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  1. Usin MF, Ramesh P, Lopez CG
    Malays J Pathol, 2004 Jun;26(1):43-8.
    PMID: 16190106
    Event reporting can provide data to study the failure points of an organization's work process. As part of the ongoing efforts to improve transfusion safety, a Medical Event Reporting System Transfusion Medicine, (MERS - TM) as designed by Kaplan et al was implemented in the Transfusion Medicine Unit of the University Malaya Medical Centre to provide a standardized means of organized data collection and analysis of transfusion errors, adverse events and near misses. An event reporting form was designed to detect, identify, classify and study the frequency and pattern of events occurring in the unit. Events detected were classified according to Eihdhoven Classification model (ECM) adopted for MERS - TM. Since our system reported all events, we called it Event Reporting System - Transfusion Medicine (ERS-TM). Data was collected and analyzed from the reporting forms for a period of five months from January 15th to June 15th 2002. The initial half of the period was a process of evaluation during which 118 events were reported, coded, analyzed and corrective measures adopted to prevent the recurrence of the same event. The latter half saw the reporting of 122 events following the adoption of corrective measures. There was a reduction in the occurrence of some events and an increase in others, which were mainly beyond the organization's control. A longer period of evaluation is necessary to identify the underlying contributory causes that can be useful to develop plans for corrective and preventive action and thereby reduce the rate of recurrence of errors through proper training and adoption of just culture.
    Matched MeSH terms: Medical Errors/classification*
  2. Yusof M, Sahroni MN
    Int J Health Care Qual Assur, 2018 Oct 08;31(8):1014-1029.
    PMID: 30415623 DOI: 10.1108/IJHCQA-07-2017-0125
    PURPOSE: The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors.

    DESIGN/METHODOLOGY/APPROACH: A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors.

    FINDINGS: Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model.

    RESEARCH LIMITATIONS/IMPLICATIONS: Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis.

    PRACTICAL IMPLICATIONS: This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors.

    ORIGINALITY/VALUE: Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.

    Matched MeSH terms: Medical Errors/classification*
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