Presenting Multiple Drug Alerts in an Ambulatory Electronic Prescribing System

Summary

Objective: This study explores alternative approaches to the display of drug alerts, and examines whether and how human-factors based interface design can be used to improve the prescriber’s perception about drug alert presentation, signal detection from noisy alert data, and their comprehension of clinical decision support during electronic prescribing.

Methods: We reviewed issues with presenting multiple drug alerts in electronic prescribing systems. User-centered design, consisting of iterative usability and prototype testing was applied. After an iterative design phase, we proposed several novel drug alert presentation interfaces; expert evaluation and formal usability testing were applied to access physician prescribers’ perceptions of the tools. We mapped drug alert attributes to different interface constructs. We examined four different interfaces for presenting multiple drug alerts.

Results: A TreeDashboard View was better perceived than a text-based ScrollText View with respect to the ability to detect critical information, the ability to accomplish tasks, and the perceptional efficacy of finding information.

Conclusion: A robust model for studying multiple drug-alert presentations was developed. Several drug alert presentation interfaces were proposed. The TreeDashboard View was better perceived than the text-based ScrollText View in delivering multiple drug alerts during a simulation of electronic prescribing.

Citation: Xie M, Weinger MB, Gregg WM, Johnson KB. Presenting multiple drug alerts in an ambulatory electronic prescribing system: A usability study of novel prototypes. Appl Clin Inf 2014; 5: 334–348 http://dx.doi.org/10.4338/ACI-2013-10-RA-0092

Keywords

Electronic prescribing - clinical decision support - drug alert - adverse drug event - user interface

 

Conflicts of interest

The authors declare that they have no conflicts of interest in the research.

