title: 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.
  
  
  METHODS
  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.
  
  
  METHODS
  a tertiary care medical center.
  
  
  METHODS
  a total of 2618 surgical patients.
  
  
  METHODS
  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.
authors.affiliation: Department of Head and Neck Surgery, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 1445, Houston, TX 77030, USA. rsweber@mdanderson.org
authors.forename: Randal S
authors.initials: RS
authors.lastname: Weber
authors.forename: Carol M
authors.initials: CM
authors.lastname: Lewis
authors.forename: Scott D
authors.initials: SD
authors.lastname: Eastman
authors.forename: Ehab Y
authors.initials: EY
authors.lastname: Hanna
authors.forename: Olubumi
authors.initials: O
authors.lastname: Akiwumi
authors.forename: Amy C
authors.initials: AC
authors.lastname: Hessel
authors.forename: Stephen Y
authors.initials: SY
authors.lastname: Lai
authors.forename: Leslie
authors.initials: L
authors.lastname: Kian
authors.forename: Michael E
authors.initials: ME
authors.lastname: Kupferman
authors.forename: Dianna B
authors.initials: DB
authors.lastname: Roberts
mesh_terms: D000046:Academic Medical Centers; D006258:Head and Neck Neoplasms / Q000401:mortality / Q000601:surgery*; D006801:Humans; D015994:Incidence; D007902:Length of Stay / Q000639:trends; D010359:Patient Readmission / Q000639:trends; D019984:Quality Indicators, Health Care; D012189:Retrospective Studies; D013514:Surgical Procedures, Operative / Q000592:standards* / Q000706:statistics & numerical data; D013530:Surgical Wound Infection / Q000453:epidemiology; D015996:Survival Rate / Q000639:trends; D014481:United States / Q000453:epidemiology