Categorization of Medication Safety Errors in Ambulatory Electronic Health Records

Authors

  • Karen Paul Zimmer, MD, MPH Jefferson Health
  • David C. Classen, MD, MS University of Utah
  • Jessica M. Cole, BS University of Utah

DOI:

https://doi.org/10.33940/med/2021.3.2

Abstract

Preventable medication errors continue to affect the quality and consistency in the delivery of care. While numerous studies on medication safety have been performed in the inpatient setting, a review of ambulatory patient safety by the American Medical Association found that medication safety errors were the most frequent safety problems in the outpatient arena. The leading cause of ambulatory safety problems, adverse drug events (ADEs), are common, with estimates of more than 2 million ADEs each year in the ambulatory Medicare population alone, and these events are frequently preventable. We conducted an environmental scan that allowed us to create our own categorization schema of medication safety errors in electronic healthcare records (EHRs) found in the outpatient setting and observed which of these were additionally supported in the literature. This study combines data from the Collaborative Healthcare Patient Safety Organization (CHPSO), with several key articles in the area of medication errors in the EHR era.

Method: To best utilize the various EHR ambulatory medication events submitted into CHPSO’s database, we chose to create a framework to bucket the near misses or adverse events (AEs) submitted to the database. This newly created categorization scheme was based on our own drafted categorization labels of events, after a high-level review, and from two leading articles on physician order entry. Additionally, we conducted a literature review of computerized provider order entry (CPOE) medication errors in the ambulatory setting. Within the newly created categorization scheme, we organized the articles based on issues addressed so we could see areas that were supported by the literature and what still needed to be researched.

Results: We initially screened the CHPSO database for ambulatory safety events and found 25,417 events. Based on those events, an initial review was completed, and 19,242 events were found in the “Medication or Other Substance” and “Other” categories, in which the EHR appeared to have been a potential contributing factor. This review identified a subset of 2,236 events that were then reviewed. One hundred events were randomly selected for further review to identify common categories. The most common categories in which errors occurred were orders in order sets and plans (n=12) and orders crossing or not crossing encounters (n=12), incorrect order placed on correct patient (n=10), orders missing (n=8), standing orders (n=8), manual data entry errors (n=6), and future orders (n=6).

Conclusion: There were several common themes seen in this analysis of ambulatory medication safety errors related to the EHR. Common among them were incorrect orders consisting of examples such as dose errors or ordering the wrong medication. The manual data entry errors consisted of height or weight being entered incorrectly or entering the wrong diagnostic codes. Lastly, different sources of medication safety information demonstrate a diversity of errors in ambulatory medication safety. This confirms the importance of considering more than one source when attempting to comprehensively describe ambulatory medication safety errors.

Author Biographies

Karen Paul Zimmer, MD, MPH, Jefferson Health

Karen Paul Zimmer (Kpzimmer@outlook.com), a pediatrician board certified in informatics, consults in the areas of health information technology (HIT), patient safety, and quality for nonprofit organizations, HIT companies, EHR vendors, and government agencies. She has over 25 years of combined experience with a focus on process improvement and strategic planning. Dr. Zimmer was formerly the medical director for the ECRI Institute Patient Safety Organization (PSO), as well as the medical director for the Patient Safety, Risk, and Quality Group. Her past works extend from implementation of IT and Quality Improvement (QI) programs at Johns Hopkins Hospital to leading government-sponsored HIT collaboratives. She is also an expert in evaluation processes, as she designed and studied a formal educational evaluation for pediatric residents at Johns Hopkins, where she held the rank of adjunct assistant professor in the Department of Pediatrics. Earlier in her career, she was involved in policy on the Clinton Health Care Task Force. She completed her term as a member of the National Quality Forum (NQF) Committee: HIT Patient Safety Measures Expert Panel. She is on the medical staff at Nemours/Alfred I. duPont Hospital for Children, an associate professor in the Department of Pediatrics at Thomas Jefferson University, and an instructor at the Jefferson College of Population Health.

