A Hybrid Center for Medicaid and Medicare Service Mortality Model in 3 Diagnoses
Bibliographic Data
| ID | 9104586 |
|---|---|
| Authors | Marta L Render (Veterans Health Administration, corresponding author), Peter L Almenoff (University of Kansas, corresponding author), Annette Christianson (0000-0002-3967-1077, corresponding author), Anne E Sales (0000-0001-9360-3334, Health Services Research & Development, corresponding author), Tammy Czarnecki (United States Department of Veterans Affairs), Jim A Deddens, J Deddens (University of Cincinnati), Ron W Freyberg (corresponding author), Julie Eyman, Julie R Eyman (corresponding author), Timothy P Hofer (0000-0003-0434-8787, Health Services Research & Development, corresponding author) |
| Year | 2012 |
| Volume | 50 |
| Issue | 6 |
| Pages | 520-526 |
| Publication date | 2012-06-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/mlr.0b013e318245a5f2 |
| PMID | 22584887 |
| OpenAlex | W2000311369 |
| Language | EN |
| References cited | 18 |
INTRODUCTION: Reliance on administrative data sources and a cohort with restricted age range (Medicare 65 y and above) may limit conclusions drawn from public reporting of 30-day mortality rates in 3 diagnoses [acute myocardial infarction (AMI), congestive heart failure (CHF), pneumonia (PNA)] from Center for Medicaid and Medicare Services. METHODS: We categorized patients with diagnostic codes for AMI, CHF, and PNA admitted to 138 Veterans Administration hospitals (2006-2009) into 2 groups (less than 65 y or ALL), then applied 3 different models that predicted 30-day mortality [Center for Medicaid and Medicare Services administrative (ADM), ADM+laboratory data (PLUS), and clinical (CLIN)] to each age/diagnosis group. C statistic (CSTAT) and Hosmer Lemeshow Goodness of Fit measured discrimination and calibration. Pearson correlation coefficient (r) compared relationship between the hospitals' risk-standardized mortality rates (RSMRs) calculated with different models. Hospitals were rated as significantly different (SD) when confidence intervals (bootstrapping) omitted National RSMR. RESULTS: The ≥ 65-year models included 57%-67% of all patients (78%-82% deaths). The PLUS models improved discrimination and calibration across diagnoses and age groups (CSTAT-CHF/65 y and above: 0.67 vs. 0. 773 vs. 0.761; ADM/PLUS/CLIN; Hosmer Lemeshow Goodness of Fit significant 4/6 ADM vs. 2/6 PLUS). Correlation of RSMR was good between ADM and PLUS (r-AMI 0.859; CHF 0.821; PNA 0.750), and 65 years and above and ALL (r>0.90). SD ratings changed in 1%-12% of hospitals (greatest change in PNA). CONCLUSIONS: Performance measurement systems should include laboratory data, which improve model performance. Changes in SD ratings suggest caution in using a single metric to label hospital performance
Confidence interval · Goodness of fit · Health care · Heart failure · Medicaid · Medical diagnosis · Myocardial infarction · Statistic · Statistics · Emergency Medicine · Internal Medicine · Medicine · Patient Satisfaction in Healthcare · Primary Care and Health Outcomes · Sepsis Diagnosis and Treatment
Use of Administrative Claims Models to Assess 30-Day Mortality Among Veterans Health Administration Hospitals
Severity Measurement Methods and Judging Hospital Death Rates for Pneumonia
Risk-Adjusting Hospital Inpatient Mortality Using Automated Inpatient, Outpatient, and Laboratory Databases
Intraclass correlations
| Citation velocity | historical |
|---|---|
| Highly cited | No |