A Retrospective Analysis of Interruptive versus Non-interruptive Clinical Decision Support for Identification of Patients Needing Contact Isolation

Summary

Background: In determining whether clinical decision support (CDS) should be interruptive or non-interruptive, CDS designers need more guidance to balance the potential for interruptive CDS to overburden clinicians and the potential for non-interruptive CDS to be overlooked by clinicians.

Objectives: (1)To compare performance achieved by clinicians using interruptive CDS versus using similar, non-interruptive CDS. (2)To compare performance achieved using non-interruptive CDS among clinicians exposed to interruptive CDS versus clinicians not exposed to interruptive CDS.

Methods: We studied 42 emergency medicine physicians working in a large hospital where an interruptive CDS to help identify patients requiring contact isolation was replaced by a similar, but non-interruptive CDS. The first primary outcome was the change in sensitivity in identifying these patients associated with the conversion from an interruptive to a non-interruptive CDS. The second primary outcome was the difference in sensitivities yielded by the non-interruptive CDS when used by providers who had and who had not been exposed to the interruptive CDS. The reference standard was an epidemiologist-designed, structured, objective assessment.

Results: In identifying patients needing contact isolation, the interruptive CDS-physician dyad had sensitivity of 24% (95% CI: 17%-32%), versus sensitivity of 14% (95% CI: 9%-21%) for the non-interruptive CDS-physician dyad (p = 0.04). Users of the non-interruptive CDS with prior exposure to the interruptive CDS were more sensitive than those without exposure (14% [95% CI: 9%-21%] versus 7% [95% CI: 3%-13%], p = 0.05).

Limitations: As with all observational studies, we cannot confirm that our analysis controlled for every important difference between time periods and physician groups.

Conclusions: Interruptive CDS affected clinicians more than non-interruptive CDS. Designers of CDS might explicitly weigh the benefits of interruptive CDS versus its associated increased clinician burden. Further research should study longer term effects of clinician exposure to interruptive CDS, including whether it may improve clinician performance when using a similar, subsequent non-interruptive CDS.

Citation: Pevnick JM, Li X, Grein J, Bell DS, Silka P. A retrospective analysis of interruptive versus non-interruptive clinical decision support for identification of patients needing contact isolation. Appl Clin Inf 2013; 4: 569–582

http://dx.doi.org/10.4338/ACI-2013-04-RA-0021

Keywords

Clinical decision support systems - computer-assisted decision making - infection control

 

