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.

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.

Beyond comorbidity: expanding the definition and measurement of complexity among older adults using administrative claims data.

BACKGROUND: Studies of patients with multiple chronic conditions using claims data are often missing important determinants of treatments and outcomes, such as function status and disease severity. We sought to identify and evaluate a class of function-related indicators (FRIs) from administrative claims data. POPULATION: The study cohort comprised US Medicare beneficiaries aged 65 years or older with Parts A and B fee-for-service and Part D coverage, with a hospitalization for acute myocardial infarction during 2007. METHODS: Measures during the year before admission included the FRIs, demographics, conventional comorbidity measures, and prior hospitalization. Outcomes were receipt of cardiac catheterization during the index hospitalization and 12-month mortality. Model development used a random sample (n=72,056) with an equal sample for validation. RESULTS: In addition to prior cardiovascular conditions (85%), 40% had ≥1 comorbid condition, 30% were hospitalized in the prior 6 months, and 65% had ≥1 FRI [eg, delirium/dementia (22.7%), depression (16.7%), mobility limitation (16.1%), and chronic skin ulcers (12.6%)]. Including the FRIs improved mortality and cardiac catheterization prediction models (C-statistics 0.71 and 0.77, respectively). Patients with more cardiovascular conditions received less cardiac catheterization [minimally adjusted odds ratio (OR) 0.83; 95% confidence interval (CI), 0.82-0.83], as did patients with more comorbidities (minimally adjusted OR 0.70; 95% CI, 0.69-0.71), but this was attenuated by adjusting for functional status (fully adjusted OR for cardiovascular conditions 0.95; 95% CI, 0.94-0.96 and for comorbid conditions 0.94; 95% CI, 0.92-0.95). CONCLUSIONS: Claims data studies that include indicators of potentially diminished patient functional status better capture heterogeneity of patients with multiple chronic conditions.

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.