Analysis of clinical decision support system malfunctions: A case series and survey

Journal of the American Medical Informatics Association

Volumn 23, Issue 6, 2016, Pages 1068-1076

  Wright, Adam ^a,b,c   Hickman, Thu Trang T ^a   McEvoy, Dustin ^c   Aaron, Skye ^a   Ai, Angela ^a   Andersen, Jan Marie ^a   Hussain, Salman ^a,d   Ramoni, Rachel ^b,e   Fiskio, Julie ^a   Sittig, Dean F ^f   Bates, David W ^a,b,c  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c PARTNERS HEALTHCARE   (United States)

^d DARTMOUTH INSTITUTE FOR HEALTH POLICY AND CLINICAL PRACTICE   (United States)

^e HARVARD SCHOOL OF DENTAL MEDICINE   (United States)

^f UNIVERSITY OF TEXAS   (United States)

Author keywords

Anomaly detection; Clinical decision support; Electronic health records; Machine learning; Safety

Indexed keywords

ACETYLSALICYLIC ACID; AMIODARONE; THIENOPYRIDINE DERIVATIVE;

ARTICLE; CLINICAL DECISION SUPPORT SYSTEM; CORONARY ARTERY DISEASE; DATA BASE; DRUG CLASSIFICATION; DRUG HYPERSENSITIVITY; ELECTRONIC HEALTH RECORD; HUMAN; KNOWLEDGE MANAGEMENT; MEDICAL INFORMATION SYSTEM; SCREENING TEST; SOFTWARE; THYROID FUNCTION; DEVICE FAILURE; HEALTH SERVICES RESEARCH; HOSPITAL; LEAD POISONING; MASSACHUSETTS; MEDICAL ERROR; PHYSICIAN ORDER ENTRY SYSTEM; PHYSIOLOGIC MONITORING; PRESCHOOL CHILD;

AMIODARONE; BOSTON; CHILD, PRESCHOOL; DECISION SUPPORT SYSTEMS, CLINICAL; ELECTRONIC HEALTH RECORDS; EQUIPMENT FAILURE; HOSPITALS, SPECIAL; HUMANS; LEAD POISONING; MEDICAL ERRORS; MEDICAL ORDER ENTRY SYSTEMS; MONITORING, PHYSIOLOGIC; ORGANIZATIONAL CASE STUDIES; SOFTWARE;

EID: 84994783028     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1093/jamia/ocw005     Document Type: Article

References (41)

