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).

Conclusion

Our findings suggest that the differences in readmission rates following LER are largely driven by hospital case mix rather than true differences in quality.

Introduction

In an effort to decrease cost and improve quality in health care, reducing readmissions has become a popular target of pay-for-performance programs. Currently, the largest pay-for-performance program aimed at reducing readmissions is the Center for Medicare and Medicaid Services (CMS) Hospital Readmissions Reduction Program (HRRP).¹ While originally encompassing only 3 medical conditions, HRRP has recently been expanded to include hip and knee surgery.² Furthermore, CMS has indicated that vascular procedures will be included in future rounds of expansion given the high readmission rate among vascular patients.³

The growing enthusiasm for using readmissions as a marker of hospital quality following vascular surgery has prompted efforts to better understand the reasons for readmission. However, the extent to which existing methodology, for profiling hospitals on medical readmissions, may be effectively applied to surgery is unknown. Because the same surgical procedure is often performed for a variety of indications, there is a significant risk of confounding by indication.⁴ For example, Rutherford classification is a strong predictor of adverse outcomes following lower extremity revascularization (LER). Data from single institution studies and clinical trials have shown that readmission rates increase as patients progress from intermittent claudication to tissue loss.5, 6 However, to date, the extent to which operative indication impacts hospital rankings remain unknown.

In this context, we sought to better understand the relationship between operative indication for LER and readmission. Specifically, we addressed 3 questions: (1) At the patient level, what is the association between operative indication and readmission? (2) Do hospitals with lower readmission rates perform better than other hospitals with high-risk patients or do they simply treat less high-risk patients? (3) What would be the impact on hospital profiling of adjusting for the mix of high- versus low-risk patients?