Generating Practice-Based Evidence in the Use of Guideline-Recommended Combination Therapy for Secondary Prevention of Acute Myocardial Infarction.

Background: Clinical guidelines recommend beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin-receptor blockers, and statins for the secondary prevention of acute myocardial infarction (AMI). It is not clear whether variation in real-world practice reflects poor quality-of-care or a balance of outcome tradeoffs across patients. Methods: The study cohort included Medicare fee-for-service beneficiaries hospitalized 2007-2008 for AMI. Treatment within 30-days post-discharge was grouped into one of eight possible combinations for the three drug classes. Outcomes included one-year overall survival, one-year cardiovascular-event-free survival, and 90-day adverse events. Treatment effects were estimated using an Instrumental Variables (IV) approach with instruments based on measures of local-area practice style. Pre-specified data elements were abstracted from hospital medical records for a stratified, random sample to create "unmeasured confounders" (per claims data) and assess model assumptions. Results: Each drug combination was observed in the final sample (N = 124,695), with 35.7% having all three, and 13.5% having none. Higher rates of guideline-recommended treatment were associated with both better survival and more adverse events. Unmeasured confounders were not associated with instrumental variable values. Conclusions: The results from this study suggest that providers consider both treatment benefits and harms in patients with AMIs. The investigation of estimator assumptions support the validity of the estimates.

Use of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers for Geriatric Ischemic Stroke Patients: Are the Rates Right?

BACKGROUND: Our objective is to estimate the effects associated with higher rates of renin-angiotensin system antagonists, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers (ACEI/ARBs), in secondary prevention for geriatric (aged >65 years) patients with new ischemic strokes by chronic kidney disease (CKD) status. METHODS AND RESULTS: The effects of ACEI/ARBs on survival and renal risk were estimated by CKD status using an instrumental variable (IV) estimator. Instruments were based on local area variation in ACEI/ARB use. Data abstracted from charts were used to assess the assumptions underlying the instrumental estimator. ACEI/ARBs were used after stroke by 45.9% and 45.2% of CKD and non-CKD patients, respectively. ACEI/ARB rate differences across local areas grouped by practice styles were nearly identical for CKD and non-CKD patients. Higher ACEI/ARB use rates for non-CKD patients were associated with higher 2-year survival rates, whereas higher ACEI/ARB use rates for patients with CKD were associated with lower 2-year survival rates. While the negative survival estimates for patients with CKD were not statistically different from zero, they were statistically lower than the estimates for non-CKD patients. Confounders abstracted from charts were not associated with the instrumental variable used. CONCLUSIONS: Higher ACEI/ARB use rates had different survival implications for older ischemic stroke patients with and without CKD. ACEI/ARBs appear underused in ischemic stroke patients without CKD as higher use rates were associated with higher 2-year survival rates. This conclusion is not generalizable to the ischemic stroke patients with CKD, as higher ACEI/ARBS use rates were associated with lower 2-year survival rates that were statistically lower than the estimates for non-CKD patients.

Association Between Preadmission Functional Status and Use and Effectiveness of Secondary Prevention Medications in Elderly Survivors of Acute Myocardial Infarction.

OBJECTIVES: To determine whether function-related indicators (FRIs), derived from preadmission claims data, help explain the frequent practice of forgoing secondary prevention medications observed in Medicare. DESIGN: Retrospective cohort. SETTING: National Medicare data. PARTICIPANTS: Elderly Medicare beneficiaries discharged alive from an acute myocardial infarction (AMI) hospitalization in 2007-2008 (N = 184,156). MEASUREMENTS: Study outcomes were number of guideline-recommended secondary prevention medications (statins, beta-blockers, and angiotensin-converting enzyme inhibitors or angiotensin receptor blockers) used after discharge and 12-month survival. Preadmission data (FRIs, cardiovascular conditions, comorbid conditions), type of AMI (non-ST-elevation myocardial infarction, anterior, other), and procedures and complications during the hospitalization were from claims data. RESULTS: Function-related indicators (FRIs) were common before admission; 50% of individuals had at least one (range 0-11). After discharge, 85.8% used at least one class of guideline medication, and 30.2% used all three; 19.6% died within 12 months. Each additional FRI reduced the likelihood of receiving all three medication classes by 5% (adjusted odds ratio = 0.95, 95% confidence interval (CI) = 0.94-0.96) and increased 12-month mortality by 20% (adjusted hazard ratio (aHR) = 1.20, 95% CI = 1.19-1.21). Individuals taking all three classes of medication were 30% less likely to die within 12 months than those not taking guideline medications (aHR = 0.70, 95% CI = 0.67-0.73). Similar survival benefit was observed in individuals with and without functional impairments. CONCLUSION: Greater impairment in preadmission functional status, using a measure derived from claims data, was associated with less use of secondary prevention medications after AMI. Survival benefits of taking these medications were consistent across functional impairment levels.

