BACKGROUND: The Centers for Medicare and Medicaid Services has removed total hip arthroplasty from the inpatient-only (IO) list in January 2020. Given the confusion created when total knee arthroplasty came off the IO list in 2018, this study aims to develop a predictive model for guiding preoperative inpatient admission decisions based upon readily available patient demographic and comorbidity data. METHODS: This is a retrospective review of 1415 patients undergoing elective unilateral primary THA between January 2018 and October 2019. Multiple logistic regression was used to develop a model for predicting LOS ≥2 days based on preoperative demographics and comorbidities. RESULTS: Controlling for other demographics and comorbidities, increased age (odds ratio [OR], 1.048; P < .001), female gender (OR, 2.284; P < .001), chronic obstructive pulmonary disorder (OR, 2.249; P = .003), congestive heart failure (OR, 8.231; P < .001), and number of comorbidities (OR, 1.216; P < .001) were associated with LOS ≥2 days while patients with increased body mass index (OR, 0.964; P = .007) and primary hypertension (OR, 0.671; P = .008) demonstrated significantly reduced odds of staying in the hospital for 2 or more days. The area under the curve was found to be 0.731, indicating acceptable discriminatory value. CONCLUSION: For patients undergoing primary THA, increased age, female gender, chronic obstructive pulmonary disorder, congestive heart failure, and multiple comorbidities are risk factors for inpatient hospital LOS of 2 or more days. Our predictive model based on readily available patient presentation and comorbidity characteristics may aid surgeons in preoperatively identifying patients requiring inpatient admission with removal of THA from the Medicare IO list.
BACKGROUND: The Centers for Medicare and Medicaid Services has removed total hip arthroplasty from the inpatient-only (IO) list in January 2020. Given the confusion created when total knee arthroplasty came off the IO list in 2018, this study aims to develop a predictive model for guiding preoperative inpatient admission decisions based upon readily available patient demographic and comorbidity data. METHODS: This is a retrospective review of 1415 patients undergoing elective unilateral primary THA between January 2018 and October 2019. Multiple logistic regression was used to develop a model for predicting LOS ≥2 days based on preoperative demographics and comorbidities. RESULTS: Controlling for other demographics and comorbidities, increased age (odds ratio [OR], 1.048; P < .001), female gender (OR, 2.284; P < .001), chronic obstructive pulmonary disorder (OR, 2.249; P = .003), congestive heart failure (OR, 8.231; P < .001), and number of comorbidities (OR, 1.216; P < .001) were associated with LOS ≥2 days while patients with increased body mass index (OR, 0.964; P = .007) and primary hypertension (OR, 0.671; P = .008) demonstrated significantly reduced odds of staying in the hospital for 2 or more days. The area under the curve was found to be 0.731, indicating acceptable discriminatory value. CONCLUSION: For patients undergoing primary THA, increased age, female gender, chronic obstructive pulmonary disorder, congestive heart failure, and multiple comorbidities are risk factors for inpatient hospital LOS of 2 or more days. Our predictive model based on readily available patient presentation and comorbidity characteristics may aid surgeons in preoperatively identifying patients requiring inpatient admission with removal of THA from the Medicare IO list.
Authors: Justin J Turcotte; McKayla E Kelly; Alyssa B Fenn; Jennifer J Grover; Christina A Wu; James H MacDonald Journal: Arthroplasty Date: 2022-02-01