探討醫院經營效率及其影響因素:以資料包絡分析法與Tobit迴歸模型分析

Abstract

在健保總額制度以及醫療資源有限的情況下，如何增進醫院的經營效率，已成為當前醫療管理面臨的重要課題。本研究利用資料包絡分析法(DEA)與Tobit迴歸模型，並以SPSS for Window 26.0 套裝軟體進行皮爾森相關性分析、Kolmogorov-Smirnov常態分佈檢定及Kruskal-Wallis進行無母數檢定，強化Tobit模型之合理性與解釋力。分析臺灣143所醫院的經營效率，研究資料範圍涵蓋2019至2022年。選取6個投入變項（總床數、醫師人數、護產人數、醫事人員數、全日平均三班護理人員數及醫療成本）和3個產出變項（住院日數、門住合計醫療點數及醫療收入），於第一階段以資料包絡分析法(DEA)計算經營效率，進一步使用Tobit迴歸分析多項解釋變數對經營效率的影響，包括急診轉住院暫留大於48小時比例(ER48)、佔床率(BOR)、出院後3日再住院比例(ER3D)、全日平均護病比(NPR)、非健保佔醫收比例(NNHI) 與住院醫療點數的比例(IPN)等，最後分析解釋變數對不同屬性醫院經營效率的影響。研究結果發現，COVID疫情對醫院經營效率有顯著負面影響。500床以上醫院效率較高，而500床以下醫院可能因床位運用不佳而影響效率。急診轉住院暫留超過48小時比例對公立醫院效率有正向影響，但對500床以上醫院則為負向影響。佔床率提高對公立醫院效率有顯著正向影響。全日平均護病比高對健保分區之北區與中區醫院效率有顯著負向影響，北區更為明顯。非健保收入比例提高對公立醫院效率有正向影響，但對區域醫院則為負向影響。住院醫療點數比例提高對健保分區之臺北區與東區醫院效率有正向影響，臺北區更為明顯。建議醫院管理者加強非健保收入管理，並建立有效的經營效率評估機制，以提升資源運用效率，能應對醫療財務壓力，並優化住院管理流程，降低急診壅塞，提高醫療資源效率，以能促進醫療體系永續發展。This study employs Data Envelopment Analysis (DEA) and the Tobit regression model to examine the operational efficiency of 143 hospitals in Taiwan, using panel data spanning from 2019 to 2022. Six input variables were selected total number of beds, number of physicians, number of nurses and midwives, number of allied healthcare personnel, average full-time three-shift nursing staff, and total medical costs. Three output variables were included: number of inpatient days, total National Health Insurance(NHI) points for inpatient and outpatient services, and total medical revenue.In the first stage, DEA was applied to calculate the efficiency scores of each hospital. In the second stage, the Tobit regression model was used to ex2024plore the effects of various explanatory variables on hospital efficiency. These included the proportion of emergency-to-inpatient transfers staying in the emergency department for over 48 hours (ER48), bed occupancy rate(BOR), 3-day readmission rate after discharge(ER3D), average full-time nurse-to-patient ratio(NPR), the proportion of non-NHI income to total medical revenue (NNHI), and the proportion of inpatient NHI points(IPN). The study also analyzed how these explanatory variables affected efficiency across hospitals with different ownership types, sizes, and regions.The results indicate that the COVID-19 pandemic had a significantly negative impact on hospital operational efficiency. Hospitals with more than 500 beds demonstrated higher efficiency, whereas hospitals with fewer than 500 beds may suffer from suboptimal bed utilization. ER48 showed a significantly positive effect on the efficiency of public hospitals but a negative effect on hospitals with more than 500 beds. Higher bed occupancy rates were associated with improved efficiency in public hospitals. Regarding workforce indicators, higher NPR values were negatively associated with efficiency in hospitals located in the Northern and Central NHI regions, with a more pronounced negative impact observed in the Northern region. For financial structure, a higher proportion of non-NHI income had a significantly positive effect on the efficiency of public hospitals but a negative effect on regional hospitals. Furthermore, a higher IPN ratio positively influenced hospital efficiency in both the Taipei and Eastern NHI regions, with Taipei exhibiting a more prominent effect.It is recommended that hospital administrators strengthen the management of non-NHI income sources and establish effective mechanisms for evaluating operational efficiency. Enhancing resource allocation efficiency can help mitigate financial pressures, optimize inpatient care processes, alleviate emergency department overcrowding, and improve overall healthcare resource efficiency—ultimately contributing to the sustainable development of the healthcare system.