David C. Classen, MD, MS, University of Utah

David C. Classen is a professor of Medicine at the University of Utah, a consultant in Infectious Diseases and Clinical Epidemiology at the University of Utah School of Medicine in Salt Lake City, and the chief medical information officer (CMIO) at Pascal Metrics. Dr. Classen developed the medication safety programs at Intermountain Healthcare, served as chair of the Intermountain Healthcare Clinical Quality Committee for Drug Use and Evaluation, and was also the initial developer of patient safety research at Intermountain Healthcare. In addition he developed, implemented, and evaluated a computerized physician order entry (CPOE) program at LDS Hospital that significantly improved the safety of medication use. He was a member of the Institute of Medicine Committee (IOM) that developed the National Quality Report on Health Care Delivery and was also a member of the IOM Committee on Patient Safety Data Standards. He was recently a member of the IOM Committee on Health Information Technology and Patient Safety. Dr. Classen is an advisor to the Leapfrog Group and has developed and implemented the CPOE/EHR flight simulator for the Agency for Healthcare Research and Quality (AHRQ) and the NQF. 

Jessica M. Cole, BS, University of Utah

Jessica M. Cole is a regulatory research coordinator (project manager) of the University of Utah Department of Internal Medicine and Division of Epidemiology. She began working at the University of Utah in 2009, supporting various roles within the School of Medicine. In 2017, she started her career path in research as a study coordinator and in two short years advanced from managing single-site projects to multisite projects. She currently supports projects within the University of Utah and the Veterans Administration (VA) Salt Lake City Health Care System.

References

Institute of Medicine. Health IT and Patient Safety: Building Safer Systems for Better Care. Washington, DC: National Academies Press, 2012.

James JT. A New, Evidence-Based Estimate of Patient Harms Associated With Hospital Care. J Patient Saf. 2013;9:122–128.

Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The Incidence and Severity of Adverse Events Affecting Patients After Discharge From the Hospital. Ann Intern Med. 2003; 138(3):161-7.

Lorincz CY, Drazen E, Sokol PE, et al. Research in Ambulatory Patient Safety 2000–2010: A 10-Year Review. Chicago, IL: American Medical Association; 2011.

Gurwitz JH, Field TS, Harrold LR et al. Incidence and Preventability of Adverse Drug Events Among Older Persons in the Ambulatory Setting. JAMA. 2003 Mar 5;289(9):1107-16.

Gandhi TK, Weingart SN, Borus J et al. Adverse Drug Events in Ambulatory Care. N Engl J Med. 2003; 348:1556-64.

Office of the National Coordinator for Health IT (ONC). Improving Medication Safety in Ambulatory Care: The Role E-Prescribing. 2015 Contract Number HHSP23320095651WC

Blumenthal D. Stimulating the Adoption of Health Information Technology. N Engl J Med. 2009;360(15):1477-9.

Office of the National Coordinator for Health IT (ONC). Health IT Dashboard. https://dashboard.healthit.gov, Accessed August 12, 2017.

Powers C, Gabriel MH, Encinosa W, Mostashari F, Bynum J. Meaningful Use Stage 2 E-Prescribing Threshold and Adverse Drug Events in the Medicare Part D Population with Diabetes. J Am Med Inform Assoc. 2015. doi: 10.1093/jamia/ocv036.

Schiff GD, Amato MG, Eguale T, et al. Computerised Physician Order Entry-Related Medication Errors: Analysis of Reported Errors and Vulnerability Testing of Current Systems. BMJ Qual Saf. 2015;24(4):264-271. doi: 10.1136/bmjqs-2014-003555.

Roe S, Long R, King K. Pharmacies Miss Half of Dangerous Drug Combinations. Dec 15, 2017 Chicago Tribune. https://www.chicagotribune.com/investigations/ct-drug-interactions-pharmacy-met-20161214-story.html

Kilbridge PM, Welebob EM, Classen DC. Development of the Leapfrog Methodology for Evaluating Hospital Implemented Inpatient Computerized Physician Order Entry Systems. Qual Saf Health Care. 2006;15(2):81-4.

