Quality and performance indicators in an academic department of head and neck surgery

Abstract

Objective: to create a method for assessing physician performance and care outcomes that are adjusted for procedure acuity and patient comorbidity.

Design: between 2004 and 2008 surgical procedures performed by 10 surgeons were stratified into high-acuity procedures (HAPs) and low-acuity procedures (LAPs). Risk adjustment was made for comorbid conditions examined singly or in groups of 2 or more.

Setting: a tertiary care medical center.

Patients: a total of 2618 surgical patients.

Main outcome measures: performance measures included length of stay; return to operating room within 7 days of surgery; and the occurrence of mortality, hospital readmission, transfusion, and wound infection within 30 days of surgery.

Results: the transfusion rate was 2.7% and 40.6% for LAPs and HAPs, respectively. Wound infection rates were 1.4% for LAPs vs 14.1% for HAPs, while 30-day mortality rate was 0.3% and 1.6% for LAPs and HAPs, respectively. The mean (SD) hospital stay for LAPs was 2.1 (3.6) vs 10.5 (7.0) days for HAPs. Negative performance factors were significantly higher for patients who underwent HAPs and had comorbid conditions. Differences among surgeons significantly affect the incidence of negative performance indicators. Factors affecting performance measures were procedure acuity, the surgeon, and comorbidity, in order of decreasing significance. Surgeons were ranked low, middle, and high based on negative performance indicators.

Conclusions: performance measures following oncologic procedures were significantly affected by comorbid conditions and by procedure acuity. Although the latter most strongly affects quality and performance indicators, both should weigh heavily in physician comparisons. The incidence of negative performance indicators was also influenced by the individual surgeon. These data may serve as a tool to evaluate and improve physician performance and outcomes and to develop risk-adjusted benchmarks. Ultimately, reimbursement may be tied to quantifiable measures of physician and institutional performance.

Figure 1

High- and low-acuity procedures performed at the study institution during fiscal years 2004 through 2008.

Figure 2

Factors affecting incidence of 2 or more negative surgical performance indicators. RE indicates risk estimate. P < .001 for all comparisons.

Figure 3

Comorbidity and negative indicators (neg ind) in low-acuity (A) and high-acuity (B) procedures by surgeon. Where each of the surgeons included in the study fell in the 2-dimensional matrices showing percentages of patients with at least 1 comorbid condition and percentages of patients who had 2 or more negative performance indicators is shown. The dashed lines indicate the boundaries of the highest and lowest 25th percentiles. In both panels, the lower right corner would have the surgeons whose patients had the lowest incidence of 2 or more negative indicators and the highest incidence of comorbidity, while the upper left corner would contain the surgeons whose patients had both the highest incidence of negative indicators and the lowest proportion with comorbid conditions.

Figure 4

High-acuity procedures (HAPs), comorbidity, and negative performance indicators by surgeon. The position of each surgeon in the 3-dimensional matrix shows percentages of patients who underwent HAPs, had at least 1 comorbid condition, and had 2 or more negative performance indicators. While Figure 3 is specific for either HAPs or low-acuity procedures, this figure highlights the percentage of HAPs in a given surgeon’s case mix. Most of the surgeons are grouped in the middle of the diagram. The surgeon represented by the dot in the lower left corner, however, has the lowest percentage of HAPs, fewest patients with comorbid conditions, and fewest cases with 2 or more negative performance indicators. On the other hand, the surgeon represented by the dot at the top of the diagram had the highest percentage of HAPs, a high percentage of patients with comorbid conditions, and a high percentage of cases with 2 or more negative performance indicators.