Statin use after acute myocardial infarction by patient complexity: are the rates right?

BACKGROUND: Guidelines suggest statin use after acute myocardial infarction (AMI) should be close to universal in patients without safety concerns yet rates are much lower than recommended, decline with patient complexity, and display substantial geographic variation. Trial exclusions have resulted in little evidence to guide statin prescribing for complex patients. OBJECTIVE: To assess the benefits and risks associated with higher rates of statin use after AMI by baseline patient complexity. RESEARCH DESIGN: Sample includes Medicare fee-for-service patients with AMIs in 2008-2009. Instrumental variable estimators using variation in local area prescribing patterns by statin intensity as instruments were used to assess the association of higher statin prescribing rates by statin intensity on 1-year survival, adverse events, and cost by patient complexity. RESULTS: Providers seem to have individualized statin use across patients based on potential risks. Higher statin rates for noncomplex AMI patients were associated with increased survival rates with little added adverse event risk. Higher statin rates for complex AMI patients were associated with tradeoffs between higher survival rates and higher rates of adverse events. CONCLUSIONS: Higher rates of statin use for noncomplex AMI patients are associated with outcome rate changes similar to existing evidence. For the complex patients in our study, who were least represented in existing trials, higher statin-use rates were associated with survival gains and higher adverse event risks not previously documented. Policy interventions promoting higher statin-use rates for complex patients may need to be reevaluated taking careful consideration of these tradeoffs.

Field methods in medical record abstraction: assessing the properties of comparative effectiveness estimates.

BACKGROUND: Comparative effectiveness studies using Medicare claims data are vulnerable to treatment selection biases and supplemental data from a sample of patients has been recommended for examining the magnitude of this bias. Previous research using nationwide Medicare claims data has typically relied on the Medicare Current Beneficiary Survey (MCBS) for supplemental data. Because many important clinical variables for our specific research question are not available in the MCBS, we collected medical record data from a subsample of patients to assess the validity of assumptions and to aid in the interpretation of our estimates. This paper seeks to describe and document the process used to collect and validate this supplemental information. METHODS: Medicare claims data files for all patients with fee-for-service Medicare benefits who had an acute myocardial infarction (AMI) in 2007 or 2008 were obtained. Medical records were obtained and abstracted for a stratified subsample of 1,601 of these patients, using strata defined by claims-based measures of physician prescribing practices and drug treatment combinations. The abstraction tool was developed collaboratively by study clinicians and researchers, leveraging important elements from previously validated tools. RESULTS: Records for 2,707 AMI patients were requested from the admitting hospitals and 1,751 were received for an overall response rate of 65%; 1,601 cases were abstracted by trained personnel at a contracted firm. Data were collected with overall 96% inter-abstractor agreement across all variables. Some non-response bias was detected at the patient and facility level. CONCLUSION: Although Medicare claims data are a potentially powerful resource for conducting comparative effectiveness analyses, observational databases are vulnerable to treatment selection biases. This study demonstrates that it is feasible to abstract medical records for Medicare patients nationwide and collect high quality data, to design the sampling purposively to address specific research questions, and to more thoroughly evaluate the appropriateness of care delivered to AMI patients.

Accounting for unobservable exposure time bias when using Medicare prescription drug data.

