A Biomedical Informatics Perspective on Human Factors - How Human Factors Influence Information Technology Adoption

Summary

Objectives

to select and summarize excellent research published in 2010 in the field of bio-medical informatics human factors.

Methods

we attempt to derive a synthetic overview of the activity and new trends in this field, from a selection of worldwide research papers published during 2010.

Results

this year again, healthcare information technology (HIT) adoption occupies a central role in the field and leads to research focused mainly on measuring impact and factors influencing it. One of the selected papers especially dissects the anatomy of a nationwide personal electronic health record adoption failure.

Conclusions

Due to the vast and increasing amount of excellent works, choosing the best papers in human factors is a challenge. More and more the published work takes into account fundamental principles expressed in Grudin’s Laws, one form of which is: “When those who beneût from a technology are not those who do the work, then the technology is likely to fail or be subverted.”.

Keywords

Medical informatics - International Medical Informatics Association - yearbook - human factors

 

• References

• 1 Ash JS, Bates DW. Factors and forces affecting EHR system adoption: report of a 2004 ACMI discussion. J Am Med Inform Assoc 2005; 12 (01) 8-12.
• 2 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: 1311-16.
• 3 Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E. et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006; 144: 742-52.
• 4 Devine EB, Hansen RN, Wilson-Norton JL, Law-less NM, Fisk AW, Blough DK. et al. The impact of computerized provider order entry on medication errors in a multispecialty group practice. J Am Med Inform Assoc 2010; 17: 78-84.
• 5 King WJ, Paice N, Rangrej J, Forestell GJ, Swartz R. The effect of computerized physician order entry on medication errors and adverse drug events in pediatric inpatients. Pediatrics 2003; 112: 506-9.
• 6 Mekhjian HS, Kumar RR, Kuehn L, Bentley TD, Teater P, Thomas A. et al. Immediate benefits realized following implementation of physician order entry at an academic medical center. J Am Med Inform Assoc 2002; 09: 529-39.
• 7 Poon EG, Keohane CA, Yoon CS, Ditmore M, Bane A, Levtzion-Korach O. et al. Effect of barcode technology on the safety of medication administration. N Engl J Med 2010; 362: 1698-707.
• 8 Teich JM. et al. Effects of computerized physician order entry on prescribing practices. Arch Intern Med 2000; 160 (18) 2741-7.
• 9 DesRoches CM, Campbell EG, Rao SR, Donelan K, Ferris TG, Jha A. et al. Electronic health records in ambulatory care, a national survey of physicians. N Engl J Med 2008; 359: 50-60.
• 10 Furukawa MF, Raghu TS, Spaulding TJ, Vinze A. Adoption of health information technology for medication safety in U.S. Hospitals, 2006. Health Aff (Millwood) 2008; 27: 865-75.
• 11 Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG. et al. Use of electronic health records in U.S. hospitals. N Engl J Med 2009; 360: 1628-38.
• 12 Pedersen CA, Gumpper KF. ASHP national survey on informatics: Assessment of the adoption and use of pharmacy informatics in US hospitals- 2007. Am J Health Syst Pharm 2008; 65: 2244-64.
• 13 Meyer R, Degoulet P. Choosing the right amount of healthcare information technologies investments. Int J Med Inform 2010; Apr; 79 (04) 225-31 doi:10.1016/j.ijmedinf.2010.01.001.
• 14 Linder JA, Ma J, Bates DW, Middleton B, Stafford RS. Electronic health record use and the quality of ambulatory care in the United States. Arch Intern Med 2007; 167: 1400-5.
• 15 Zhou L, Soran CS, Jenter CA, Volk LA, Orav EJ, Bates DW. et al. The relationship between electronic health record use and quality of care over time. J Am Med Inform Assoc 2009; 16: 457-64.
• 16 Stead WW, Lin HS. editors. Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions. Washington DC: National Academies Press; 2009
• 17 US Department of Health and Human Services. Final rule on meaningful use. http:/edocket. access.gpo.gov/2010/pdf/2010-17207.pdf (accessed april 2011)
• 18 Ash JS, Sittig DF, Dykstra R, Campbell E, Guappone K. The unintended consequences of computerized provider order entry: Findings from a mixed methods exploration. Int J Med Inform 2009; 78 (Suppl. 01) S69-76.
• 19 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. J Am Med Inform Assoc 2005; 293: 1197-203.
• 20 Koppel R, Wetterneck T, Telles JL, Karsh BT. Workarounds to barcode medication administration systems: occurrences, causes and threats to patient safety. J Am Med Inform Assoc 2008; 15: 408-28.
• 21 Nebeker JR, Hoffman JM, Weir CR, Bennett CL, Hurdle JF. High rates of adverse drug events in a highly computerized hospital. Arch Intern Med 205; 165: 1111-16.
• 22 Peute LW, Aarts J, Bakker PJ, Jaspers MW. Anatomy of a failure: A sociotechnical evaluation of a laboratory physician order entry system implementation. Int J Med Inform 2010; Apr; 79 (04) e58-70.
• 23 Wears RL, Cook RI, Perry SJ. Automation, interaction, complexity, and failure: A case study. Reliability Engineering & System Safety 2006; 91: 1494-501.
• 24 Magrabi F, Ong MS, Runciman W, Coiera E. An analysis of computer-related patient safety incidents to inform the development of a classification. J Am Med Inform Assoc 2010; 17: 663-70.
• 25 Palm JM, Dart T, Dupuis I, Leneveut L, Degoulet P. Clinical Information System Post-Adoption Evaluation at the Georges Pompidou University Hospital. AMIA 2010 Symposium Proceedings 582-6.
• 26 Greenhalgh T, Hinder S, Stramer K, Bratan T, Russell J. Adoption, non-adoption, and abandonment of a personal electronic health record: case study of HealthSpace. BMJ 2010; 341: c5814.
• 27 Zheng K, Padman R, Krackhardt D, Johnson MP, Diamond HS. Social networks and physician adoption of electronic health records: insights from an empirical study. J Am Med Inform Assoc 2010; 17: 328-36.
• 28 Karsh BT, Weinger MB, Abbott PA, Wears RL. Health information technology: fallacies and sober realities. J Am Med Inform Assoc 2010; 17: 617-23.
• 29 Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Quart 2003; 27: 425e78.
• 30 Homans GC. The human group. New York: Harcourt Brace; 1950
• 31 Andre AD, Wickens CD. When users want what’s not best for them. Ergon Des 1995; 10-4.
• 32 Diaper D, Stanton N. editors. The Handbook of Task Analysis for Human-Computer Interaction. Mahwah, NJ: CRC Press, Lawrence Erlbaum Associates; 2003
• 33 Meyer R. A Bio-Medical Informatics Perspective on Human Factors. Findings from the Yearbook 2009 Section on Human Factors. Yearb Med Inform 2010; 106-9.
• 34 US Department of Health and Human Services. Strategic Health IT Advanced Research Projects (SHARP) Program. http://healthit.hhs.gov/ (accessed in May 2011)