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DOI: 10.1055/s-0038-1638683
A Bio-medical Informatics Perspective on Human Factors
How Human Factors Influence Adoption of Healthcare Information TechnologyCorrespondence to:
Publication History
Publication Date:
07 March 2018 (online)
Summary
Objectives: to select and summarize excellent research papers published in 2009 in the field of human factors in bio-medical informatics.
Methods: we attempt to derive a synthetic overview of the activity and new trends in this field, from a selection of research papers published in 2009.
Results: it is possible to identify commonalities in this diverse domain: healthcare information technologies (HIT) adoption still occupies a central role in the fieldwith research focused mainly on measuring impact and influence of this adoption.
Conclusion: The HIT community is giving birth to interdisciplinary research and clear methods to optimize implementation and subsequent achievement of managerial objectives. It also tries to synthesize the major findings in workshops, meetings and networks. The best paper selection of articles on human factors shows examples of excellent research on methods concerning original options to assess the importance of healthcare personnel psycho-sociology when confronted to the adoption of new tools and process which still does not prevent failures but will help learning from them.
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Keywords
Medical informatics - International Medical Informatics Association - yearbook - human factors
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References
- 1 Dick RS, Steen EB. The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC: National Academies Press; 1991
- 2 Dick RS, Steen EB, Detmer DE. The Computer- Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC: National Academies Press; 1997
- 3 Bates DW, Leape LL, Cullen DJ, Laird N, Petersen LA, Teich JM. et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998; 280 (15) 1311-6.
- 4 Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma’Luf N. et al. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc 1999; 06 (04) 313-21.
- 5 Teich J M, Merchia PR, Schmiz JL, Kuperman GJ, Spurr CD, Bates DW. Effects of computerized physician order entry on prescribing practices. Arch Intern Med 2000; 160 (18) 2741-7.
- 6 Ash JS, Bates DW. Factors and forces affecting EHR system adoption: report of a 2004ACMI discussion. J Am Med Inform Assoc 2005; 12 (01) 8-12.
- 7 Initiative, eHealth. Electronic prescribing: Toward maximum value and rapid adoption. Washington, DC: eHealth Initiative; 2004
- 8 Schade CP, Sullivan FM, de Lusignan S, Madeley J. e-Prescribing, efûciency, quality: lessons from the computerization of UK family practice. J Am Med InformAssoc 2006; 13 (05) 470-5.
- 9 Gans D, Kralewski J, Hammons T, Dowd B. Medical groups’ adoption of electronic health records and information systems. Practices are encountering greater-than-expected barriers to adopting an EHR system, but the adoption rate continues to rise. Millwood: s.n., Health Aff 2005; 24 (05) 1323-33.
- 10 Burt CW, Hing E, Woodwell D. Electronic medical record use by ofûce-based physicians. s.l.: United States: National Center for Health Statistics. 2005
- 11 Poon EG, Blumenthal D, Jaggi T, Honour MM, Bates DW, Kaushal R. Overcoming barriers to adopting and implementing computerized physician order entry systems in U.S. hospitals. Health Aff 2004; 23 (04) 184-90.
- 12 Halamka J, Aranow M, Ascenzo C, Bates DW, Berry K, Debor G. et al. E-Prescribing collaboration in Massachusetts: early experiences from regional prescribing projects. J Am Med Inform Assoc 2006; 13 (03) 239-44.
- 13 Koppel R, Metlay JP, Cohen A, Abaluck B, Localio AR, Kimmel SE. et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005; 293 (10) 1197-203.
- 14 Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC. et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005; 116 (06) 1506-12.
- 15 Middleton B, Hammond WE, Brennan PF, Cooper GF. Accelerating U.S. EHR adoption: how to get there from here. Recommendations based on the 2004 ACMI retreat. J Am Med Inform Assoc 2005; 12 (01) 13-9.
- 16 Nebeker JR, Hoffman JM, Weir CR. High rates of adverse drug events in a highly computerized hospital. Arch Intern Med 2005; 165 (10) 1111-6.
