What Do We Know About Health Care Access and Quality in Medicare Advantage Versus the Traditional Medicare Program?


This study seeks to fill the gap in available information on current evidence comparing quality and access in Medicare Advantage plans and traditional Medicare. Unlike earlier literature reviews, the focus of this paper is on Medicare, and limited to studies that are relatively current; that is, published between 2000 and early 2014.

Study Sources and Inclusion Criteria

We identified the initial list of studies using a Google Scholar search for articles on “Medicare Advantage/Medicare HMOs” published since 2000. We reviewed titles and abstracts to identify studies focusing on access/quality metrics and including a design that had some comparison group—typically traditional Medicare, or what some still refer to as Medicare fee-for-service (FFS). Because Google Scholar does not index the most recent year’s publications and is a less established search source, we also contracted with a trained health research librarian to conduct a formal Medline search covering the period 2000−2014.1 That search used the terms “Medicare health plans,” “Medicare HMO,” “Medicare Advantage,” and “Medicare Advantage PPO” in comparison to “FFS Medicare,” “Medicare,” and “traditional Medicare,” with the keywords “quality of care,” “access,” and “outcomes”.2 To ensure coverage of studies that may be relevant to the policy debate but are not found in the academic literature, we also reviewed the sources cited in industry briefs and the most recent Medicare Payment Advisory Commission (MedPAC) report to Congress on Medicare Advantage.3 In addition, we checked citations in those studies identified for any other relevant studies not already identified.4

To be included in the review, studies had to include (1) a written description of methods and data sources, (2) a formal comparison group, and (3) outcome measures relevant to access or quality. Although we did not otherwise exclude studies based on the quality of their methods, we reviewed articles for how they handled such potentially confounding factors as geographic location, enrollee mix, and health and risk factors associated with selection. Because our analysis focused on Medicare health plans available for general enrollment, we excluded studies focused on specialized plans—particularly social HMOs, PACE, and Special Needs Plans (SNPs).

Relevant Metrics of Interest

Health care quality problems can arise though underuse, overuse, and misuse of services.5 Some of these domains are better captured in existing quality metrics than others.6 Because the review was focused on access and quality of health care received by beneficiaries in different types of insurance arrangements, rather than insurance per se, studies focused primarily on benefits or the factors that influence health plan selection were not considered. Five categories of metrics are considered in this paper.

HEDIS Effectiveness of Care Metrics.

HEDIS measures, which Medicare health plans report to the Centers for Medicare and Medicaid Services (CMS), are central to oversight in Medicare Advantage. In 2014, Medicare Advantage plans were required to submit audited data consistent with National Committee for Quality Assurance (NCQA) specifications for 25 metrics on health care effectiveness and another three on access and availability of services, among other metrics.7 HEDIS effectiveness indicators focus on the processes of care or intermediate outcomes rather than ultimate outcomes; metrics relevant to those with chronic illness are limited, though efforts are underway to broaden the measure set. Patient-level data used to support these metrics come from claims, encounter data, and for some metrics, medical records. A subset of these metrics is used to support calculation of Medicare Advantage plan star quality ratings, the basis for bonus payments to plans. Increasing efforts have been made to align reporting requirements across Medicare Advantage plans of different types, but data historically have been most available for HMOs and least available for private FFS plans and regional PPOs.8 HEDIS metrics are not routinely calculated for traditional Medicare. MedPAC is considering better ways to align requirements and metrics across programs, taking into account the differences in data sources used in each sector.9

CAHPS™ Quality Metrics.

CAHPS is a health plan member survey that provides patient reports of care experiences with their plan, including ratings of access to care and satisfaction with the plan and its providers.10 To support its use, CMS conducted a related survey of beneficiaries in traditional Medicare residing in those same geographical areas (in 2011, it replaced this survey with a requirement that freestanding prescription drug plans collect CAHPS data). Using its contractors, CMS has developed a number of composite measures of reported care and use of preventive services, as well as global health ratings. Some of the same items are included in standard national surveys, such as the Medicare Current Beneficiary Survey (MCBS) and the National Health Interview Survey (NHIS). Because they provide insight into how beneficiaries view care, beneficiary surveys long have been a central component of most efforts to examine access and quality of care in Medicare.

Quality Metrics around Hospitalizations.

From a quality and value perspective, metrics that provide information on the appropriateness and quality of hospital care are of growing interest. Key metrics in this area focus on the appropriateness of hospital admissions that potentially could be avoided by more timely and appropriate primary care, the appropriateness and quality of facilities and professional services used, and the ability to structure discharges in ways that avoid personally and financially costly complications and hospital readmissions. CMS now captures data on case-mix adjusted Medicare rehospitalization rates as part of HEDIS reporting from health plans. In the absence of national data, most research on this topic has used data available through all-payer discharge data sets available in selected states and from the Agency for Healthcare Research and Quality’s (AHRQ’s) databases. Only some of these files have appropriate identifiers to distinguish enrollment in Medicare health plans, and the timeliness of information often lags. While adjusting for case mix and severity is important in all comparisons of quality, it is particularly important in studies of hospital appropriateness or outcomes, when poor outcomes may be small in number and highly sensitive to the mix of enrollees.

Other Utilization Metrics.

Given the limitations in available data that directly measure access and quality of health services for beneficiaries in Medicare Advantage and traditional Medicare, researchers have included various other measures of utilization as a proxy for direct measures of these aspects of care. Like the hospital utilization measures, some of these metrics target specific kinds of utilization that have been used as markers for overuse, underuse, or misuse of services, including emergency department (ED) visits, patterns of care at the end of life, procedure use for urgent versus non-urgent conditions, or high-cost procedures versus others. Medicare Advantage plans report on some of these metrics in the Utilization and Relative Resource Use section of the HEDIS performance monitoring submission form. Utilization-based measures can be difficult to interpret as quality metrics when norms defining appropriateness are lacking or in dispute, and when it is unclear what constitutes overuse or underuse and whether overuse or underuse are markers for better or worse care. Such measures also require careful risk adjustment for selection. Studies that use aggregate measures of utilization probably are better interpreted as indications of resource use rather than quality of care.

Health Care Outcomes and Mortality.

Ultimately, the goal of medical care is to improve patient outcomes and quality of life. Data sets available for studies of this type are limited and those that exist do not always include good information on health insurance type or adequate data to link with other sources containing such data. There are also methodological challenges in adjusting for patient selection and mix adequately. Cancer studies are supported by cancer registry data maintained by states and the National Cancer Institute’s Surveillance and Epidemiology and End Results (SEER) data, among others.


Introduction Findings

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