Racial/Ethnic Differences in the Risk of Surgical Complications and Posthysterectomy Hospitalization among Women Undergoing Hysterectomy for Benign Conditions.

STUDY OBJECTIVE: Evaluate whether 30- and 90-day surgical complication and postoperative hospitalization rates after hysterectomy for benign conditions differ by race/ethnicity and whether the differences remain after controlling for patient, hospital, and surgical characteristics. DESIGN: Retrospective cohort study using administrative data. The exposure was race/ethnicity. The outcomes included 5 different surgical complications/categories and posthysterectomy inpatient hospitalization, all identified through 30 and 90 days after hysterectomy hospital discharge, with the exception of hemorrhage/hematoma, which was only identified through 30 days. To examine the association between race/ethnicity and each outcome, we used logistic regression with clustering of procedures within hospitals, adjusting for patient and hospital characteristics and surgical approach. SETTING: Multistate, including Florida and New York. PATIENTS: Women aged ≥18 years who underwent hysterectomy for benign conditions using State Inpatient Databases and State Ambulatory Surgery Databases. INTERVENTIONS: Hysterectomy for benign conditions. MEASUREMENTS AND MAIN RESULTS: We included 183 697 women undergoing hysterectomy for benign conditions from January 2011 to September 2014. In analysis, adjusting for surgery route and other factors, black race was associated with increased risk of 30-day digestive system complications (multivariable adjusted odds ratio [aOR], 1.98; 95% confidence interval [CI], 1.78-2.21), surgical-site infection (aOR, 1.34; 95% CI, 1.18-1.53), posthysterectomy hospitalization (aOR, 1.31; 95% CI, 1.22-1.40), and urologic complications (aOR, 1.16; 95% CI, 1.01-1.34) compared with white race. Asian/Pacific Islander race was associated with increased risk of 30-day urologic complications (aOR, 1.48; 95% CI, 1.08-2.03), intraoperative injury to abdominal/pelvic organs (aOR, 1.46; 95% CI, 1.23-1.75), and hemorrhage/hematoma (aOR, 1.33; 95% CI, 1.06-1.67) compared with white race. Hispanic ethnicity was associated with increased risk of 30-day posthysterectomy hospitalization (aOR, 1.11; 95% CI, 1.02-1.20) compared with white race. All findings were similar at 90 days. CONCLUSION: Black and Asian/Pacific Islander women had higher risk of some 30- and 90-day surgical complications after hysterectomy than white women. Black and Hispanic women had higher risk of posthysterectomy hospitalization. Intervention strategies aimed at identifying and better managing disparities in pre-existing conditions/comorbidities could reduce racial/ethnic differences in outcomes.

Development of an Algorithm to Distinguish Smoldering Versus Symptomatic Multiple Myeloma in Claims-Based Data Sets.

Purpose: The distinction of patients with symptomatic multiple myeloma (MM) from those with smoldering MM poses a challenge for researchers who use administrative databases. Historically, researchers either have included all patients or used treatment receipt as the distinguishing factor; both methods have drawbacks. We present an algorithm for distinguishing between symptomatic and smoldering MM using ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) codes for the classic defining events of symptomatic MM commonly referred to as the CRAB criteria (hypercalcemia, renal impairment, anemia, and bone lesions). Patients and Methods: SEER-Medicare-linked data from 4,187 patients with MM diagnosed between 2007 and 2011 were used for this analysis. Results: Eighty-four percent had ICD-9-CM codes consistent with CRAB criteria, whereas only 57% received treatment. Overall survival of patients with symptomatic MM defined as receipt of treatment was 32.3 months versus 26.6 months for the overall population and 22.9 months for patients with symptomatic MM defined by CRAB criteria. Conceptually, removal of patients with smoldering MM should result in a reduction in overall survival; however, the cohort of patients who received treatment tended to be younger and healthier than the overall population, which could have skewed the results. Conclusion: The algorithm we present resulted in a larger and more representative sample than classification by treatment status and reduced potential bias that could result from including all patients with smoldering MM in the analysis. Although this study was performed using the SEER-Medicare database, the methodology was broad enough that the algorithm could be extended to additional claims-based data sets with relative ease.