Conflicts of Interest Statement

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

• References

• 1 Garg AX, Adhikari NKJ, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. JAMA 2005; 293 (10) 1223-1238. doi: 10.1001/jama.293.10.1223.
• 2 Moxey A, Robertson J, Newby D, Hains I, Williamson M, Pearson SA. Computerized clinical decision support for prescribing: provision does not guarantee uptake. J Am Med Inform Assoc 2010; 17 (Suppl. 01) 25-33. Epub 2010/01/13. doi: 10.1197/jamia. M3170. PubMed PMID: 20064798; PubMed Central PMCID: PMC2995634.
• 3 McDonald CJ. Use of a computer to detect and respond to clinical events: its effect on clinician behavior. Annals of Internal Medicine 1976; 84 (Suppl. 02) 162. PubMed PMID: 6964557.
• 4 van der Sijs H, Aarts J, Vulto A, Berg M. Overriding of drug safety alerts in computerized physician order entry. Journal of the American Medical Informatics Association 2006; 13 (Suppl. 02) 138-47. doi: 10.1197/jamia. M1809.
• 5 Weingart SN, Toth M, Sands DZ, Aronson MD, Davis RB, Phillips RS. Physicians’ decisions to override computerized drug alerts in primary care. Archives of internal medicine 2003; 163 (21) 2625-2631. Epub 2003/11/26. doi: 10.1001/archinte.163.21.2625. PubMed PMID: 14638563.
• 6 Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. New England Journal of Medicine 2010; 363 (Suppl. 06) 501-504. doi: doi:10.1056/NEJMp1006114.
• 7 Langberg M. Challenges to implementing CPOE: a case study of a work in progress at Cedars-Sinai. Mod Physician 2003; 7: 21-22.
• 8 Saleem JJ, Patterson ES, Militello L, Render ML, Orshansky G, Asch SM. Exploring barriers and facilitators to the use of computerized clinical reminders. J Am Med Inform Assoc 2005; 12 (Suppl. 04) 4384-47. Epub 2005/04/02. doi: 10.1197/jamia. M1777. PubMed PMID: 15802482; PubMed Central PMCID: PMC1174889.
• 9 Strom BL, Schinnar R, Aberra F, Bilker W, Hennessy S, Leonard CE, Pifer E. Unintended effects of a computerized physician order entry nearly hard-stop alert to prevent a drug interaction: a randomized controlled trial. Archives of internal medicine 2010; 170 (17) 1578-1583. Epub 2010/09/30. doi: 10.1001/arch-internmed.2010.324. PubMed PMID: 20876410.
• 10 Strom BL, Schinnar R, Bilker W, Hennessy S, Leonard CE, Pifer E. Randomized clinical trial of a customized electronic alert requiring an affirmative response compared to a control group receiving a commercial passive CPOE alert: NSAID–warfarin co-prescribing as a test case. Journal of the American Medical Informatics Association 2010; 17 (Suppl. 04) 411-415. doi: 10.1136/jamia.2009.000695.
• 11 Tamblyn R, Huang A, Taylor L, Kawasumi Y, Bartlett G, Grad R, Jacques A, Dawes M, Abrahamowicz M, Perreault R, Winslade N, Poissant L, Pinsonneault A. A randomized trial of the effectiveness of on-demand versus computer-triggered drug decision support in primary care. J Am Med Inform Assoc 2008; 15 (Suppl. 04) 430-438. Epub 2008/04/26. doi: 10.1197/jamia. M2606. PubMed PMID: 18436904; PubMed Central PMCID: PMCPMC2442270.
• 12 Matheny ME, Sequist TD, Seger AC, Fiskio JM, Sperling M, Bugbee D, Bates DW, Gandhi TK. A randomized trial of electronic clinical reminders to improve medication laboratory monitoring. J Am Med Inform Assoc 2008; 15 (Suppl. 04) 424-429. Epub 2008/04/26. doi: 10.1197/jamia. M2602. PubMed PMID: 18436905; PubMed Central PMCID: PMCPMC2442256.
• 13 Rollman Bl, Hanusa BH, Gilbert T, Lowe HJ, Kapoor WN, Schulberg HC. The electronic medical record: A randomized trial of its impact on primary care physicians and initial management of major depression. Archives of Internal Medicine 2001; 161 (Suppl. 02) 189-197.
• 14 Phansalkar S, van der Sijs H, Tucker AD, Desai AA, Bell DS, Teich JM, Middleton B, Bates DW. Drug–drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records. Journal of the American Medical Informatics Association 2013; 20 (Suppl. 03) 489-493. doi: 10.1136/amiajnl-2012-001089.
• 15 Lobach D, Sanders GD, Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux R, Samsa G, Hasselblad V, Williams JW, Wing L, Musty M, Kendrick AS. Enabling health care decisionmaking through clinical decision support and knowledge management. Evidence Report No. 203. (Prepared by the Duke Evidence-based Practice Center under Contract No. 290-2007-10066-I.) AHRQ Publication No. 12-E001-EF. Rockville, MD: Agency for Healthcare Research and Quality.; April 2012.