- 17 Hollingworth W, Devine EB, Hansen RN, Lawless NM, Comstock BA, Wilson-Norton JL. et al. The impact of e-prescribing on prescriber and staff time in ambulatory care clinics: a time motion study. J Am Med Inform Assoc 2007; 14: 722-30.
- 18 Tierney WM, Miller ME, Overhage JM, McDonald CJ. Physician inpatient order writing on microcomputer workstations. Effects on resource utilization. JAMA 1993; 269 (03) 379-83.
- 19 Bates DW, Boyle DL, Teich JM. Impact of computerized physician order entry on physician time. Proc Annu Symp Comput Appl Med Care 1994; 996.
- 20 Shu K, Boyle D, Spurr C, Horsky J, Heiman H, O’Connor P. et al. Comparison of time spent writing orders on paper with computerized physician order entry. Medinfo 2001; 10 (Suppl. 02) 1207-11.
- 21 Overhage J M, Perkins S, Tierney WM, McDonald CJ. Controlled trial of direct physician order entry: effects on physicians’ time utilization in ambulatory primary care internal medicine practices. J Am Med Inform Assoc 2001; 04: 361-71.
- 22 Pizziferri L, Kittler AF, Volk LA, Honour MM, Gupta S, Wang S. et al. Primary care physician time utilization before and after implementation of an electronic health record: a time-motion study. J Biomed Inform 2005; 38 (03) 176-88.
- 23 Bosman RJ. Impact of computerized information systems on workload in operating room and intensive care unit. Best Practice & Research Clinical Anaesthesiology 2009; 23: 15-26.
- 24 Mador RL, Shaw NT. The impact of a Critical Care Information System (CCIS) on time spent charting and in direct patient care by staff in the ICU: A review of the literature. Int J Med Inform. 2009 In press.
- 25 Beuscart-Zephir MC, Elkin P, Pelayo S, Beuscart R. The human factors engineering approach to biomedical informatics projects: state of the art, results, beneûts and challenges. Yearb Med Inform 2007; 109-27.
- 26 Horvath J. User experience & the business of healthcare. Human Factor Inc. white paper: 2010
- 27 Meyer R. A Bio-Medical Informatics Perspective on Human Factors. Findings from the Yearbook 2008 Section on Human Factors.Yearb Med Inform 2009; 59-62.
- 28 Beuscart-Zephir MC, Aarts J, Elkin P. Human factors engineering for healthcare IT clinical applications. Int J Med Inform 2010; 79 (04) 223-4.
Correspondence to:
-
References
- 1 Dick RS, Steen EB. The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC: National Academies Press; 1991
- 2 Dick RS, Steen EB, Detmer DE. The Computer- Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC: National Academies Press; 1997
- 3 Bates DW, Leape LL, Cullen DJ, Laird N, Petersen LA, Teich JM. et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998; 280 (15) 1311-6.
- 4 Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma’Luf N. et al. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc 1999; 06 (04) 313-21.
- 5 Teich J M, Merchia PR, Schmiz JL, Kuperman GJ, Spurr CD, Bates DW. Effects of computerized physician order entry on prescribing practices. Arch Intern Med 2000; 160 (18) 2741-7.
- 6 Ash JS, Bates DW. Factors and forces affecting EHR system adoption: report of a 2004ACMI discussion. J Am Med Inform Assoc 2005; 12 (01) 8-12.
- 7 Initiative, eHealth. Electronic prescribing: Toward maximum value and rapid adoption. Washington, DC: eHealth Initiative; 2004
- 8 Schade CP, Sullivan FM, de Lusignan S, Madeley J. e-Prescribing, efûciency, quality: lessons from the computerization of UK family practice. J Am Med InformAssoc 2006; 13 (05) 470-5.
- 9 Gans D, Kralewski J, Hammons T, Dowd B. Medical groups’ adoption of electronic health records and information systems. Practices are encountering greater-than-expected barriers to adopting an EHR system, but the adoption rate continues to rise. Millwood: s.n., Health Aff 2005; 24 (05) 1323-33.