• References

• 1 eHealth Initiative.. Electronic Prescribing: toward maximum value and rapid adoption. Recommendations for optimal design and implementation to improve care, increase efficiency and reduce costs in ambulatory care (eRx Report). A Report of the Electronic Prescribing Initiative eHealth Initiative.; Washington, D. C.: April 14, 2004. 2004
• 2 Bell DS, Cretin S, Marken RS, Landman AB. A conceptual framework for evaluating outpatient electronic prescribing systems based on their functional capabilities. J Am Med Inform Assoc 2004; 11 (Suppl. 01) 60-70. PubMed PMID: 14527975. Pubmed Central PMCID: 305459.
• 3 Miller RA, Gardner RM, Johnson KB, Hripcsak G. Clinical decision support and electronic prescribing systems: a time for responsible thought and action. J Am Med Inform Assoc 2005; 12 (Suppl. 04) 403-409. PubMed PMID: 15905481. Pubmed Central PMCID: 1174885.
• 4 Magrabi F, Aarts J, Nohr C, Baker M, Harrison S, Pelayo S, Talmon J, Sittig DF, Coiera E. A comparative review of patient safety initiatives for national health information technology. Int J Med Inform 2013; 82 (Suppl. 05) e139-e148. PubMed PMID: 23266061.
• 5 Teich JM, Osheroff JA, Pifer EA, Sittig DF, Jenders RA, Panel CDSER. Clinical decision support in electronic prescribing: recommendations and an action plan: report of the joint clinical decision support workgroup. J Am Med Inform Assoc 2005; 12 (Suppl. 04) 365-376. PubMed PMID: 15802474. Pubmed Central PMCID: 1174880.
• 6 Miller RA, Waitman LR, Chen S, Rosenbloom ST. The anatomy of decision support during inpatient care provider order entry (CPOE): empirical observations from a decade of CPOE experience at Vanderbilt. J Biomed Inform 2005; 38 (Suppl. 06) 469-485. PubMed PMID: 16290243. Pubmed Central PMCID: 1518541.
• 7 Center for Information Technology Leadership.. The Value of CPOE in ambulatory settings. Full Report. Available from www. CITL.org and www.HIMSS.org. 2003
• 8 First DataBank.. Drug Information Framework www.FirstDatabank.com.
• 9 Bergk V, Gasse C, Schnell R, Haefeli WE. Requirements for a successful implementation of drug interaction information systems in general practice: results of a questionnaire survey in Germany. Eur J Clin Pharmacol 2004; 60 (Suppl. 08) 595-602. PubMed PMID: 15351924.
• 10 Taylor LK, Tamblyn R. Reasons for physician non-adherence to electronic drug alerts. Stud Health Technol Inform 2004; 107 Pt 2 1101-1105. PubMed PMID: 15360983.
• 11 Surescripts.. Surescripts’ National Progress Report on E-Prescribing and Safe-Rx Rankings, Year 2012 ( http://www.surescripts.com/downloads/npr/National Progress Report on E Prescribing Year 2012.pdf.
• 12 Aspden P, Wolcott J, Bootman JL, Cronenwett LR. Preventing Medication Errors: Quality Chasm Series. The National Academies Press; 2007.
• 13 Centers for Medicare and Medicaid Services.. Medicare Prescription Drug Improvement and Modernization Act (MMA). 2003
• 14 Middleton B, Bloomrosen M, Dente MA, Hashmat B, Koppel R, Overhage JM, Payne TH, Rosenbloom ST, Weaver C, Zhang J, American Medical Informatics A. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J Am Med Inform Assoc 2013; 20 e1 e2-e8. PubMed PMID: 23355463. Pubmed Central PMCID: 3715367.
• 15 Horsky J, Schiff GD, Johnston D, Mercincavage L, Bell D, Middleton B. Interface design principles for usable decision support: a targeted review of best practices for clinical prescribing interventions. J Biomed Inform 2012; 45 (Suppl. 06) 1202-1216. PubMed PMID: 22995208.
• 16 Armijo DMC, Werner K. Electronic Health Record Usability: Interface Design Considerations. AHRQ Publication No. 09(10)-0091–2-EF. Rockville, MD: Agency for Healthcare Research and Quality.; 2009
• 17 Ash JS, Sittig DF, Campbell EM, Guappone KP, Dykstra RH. Some unintended consequences of clinical decision support systems. AMIA Annu Symp Proc 2007; 26-30. PubMed PMID: 18693791. Pubmed Central PMCID: 2813668.
• 18 Coleman JJ, van der Sijs H, Haefeli WE, Slight SP, McDowell SE, Seidling HM, Eiermann B, Aarts J, Ammenwerth E, Ferner RE, Slee A. On the alert: future priorities for alerts in clinical decision support for computerized physician order entry identified from a European workshop. BMC Med Inform Decis Mak 2013; 13: 111. PubMed PMID: 24083548. Pubmed Central PMCID: 3850158.
• 19 Coleman JJ, van der Sijs H, Haefeli WE, Slight SP, McDowell SE, Seidling HM, Eiermann B, Aarts J, Ammenwerth E, Slee A, Ferner RE. Correction: on the alert: future priorities for alerts in clinical decision support for computerized physician order entry identified from a European workshop. BMC Med Inform Decis Mak 2013; 13 (Suppl. 01) 122. PubMed PMID: 24188454. Pubmed Central PMCID: 3830500.
• 20 Embi PJ, Leonard AC. Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study. J Am Med Inform Assoc 2012; 19 e1 e145-e148. PubMed PMID: 22534081. Pubmed Central PMCID: 3392862.
• 21 Payne TH, Nichol WP, Hoey P, Savarino J. Characteristics and override rates of order checks in a practitioner order entry system. Proc AMIA Symp 2002; 602-606 PubMed PMID: 12463894. Pubmed Central PMCID: 2244252.
• 22 Isaac T, Weissman JS, Davis RB, Massagli M, Cyrulik A, Sands DZ, Weingart SN. Overrides of medication alerts in ambulatory care. Arch Intern Med 2009; 169 (Suppl. 03) 305-311. PubMed PMID: 19204222.
• 23 Rosenbloom ST, Geissbuhler AJ, Dupont WD, Giuse DA, Talbert DA, Tierney WM, Plummer WD, Stead WW, Miller RA. Effect of CPOE user interface design on user-initiated access to educational and patient information during clinical care. J Am Med Inform Assoc 2005; 12 (Suppl. 04) 458-473. PubMed PMID: 15802487. Pubmed Central PMCID: 1174891.
• 24 Johnson KB, Lehmann CU. Council on Clinical Information Technology of the American Academy of P. Electronic prescribing in pediatrics: toward safer and more effective medication management. Pediatrics 2013; 131 (Suppl. 04) e1350-e1356. PubMed PMID: 23530183.
• 25 Sears A, Jacko J. The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications. 2002
• 26 Horn RE. Mapping Hypertext: The Analysis, Organization, and Display of Knowledge for the Next Generation of On-Line Text and Graphics. Lexington, MA: The Lexington Institute; 1989
• 27 Xie M, Tomlinson M, Bodenheimer B. Interface design for a modern software ticketing system. Proceedings of the 42nd annual Southeast regional conference; Huntsville, Alabama: ACM; 2004
• 28 Julie A, Jacko AS. The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications (Human Factors and Ergonomics). Lea; 2002.
• 29 Jaspers MW. A comparison of usability methods for testing interactive health technologies: methodological aspects and empirical evidence. Int J Med Inform 2009; 78 (Suppl. 05) 340-353. PubMed PMID: 19046928.
• 30 Jaspers MW, Steen T, van den Bos C, Geenen M. The think aloud method: a guide to user interface design. Int J Med Inform 2004; 73 (11–12) 781-795. PubMed PMID: 15491929.
• 31 Kushniruk A, Patel V, Cimino JJ, Barrows RA. Cognitive evaluation of the user interface and vocabulary of an outpatient information system. Proc AMIA Annu Fall Symp 1996; 22-26 PubMed PMID: 8947620. Pubmed Central PMCID: 2232971.
• 32 Nielsen J, Landauer TK. A mathematical model of the finding of usability problems. Proceedings of the INTERACT ’93 and CHI ’93 Conference on Human Factors in Computing Systems. Amsterdam; The Netherlands: 169166: ACM 1993: 206-213.
• 33 Kantner L, Rosenbaum S. Usability studies of WWW sites: heuristic evaluation vs. laboratory testing. Proceedings of the 15th annual international conference on Computer documentation; Salt Lake City, Utah, USA. 263388: ACM 1997: 153-160.
• 34 Norman K, Shneiderman B, Harper B. QUIS: The Questionnaire for User Interface Satisfaction. http://www.cs.umd.edu/hcil/quis.
• 35 Christian K, Benjamin BB. Benefits of animated scrolling. CHI ’05 extended abstracts on Human factors in computing systems Portland, OR, USA: ACM; 2005
• 36 Tidwell J. Showing Complex Data Using TreeTable. Designing Interfaces: Patterns for Effective Interaction Design. 2005
• 37 Spang L, Trell E, Fioretos M, Kielstein V, Nasr M. „Healthometer“ –an instrument for self-distributed health screening and prevention in the population. J Med Syst 1998; Oct; 22 (Suppl. 05) 339-355 PubMed PMID: 9809274.
• 38 van Twillert B, Bremer M, Faber AW. Computer-generated virtual reality to control pain and anxiety in pediatric and adult burn patients during wound dressing changes. J Burn Care Res 2007; 28 (Suppl. 05) 694-702. PubMed PMID: 17667488.
• 39 Xie M, Johnson K. Applying human factors research to alert-fatigue in e-prescribing. AMIA Annu Symp Proc 2007; 1161. PubMed PMID: 18694257.