Development of a Taxonomy for Medication-Related Patient Safety Events Related to Health Information Technology in Pediatrics
Background Although electronic health records (EHRs) are designed to improve patient safety, they have been associated with serious patient harm. An agreed-upon and standard taxonomy for classifying health information technology (HIT) related patient safety events does not exist.
Objectives We aimed to develop and evaluate a taxonomy for medication-related patient safety events associated with HIT and validate it using a set of events involving pediatric patients.
Methods We performed a literature search to identify existing classifications for HIT-related safety events, which were assessed using real-world pediatric medication-related patient safety events extracted from two sources: patient safety event reporting system (ERS) reports and information technology help desk (HD) tickets. A team of clinical and patient safety experts used iterative tests of change and consensus building to converge on a single taxonomy. The final devised taxonomy was applied to pediatric medication-related events assess its characteristics, including interrater reliability and agreement.
Results Literature review identified four existing classifications for HIT-related patient safety events, and one was iteratively adapted to converge on a singular taxonomy. Safety events relating to usability accounted for a greater proportion of ERS reports, compared with HD tickets (37 vs. 20%, p = 0.022). Conversely, events pertaining to incorrect configuration accounted for a greater proportion of HD tickets, compared with ERS reports (63 vs. 8%, p < 0.01). Interrater agreement (%) and reliability (kappa) were 87.8% and 0.688 for ERS reports and 73.6% and 0.556 for HD tickets, respectively.
Discussion A standardized taxonomy for medication-related patient safety events related to HIT is presented. The taxonomy was validated using pediatric events. Further evaluation can assess whether the taxonomy is suitable for nonmedication-related events and those occurring in other patient populations.
Conclusion Wider application of standardized taxonomies will allow for peer benchmarking and facilitate collaborative interinstitutional patient safety improvement efforts.
Keywordspatient safety - patient harm - safety management - electronic health records - medical informatics
Protection of Human and Animal Subjects
This project was reviewed by the Mayo Clinic Institutional Review Board and classified as quality improvement.
Received: 29 June 2020
Accepted: 21 August 2020
28 October 2020 (online)
© 2020. Thieme. All rights reserved.
Georg Thieme Verlag KG
Stuttgart · New York
- 1 Varghese J, Kleine M, Gessner SI, Sandmann S, Dugas M. Effects of computerized decision support system implementations on patient outcomes in inpatient care: a systematic review. J Am Med Inform Assoc 2018; 25 (05) 593-602
- 2 Brown CL, Mulcaster HL, Triffitt KL. et al. A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care. J Am Med Inform Assoc 2017; 24 (02) 432-440
- 3 Institute of Medicine. Health IT and Patient Safety: Building Safer Systems for Better Care. Available at: https://essentialhospitals.org/wp-content/uploads/2014/07/IOM-report-on-EHR-and-Safety.pdf . Accessed September 8, 2020
- 4 Prgomet M, Li L, Niazkhani Z, Georgiou A, Westbrook JI. Impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: a systematic review and meta-analysis. J Am Med Inform Assoc 2017; 24 (02) 413-422
- 5 Singh H, Sittig DF. Measuring and improving patient safety through health information technology: The Health IT Safety Framework. BMJ Qual Saf 2016; 25 (04) 226-232
- 6 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 (02) 472-478
- 7 Sittig DF, Ash JS, Singh H. The SAFER guides: empowering organizations to improve the safety and effectiveness of electronic health records. Am J Manag Care 2014; 20 (05) 418-423
- 8 Sittig DF, Singh H. Electronic health records and national patient-safety goals. N Engl J Med 2012; 367 (19) 1854-1860
- 9 Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Qual Saf Health Care 2010; 19 (Suppl. 03) i68-i74
- 10 Kim MO, Coiera E, Magrabi F. Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review. J Am Med Inform Assoc 2017; 24 (02) 246-250
- 11 Phipps AR, Paradis M, Peterson KA. et al. Reducing serious safety events and priority hospital-acquired conditions in a pediatric hospital with the implementation of a patient safety program. Jt Comm J Qual Patient Saf 2018; 44 (06) 334-340
- 12 Lyren A, Brilli RJ, Zieker K, Marino M, Muething S, Sharek PJ. Children's hospitals' solutions for patient safety collaborative impact on hospital-acquired harm. Pediatrics 2017; 140 (03) e20163494
- 13 Lannon CM, Peterson LE. Pediatric collaborative networks for quality improvement and research. Acad Pediatr 2013; 13 (6, suppl): S69-S74
- 14 Martin BS, Arbore M. Measurement, standards, and peer benchmarking: one hospital's journey. Pediatr Clin North Am 2016; 63 (02) 239-249
- 15 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 (06) 663-670
- 16 Palojoki S, Mäkelä M, Lehtonen L, Saranto K. An analysis of electronic health record-related patient safety incidents. Health Informatics J 2017; 23 (02) 134-145
- 17 Cheung KC, van der Veen W, Bouvy ML, Wensing M, van den Bemt PM, de Smet PA. Classification of medication incidents associated with information technology. J Am Med Inform Assoc 2014; 21 (e1): e63-e70
