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      Process support for risk mitigation: a case study of variability and resilience in vascular surgery

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          Abstract

          Objective

          To inform the design of IT support, the authors explored the characteristics and sources of process variability in a surgical care process that transcends multiple institutions and professional boundaries.

          Setting

          A case study of the care process in the Abdominal Aortic Aneurysm surveillance programme of three hospitals in Norway.

          Design

          Observational study of encounters between patients and surgeons accompanied by semistructured interviews of patients and key health personnel.

          Results

          Four process variety dimensions were identified. The captured process variations were further classified into intended and unintended variations according to the cause of the variations. Our main findings, however, suggest that the care process is best understood as systematised analysis and mitigation of risk. Even if major variations accommodated for the flexibility needed to achieve particular clinical aims and/or to satisfy patient preferences, other variations reflected healthcare actors' responses to risks arising from a lack of resilience in the existing system. On this basis, the authors outlined suggestions for a resilience-based approach by including awareness in workflow as well as feedback loops for adaptive learning. The authors suggest that IT process support should be designed to prevent process breakdowns with patient dropouts as well as to sustain risk-mitigating performance.

          Conclusion

          Process variation was in part induced by systemised risk mitigation. IT-based process support for monitoring processes such as that studied here should aim to ensure resilience and further mitigate risk to enhance patient safety.

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          Most cited references18

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          Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

          Developers of health care software have attributed improvements in patient care to these applications. As with any health care intervention, such claims require confirmation in clinical trials. To review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting benefit. We updated our earlier reviews by searching the MEDLINE, EMBASE, Cochrane Library, Inspec, and ISI databases and consulting reference lists through September 2004. Authors of 64 primary studies confirmed data or provided additional information. We included randomized and nonrandomized controlled trials that evaluated the effect of a CDSS compared with care provided without a CDSS on practitioner performance or patient outcomes. Teams of 2 reviewers independently abstracted data on methods, setting, CDSS and patient characteristics, and outcomes. One hundred studies met our inclusion criteria. The number and methodologic quality of studies improved over time. The CDSS improved practitioner performance in 62 (64%) of the 97 studies assessing this outcome, including 4 (40%) of 10 diagnostic systems, 16 (76%) of 21 reminder systems, 23 (62%) of 37 disease management systems, and 19 (66%) of 29 drug-dosing or prescribing systems. Fifty-two trials assessed 1 or more patient outcomes, of which 7 trials (13%) reported improvements. Improved practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system (success in 73% of trials vs 47%; P = .02) and studies in which the authors also developed the CDSS software compared with studies in which the authors were not the developers (74% success vs 28%; respectively, P = .001). Many CDSSs improve practitioner performance. To date, the effects on patient outcomes remain understudied and, when studied, inconsistent.
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            Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.

            Experts consider health information technology key to improving efficiency and quality of health care. To systematically review evidence on the effect of health information technology on quality, efficiency, and costs of health care. The authors systematically searched the English-language literature indexed in MEDLINE (1995 to January 2004), the Cochrane Central Register of Controlled Trials, the Cochrane Database of Abstracts of Reviews of Effects, and the Periodical Abstracts Database. We also added studies identified by experts up to April 2005. Descriptive and comparative studies and systematic reviews of health information technology. Two reviewers independently extracted information on system capabilities, design, effects on quality, system acquisition, implementation context, and costs. 257 studies met the inclusion criteria. Most studies addressed decision support systems or electronic health records. Approximately 25% of the studies were from 4 academic institutions that implemented internally developed systems; only 9 studies evaluated multifunctional, commercially developed systems. Three major benefits on quality were demonstrated: increased adherence to guideline-based care, enhanced surveillance and monitoring, and decreased medication errors. The primary domain of improvement was preventive health. The major efficiency benefit shown was decreased utilization of care. Data on another efficiency measure, time utilization, were mixed. Empirical cost data were limited. Available quantitative research was limited and was done by a small number of institutions. Systems were heterogeneous and sometimes incompletely described. Available financial and contextual data were limited. Four benchmark institutions have demonstrated the efficacy of health information technologies in improving quality and efficiency. Whether and how other institutions can achieve similar benefits, and at what costs, are unclear.
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              Tensions and paradoxes in electronic patient record research: a systematic literature review using the meta-narrative method.

              The extensive research literature on electronic patient records (EPRs) presents challenges to systematic reviewers because it covers multiple research traditions with different underlying philosophical assumptions and methodological approaches. Using the meta-narrative method and searching beyond the Medline-indexed literature, this review used "conflicting" findings to address higher-order questions about how researchers had differently conceptualized and studied the EPR and its implementation. Twenty-four previous systematic reviews and ninety-four further primary studies were considered. Key tensions in the literature centered on (1) the EPR ("container" or "itinerary"); (2) the EPR user ("information-processer" or "member of socio-technical network"); (3) organizational context ("the setting within which the EPR is implemented" or "the EPR-in-use"); (4) clinical work ("decision making" or "situated practice"); (5) the process of change ("the logic of determinism" or "the logic of opposition"); (6) implementation success ("objectively defined" or "socially negotiated"); and (7) complexity and scale ("the bigger the better" or "small is beautiful"). The findings suggest that EPR use will always require human input to recontextualize knowledge; that even though secondary work (audit, research, billing) may be made more efficient by the EPR, primary clinical work may be made less efficient; that paper may offer a unique degree of ecological flexibility; and that smaller EPR systems may sometimes be more efficient and effective than larger ones. We suggest an agenda for further research.
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                Author and article information

                Journal
                BMJ Qual Saf
                qshc
                qhc
                BMJ quality & safety
                BMJ Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-5415
                2044-5423
                16 February 2011
                August 2011
                16 February 2011
                : 20
                : 8
                : 672-679
                Affiliations
                [1 ]Department of Radiography, Sør-Trøndelag University College (HiST), Trondheim, Norway
                [2 ]Norwegian EHR Research Centre (NSEP), Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
                [3 ]Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
                [4 ]SINTEF Technology and Society, Industrial Management,Trondheim, Norway
                Author notes
                Correspondence to Berit Brattheim, Department of Radiography, Sør-Trøndelag University College (HiST), MTFS, O Kyrresegt 9, NO-7489 Trondheim, Norway; berit.j.brattheim@ 123456ntnu.no
                Article
                qhc45062
                10.1136/bmjqs.2010.045062
                3142343
                21325658
                c0f76227-add8-407f-af16-e0674296170b
                © 2011, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

                History
                : 19 January 2011
                Categories
                Original Research
                1506

                Public health
                risk management,process variation,information technology,healthcare quality improvement,patient safety

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