Sreeram Penna1, Kerri L Bell1, Feng-Chih Kuo2, Robert Andrew Henderson1, Carol Foltz1, Antonia F Chen3. 1. Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, PA. 2. Department of Orthopaedic Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan. 3. Department of Orthopaedic Surgery at Brigham and Women's Hospital, Boston, MA.
Abstract
BACKGROUND: The Comprehensive Care for Joint Replacement model is the newest iteration of the bundled payment methodology introduced by the Centers for Medicare and Medicaid Services. Comprehensive Care for Joint Replacement model, while incentivizing providers to deliver care at a lower cost, does not incorporate any patient-level risk stratification. Our study evaluated the impact of specific medical co-morbidities on the cost of care in total joint arthroplasty (TJA) patients. METHODS: A retrospective study was conducted on 1258 Medicare patients who underwent primary elective TJA between January 2015 and July 2016 at a single institution. There were 488 males, 552 hips, and the mean age was 71 years. Cost data were obtained from the Centers for Medicare and Medicaid Services. Co-morbidity information was obtained from a manual review of patient records. Fourteen co-morbidities were included in our final multiple linear regression models. RESULTS: The regression models significantly predicted cost variation (P < .001). For index hospital costs, a history of cardiac arrhythmias (P < .001), valvular heart disease (P = .014), and anemia (P = .020) significantly increased costs. For post-acute care costs, a history of neurological conditions like Parkinson's disease or seizures (P < .001), malignancy (P = .001), hypertension (P = .012), depression (P = .014), and hypothyroidism (P = .044) were associated with increases in cost. Similarly, for total episode cost, a history of neurological conditions (P < .001), hypertension (P = .012), malignancy (P = .023), and diabetes (P = .029) were predictors for increased costs. CONCLUSION: The cost of care in primary elective TJA increases with greater patient co-morbidity. Our data provide insight into the relative impact of specific medical conditions on cost of care and may be used in risk stratification in future reimbursement methodologies.
BACKGROUND: The Comprehensive Care for Joint Replacement model is the newest iteration of the bundled payment methodology introduced by the Centers for Medicare and Medicaid Services. Comprehensive Care for Joint Replacement model, while incentivizing providers to deliver care at a lower cost, does not incorporate any patient-level risk stratification. Our study evaluated the impact of specific medical co-morbidities on the cost of care in total joint arthroplasty (TJA) patients. METHODS: A retrospective study was conducted on 1258 Medicare patients who underwent primary elective TJA between January 2015 and July 2016 at a single institution. There were 488 males, 552 hips, and the mean age was 71 years. Cost data were obtained from the Centers for Medicare and Medicaid Services. Co-morbidity information was obtained from a manual review of patient records. Fourteen co-morbidities were included in our final multiple linear regression models. RESULTS: The regression models significantly predicted cost variation (P < .001). For index hospital costs, a history of cardiac arrhythmias (P < .001), valvular heart disease (P = .014), and anemia (P = .020) significantly increased costs. For post-acute care costs, a history of neurological conditions like Parkinson's disease or seizures (P < .001), malignancy (P = .001), hypertension (P = .012), depression (P = .014), and hypothyroidism (P = .044) were associated with increases in cost. Similarly, for total episode cost, a history of neurological conditions (P < .001), hypertension (P = .012), malignancy (P = .023), and diabetes (P = .029) were predictors for increased costs. CONCLUSION: The cost of care in primary elective TJA increases with greater patient co-morbidity. Our data provide insight into the relative impact of specific medical conditions on cost of care and may be used in risk stratification in future reimbursement methodologies.
Authors: Aaron Samuel Breslow; Nathaniel M Tran; Frederick Q Lu; Jonathan E Alpert; Benjamin Lê Cook Journal: Curr Psychiatry Rep Date: 2019-09-21 Impact factor: 5.285
Authors: Angela V Bedenbaugh; Machaon Bonafede; Elizabeth H Marchlewicz; Vinson Lee; Jeyanesh Tambiah Journal: Clinicoecon Outcomes Res Date: 2021-05-21