1. Buntin MB, Burke MF, Hoaglin MC, Blumenthal D. The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Affairs (Project Hope). 2011;30(3):464-471.
2. Lyman JA, Cohn WF, Bloomrosen M, Detmer DE. Clinical decision support: progress and opportunities. J Am Med Inform Assoc. 2010;17(5):487-492.
3. Kawamoto K, Lobach DF. Proposal for fulfilling strategic objectives of the U.S. Roadmap for national action on clinical decision support through a serviceoriented architecture leveraging HL7 services. J Am Med Inform Assoc. 2007;14(2):146-155.
4. Garg AX, Adhikari NKJ, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. JAMA. 2005;293(10):1223-1238.
5. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330(7494):765.
6. Chaudhry B, Wang J, Wu S, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Int Med. 2006;144(10):742-752.
7. Office of the National Coordinator for Health Information Technology. Step 5: Achieve Meaningful Use Stage 1 -Clinical Decision Support Rule. 2014. https://www.healthit.gov/providers-professionals/achieve-meaningful-use/core-measures-2/clinical-decision-support-rule. Accessed February 2, 2016.
8. Centers for Medicare and Medicaid Services (CMS). Stage 2 Eligible Professional Meaningful Use Core Measures Measure 6 of 17. 2012. http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentive Programs/downloads/Stage2_EPCore_6_ClinicalDecisionSupport.pdf. Accessed February 12, 2016.
9. Vashitz G, Meyer J, Parmet Y, Liebermann N, Gilutz H. Factors affecting physicians compliance with enrollment suggestions into a clinical reminders intervention. Stud Health Technol Informatics. 2010;160 (Pt 2):796-800.
10. Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Qual Safety Health Care. 2010;19(Suppl 3):i68-i74.
11. Shackelton RJ, Marceau LD, Link CL, McKinlay JB. The intended and unintended consequences of clinical guidelines. J Eval Clin Pract. 2009;15(6):1035-1042.
12. McCoy AB, Waitman LR, Lewis JB, et al. A framework for evaluating the appropriateness of clinical decision support alerts and responses. J Am Med Inform Assoc. 2012;19(3):346-352.
13. Landman AB, Takhar SS, Wang SL, et al. The hazard of software updates to clinical workstations: a natural experiment. J Am Med Inform Assoc. 2013;20:187-190.
14. Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2006;13(5):547-556.
15. Bright TJ, Wong A, Dhurjati R, et al. Effect of clinical decision-support systems: a systematic review. Ann Int Med. 2012;157(1):29-43.
16. Ash JS, Sittig DF, Poon EG, Guappone K, Campbell E, Dykstra RH. The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2007;14(4):415-423.
17. Ash JS, Sittig DF, Campbell EM, Guappone KP, Dykstra RH. Some unintended consequences of clinical decision support systems. AMIA Annual Symposium Proceedings/AMIA Symposium AMIA Symposium. 2007; 26-30.
18. Aleccia J. MSNBC.com. 2011. Nurse's suicide highlights twin tragedies of medical errors. http://www.msnbc.msn.com/id/43529641/ns/healthhealth_ care/t/nurses-suicide-highlights-twin-tragedies-medical-errors/. Accessed February 12, 2016.
19. Associated Press. Veterans Given Wrong Drug Doses due to Glitch. 2009. http://www.msnbc.msn.com/id/28655104/#. Tph-b3I2Y9Z. Accessed February 12, 2016.
20. Graham J, Dizikes C. Baby's death spotlights safety risks linked to computerized systems. 2011. http://www.latimes.com/health/ct-met-technologyerrors-20110627,0,2158183.story. Accessed February 12, 2016.
21. Schulte F, Schwartz E. As Doctors Shift to Electronic Health Systems, Signs of Harm Emerge. 2010. http://huffpostfund.org/stories/2010/04/doctors-shiftelectronic-health-systems-signs-harm-emerge. Accessed September 9, 2013.
22. Silver JD, Hamill SD. Doctor, Nurse Disciplined by UPMC in Kidney Transplant Case. 2011. http://www.post-gazette.com/pg/11147/1149429-114-0.stm#ixzz1amZZEw6Y. Accessed February 12, 2016.
23. US News. E-prescribing Doesn't Slash Errors, Study Finds. 2011. http://health.usnews.com/health-news/family-health/articles/2011/06/30/e-prescribing-doesnt-slash-errors-study-finds. Accessed February 12, 2016.
24. Institute of Medicine Committee on Patient Safety and Health Information Technology. Health IT and Patient Safety Building Safer Systems for Better Care. Washington, DC: Institute of Medicine; 2012.
25. McCoy AB, Wright A, Sittig DF. Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development. J Am Med Inform Assoc. 2015;22(5):1081-1088.
26. Matheny ME, Sequist TD, Seger AC, et al. A randomized trial of electronic clinical reminders to improve medication laboratory monitoring. J Am Med Inform Assoc. 2008;15(4):424-429.
27. Hripcsak G. Monitoring the monitor: automated statistical tracking of a clinical event monitor. Comp Biomed Res. 1993;26(5):449-466.
28. Sittig DF, Pace NL, Gardner RM, Beck E, Morris AH. Implementation of a computerized patient advice system using the HELP clinical information system. Comp Biomed Res. 1989;22(5):474-487.
29. Office of the National Coordinator for Health Information Technology, Ash JS, Singh H, Sittig DF. System Interfaces SAFER Guide. 2014. https://www. healthit.gov/safer/guide/sg005. Accessed February 12, 2016.
30. Institute of Medicine. Committee on Patient Safety and Health Information Technology. Health IT and Patient Safety: Building Safer Systems for Better Care. Washington, DC: National Academies Press; 2012.
31. Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223-1238.
32. Wright A, Goldberg H, Hongsermeier T, Middleton B. A description and functional taxonomy of rule-based decision support content at a large integrated delivery network. J Am Med Inform Assoc. 2007;14(4):489-496.
33. Collins SA, Bavuso K, Zuccotti G, Rocha RA. Lessons learned for collaborative clinical content development. Appl Clin Informatics. 2013;4(2): 304-316.
34. Sittig DF, Wright A, Meltzer S, et al. Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records. BMC Med Informatics Decis Mak. 2011;11:13.
35. Sittig DF, Wright A, Simonaitis L, et al. The state of the art in clinical knowledge management: an inventory of tools and techniques. Int J Med Informatics. 2010;79(1):44-57.
36. Hongsermeier T, Glaser J. Managing the investment in clinical decision support. In: Greenes RA, ed. Clinical Decision Support. The Road to Broad Adoption, 2nd edn. New York: Elsevier; 2014:665-688.
37. Sittig DF, Classen DC, Singh H. Patient safety goals for the proposed Federal Health Information Technology Safety Center. J Am Med Inform Assoc. 2015;22(2):472-478.
38. US Department of Health and Human Services. 45 CFR Part 170: 2015 Edition Health Information Technology (Health IT) Certification Criteria, 2015 Edition Base Electronic Health Record (EHR) Definition, and ONC Health IT Certification Program Modifications. 2015. https://s3.amazonaws.com/public-inspection.federalregister.gov/2015-06612.pdf. Accessed February 12, 2016.
39. Sittig DF, Ash JS, Singh H. The SAFER guides: empowering organizations to improve the safety and effectiveness of electronic health records. Am J Managed Care. 2014;20(5):418-423.
40. Sittig DF, Classen DC. Safe electronic health record use requires a comprehensive monitoring and evaluation framework. JAMA. 2010;303(5): 450-451.
41. Office of the National Coordinator for Health Information Technology. Health Information Technology Patient Safety Action & Surveillance Plan. 2014. https://www.healthit.gov/sites/default/files/safety_plan_master.pdf. Accessed February 12, 2016.