Assessment of utilization efficiency using machine learning techniques: A study of heterogeneity in preoperative healthcare utilization among super-utilizers - 05/09/20
Abstract |
Introduction |
In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.
Methods |
Medicare super-utilizers undergoing either a total hip or knee arthroplasty were identified and entered into a cluster analysis using annual preoperative charges to identify distinct patterns of utilization.
Results |
Among 19,522 super-utilizers who underwent THA or TKA, there was a marked heterogeneity in overall utilization with 5 distinct clusters of utilization patterns. Of note, comorbidity burden was similar among the 5 clusters. Patient outcomes also varied by Cluster type, ranging from 6.9% to 16.5% experiencing complications and 1.0%–3.2% experiencing 90-day mortality.
Conclusion |
While previous studies have suggested that super-utilizers are a homogenous group of patients, the current study demonstrated a large degree of heterogeneity within super-utilizers. Variations in utilization patterns were associated with postoperative outcomes and subsequent health care costs.
Le texte complet de cet article est disponible en PDF.Highlights |
• | Among preoperative super-utilizers, 5 distinct patterns of preoperative utilization were identified. |
• | Variations in utilization patterns were associated with postoperative outcomes and subsequent health care costs. |
• | The group with the lowest preoperative expenditure had the highest complication (16.5%) and 90-day readmission rate (24.3%). |
• | Annual expenditure dropped as much as 84% postoperatively, indicating a differential effect of surgery on health care costs. |
Keywords : Morbidity, Complexity, Risk factors, Machine learning
Plan
Vol 220 - N° 3
P. 714-720 - septembre 2020 Retour au numéro
Article précédent
- Using appropriateness criteria to identify opportunities to improve perioperative urinary catheter use
- Ana C. De Roo, Samantha Hendren, Jessica M. Ameling, Jennifer Meddings
- Efficacy of telehealth visits for postoperative care at the Minneapolis VA
- Jack Dirnberger, Steven Waisbren
Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.
Déjà abonné à cette revue ?