The Implications of Regional Variations in Medicare Spending. Part 1: The Content, Quality, and Accessibility of Care

Context Per capita Medicare spending varies considerably from region to region. The effect of greater Medicare spending on quality of care and access is not known. Contribution Using end-of-life care spending as an indicator of Medicare spending, the researchers categorized geographic regions into five quintiles of spending and examined costs and outcomes of care for hip fracture, colorectal cancer, and acute myocardial infarction. Residents of high-spending regions received 60% more care but did not have better quality or outcomes of care. Implications Medicare beneficiaries who live in higher Medicare spending regions do not necessarily get better-quality care than those in lower-spending regions. The Editors Health care spending in the United States is expected to increase dramatically in this decade. By 2011, per capita spending is forecast to increase by 49% in real terms, reaching $9216 per capita or 17% of the gross domestic product (1). The likely consequences of such dramatic growth in health care costs include further increases in the numbers of uninsured persons and reduced public and private spending in other sectors of the economy. Spending growth, however, is seen as an inexorable consequence of the aging of the population and advancing technology (2, 3). Moreover, the effectiveness of specific interventions in cardiovascular disease, neonatal care, and cancer treatment has been used to argue that the overall gains from increased spending are worth the costs (3) and that any constraints on the expansion of the specialist workforce or on further spending growth could be harmful (2-4). These forecasts and the policy prescriptions that depend on them do not take into account the dramatic regional variations in spending and medical practice observed across the United States (5-8). For example, age-, sex-, and race-adjusted spending for traditional (fee-for-service) Medicare in 1996 was $8414 per enrollee in the Miami, Florida, region compared with $3341 in the Minneapolis, Minnesota, region (9). The greater-than-twofold differences observed across U.S. regions are not due to differences in the prices of medical services (7, 10) or to apparent differences in average levels of illness or socioeconomic status (10-12). Rather, they are due to the overall quantity of medical services provided and the relative predominance of internists and medical subspecialists in high-cost regions (2, 13). The implications for health and health care of these regional differences in resources and spending, although directly relevant to current policy debates, remain relatively unexplored (14). The financial implications are clear: Savings of up to 30% of Medicare spending might be possible, and the Medicare Trust Fund would remain solvent into the indefinite future (10). However, remarkably little is known about whether the increased spending in high-cost regions results in better care or improved health. Although recent studies have found no improvement in mortality (12, 15, 16), they have been criticized because of weak designs (most were cross-sectional and ecologic), inadequate individual-level measures to control for potential differences in case mix, insufficient clinical detail on the process of care to allow inferences on potential causal pathways to be drawn, and limited outcome measures. We designed a research project to address these concerns. We present our findings in two articles. This article, Part 1, provides an overview of the study design and addresses the question, What are the differences in the content, quality, and accessibility of care across U.S. regions that differ in per capita Medicare spending? The second article, Part 2, asks, Do regions with higher Medicare spending achieve better health outcomes and improved patient satisfaction? Methods Design Overview One approach to determining whether the increased spending in some U.S. regions leads to better care and better outcomes would be to conduct a randomized trial. This would ensure that assignment to the treatment and control groups (those receiving more and less spending) was independent of patient characteristics. Logistic barriers to such a trial, however, would be substantial. We therefore conducted a cohort study in four parallel cohorts using a natural randomization approach (17), in which one or more exposure variables allowed assignment of patients into treatment groups (different levels of average spending), as would a randomized trial. An overview of the design is provided in Figure 1. Figure 1. Overview of study design. Because some of the regional differences in Medicare spending are due to differences in illness levels (enrollees in Louisiana are sicker than those in Colorado) and price (Medicare pays more for the same service in New York than in Iowa), we could not use Medicare spending itself as the exposure. We therefore assigned U.S. hospital referral regions (HRRs), and thus the cohort members residing within them, to different exposure levels. We did this by using the End-of-Life Expenditure Index (EOL-EI), a measure reflecting the component of regional variation in Medicare spending that is due to physician practice rather than regional differences in illness or price. Because regional differences in end-of-life spending are unrelated to underlying illness levels, it is reasonable to consider residence in HRRs with different end-of-life spending as a random event. The index was calculated as standardized spending on hospital and physician services provided to a reference cohort distinct from the study cohorts: Medicare enrollees in their last 6 months of life. We confirmed that the exposure used to assign the HRRs achieved the goals of natural randomization: 1) Study samples assigned to different levels of the exposure [the EOL-EI] were similar in baseline health status, and 2) the actual quantity of services delivered to the individuals within the study samples nevertheless differed substantially across exposure levels and was highly correlated with average per capita Medicare spending in the HRRs. We then followed the cohort members for up to 5 years after study enrollment and compared the processes of care (Part 1) and health outcomes (Part 2) across HRRs assigned to different exposure levels. Study Cohorts We sought study samples that would be similarly ill across regions based on the occurrence of an incident illness (acute myocardial infarction [MI], hip fracture, colorectal cancer) or in which we had excellent data for case-mix adjustment (acute MI, Medicare Current Beneficiary Survey [MCBS] sample). We restricted the eligible population to Medicare enrollees between the ages of 65 and 99 years who, at the time of study enrollment, were eligible for both Medicare Parts A and B and were not enrolled in a Medicare health maintenance organization (HMO). The acute MI cohort was drawn from patients included in the Cooperative Cardiovascular Project, which identified from billing records a national sample of Medicare beneficiaries who were discharged after acute MI between February 1994 and November 1995 (18). We excluded patients with an unconfirmed acute MI (with the same criteria as in previous studies [19]) and included only the first episode of acute MI for a given patient. The hip fracture and colorectal cancer cohorts were selected based on a first admission between 1993 and 1995 for a primary diagnosis of hip fracture or colorectal cancer with resection, using the same International Classification of Diseases, Ninth Revision, Clinical Modification codes as in earlier work (20). Hospitalization rates for acute MI, hip fracture, and colorectal cancer vary little across regions (21), and patients with incident cases of these conditions are likely to be similarly ill in different communities (20). We excluded patients with a previous hospitalization for the same diagnosis in the year before their index stay. The general population cohort was drawn from the access-to- care component of the MCBS, a continuous panel survey that is representative of the Medicare population (22). Our inclusion criteria are detailed in the Appendix. Baseline Characteristics of the Study Cohorts Trained abstractors working in the Cooperative Cardiovascular Project obtained characteristics of patients in the acute MI cohort from the medical record (18). Quality of the chart review process was monitored by random reabstractions, and percentage agreement was generally very high (93.3% to 94.8%) (23). Missing data for clinical variables were handled by including a specific categorical variable for patients with each missing variable (for example, admission blood pressure missing). Income was defined based on ZIP code of residence by using 1990 U.S. Census data. For the hip fracture and colorectal cancer cohorts, we coded the presence of specific comorbid conditions based on diagnoses recorded on the discharge abstract, as was done in previous work (24, 25). Cancer stage was classified as distant versus local or regional because this classification has been found to correspond most closely to reported stage, according to analyses of linked MedicareSurveillance, Epidemiology, and End Results data (26). Data from the 1990 U.S. Census, measured at the level of the ZIP code, were used to provide measures of income, education, disability status, urban or rural residence, employment, marital status, and Hispanic origin. For all three chronic disease cohorts, we used American Hospital Association data to characterize the hospital teaching status (27) and the Medicare claims files of patients' index hospitals to determine the volume of cases of hip fracture, colorectal cancer, and acute MI treated per year. Data collection and preparation procedures for the MCBS are described elsewhere (22). Because not all respondents completed all survey items, analyses of utilization, access to care, satisfaction, and survival are based on slightly different numbers o