Prospective casemix-based funding, analysis and financial impact of cost outliers in all-patient refined diagnosis related groups in three Belgian general hospitals

被引:7
作者
Pirson M. [1 ,4 ]
Martins D. [1 ]
Jackson T. [2 ]
Dramaix M. [3 ,4 ]
Leclercq P. [1 ]
机构
[1] Health Economics Department, School of Public Health, Université de Bruxelles
[2] School of Public Health, LaTrobe University, Bundoora, Vic.
[3] Biostatistics, School of Public Health, Université Libre de Bruxelles, Brussels
[4] School of Public Health, Université Libre de Bruxelles, Brussels
关键词
All-patient refined diagnosis related groups; Hospital costs; Hospital funding; Outliers; Prospective payment system;
D O I
10.1007/s10198-005-0331-0
中图分类号
学科分类号
摘要
This study examined the impact of cost outliers in term of hospital resources consumption, the financial impact of the outliers under the Belgium casemix-based system, and the validity of two "proxies" for costs: length of stay and charges. The cost of a 11 hospital stays at three Belgian general hospitals were calculated for the year 2001. High resource use outliers were selected according to the following rule: 75th percentile + 1.5 xinter-quartile range. The frequency of cost outliers varied from 7% to 8% across hospitals. Explanatory factors were: major or extreme severity of illness, longer length of stay, and intensive care unit stay. Cost outliers account for 22-30% of hospital costs. One-third of length-of-stay outliers are not cost outliers, and nearly one-quarter of charges outliers are not cost outliers. The current funding system in Belgium does not penalise hospitals having a high percentage of outliers. The billing generated by these patients largely compensates for costs generated. Length of stay and charges are not a good approximation to select cost outliers. © Springer Medizin Verlag 2006.
引用
收藏
页码:55 / 65
页数:10
相关论文
共 34 条
[1]  
Closon M.C., Maes N., Réformes du système de financement des hôpitaux en Belgique, J Econ Med, 1, pp. 69-82, (1998)
[2]  
Averill R., Goldfield N., Hughes J., Bonazelli J., McCullough E., Steinbeck B., Mullin R., Tangg A., All Patient Refined Diagnosis Related Groups (APR-DRGs) Version 20.0. Methodology Overview, (2003)
[3]  
Jackson T., Using computerised patient-level costing data for setting DRG weights: The Victorian (Australia) cost weight studies, Health Policy, 56, pp. 149-163, (2001)
[4]  
Change in methodology for determining payment for extraordinarily high-cost cases (cost outliers) under the acute care hospital inpatient and long-term care hospital prospective payment systems, Fed Regist, 68, pp. 34493-34515, (2003)
[5]  
Konig B., Toepfer T., DRGs: The new course of therapy for German health care, McKinsey Health Eur, 3, pp. 42-49, (2004)
[6]  
Cots F., Elvira D., Castells X., Relevance of outlier cases in case mix systems and evaluation of trimming methods, Health Care Manag Sci, 6, pp. 27-35, (2003)
[7]  
Oye R.K., Bellamy P.E., Patterns of resource consumption in medical intensive care, Chest, 99, pp. 685-689, (1991)
[8]  
Cots F., Elvira D., Castells X., Dalmau E., Medicare's DRG-weights in a European environment: The Spanish experience, Health Policy, 51, pp. 31-47, (2000)
[9]  
Beaver C., Zhao Y., McDermid S., Hindle D., Casemix-based funding of Northern Territory public hospitals: Adjusting for severity and socioeconomic variations, Health Econ, 7, pp. 53-61, (1998)
[10]  
Bertges D.J., Zwolak R.M., Deaton D.H., Teigen C., Tapper S., Koslow A.R., Makaroun M.S., Current hospital costs and Medicare reimbursement for endovascular abdominal aortic aneurysm repair, J Vasc Surg, 37, pp. 272-279, (2003)