OBJECTIVE: To describe the prevalence and correlates of unobservable medication exposure time, and to recommend approaches for minimizing bias, in studies using Medicare Part D data.. SAMPLE: 179,065 Medicare patients hospitalized for an AMI in 2007 or 2008. METHODS: We compared two methods for creating medication exposure observation periods using acute care discharge vs. post-acute care discharge dates. We examined options for increasing cohort sizes by requiring different thresholds for observable days, or by using as a covariate, in the observation period. We calculated the extent and health status correlates of unobserved Medicare Part D exposure time and examined its association with receipt of beta-blockers. RESULTS: 39% of patients had unobservable time during the 30 day exposure assessment period following acute care; they were significantly older, had more comorbidity and longer acute care stays, had worse 1-year survival, and were significantly less likely to be classified as beta-blocker users. Using the alternative exposure assessment window, only 29% of the sample had unobservable time, and differences between groups were less pronounced. Significant gains in sample size can be obtained by restricting or controlling for the number of observable days required in the exposure assessment period. CONCLUSIONS: Unobservable exposure time is common among Medicare Part D beneficiaries, and they are often in worse health. To retain patients with unobservable exposure time, we recommend stratifying patients on receipt of post-acute facility-based care, calculating and using observable days as a covariate and, when appropriate, using the discharge date from contiguous post-acute facility care for beginning the exposure assessment period.

Standardizing Medicare payment information to support examining geographic variation in costs.

OBJECTIVES: Examination of efficiency in health care requires that cost information be normalized. Medicare payments include both geographic and policy-based facility type differentials (e.g., wage index and disproportionate share hospital), which can bias cost comparisons of hospitals and averages across geographic areas. Standardizing payment information to remove the area- and policy-based payment differentials should normalize much of the observed geographic variability in payments, allowing for a more accurate comparison of resource use between providers and across geographic regions. Use of standardized payments will ensure that observed payment variation is due to differences in practice patterns and service use, rather than Medicare payment differences over which the providers have no control. This paper describes a method for standardizing claim payments, and demonstrates the difference in actual versus standardized payments by geographic region. STUDY DESIGN AND METHODS: We used a nationwide cohort of Medicare patients hospitalized with an acute myocardial infarction (AMI) in 2007, then limited our study to those with Medicare Part A and Part B fee-for-service (FFS), and Part D coverage (n = 143,123). Standardized payment amounts were calculated for each Part A and Part B claim; standardized and actual payments were summed for all services for each patient beginning with the index hospitalization through 12 months post discharge. PRINCIPAL FINDINGS: Without standardization of payments, certain areas of the country are mischaracterized as either high or low healthcare resource-consuming areas. The difference between actual and standardized payments varies by care setting. CONCLUSIONS: Standardized payment amounts should be calculated when comparing Medicare resource use across geographic areas.

Prevalence of multiple chronic conditions in the United States' Medicare population.

In 2006, the Centers for Medicare & Medicaid Services, which administers the Medicare program in the United States, launched the Chronic Condition Data Warehouse (CCW). The CCW contains all Medicare fee-for-service (FFS) institutional and non-institutional claims, nursing home and home health assessment data, and enrollment/eligibility information from January 1, 1999 forward for a random 5% sample of Medicare beneficiaries (and 100% of the Medicare population from 2000 forward). Twenty-one predefined chronic condition indicator variables are coded within the CCW, to facilitate research on chronic conditions. The current article describes this new data source, and the authors demonstrate the utility of the CCW in describing the extent of chronic disease among Medicare beneficiaries. Medicare claims were analyzed to determine the prevalence, utilization, and Medicare program costs for some common and high cost chronic conditions in the Medicare FFS population in 2005. Chronic conditions explored include diabetes, chronic obstructive pulmonary disease (COPD), heart failure, cancer, chronic kidney disease (CKD), and depression. Fifty percent of Medicare FFS beneficiaries were receiving care for one or more of these chronic conditions. The highest prevalence is observed for diabetes, with nearly one-fourth of the Medicare FFS study cohort receiving treatment for this condition (24.3 percent). The annual number of inpatient days during 2005 is highest for CKD (9.51 days) and COPD (8.18 days). As the number of chronic conditions increases, the average per beneficiary Medicare payment amount increases dramatically. The annual Medicare payment amounts for a beneficiary with only one of the chronic conditions is $7,172. For those with two conditions, payment jumps to $14,931, and for those with three or more conditions, the annual Medicare payments per beneficiary is $32,498. The CCW data files have tremendous value for health services research. The longitudinal data and beneficiary linkage within the CCW are features of this data source which make it ideal for further studies regarding disease prevalence and progression over time. As additional years of administrative data are accumulated in the CCW, the expanded history of beneficiary services increases the value of this already rich data source.