Comparison of self-reported and Medicare claims-identified acute myocardial infarction.

BACKGROUND: Cardiovascular disease is often studied through patient self-report and administrative data. However, these 2 sources provide different information, and few studies have compared them. METHODS AND RESULTS: We compared data from a longitudinal, nationally representative survey of older Americans with matched Medicare claims. Self-reported heart attack in the previous 2 years was compared with claims-identified acute myocardial infarction (AMI) and acute coronary syndrome. Among the 3.1% of respondents with self-reported heart attack, 32.8% had claims-identified AMI, 16.5% had non-AMI acute coronary syndrome, and 25.8% had other cardiac claims; 17.3% had no inpatient visits in the previous 2.5 years. Claims-identified AMIs were found in 1.4% of respondents; of these, 67.8% reported a heart attack. Self-reports were less likely among respondents >75 years of age (62.7% versus 74.6%; P=0.006), with less than high school education (61.6% versus 71.4%; P=0.015), with at least 1 limitation in activities of daily living (59.6% versus 74.7%; P=0.001), or below the 25th percentile of a word recall memory test (60.7% versus 71.3%; P=0.019). Both self-reported and claims-identified cardiac events were associated with increased mortality; the highest mortality was observed among those with claims-identified AMI who did not self-report (odds ratio, 2.8; 95% confidence interval, 1.5-5.1) and among those with self-reported heart attack and claims-identified AMI (odds ratio, 2.5; 95% confidence interval, 1.7-3.6) or non-AMI acute coronary syndrome (odds ratio, 2.7; 95% confidence interval, 1.8-4.1). CONCLUSIONS: There is considerable disagreement between self-reported and claims-identified events. Although self-reported heart attack may be inaccurate, it indicates increased risk of death, regardless of whether the self-report is confirmed by Medicare claims.

Association between physician supply, local practice norms, and outpatient visit rates.

BACKGROUND: There is considerable regional variation in Medicare outpatient visit rates; such variations may be the consequence of patient health, race/ethnicity differences, patient preferences, or physician supply and beliefs about the efficacy of frequently scheduled visits. OBJECTIVE: The objective of the study was to test associations between varying regional Medicare outpatient visit rates and beneficiaries' health, race/ethnicity, preferences, and physician practice norms and supply. METHODS: We used Medicare claims from 2006 and 2007 and data from national surveys of 3 different groups in 2005-Medicare beneficiaries, cardiologists, and primary care physicians. Regression analysis tested explanations for outpatient visit rates: patient health (self-reported and hierarchical condition category score), self-reported race/ethnicity, preferences for care, and local physician practice norms and supply in beneficiaries' Hospital Referral Regions (HRRs) of residence. RESULTS: Beneficiaries in the highest quintile of the hierarchical condition category scores experienced 4.99 more visits than those in the lowest. Beneficiaries who were black experienced 2.14 fewer visits than others with similar health and preferences. Higher care-seeking preferences were marginally significantly associated with more visits, whereas education and poverty were insignificant. HRRs with high physician supply and high-frequency practice norms were associated with 2.04 additional visits per year, whereas HRRs with high supply but low-frequency norms were associated with 1.45 additional visits. Adjusting for all individual beneficiary covariates explained <20% of the original associations between visit rates and physician supply and practice norms. CONCLUSIONS: Medicare beneficiaries' health status, race, and preferences help explain individual office visit frequency; in particular, African-American patients appear to experience lower access to care. Yet, these factors explain a small fraction of the observed regional differences associated with physician supply and beliefs about the appropriate frequency of office visits.

Cardiac intervention rates for older patients with acute myocardial infarction in the United States and Ontario, 2003-2013: a retrospective cohort study.

