Process and risk analysis to reduce errors in clinical laboratories

被引:21
作者
Signori, Chiara
Ceriotti, Ferruccio
Sanna, Alberto
Plebani, Mario
Messeri, Gianni
Ottomano, Cosimo
Di Serio, Francesca
Bonini, Pierangelo
机构
[1] Diagnostica e Ricerca, San Raffaele SpA, Milan
[2] Department of Laboratory Medicine, University Hospital of Padova, Padova
[3] Central Laboratory, University Hospital of Florence, Florence
[4] Department of Laboratory Medicine, Ospedali Riuniti, Bergamo
[5] University Hospital of Bari, Bari
[6] Università Vita-Salute, San Raffaele, Milan
[7] Diagnostica e Ricerca, San Raffaele SpA, 20132 Milano
关键词
Error and risk of error; Iatrogenic damage; Process analysis; Risk assessment;
D O I
10.1515/CCLM.2007.172
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Background: An important point in improving laboratory quality is the definition of some indicators to be monitored as measures of a laboratory trend. The continuous observation of these indicators can help to reduce errors and risk of errors, thus enhancing the laboratory outcome. In addition, the standardization of risk evaluation techniques and the definition of a set of indicators can eventually contribute to a benchmarking process in clinical laboratories. Methods: Five Italian hospital laboratories cooperated in a project in which methodologies for process and risk analysis, usually applied in fields other than healthcare (typically aeronautical and transport industries), were adapted and applied to laboratory medicine. The collaboration of a board of experts played a key role in underlining the limits of the proposed techniques and adapting them to the laboratory situation. A detailed process analysis performed in each center was the starting point, followed by risk analysis to evaluate risks and facilitate benchmarking among the participants. Results and conclusions: The techniques applied allowed the formulation of a list of non-conformities that represented risks of errors. The level of risk related to each was quantified and graphically represented for each laboratory to identify the risk area characteristic for each of the centers involved. ©2007 by Walter de Gruyter.
引用
收藏
页码:742 / 748
页数:7
相关论文
共 14 条
[1]  
Plebani M., Ceriotti F., Messeri G., Ottomano C., Pansini N., Bonini P.A., Laboratory network of excellence: Enhancing patient safety and service effectiveness, Clin Chem Lab Med, 44, pp. 150-160, (2006)
[2]  
Integration DEfinition for Function modeling (IDEF). Draft, Federal Information Processing Standards Publication, 183, (1993)
[3]  
Cognitive task analysis, (2000)
[4]  
Bonar J., Cunningham R., Schultz J., An object-oriented architecture for intelligent tutoring, Proceedings of the ACM Conference on Object-Oriented Programming Systems, Language and Applications, pp. 269-276, (1986)
[5]  
Zachary W.W., Ryder J.M., Hicinbothom J.H., Cognitive task analysis and modeling of decision making in complex environments, Decision making under stress: Implications for training and simulation, (1998)
[6]  
Redmill F., Chudleigh M., Catmur J., System safety: HAZOP and software HAZOP, (1999)
[7]  
Kennedy R., Kirwan B., Development of a hazard and operability-based method for identifying safety management vulnerabilities in high risk systems, Saf Sci, 30, pp. 249-274, (1998)
[8]  
Kirwan B., A guide to practical human reliability assessment, (1994)
[9]  
Cagno E., Di Giulio A., Trucco P., Risk and causes-of-risk assessment for an effective industrial safety management, Int J Reliab Qual Saf Eng, 7, pp. 113-128, (2000)
[10]  
Atkins, IOE, Rail Safety and Standards Board - Final Report, (2004)