Risk adjustment for complications of hysterectomy: utility of routinely collected administrative data.

Abstract Objective: To determine the ability of risk adjustment methods that use routinely collected administrative data to explain variability in complication rates after hysterectomy. Methods: Discharge data on all non-radical hysterectomies performed in North Carolina between January 1988 and September 1994 were obtained from the North Carolina Medical Database Commission. Complications were categorized as 1) surgical (eg, hemorrhage, organ injury) and 2) medical (eg, myocardial infarction, pneumonia). Comorbidities included peritoneal adhesions and chronic medical problems. Hospital charges were adjusted for inflation. Univariate analyses were performed using the Kruskall-Wallis test for skewed continuous variables and χ 2 tests for categorical variables. Multivariate analysis was performed using unconditional logistic regression, with complication rate as the dependent variable. Results: There were 107,648 cases performed at 134 hospitals, with an overall complication rate of 9.5%. When cancer and pregnancy cases were excluded, the surgical complication rate was 5.0%, medical 3.2%. Patients with surgical complications were significantly younger (median age 42 vs 46) and had significantly higher total hospital charges (median $8,127 vs $7,496) than patients with medical complications. Complication rates for individual hospitals varied from 1.5% to 29.3%, with rates highest for academic medical centers (24.3% vs 7.2% for non-teaching hospitals). Significant predictors of complications in univariate analyses included type of hysterectomy, indication, age ≥65 years, insurance status, and teaching hospital status. Coded comorbid conditions were variable in their association with complications. Adjusted odds ratios, controlled for indication and type of procedure, for age ≥65, Medicaid or no insurance, and teaching hospital status were all greater for medical complications than for surgical complications in multivariate analysis (table). The predictive ability of multivariate analysis was better for medical complications than for surgical complications (C-statistic for medical complication model 0.763 vs 0.644 for surgical complications). Risk Factor Surgical Complications Medical Complications Adjusted odds ratio 95% CI Adjusted odds ratio 95% CI Age ≥65 years 1.73 1.58, 1.90 4.54 4.16, 4.96 Medicaid/ no insurance (compared to private/ Medicare/HMO 1.36 1.26, 1.47 1.62 1.48, 1.77 Academic medical center (compared to non-teaching hospital) 1.86 1.74, 1.99 3.28 3.06, 3.52 Conclusions: Surgical complications of hysterectomy are more common, occur in younger women, and are associated with higher hospital charges than medical complications. Complication rates vary widely between hospitals, with teaching hospitals having the highest rates. This difference persists after adjustment for coded comorbidities. Possible explanations for the inability of multivariate analysis to explain the wide range in observed complication rates include 1) shortcomings in the available data or models, such as variability in coding practices between hospitals or variability in surgical difficulty between hospitals that is not captured with ICD-9-CM codes (eg, uterine size, cancer stage) and 2) variability in the quality of care between hospitals. Further research is needed to help determine the role of each of these explanations. Risk adjustment methods that use administrative data based on currently available coding standards are poor predictors of surgical complication rates after hysterectomy and should not be used to reach conclusions about quality of care.