Metzger J, Welebob E, Bates DW, Lipsitz S, Classen DC. Mixed Results in the Safety Performance of Computerized Physician Order Entry. Health Aff (Millwood). 2010;29(4):655-63.

Jha AK, Orav EJ, Ridgway AB, Zheng J, Epstein AM. Does the Leapfrog Program Help Identify High-Quality Hospitals? Jt Comm J Qual Patient Saf. 2008;34(6):318-25.

Chaparro JD, Classen DC, Danforth M, Stockwell DC, Longhurst CA. National Trends in Safety Performance of Electronic Health Record Systems in Children’s Hospitals. J Am Med Inform Assoc. 2016 Sep 16.

Brigham and Women’s Hospital, Harvard Medical School, Partners HealthCare. (2015). Computerized Prescriber Order Entry Medication Safety (CPOEMS): Uncovering and Learning From Errors. Washington, DC: US FDA.

Schiff GD, Amato MG, Eguale T, Boehne JJ, Wright A, Koppel R, Seger AC. (2015). Computerised Physician Order Entry-Related Medication Errors: Analysis of Reported Errors and Vulnerability Testing of Current Systems. BMJ Qual Saf, 24(4), 264–271.

Aita M, Belvedere O, De Carlo E, Deroma L, De Pauli F, Gurrieri L, Gianpiero F. (2013). Chemotherapy Presribing Errors: An Observational Study on the Role of Information Technology and Computerized Order Entry Systems. BMC Health Services Research, 13, 522.

Nanji KC, Rothschild JM, Boehne JJ, Keohane CA, Ash JS, & Poon EG (2014). Unrealized Potential and Residual Consequences of Electronic Prescribing on Pharmacy Workflow in the Outpatient Pharmacy. J Am Med Inform Assoc, 21(3), 481–486.

Priya K, Joy N, Thottumkal AV, Warrier AR, Krishna SG, & Joseph N. (2017). Impact of Electronic Prescription Audit Process to Reduce Outpatient Medication Errors. Indian J Pharm Sci, 79(6), 1017-1022.

Magrabi F, Liaw ST, Arachi D, Runciman W, Coiera E, & Kidd MR. (2016). Identifying Patient Safety Problems Associated With Information Technology in General Practice: An Analysis of Incident Reports. BMJ Qual Saf, 25(11), 870-880.

Quist AJ, Hickman TT, Amato MG, Volk LA, Salazar A, Robertson A, Schiff GD. (2017). Analysis of Variations in the Display of Drug Names in Computerized Prescriber-Order-Entry Systems. Am J Health-Syst Pharm, 74(7), 499-509.

Quist AJ, Robertson A, Thach TT, Volk LA, Wright A, Phansalkar S, Schiff GD. (2014). Examining the Potential for CPOE System Design and Functionality to Contribute to Medication Errors. J Gen Intern Med, S92.

Nanji KC, Rothschild JM, Salzberg C, Keohane CA, Zigmont K, Devita J, Poon EG. (2011). Errors Associated With Outpatient Computerized Prescribing Systems. J Am Med Inform Assoc, 18(6), 767-773.

Dhavle AA, Rupp MT, Sow M, & Lengkong V. (2015). A Continuous Quality Improvement Initiative for Electronic Prescribing in Ambulatory Care. Am J Med Qual, 30(6), 598-600.

Eguale T, Amato M, Slight SP, Seger AC, Whitney DL, Bates DW, & Schiff GD. (2014). Where Do Current Computerized Physician Order Entries (CPOE) Stand in Averting/Facilitating Medication Errors in the United States and Canada? J Gen Intern Med, S256.

Hou J-Y, Cheng K-J, Bai K-J, Chen H-Y, Wu W-H, Lin Y-M, & Wu M-TM. (2013). The Effect of a Computerized Pediatric Dosing Decision Support System on Pediatric Dosing Errors. J Food Drug Anal, 21(3), 286-291.