- 18 Warm D, Edwards P. Classifying health information technology patient safety related incidents - an approach used in Wales. Appl Clin Inform 2012; 3 (02) 248-257
- 19 Magrabi F, Ong MS, Runciman W, Coiera E. Using FDA reports to inform a classification for health information technology safety problems. J Am Med Inform Assoc 2012; 19 (01) 45-53
- 20 Sparnon E, Marella WM. The role of the electronic health record in patient safety events. Pennsylvania Patient Safety Adv 2012; 9 (04) 113-121
- 21 Sittig DF, Singh H. Defining health information technology-related errors: new developments since to err is human. Arch Intern Med 2011; 171 (14) 1281-1284
- 22 Classen DC, Holmgren AJ, Co Z. et al. National trends in the safety performance of electronic health record systems from 2009 to 2018. JAMA Netw Open 2020; 3 (05) e205547
- 23 Kottner J, Audigé L, Brorson S. et al. Guidelines for reporting reliability and agreement studies (GRRAS) were proposed. J Clin Epidemiol 2011; 64 (01) 96-106
- 24 Kang H, Wang J, Yao B, Zhou S, Gong Y. Toward safer health care: a review strategy of FDA medical device adverse event database to identify and categorize health information technology related events. JAMIA Open 2018; 2 (01) 179-186
- 25 Wang J, Liang H, Kang H, Gong Y. Understanding Health Information Technology Induced Medication Safety Events by Two Conceptual Frameworks. Appl Clin Inform 2019; 10 (01) 158-167
- 26 ISO/TS 20405: Health informatics—Framework of event data and reporting definitions for the safety of health software. available at: https://standards.iteh.ai/catalog/standards/iso/68edd25c-a3b2-419d-9254-a0ff3cfb92bf/iso-ts-20405-2018 . Accessed September 8. 2020
- 27 Ratwani RM, Savage E, Will A. et al. Identifying electronic health record usability and safety challenges in pediatric settings. Health Aff (Millwood) 2018; 37 (11) 1752-1759
- 28 Common Formats for Event Reporting–Hospital Version 1.2. Available at: https://www.psoppc.org/psoppc_web/publicpages/commonFormatsV1.2 . Accessed September 8, 2020
- 29 Menon S, Singh H, Giardina T. et al. Safety huddles to proactively identify and address electronic health record safety. J Am Med Inform Assoc 2017; 24 (02) 261-267
- 30 Walker JM, Hassol A, Bradshaw B, Rezaee ME. Final report: Health IT Hazard Manager Beta-Test: Agency for Healthcare Research and Quality. Available at: https://digital.ahrq.gov/sites/default/files/docs/citation/HealthITHazardManagerFinalReport.pdf . Accessed September 8, 2020
- 31 Castro GM, Buczkowski L, Hafner JM. The contribution of sociotechnical factors to health information technology-related sentinel events. Jt Comm J Qual Patient Saf 2016; 42 (02) 70-76
- 32 Food and Drug Adminnistration. Computerized prescriber order entry medication safety (CPOEMS): uncovering and learning from issues and errors. Available at: https://www.fda.gov/drugs/medication-errors-related-cder-regulated-drug-products/computerized-prescriber-order-entry-medication-safety-cpoems . Accessed August 4, 2020
- 33 Classen DC, Resar R, Griffin F. et al. ‘Global trigger tool’ shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood) 2011; 30 (04) 581-589
- 34 Evans SM, Berry JG, Smith BJ. et al. Attitudes and barriers to incident reporting: a collaborative hospital study. Qual Saf Health Care 2006; 15 (01) 39-43
- 35 Sari AB, Sheldon TA, Cracknell A, Turnbull A. Sensitivity of routine system for reporting patient safety incidents in an NHS hospital: retrospective patient case note review. BMJ 2007; 334 (7584): 79
- 36 Sammer C, Miller S, Jones C. et al. Developing and evaluating an automated all-cause harm trigger system. Jt Comm J Qual Patient Saf 2017; 43 (04) 155-165
- 37 Kuklik N, Stausberg J, Amiri M, Jöckel KH. Improving drug safety in hospitals: a retrospective study on the potential of adverse drug events coded in routine data. BMC Health Serv Res 2019; 19 (01) 555
- 38 Fong A, Komolafe T, Adams KT, Cohen A, Howe JL, Ratwani RM. Exploration and initial development of text classification models to identify health information technology usability-related patient safety event reports. Appl Clin Inform 2019; 10 (03) 521-527
- 39 Kalenderian E, Obadan-Udoh E, Yansane A. et al. Feasibility of electronic health record-based triggers in detecting dental adverse events. Appl Clin Inform 2018; 9 (03) 646-653
- 40 Feng C, Le D, McCoy AB. Using electronic health records to identify adverse drug events in ambulatory care: a systematic review. Appl Clin Inform 2019; 10 (01) 123-128
- 41 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 (02) 81-84
- 42 Horsky J, Drucker EA, Ramelson HZ. Accuracy and completeness of clinical coding using ICD-10 for ambulatory visits. AMIA Annu Symp Proc 2018; 2017: 912-920
- 43 Leape L, Berwick D, Clancy C. et al. Lucian Leape Institute at the National Patient Safety Foundation. Transforming healthcare: a safety imperative. Qual Saf Health Care 2009; 18 (06) 424-428
- 44 Koppel R, Kreda D. Health care information technology vendors' “hold harmless” clause: implications for patients and clinicians. JAMA 2009; 301 (12) 1276-1278
- 45 Adams KT, Howe JL, Fong A. et al. An analysis of patient safety incident reports associated with electronic health record interoperability. Appl Clin Inform 2017; 8 (02) 593-602
- 46 Aaron S, McEvoy DS, Ray S, Hickman TT, Wright A. Cranky comments: detecting clinical decision support malfunctions through free-text override reasons. J Am Med Inform Assoc 2019; 26 (01) 37-43