Indication for Lower Extremity Revascularization and Hospital Profiling of Readmissions.
BACKGROUND
Surgical readmissions are common, costly, and the focus of national quality improvement efforts. Given the relatively high readmission rates among vascular patients, pay-for-performance initiatives such as Medicare's Hospital Readmissions Reduction Program (HRRP) have targeted vascular surgery for increased scrutiny in the near future. Yet, the extent to which institutional case mix influences hospital profiling remains unexplored. We sought to evaluate whether higher readmission rates in vascular surgery are a reflection of worse performance or of treating sicker patients.


METHODS
This retrospective observational cohort study of the national Medicare population includes 479,047 beneficiaries undergoing lower extremity revascularization (LER) in 1,701 hospitals from 2005 to 2009. We employed hierarchical logistic regression to mimic Center for Medicare and Medicaid Services methodology accounting for age, gender, preexisting comorbidities, and differences in hospital operative volume. We estimated 30-day risk-standardized readmission rates (RSRR) for each hospital when including (1) all LER patients; (2) claudicants; or (3) high-risk patients (rest pain, ulceration, or tissue loss). We stratified hospitals into quintiles based on overall RSRR for all LERs and examined differences in RSRR for claudicants and high-risk patients between and within quintiles. Next, we evaluated differences in case mix (the proportion of claudicants and high-risk patients treated) across quintiles. Finally, we simulated differences in the receipt of penalties before and after adjusting for hospital case mix.


RESULTS
Readmission rates varied widely by indication: 7.3% (claudicants) vs. 19.5% (high risk). Even after adjusting for patient demographics, length of stay, and discharge destination, high-risk patients were significantly more likely to be readmitted (odds ratio 1.76, 95% confidence interval 1.71-1.81). The Best hospitals (top quintile) under the HRRP treated a much lower proportion of high-risk patients compared with the Worst hospitals (bottom quintile) (20% vs. 56%, P < 0.001). In the absence of case-mix adjustment, we observed a stepwise increase in the proportion of hospitals penalized as the proportion of high-risk patients treated increased (35-60%, P < 0.001). However, after case-mix adjustment, there were no differences between quintiles in the proportion of hospitalized penalized (50-46%, P = 0.30).


CONCLUSIONS
Our findings suggest that the differences in readmission rates following LER are largely driven by hospital case mix rather than true differences in quality.
Department of Surgery, University of Illinois Hospital & Health Sciences System, Chicago, IL. Electronic address: agonza32@uic.edu.
Andrew A
AA
Gonzalez
Department of Surgery, University of Illinois Hospital & Health Sciences System, Chicago, IL.
Celeste G
CG
Cruz
Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL.
Shantanu
S
Dev
Institute for Healthcare Policy and Innovation, North Campus Research Complex, University of Michigan, Ann Arbor, MI; Section of Vascular Surgery, University of Michigan, Ann Arbor MI.
Nicholas H
NH
Osborne
D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D054625:Healthcare Disparities / Q000639:trends; D006761:Hospitals / Q000639:trends*; D006801:Humans; D007383:Intermittent Claudication / Q000175:diagnosis / Q000601:surgery*; D016015:Logistic Models; D035002:Lower Extremity / Q000098:blood supply*; D008297:Male; D006278:Medicare; D015999:Multivariate Analysis; D016017:Odds Ratio; D010359:Patient Readmission / Q000639:trends*; D058729:Peripheral Arterial Disease / Q000175:diagnosis / Q000601:surgery*; D019984:Quality Indicators, Health Care / Q000639:trends*; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D014481:United States; D014656:Vascular Surgical Procedures / Q000009:adverse effects*