- 10 Burt CW, Hing E, Woodwell D. Electronic medical record use by ofûce-based physicians. s.l.: United States: National Center for Health Statistics. 2005
- 11 Poon EG, Blumenthal D, Jaggi T, Honour MM, Bates DW, Kaushal R. Overcoming barriers to adopting and implementing computerized physician order entry systems in U.S. hospitals. Health Aff 2004; 23 (04) 184-90.
- 12 Halamka J, Aranow M, Ascenzo C, Bates DW, Berry K, Debor G. et al. E-Prescribing collaboration in Massachusetts: early experiences from regional prescribing projects. J Am Med Inform Assoc 2006; 13 (03) 239-44.
- 13 Koppel R, Metlay JP, Cohen A, Abaluck B, Localio AR, Kimmel SE. et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005; 293 (10) 1197-203.
- 14 Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC. et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005; 116 (06) 1506-12.
- 15 Middleton B, Hammond WE, Brennan PF, Cooper GF. Accelerating U.S. EHR adoption: how to get there from here. Recommendations based on the 2004 ACMI retreat. J Am Med Inform Assoc 2005; 12 (01) 13-9.
- 16 Nebeker JR, Hoffman JM, Weir CR. High rates of adverse drug events in a highly computerized hospital. Arch Intern Med 2005; 165 (10) 1111-6.
- 17 Hollingworth W, Devine EB, Hansen RN, Lawless NM, Comstock BA, Wilson-Norton JL. et al. The impact of e-prescribing on prescriber and staff time in ambulatory care clinics: a time motion study. J Am Med Inform Assoc 2007; 14: 722-30.
- 18 Tierney WM, Miller ME, Overhage JM, McDonald CJ. Physician inpatient order writing on microcomputer workstations. Effects on resource utilization. JAMA 1993; 269 (03) 379-83.
- 19 Bates DW, Boyle DL, Teich JM. Impact of computerized physician order entry on physician time. Proc Annu Symp Comput Appl Med Care 1994; 996.
- 20 Shu K, Boyle D, Spurr C, Horsky J, Heiman H, O’Connor P. et al. Comparison of time spent writing orders on paper with computerized physician order entry. Medinfo 2001; 10 (Suppl. 02) 1207-11.
- 21 Overhage J M, Perkins S, Tierney WM, McDonald CJ. Controlled trial of direct physician order entry: effects on physicians’ time utilization in ambulatory primary care internal medicine practices. J Am Med Inform Assoc 2001; 04: 361-71.
- 22 Pizziferri L, Kittler AF, Volk LA, Honour MM, Gupta S, Wang S. et al. Primary care physician time utilization before and after implementation of an electronic health record: a time-motion study. J Biomed Inform 2005; 38 (03) 176-88.
- 23 Bosman RJ. Impact of computerized information systems on workload in operating room and intensive care unit. Best Practice & Research Clinical Anaesthesiology 2009; 23: 15-26.
- 24 Mador RL, Shaw NT. The impact of a Critical Care Information System (CCIS) on time spent charting and in direct patient care by staff in the ICU: A review of the literature. Int J Med Inform. 2009 In press.
- 25 Beuscart-Zephir MC, Elkin P, Pelayo S, Beuscart R. The human factors engineering approach to biomedical informatics projects: state of the art, results, beneûts and challenges. Yearb Med Inform 2007; 109-27.
- 26 Horvath J. User experience & the business of healthcare. Human Factor Inc. white paper: 2010
- 27 Meyer R. A Bio-Medical Informatics Perspective on Human Factors. Findings from the Yearbook 2008 Section on Human Factors.Yearb Med Inform 2009; 59-62.
- 28 Beuscart-Zephir MC, Aarts J, Elkin P. Human factors engineering for healthcare IT clinical applications. Int J Med Inform 2010; 79 (04) 223-4.