Using Claims Data to Examine Mortality Trends Following Hospitalization for Heart Attack in Medicare

Abstract

Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends.

Statins and New-Onset Diabetes Mellitus and Diabetic Complications: A Retrospective Cohort Study of US Healthy Adults

“…15 The method of creation and validation of AHRQ-CCS was previously published. [19][20][21][22][23] AHRQ-CCS disease categories have been widely used in numerous publications to identify comorbidities and outcomes, [24][25][26][27][28][29] predict mortality, 30,31 and estimate utilization and costs. [32][33][34][35] AHRQ-CCS disease categories are recognized by the Department of Defense Military Health System and are incorporated into Tricare data as an industry standard.…”

Care in the Months before Death and Hospice Enrollment Among Older Women with Advanced Breast Cancer

“…37 DCGs are highly predictive of mortality for Medicare beneficiaries with myocardial infarction 38 and cancer, 39 and because they capture so many conditions, they may be particularly useful in differentiating among women whose Charlson score is 0. We calculated summary DCG scores (categorized in quartiles; excluding breast cancer codes) based on the 12 months before death.…”

Variations in the Associations Between Psychiatric Comorbidity and Hospital Mortality According to the Method of Identifying Psychiatric Diagnoses

“…22 Nevertheless, numerous prior studies have used administrative data to measure quality 23,24 including several VA studies. [25][26][27] Moreover, in a comparison of statistical models based on administrative data and clinical data from medical records, Krakauer et al 28 found that administrative data are satisfactory for characterizing variations in hospital mortality rates, whereas Ash et al 29 concluded that prediction models based on claims data can be accurate. Additionally, our inclusion of a laboratory-based measure addresses some of the limitations of administrative data regarding unmeasured severity of illness.…”