Development and Validation of a Hospital Indicator of Activity-Based Costs for Injury Admissions

被引:1
|
作者
Porgo, Teegwende V. [1 ,2 ]
Moore, Lynne [1 ,2 ]
Assy, Coralie [1 ,2 ]
Neveu, Xavier [2 ]
Gonthier, Catherine [3 ]
Berthelot, Simon [2 ,4 ]
Gabbe, Belinda J. [5 ]
Cameron, Peter A. [5 ]
Bernard, Francis [6 ]
Turgeon, Alexis F. [1 ,2 ,7 ]
机构
[1] Univ Laval, Dept Social & Prevent Med, Quebec City, PQ, Canada
[2] Univ Laval, CHU Quebec, Hop Enfant Jesus,Axe Sante Populat & Prat Optim S, Ctr Rech,Traumatol Urgence Soins Intensifs Trauma, Quebec City, PQ, Canada
[3] Inst Natl Cellence Sante & Serv Sociaux INESSS, Unite Evaluat Traumatol & Soins Crit, Quebec City, PQ, Canada
[4] Univ Laval, Dept Family Med, Quebec City, PQ, Canada
[5] Monash Univ, Dept Epidemiol & Prevent Med, Melbourne, Vic, Australia
[6] Univ Montreal, Dept Med, Montreal, PQ, Canada
[7] Univ Laval, Dept Anesthesiol & Crit Care Med, Div Crit Care Med, Quebec City, PQ, Canada
基金
加拿大健康研究院; 澳大利亚研究理事会;
关键词
activity-based costing; benchmark; indicator; interprovider variations; resource use; risk-adjustment model trauma;
D O I
10.1016/j.jval.2020.11.011
中图分类号
F [经济];
学科分类号
02 ;
摘要
Objectives: To develop a hospital indicator of resource use for injury admissions. Methods: We focused on resource use for acute injury care and therefore adopted a hospital perspective. We included patients >= 16 years old with an Injury Severity Score.9 admitted to any of the 57 trauma centers of an inclusive Canadian trauma system from 2014 to 2018. We extracted data from the trauma registry and hospital financial reports and estimated resource use with activity-based costing. We developed risk-adjustment models by trauma center designation level (I/II and III/IV) for the whole sample, traumatic brain injuries, thoraco-abdominal injuries, orthopedic injuries, and patients >= 65 years old. Candidate variables were selected using bootstrap resampling. We performed benchmarking by comparing the adjusted mean cost in each center, obtained using shrinkage estimates, to the provincial mean. Results: We included 38 713 patients. The models explained between 12% and 36% (optimism-corrected r2) of the variation in resource use. In the whole sample and in all subgroups, we identified centers with higher- or lower-than-expected resource use across level I/II and III/IV centers. Conclusions: We propose an algorithm to produce the indicator using data routinely collected in trauma registries to prompt targeted exploration of potential areas for improvement in resource use for injury admissions. The r(2) of our models suggest that between 64% and 88% of the variation in resource use for injury care is dictated by factors other than patient baseline risk.
引用
收藏
页码:530 / 538
页数:9
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