Patient-Level Value Analysis: An Innovative Approach to Optimize Care Delivery

被引:11
作者
McCreary, Dylan L. [1 ]
Dugarte, Anthony J. [1 ]
Vang, Sandy [1 ]
Plowman, Brad [2 ]
Williams, Benjamin R. [1 ]
Parikh, Harsh R. [1 ]
Cunningham, Brian P. [1 ,3 ]
机构
[1] Univ Minnesota, Dept Orthopaed Surg, Minneapolis, MN 55455 USA
[2] Reg Hosp, Dept Financial Planning & Decis Support, St Paul, MN USA
[3] Methodist Hosp, Dept Orthopaed Surg, St Louis Pk, MN USA
关键词
patient; level; value; analysis; fracture; COST-UTILITY ANALYSES; LOWER-EXTREMITY; HEALTH-CARE; RECOMMENDATIONS; QUALITY; BIAS;
D O I
10.1097/BOT.0000000000001624
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Background: An increasing emphasis has been placed on developing value-based care delivery systems in orthopaedics to combat rising health care costs. The goal of these systems is to both measure and improve the provisional value of care. Patient-level value analysis creates a mechanism to quantify and optimize value within a procedure, in contrast to traditional methods, which only measures value. The purpose of this study was to develop a patientlevel value analysis model and determine the efficacy of this model to improve value in orthopaedic care. Methods: Patients treated operatively for isolated closed ankle fractures at a single level 1 trauma center were prospectively identified. Short musculoskeletal function assessment was collected at the time of the initial clinical presentation and 6 months postoperatively. The cost of care was determined using time-driven activity-based costing, which included personnel, supplies, length of stay, implants, pharmacy, and radiology. Value was defined as each patient's change in the outcome score divided by their cost as determined by time-driven activity-based costing. A multiple linear regression was performed to determine which aspects of care significantly predicted value. Results: Forty-nine patients met inclusion/exclusion criteria. The multiple linear regression indicated treatment by physician D (beta = 20.135, P = 0.04) and inpatient stay (beta = -0.468, P < 0.01) were predictors of lesser value and represent areas for potential care pathway and value improvement. Conclusions: Patient-level value analysis represents a paradigm shift in the quantification of value. We recommend surgeons, practices, and health care systems begin implementing a system to quantify and optimize the value of care provided.
引用
收藏
页码:S49 / S52
页数:4
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