Objective: The goal of this research was to analyze if disparities in route of hysterectomy for endometrial cancer exist in Florida. Materials and Methods: In this retrospective cohort study, Florida inpatient and ambulatory surgery databases (2014-2016) were examined to find cases of patients with endometrial cancer who underwent hysterectomy in the state. Logistic regression models were used to compare patient- and hospital-level factors associated with having minimally invasive surgery (MIS) versus open surgery, and complications in patients having open hysterectomy versus MIS. Results: Overall, 6513 patients met the inclusion criteria. MIS was performed in 81.4% of cases. The odds of using a minimally invasive approach to hysterectomy (vaginal, robotic, or laparoscopic) were significantly lower for black women (odds ratio [OR]: 0.41; 95% confidence interval [CI]: 0.34-0.50) as well as for other non-white patients (OR: 0.64; 95% CI: 0.49-0.84). Patients with Medicaid (OR: 0.42; 95% CI: 0.30-0.59) or Medicare managed care (OR: 0.73; 95% CI: 0.59-0.91), or who received care at a teaching hospital (OR: 0.82; 95% CI: 0.68-0.98) or government hospital (OR: 0.50; 95% CI: 0.38-0.65) were also less likely to receive MIS. Patients receiving care at a high-volume (OR: 1.69; 95% CI: 1.30-2.20) or medium-volume (OR: 3.11; 95% CI: 2.37-4.08) hospital, or patients who were located in the Central (OR: 1.71; 95% CI: 1.17-2.48) or Peninsula (OR: 1.73; 95% CI: 1.17-2.56) regions, compared to the Florida Panhandle, had greater odds of receiving MIS. Conclusions: Although Florida has a high adoption of MIS for treating endometrial cancer, disparities persist. Efforts of state-level entities should focus on improving access to minimally invasive hysterectomy for racial minorities with endometrial cancer.
Keyphrases
- endometrial cancer
- minimally invasive
- healthcare
- end stage renal disease
- ejection fraction
- newly diagnosed
- affordable care act
- palliative care
- quality improvement
- robot assisted
- peritoneal dialysis
- machine learning
- pain management
- adipose tissue
- chronic pain
- skeletal muscle
- metabolic syndrome
- acute coronary syndrome
- atrial fibrillation
- coronary artery bypass
- case report
- patient reported outcomes
- deep learning