior quality, through their flexibility in benefit structure, network contracting, and ability to coordinate and manage care. These very features of clinical integration, however, may differentially appeal to beneficiaries with different types of health risks, creating potential incentives on the part of both beneficiaries and plans for selection. For example, the efficiencies from integration may not be uniform across diseases, and therefore plans may be able to achieve more savings for some conditions than others.

The heterogeneity in beneficiary preferences for the various instruments of integration and the heterogeneity across diseases in opportunities for integration efficiencies would not matter if risk adjustment balanced incentives across diseases. But because the current Medicare risk adjustment algorithms are based on both the administered prices and the practice patterns of TM in treating a given disease, the resulting relative prices may depart from MA relative costs. Conditions that are amenable to greater cost savings from integration may be relatively more profitable for MA plans, generating incentives for MA plans to try to attract enrollees with these conditions by engaging in selection behavior. Importantly from an economics perspective, plans attempting to influence enrollment patterns may distort their delivery of services to attract profitable beneficiaries, thereby not making full use of integration possibilities and making the delivery of care inefficient.  For example, if the risk adjustment scheme fails to give patients with a given disease sufficient weight, plans may try to exclude providers with a strong reputation for treating that disease from their network. Thus, integration and selection are intimately intertwined.

This project estimates the size of integration efficiencies and the effects of Medicare reimbursement policy on both integration efficiencies and on selection. Its specific Aims are:

Aim 1:  Assess the value of clinical integration in MA plans by comparing the quality and intensity of care for MA and TM enrollees. This will be done using measures from the Healthcare Effectiveness Data and Information Set (HEDIS®) measures of MA quality of care and resource use, corresponding measures to be developed from Part B claims data for TM enrollees, and MA and TM enrollees’ reports of quality of care in the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey.

Aim 2:  Assess the predictive accuracy and explained variance of current risk adjustment methods using individual-level MA plan data from Kaiser Permanente of Northern California (KP-NC). Currently, Medicare’s risk adjustment is calibrated with TM data. Since TM may have significantly different patterns of care than MA plans, plans may have corresponding incentives to favor or disfavor enrollees with certain diagnoses.

Aim 3:  Measure selection using data from MA rather than TM. Specifically, estimate any changes in the amount of selection (favorable or unfavorable) into KP-NC from 1998-2011 as risk adjustment that used diagnostic information was phased in starting in 2000 and as lock-in periods changed starting in 2006.  Using results from Aim 2, determine if flows into and out of KP-NC are related to pricing errors from using TM data to calibrate risk adjustment.

Aim 4:  Apply the results from Aim 2 to evaluate whether incentives for selection and integration lead to differences in drug plan design between MA-Part D plans (MA-PD) and standalone Part D drug plans (PDPs).

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Project 4 – The Spillover Effects of Medicare Advantage – Katherine Baicker, PhD, Principal Investigator

The Medicare program consists of two distinct components: (1) traditional Medicare (TM), a government-administered fee-for-service insurance plan with a legislatively-defined benefit structure, administered prices, and few utilization controls; and (2) Medicare Advantage (MA), a program of competing private health plans that may offer varying levels of benefits and utilize various cost-containment and quality-improvement strategies. The MA program gives beneficiaries choice of health insurance plans. It was hoped that this private competition would result in more efficient plans that provided Medicare beneficiaries with higher-quality, higher-value care. 

Because the same health care providers generally serve both MA and TM patients, changes in care induced by the MA program may “spill over” to care delivered to TM enrollees – and, indeed, to all patients. The ramifications of MA incentives may thus be felt throughout the health care system if, for example, they affect standards of care or hospital investment. Previous research in other contexts, such as the spread of commercial managed care plans in the 1990s, suggests that these spillovers may be substantial, but there is little research as yet on spillovers from MA plans. Any spillover effects of MA plans to others’ spending or outcomes have direct implications for designing an efficient MA program. Gauging the magnitude of such spillovers and establishing causal connections requires careful empirical research to isolate causal pathways. Other components of this project address the enrollment decisions of Medicare beneficiaries (Project 1), MA plan responses to changes in MA payment rates (Project 2), and the role of integration and risk selection in MA (Project 3).  This project examines the effect of changes in the MA sector induced by MA payment changes on the care received by other patients via three specific Aims:

Aim 1:  Examine the effect of changes in MA penetration on spending and patterns of utilization by beneficiaries in TM and by the privately insured.  This Aim will test the hypotheses that increased MA penetration leads to a decrease in total spending by TM and commercial enrollees and a convergence of utilization patterns between MA enrollees and TM and commercial enrollees.  We will evaluate various components of spending including inpatient and outpatient utilization for specific conditions and utilization of particularly intensive services.

Aim 2:  Evaluate whether MA penetration and utilization patterns affect the quality of care received by TM beneficiaries and other patients within the hospital setting. This Aim will test the hypothesis that greater MA penetration is associated with higher-quality care for other patients within hospitals. Greater MA penetration may promote higher-quality care hospital-wide, but other provider reactions are possible, including cost-shifting among patients that would dampen the social benefits of MA penetration. The quality metrics that will be evaluated include both process, such as use of best practices, and outcomes, such as in-hospital mortality.

Aim 3: Investigate the effect of changes in MA penetration and plan characteristics on quality and health outcomes of TM beneficiaries and other insured populations beyond the hospital setting. This Aim will test the hypothesis that greater MA penetration leads to diffusion of high-quality care throughout the community, both through spillovers between hospitals and through improvements to ambulatory care. Evaluating the effect of MA enrollment on broader measures of care received in the area, including quality of outpatient care and longer-run mortality, will capture other potential spillover mechanisms from those identified in Aims 1 and 2.

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Project 5 – Improving the Design of Medicare Advantage – Thomas G. McGuire, PhD, Principal Investigator

This project applies methodologies from the “mechanism design” literature, broadly construed, to policy decision for Medicare Advantage (MA). Medicare decides about the level of plan payment, regulation of the form of plans, benefits plans must provide, premiums that can be charged, conditions of plan entry and bidding, rules for beneficiary enrollment, and mandatory reports on quality and consumer satisfaction, among other policies. These choices affect overall Medicare costs and beneficiary welfare. Medicare may also impose spillover effects on the entire U.S. health care system.  Rigorous analysis of Medicare policy choices can improve our scientific understanding of the effects of these policies, and ultimately lead to policy improvements. Mechanism design analysis is powerful and flexible, capable of working with nonstandard objective functions (e.g., including outcomes other than profits in the objective function), as well as with a range of market structures and information imperfections.  The mechanism design methodology has guided the design of health insurance coverage and health care payment policies.  The specific Aims of this project are:

Aim 1: Study whether and how Medicare should play a more active role in regulating entry, determining the number of MA plans that will function in a market, and establishing the degree and dimensions of competition among these plans. Taking the perspective from industrial organization that Medicare is in a vertical relationship with MA plans, we will draw analogies from concepts of Entry Management, Exclusive Territories, Retail Price Maintenance and Option Contracts to derive implications for Medicare regulatory policy. We expect to study regulatory policies for Medicare that rely not only on verifiable characteristics of plans, but also on their observable (but not verifiable) characteristics.

Aim 2: Characterize the optimal payment to private plans in Medicare, including issues related to setting the premium paid by beneficiaries, the level of the benchmark payment, and risk adjustment of the benchmark payment.  Characterize the combination of policies that have the potential to maximize social welfare, giving varying weights to total program costs. This analysis will incorporate consideration of efficiencies from integration in MA plans possible and possible spillovers from MA plans to traditional Medicare (TM) and private payers.

Aim 3: Study the potential for quality reporting to improve outcomes, including the positive and negative effects of commonly used quality reporting mechanisms, such as the Global Weighted Report and the Binary Report, on plans’ incentives to provide the socially efficient quality of care. Incorporate the goal of sorting beneficiaries efficiently among MA plans and TM, and analyze the tradeoff between efficient incentives to plans and information enable beneficiary choice. Compare and rank widely used quality reporting mechanisms. Derive implications for the optimal design of quality reports in the MA market.