Chaparro JD, Classen DC, Danforth M, Stockwell DC, & Longhurst CA. (2017). National Trends in Safety Performance of Electronic Health Record Systems in Children’s Hospitals. J Am Med Inform Assoc, 24(2), 268-274

Kukreti V, Cosby R, Cheung A, & Lankshear S. (2014, August). Computerized Prescriber Order Entry in the Outpatient Oncology Setting: From Evidence to Meaningful Use. Curr Oncol, 21(4), e604-e612.

Linsky A, & Simon SR. (2013). Medication Discrepancies in Integrated Electronic Health Records. BMJ Qual Saf, 22(2), 103-109.

Sethurama U, Kannikeswaran N, Murray KP, Zidan MA, & Chamberlain JM. (2015). Prescription Errors Before and After Introduction of Electronic Medication Alert System in a Pediatric Emergency Department. Acad Emerg Med, 22(6), 714-719.

Abramson, EL, Malhotra, S, Fischer, K, Edwards, A, Pfoh, ER., Osorio, SN, Kaushal, R. (2011). Transitioning Between Electronic Health Records: Effects on Ambulatory Prescribing Safety. J Gen Intern Med, 26(8), 868-874.

Slight S, Eguale T, Amato M, Seger A, Whitney D, Bates D, & Schiff G. (2014). Understanding the Vulnerabilities of Electronic Prescribing Systems for Patient Safety. Int J Pharm Pract, 22(2), S68.

Ranji SR, Rennke S, & Wachter RM. (2014). Computerised Provider Order Entry Combined With Clinical Decision Support Systems to Improve Medication Safety: A Narrative Review. BMJ Qual Saf, 23(9), 773-780.

Abramson EL, & Bates DW. (2012). Ambulatory Prescribing Errors Among Community-Based Providers in Two States. J Am Med Inform Assoc, 19(4), 644-48.

Beeler PE, Orav EJ, Seger DL, Dykes PC, & Bates DW. (2016). Provider Variation in Responses to Warnings: Do the Same Providers Run Stop Signs Repeatedly? J Am Med Inform Assoc, 23(e1), e93–e98.

Cho I, Slight SP, Nanji KC, Seger DL, Maniam N, Dykes PC, & Bates DW. (2014). Understanding Physicians’ Behavior Toward Alerts About Nephrotoxic Medications in Outpatients: A Cross-Sectional Analysis. BMC Nephrol, 15(1), 200.

Cho, I, Slight SP, Nanji KC, Seger DL, Maniam N, Fiskio JM, Bates DW. (2015). The Effect of Provider Characteristics on the Responses to Medication-Related Decision Support Alerts. Int J Med Inform, 84(9), 630-639.

Czock D, Konias M, Seidling HM, Kaitschmidt J, Schwenger V, Zeier M, & Haefeli WE. (2015). Tailoring of Alerts Substantially Reduces the Alert Burden in Computerized Clinical Decision Support for Drugs That Should Be Avoided in Patients With Renal Disease. J Am Med Inform Assoc, 22(4), 881–887.

Duke JD, Li X, & Dexter P. (2013). Adherence to Drug-Drug Interaction Alerts in High-Risk Patients: A Trial of Context-Enhanced Alerting. J Am Med Inform Assoc, 20(3), 494–498.

Vanderman AJ, Moss JM, Bryan III WE, Sloane R, Jackson GL, & Hastings SN. (2017). Evaluating the Impact of Medication Safety Alerts on Prescribing of Potentially Inappropriate Medications for Older Veterans in an Ambulatory Care Setting. J Pharm Pract, 30(1), 82-88.

image of pharmacist will pill bottle in room of file drawers on screen of laptop

Published

2021-03-17

How to Cite

Zimmer, K. P., Classen, D. C., & Cole, J. M. (2021). Categorization of Medication Safety Errors in Ambulatory Electronic Health Records. Patient Safety, 3(1), 23–33. https://doi.org/10.33940/med/2021.3.2

Issue

Section

Original Research and Articles
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