• 16 Horsky J, Schiff G, Johnston D, Mercincavage L, Bell DS, Middleton B. Interface design principles for usable decision support: A targeted review of best practices for clinical prescribing interventions. Journal of Biomedical Informatics 2012; 45 (Suppl. 06) 1202-1216.
• 17 Siegel JD, Rhinehart E, Jackson M, Chiarello L. and the Healthcare Infection Control Practices Advisory Committee, 2007 Guideline for isolation precautions: preventing transmission of infectious agents in healthcare settings.
• 18 Afif W, Huor P, Brassard P, Loo VG. Compliance with methicillin-resistant Staphylococcus aureus precautions in a teaching hospital. American Journal of Infection Control 2002; 30 (Suppl. 07) 430-433. doi: 10.1067/mic.2002.125174.
• 19 Clock SA, Cohen B, Behta M, Ross B, Larson EL. Contact precautions for multidrug-resistant organisms: Current recommendations and actual practice. American Journal of Infection Control 2010; 38 (Suppl. 02) 105-111.
• 20 Mamlin BW, Overhage JM, Tierney W, Dexter P, McDonald CJ. Clinical decision support within the Regenstrief medical record system. In: Berner ES, ed: Springer New York 2007: 190-190.
• 21 Kho AN, Dexter PR, Warvel JS, Belsito AW, Commiskey M, Wilson SJ, Hui SL, McDonald CJ. An effective computerized reminder for contact isolation of patients colonized or infected with resistant organisms. International journal of medical informatics 2008; 77 (Suppl. 03) 194-198.
• 22 Owen CB, Galewsky A. EmSTAT™, A comprehensive point-of-care clinical information system for emergency medicine. Proc Annu Symp Comput Appl Med Care 1990: 944-945.
• 23 Muto CA, Jernigan JA, Ostrowsky BE, Richet HM, Jarvis WR, Boyce JM, Farr BM. SHEA guideline for preventing nosocomial transmission of multidrug-resistant strains of Staphylococcus aureus and enter-ococcus. Infection control and hospital epidemiology : the official journal of the Society of Hospital Epidemiologists of America 2003; 24 (Suppl. 05) 362-386. Epub 2003/06/06. doi: 10.1086/502213. PubMed PMID: 12785411.
• 24 Pittet D, Safran E, Harbarth S, Borst F, Copin P, Rohner P, Scherrer JR, Auckenthaler R. Automatic alerts for methicillin-resistant Staphylococcus aureus surveillance and control: role of a hospital information system. Infection control and hospital epidemiology : the official journal of the Society of Hospital Epidemiologists of America 1996; 17 (Suppl. 08) 496-502. Epub 1996/08/01. PubMed PMID: 8875292.
• 25 Schriger DL, Baraff LJ, Buller K, Shendrikar MA, Nagda S, Lin EJ, Mikulich VJ, Cretin S. Implementation of clinical guidelines via a computer charting system. Journal of the American Medical Informatics Association 2000; 7 (Suppl. 02) 186-195. doi: 10.1136/jamia.2000.0070186.
• 26 Schriger DL, Baraff LJ, Rogers WH, Cretin S. Implementation of clinical guidelines using a computer charting system. JAMA: The Journal of the American Medical Association 1997; 278 (19) 1585-1590. doi: 10.1001/jama.1997.03550190049043.
• 27 Berner ES, Lande TJ. Overview of clinical decision support systems, clinical decision support systems. In: Berner ES, ed: Springer New York 2007: 3-3.
• 28 Ray HN, Boxwala AA, Anantraman V, Ohno-Machado L. Providing context-sensitive decision-support based on WHO guidelines. Proceedings of the AMIA Symposium 2002: 637-641. PubMed PMID: 12463901.
• 29 McCoy AB, Waitman LR, Lewis JB, Wright JA, Choma DP, Miller RA, Peterson JF. A framework for evaluating the appropriateness of clinical decision support alerts and responses. Journal of the American Medical Informatics Association 2012; 19 (Suppl. 03) 346-352. doi: 10.1136/amiajnl-2011-000185.
• 30 Bates DW, Kuperman GJ, Wang S, Gandhi T, Kittler A, Volk L, Spurr C, Khorasani R, Tanasijevic M, Middleton B. Ten commandments for effective clinical decision support: Making the practice of evidence-based medicine a reality. Journal of the American Medical Informatics Association 2003; 10 (Suppl. 06) 523-530. doi: 10.1197/jamia. M1370.
• 31 Sim I, Berlin A. A framework for classifying decision support systems. AMIA Annu Symp Proc. 2003: 599-603. Epub 2004/01/20. PubMed PMID: 14728243; PubMed Central PMCID: PMC1480261.
• 32 Shea S, DuMouchel W, Bahamonde L. A Meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting. Journal of the American Medical Informatics Association 1996; 3: 399-409.