BACKGROUND: Previous work showed lower cardiac intervention rates for patients with acute myocardial infarction (AMI) in Ontario than in the United States. We assessed whether Ontario's efforts to improve access to rapid percutaneous coronary intervention (PCI) for AMI were associated with improved timeliness of care and whether this closed the gap between the 2 jurisdictions. METHODS: In this retrospective cohort study, we followed adults aged 66-99 years in the US and Ontario for 30 days after admission for incident AMI between 2003 and 2013 using health administrative data from both countries. We calculated the proportion of patients who received cardiac catheterization, PCI and coronary artery bypass grafting on the day of and within 30 days of admission overall and according to AMI type (ST-segment elevation AMI [STEMI] v. non-STEMI) and risk group (low, medium or high predicted risk of 30-d mortality). RESULTS: We followed 414 216 patients in the US and 112 484 in Ontario. The large disparities in cardiac intervention rates observed in 2003 mostly disappeared over time. By 2013, the proportion of patients who received same-day PCI was only slightly higher in the US than in Ontario (22.3% v. 19.2%), whereas the converse was true for 30-day PCI (44.0% v. 41.3%). In 2013, patients with STEMI in the US and Ontario received PCI at nearly identical rates on the day of admission (66.3% v. 63.8%); however, more patients at high risk with STEMI in the US than in Ontario received PCI, both on the day of admission (55.5% v. 44.7%) and by 30 days (60.5% v. 55.0%). INTERPRETATION: Despite differences in resources and organization of delivery systems, by 2013, timely receipt of PCI by Ontario patients with AMI lagged only slightly behind that by US patients. A higher supply of PCI centres in the US may have facilitated earlier intervention among patients at high risk with STEMI.

Physicians' Participation In ACOs Is Lower In Places With Vulnerable Populations Than In More Affluent Communities.

Early evidence suggested that accountable care organizations (ACOs) could improve health care quality while constraining costs, and ACOs are expanding throughout the United States. However, if disadvantaged patients have unequal access to physicians who participate in ACOs, that expansion may exacerbate health care disparities. We examined the relationship between physicians' participation in both Medicare and commercial ACOs across the country and the sociodemographic characteristics of their likely patient populations. Physicians' participation in ACOs varied widely across hospital referral regions, from nearly 0 percent to over 85 percent. After we adjusted for individual physician and practice characteristics, we found that physicians who practiced in ZIP Code Tabulation Areas where a higher percentage of the population was black, living in poverty, uninsured, or disabled or had less than a high school education-compared to other areas-had significantly lower rates of ACO participation than other physicians. Our findings suggest that vulnerable populations' access to physicians participating in ACOs may not be as great as access for other groups, which could exacerbate existing disparities in health care quality.

Comparison of estimation methods for creating small area rates of acute myocardial infarction among Medicare beneficiaries in California.

Creating local population health measures from administrative data would be useful for health policy and public health monitoring purposes. While a wide range of options--from simple spatial smoothers to model-based methods--for estimating such rates exists, there are relatively few side-by-side comparisons, especially not with real-world data. In this paper, we compare methods for creating local estimates of acute myocardial infarction rates from Medicare claims data. A Bayesian Monte Carlo Markov Chain estimator that incorporated spatial and local random effects performed best, followed by a method-of-moments spatial Empirical Bayes estimator. As the former is more complicated and time-consuming, spatial linear Empirical Bayes methods may represent a good alternative for non-specialist investigators.

Local population characteristics and hemoglobin A1c testing rates among diabetic medicare beneficiaries.

BACKGROUND: Proposed payment reforms in the US healthcare system would hold providers accountable for the care delivered to an assigned patient population. Annual hemoglobin A1c (HbA1c) tests are recommended for all diabetics, but some patient populations may face barriers to high quality healthcare that are beyond providers' control. The magnitude of fine-grained variations in care for diabetic Medicare beneficiaries, and their associations with local population characteristics, are unknown. METHODS: HbA1c tests were recorded for 480,745 diabetic Medicare beneficiaries. Spatial analysis was used to create ZIP code-level estimated testing rates. Associations of testing rates with local population characteristics that are outside the control of providers--population density, the percent African American, with less than a high school education, or living in poverty--were assessed. RESULTS: In 2009, 83.3% of diabetic Medicare beneficiaries received HbA1c tests. Estimated ZIP code-level rates ranged from 71.0% in the lowest decile to 93.1% in the highest. With each 10% increase in the percent of the population that was African American, associated HbA1c testing rates were 0.24% lower (95% CI -0.32--0.17); for identical increases in the percent with less than a high school education or the percent living in poverty, testing rates were 0.70% lower (-0.95--0.46) and 1.6% lower (-1.8--1.4), respectively. Testing rates were lowest in the least and most densely populated ZIP codes. Population characteristics explained 5% of testing rate variations. CONCLUSIONS: HbA1c testing rates are associated with population characteristics, but these characteristics fail to explain the vast majority of variations. Consequently, even complete risk-adjustment may have little impact on some process of care quality measures; much of the ZIP code-related variations in testing rates likely result from provider-based differences and idiosyncratic local factors not related to poverty, education, or race.