Publications by authors named "Debra Anoff"
Article Synopsis
- - The study analyzes two Medicare payment programs for treating acute myocardial infarction (AMI) using different classification methods: the Hospital Readmissions Reduction Program (using ) codes) and the Bundled Payments for Care Improvement Advanced (using diagnosis-related groups, or DRGs).
- - Among 2,176 patients, only 19.3% were common to both cohorts, with DRG patients being older, more often female, and having higher rates of heart and kidney diseases; they also experienced higher mortality and readmission rates compared to the AMI cohort.
- - The findings indicate that the choice of classification method significantly impacts patient demographics and outcomes, highlighting the need for careful consideration in quality assessment initiatives.
Background: Medicaid is often associated with longer hospitalizations and higher in-hospital mortality than other insurance types.
Objective: To characterize the impact of state Medicaid expansion status under the Affordable Care Act (ACA) on payer mix, length of stay (LOS), and in-hospital mortality.
Design/setting/patients: Retrospective cohort study of general medicine patients discharged from academic medical centers (AMCs) within the University HealthSystem Consortium from October 1, 2012 to September 30, 2015.
Although uncompensated care for hospital-based care has fallen dramatically since the implementation of the Affordable Care Act and Medicaid expansion, the changes in hospital physician reimbursement are not known. We evaluated if payer mix and physician reimbursement by encounter changed between 2013 and 2014 in an academic hospitalist practice in a Medicaid expansion state. This was a retrospective cohort study of all general medicine inpatient admissions to an academic hospitalist group in 2013 and 2014.
View Article and Find Full Text PDFTargeting patients with prolonged hospitalizations may represent an effective strategy for reducing average hospital length of stay (LOS). We sought to characterize predictors of prolonged hospitalizations among general medicine patients to guide future improvement efforts. We conducted a retrospective cohort study using administrative data of general medicine patients discharged from inpatient status from our academic medical center between 2012 and 2014.
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