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Published on: January 17, 2019
The Role of Self-Classified Race/Ethnicity, Insurance Status, and Hospital Type in Benign Hysterectomy
Maya A Wright1,2, Alan C Kinlaw2,3, Asha B McClurg4
1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Objective:
To explore the associations of self-classified race/ethnicity, insurance status, and hospital type with updated appropriateness ratings of hysterectomy among premenopausal patients.
Study Design:
The study population consisted of patients 18-44 years of age who received a hysterectomy for benign and non-obstetric gynecological conditions between October 2014 and December 2017. Structured and unstructured data were abstracted from electronic medical records (EMR). We estimated weighted prevalence differences (PDw), ratios (PRw), and 95% confidence intervals (CIs) between self-classified race/ethnicity (Hispanic, Non-Hispanic Black, and Non-Hispanic White), insurance status at time of surgery (uninsured, Medicaid, and private insurance), and hospital type (non-academic and academic) and the Wright appropriateness rating (inappropriate, ambiguous, and appropriate). To assess potential missing data bias, we conducted sensitivity analyses with stratification of prevalence estimates by a proxy for EMR completeness (1, ≥2 preoperative notes from the primary surgeon).
Results:
Among the 1,613 hysterectomies analyzed, 26.5% received an inappropriate rating, 15.8% an ambiguous rating, and 57.7% an appropriate rating. Patients with Medicaid had 17.2% (95% CI = -22.3%, -12.1%) lower prevalence of inappropriate ratings compared with patients with private insurance. Surgeries at non-academic medical centers had 20.4% (95% CI = 17.0%, 23.8%) higher prevalence of inappropriate ratings compared with surgeries at academic medical centers. In sensitivity analyses, among surgeries with ≥2 preoperative notes from the primary surgeon, the prevalence of an inappropriate rating was similar between non-academic and academic medical centers (PDw = -2.1%, 95% CI = -6.8%).
Conclusions:
Associations between insurance status, hospital type, and inappropriate rating may be partially explained by EMR completeness. EMR completeness, provider documentation, and data management are important determinants of equitable clinical care. Additional research to improve assessment of appropriate hysterectomy care and efforts to improve EMR completeness are important next steps in gynecological research.
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