Acute Myocardial Infarction Cohorts Defined by International Classification of Diseases, Tenth Revision Versus Diagnosis-Related Groups: Analysis of Diagnostic Agreement and Quality Measures in an Integrated Health System.

BACKGROUND: Among Medicare value-based payment programs for acute myocardial infarction (AMI), the Hospital Readmissions Reduction Program uses International Classification of Diseases, Tenth Revision (ICD-10) codes to identify the program denominator, while the Bundled Payments for Care Improvement Advanced program uses diagnosis-related groups (DRGs). The extent to which these programs target similar patients, whether they target the intended population (type 1 myocardial infarction), and whether outcomes are comparable between cohorts is not known. METHODS: In a retrospective study of 2176 patients hospitalized in an integrated health system, a cohort of patients assigned a principal ICD-10 diagnosis of AMI and a cohort of patients assigned an AMI DRG were compared according to patient-level agreement and outcomes such as mortality and readmission. RESULTS: One thousand nine hundred thirty-five patients were included in the ICD-10 cohort compared with 662 patients in the DRG cohort. Only 421 patients were included in both AMI cohorts (19.3% agreement). DRG cohort patients were older (70 versus 65 years, P<0.001), more often female (48% versus 30%, P<0.001), and had higher rates of heart failure (52% versus 33%, P<0.001) and kidney disease (42% versus 25%, P<0.001). Comparing outcomes, the DRG cohort had significantly higher unadjusted rates of 30-day mortality (6.6% versus 2.5%, P<0.001), 1-year mortality (21% versus 8%, P<0.001), and 90-day readmission (26% versus 19%, P=0.006) than the ICD-10 cohort. Two observations help explain these differences: 61% of ICD-10 cohort patients were assigned procedural DRGs for revascularization instead of an AMI DRG, and type 1 myocardial infarction patients made up a smaller proportion of the DRG cohort (34%) than the ICD-10 cohort (78%). CONCLUSIONS: The method used to identify denominators for value-based payment programs has important implications for the patient characteristics and outcomes of the populations. As national and local quality initiatives mature, an emphasis on ICD-10 codes to define AMI cohorts would better represent type 1 myocardial infarction patients.

Impact of state medicaid expansion status on length of stay and in-hospital mortality for general medicine patients at US academic medical centers.

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. INTERVENTION/MEASUREMENTS: Hospitals were stratified according to state Medicaid expansion status. The proportion of discharges by primary payer, LOS index, and mortality index were compared between Medicaid-expansion and nonexpansion hospitals before and after ACA implementation. ACA implementation was defined as January 1, 2014, for all states except Michigan, New Hampshire, Pennsylvania, and Indiana, which had unique dates of Medicaid expansion. RESULTS: We identified 3,144,488 discharges from 156 hospitals in 24 Medicaid-expansion states and Washington, DC, and 1,114,464 discharges from 55 hospitals in 14 nonexpansion states during the study period. Hospitals in Medicaid-expansion states experienced a significant 3.7% increase in Medicaid discharges (P = 0.013) and a 2.9% decrease in uninsured discharges (P < 0.001) after ACA implementation, whereas hospitals in nonexpansion states saw no significant change in payer mix. In a difference-in-differences analysis, the changes in LOS and mortality indices pre- to post-ACA implementation did not differ significantly between hospitals in Medicaid-expansion versus nonexpansion states. CONCLUSIONS: The differential shift in payer mix between Medicaid-expansion and nonexpansion states under the ACA did not influence LOS or in-hospital mortality for general medicine patients at AMCs in the United States. Journal of Hospital Medicine 2015;11:847-852. © 2015 Society of Hospital Medicine.

Changes in Payer Mix and Physician Reimbursement After the Affordable Care Act and Medicaid Expansion.

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. The proportion of encounters by payer and reimbursement/inpatient encounter were compared in 2013 versus 2014. A sensitivity analysis determined the relative contribution of different factors to the change in reimbursement/encounter. Among 37 540 and 40 397 general medicine inpatient encounters in 2013 and 2014, respectively, Medicaid encounters increased (17.3% to 30.0%, P < .001), uninsured encounters decreased (18.4% to 6.3%, P < 0.001), and private payer encounters also decreased (14.1% to 13.3%, P = .001). The median reimbursement/encounter increased 4.2% from $79.98/encounter in 2013 to $83.36/encounter in 2014 (P < .001). In a sensitivity analysis, changes in length of stay, proportions in encounter type by payer, payer mix, and reimbursement for encounter type by payer accounted for -0.7%, 0.8%, 2.0%, and 2.3% of the reimbursement change, respectively. From 2013 to 2014, Medicaid encounters increased, and uninsured and private payer encounters decreased within our hospitalist practice. Reimbursement/encounter also increased, much of which could be attributed to a change in payer mix. Further analyses of physician reimbursement in Medicaid expansion and non-expansion states would further delineate reimbursement changes that are directly attributable to Medicaid expansion.

Understanding predictors of prolonged hospitalizations among general medicine patients: A guide and preliminary analysis.

Targeting 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. Multivariable logistic regression was performed to assess the association between sociodemographic and clinical variables with prolonged LOS, defined as >21 days. Of 18,363 discharges, 416 (2.3%) demonstrated prolonged LOS. Prolonged hospitalizations accounted for 18.6% of total inpatient days and contributed 0.8 days to an average LOS of 4.8 days during the study period. Prolonged hospitalizations were associated with younger age (odds ratio [OR]: 0.80 per 10-year increase in age, 95% confidence interval [CI]: 0.73-0.87) and Medicaid insurance (OR: 1.99, 95% CI: 1.29-3.05, REF = Medicare). Compared to patients without prolonged LOS, prolonged LOS patients were more likely to have methicillin-resistant Staphylococcus aureus septicemia (OR: 8.83, 95% CI: 1.72-45.36); require a palliative care consult (OR: 4.63, 95% CI: 2.86-7.49), ICU stay (OR: 6.66, 95% CI: 5.22-8.50), or surgery (OR: 5.04, 95% CI: 3.90-6.52); and be discharged to a post-acute-care facility (OR: 10.37, 95% CI: 6.92-15.56). Prolonged hospitalizations in a small proportion of patients were an important contributor to overall LOS and particularly affected Medicaid enrollees with complex hospital stays who were not discharged home. Further studies are needed to determine the reasons for discharge delays in this population.