title: Impact of Unaccounted Risk Factors on the Interpretation of Surgical Outcomes.
abstract: BACKGROUND
  Systems that report hospital-based risk-adjusted surgical outcomes are potentially sensitive to the underlying methods used for risk adjustment. If a body of operations has a true level of risk that is higher than the estimated risk, then these operations might generate bias in the output of these reports. The objective of this study was to quantify the impact of unaccounted risk on the results of a surgical outcomes report.
  
  
  METHODS
  We constructed a model simulating a universe of 500 hospitals, each providing care to 1,500 patients in a given year. The likelihood of morbidity and mortality for each of these patients was drawn from a random sampling of patients in the American College of Surgeons NSQIP. A single additional hospital was also simulated, within which a certain proportion (proportion varied from 2% to 10%) of patients had a significantly higher (odds ratio varied from 1 to 5) actual likelihood of mortality.
  
  
  RESULTS
  The presence of even a small proportion (2%) of patients with unaccounted risk had the potential to greatly increase the likelihood of a hospital being considered a statistical outlier (poor performer). This impact was greater in the assessment of complications than mortality.
  
  
  CONCLUSIONS
  This study shows that even a small proportion of patients with substantial levels of unaccounted risk can have a dramatic impact on the assessment of hospital-level risk-adjusted surgical outcomes. To avoid the unintended consequences associated with risk-averse behavior from providers, policy should be constructed to address this potential source of bias.
authors.affiliation: Department of Surgery, Mayo Clinic, Phoenix, AZ; Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN. Electronic address: etzioni.david@mayo.edu.
authors.forename: David A
authors.initials: DA
authors.lastname: Etzioni
authors.affiliation: Department of Surgery, Mayo Clinic, Phoenix, AZ; Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN.
authors.forename: Nabil
authors.initials: N
authors.lastname: Wasif
authors.affiliation: Department of Surgery, Mayo Clinic, Phoenix, AZ; Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN.
authors.forename: Amit K
authors.initials: AK
authors.lastname: Mathur
authors.affiliation: Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN.
authors.forename: Elizabeth B
authors.initials: EB
authors.lastname: Habermann
authors.affiliation: Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN; Department of Surgery, Mayo Clinic, Rochester, MN.
authors.forename: Robert R
authors.initials: RR
authors.lastname: Cima
authors.affiliation: Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN.
authors.forename: Yu-Hui H
authors.initials: YH
authors.lastname: Chang
mesh_terms: D003198:Computer Simulation; D013505:Digestive System Surgical Procedures; D006801:Humans; D009017:Morbidity / Q000639:trends; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011183:Postoperative Complications / Q000453:epidemiology*; D011787:Quality of Health Care; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D014481:United States / Q000453:epidemiology