A Framework for Time-Driven Activity-Based Costing for Orthopedic Procedure

Bayan Holozadah, S. Pokharel
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Abstract

This study used method of Time-Driven Activity-Based costing (TDABC) approach to examined cost reduction in healthcare sector, Knee Arthroplasty Department in Al-Emadi Hospital as case-study for delivering a primary knee arthroplasty consultation. The purpose of the study is to propose an optimization model that tends to determine significant and insignificant resources and cost uncertainties in a particular healthcare service. Then compare results of optimization model with current costing methods used in healthcare. Eight-steps of TDABC method are applied to obtain Capacity Cost Rate (CCR) of each human resource involved in care-delivery cycle. Data was collected from interviewing staff and patients, financial reports, and human resource reports. Multiple linear regression (MLR) model is used to test strength of relationship between time and cost variable. Optimization model applied to decrease uncertainties by using Least Square method. Optimized model showed that human resources are not fully utilized which leads to error in costing model. Seven human resources out of eight are significant to model. Accuracy of optimized model is equal to 3%, with RMSE equal to 6. Total cost of the optimized model equal $177,492.45 which is better simulate actual cost $180,048. The research value is about building a new statistical model using MLR analysis to predict behavior and data trend of main healthcare segmentation: Human Resource. Also, propose a generic optimization model that can be used for specific healthcare service costing.
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骨科手术时间驱动的作业成本核算框架
本研究采用时间驱动的基于活动的成本核算(TDABC)方法来检查医疗保健部门的成本降低,Al-Emadi医院膝关节置换术科作为提供初级膝关节置换术咨询的案例研究。本研究的目的是提出一个优化模型,倾向于确定在特定的医疗保健服务显著和不显著的资源和成本的不确定性。然后将优化模型的结果与当前医疗成本计算方法进行比较。采用TDABC方法的8个步骤,得到了每个人力资源在护理提供周期中的能力成本率(CCR)。数据收集自对工作人员和患者的访谈、财务报告和人力资源报告。采用多元线性回归(MLR)模型检验时间与成本变量之间的关系强度。应用最小二乘法优化模型来减小不确定性。优化模型表明人力资源没有得到充分利用,导致成本计算模型出现误差。8个人力资源中有7个对模型很重要。优化后的模型精度为3%,RMSE为6。优化模型的总成本为$177,492.45,较好地模拟了实际成本$180,048。研究价值在于利用MLR分析建立新的统计模型来预测医疗保健主要细分市场:人力资源的行为和数据趋势。此外,提出可用于特定医疗保健服务成本计算的通用优化模型。
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