Use, Perceived Usability, and Barriers to Implementation of a Patient Safety Dashboard Integrated within a Vendor EHR

Abstract

Background Preventable adverse events continue to be a threat to hospitalized patients. Clinical decision support in the form of dashboards may improve compliance with evidence-based safety practices. However, limited research describes providers' experiences with dashboards integrated into vendor electronic health record (EHR) systems.

Objective This study was aimed to describe providers' use and perceived usability of the Patient Safety Dashboard and discuss barriers and facilitators to implementation.

Methods The Patient Safety Dashboard was implemented in a cluster-randomized stepped wedge trial on 12 units in neurology, oncology, and general medicine services over an 18-month period. Use of the Dashboard was tracked during the implementation period and analyzed in-depth for two 1-week periods to gather a detailed representation of use. Providers' perceptions of tool usability were measured using the Health Information Technology Usability Evaluation Scale (rated 1–5). Research assistants conducted field observations throughout the duration of the study to describe use and provide insight into tool adoption.

Results The Dashboard was used 70% of days the tool was available, with use varying by role, service, and time of day. On general medicine units, nurses logged in throughout the day, with many logins occurring during morning rounds, when not rounding with the care team. Prescribers logged in typically before and after morning rounds. On neurology units, physician assistants accounted for most logins, accessing the Dashboard during daily brief interdisciplinary rounding sessions. Use on oncology units was rare. Satisfaction with the tool was highest for perceived ease of use, with attendings giving the highest rating (4.23). The overall lowest rating was for quality of work life, with nurses rating the tool lowest (2.88).

Conclusion This mixed methods analysis provides insight into the use and usability of a dashboard tool integrated within a vendor EHR and can guide future improvements and more successful implementation of these types of tools.

Keywords

clinical decision support - health information technology - electronic health record - patient safety - information/data visualization - usability - dashboard

Protection of Human and Animal Subjects

This study was approved by the Partners HealthCare Institutional Review Board.

• References

• 1 Agency for Healthcare Research and Quality. Adverse events, near misses and errors. Available at: https://psnet.ahrq.gov/primer/adverse-events-near-misses-and-errors . Accessed October 19, 2019
• 2 Institute of Medicine (U.S.) Committee on Quality of Health Care in America; Kohn LT, Corrigan JM, Donaldson MS. , eds.; To Err is Human: Building a Safer Health System. Washington (DC): National Academies Press (US); 2000
• 3 The Office of the National Coordinator for Health Information Technology. Nonfederal acute care hospital electronic record adoption. Available at: https://dashboard.healthit.gov/quickstats/pages/FIG-Hospital-EHR-Adoption.php . Accessed April 9, 2019
• 4 The Office of the National Coordinator for Health Information Technology. Hospital health IT developers: certified health IT developers and editions reported by hospitals participating in the Medicare EHR incentive program. Available at: dashboard.healthit.gov/quickstats/pages/FIG-Vendors-of-EHRs-to-Participating-Hospitals.php . Accessed July 2017
• 5 Abernethy AP, Etheredge LM, Ganz PA. , et al. Rapid-learning system for cancer care. J Clin Oncol 2010; 28 (27) 4268-4274
• 6 Singh H, Spitzmueller C, Petersen N, Sawhney M, Sittig D. Information overload and missed test results in EHR-based settings. JAMA Intern Med 2013; 173 (08) 702-704
• 7 Murphy DR, Meyer AN, Russo E, Sittig DF, Wei L, Singh H. The burden of inbox notifications in commercial electronic health records. JAMA Intern Med 2016; 176 (04) 559-560
• 8 Miriovsky BJ, Shulman LN, Abernethy AP. Importance of health information technology, electronic health records, and continuously aggregating data to comparative effectiveness research and learning health care. J Clin Oncol 2012; 30 (34) 4243-4248
• 9 Egan M. Clinical dashboards: impact on workflow, care quality, and patient safety. Crit Care Nurs Q 2006; 29 (04) 354-361
• 10 Pageler NM, Longhurst CA, Wood M. , et al. Use of electronic medical record-enhanced checklist and electronic dashboard to decrease CLABSIs. Pediatrics 2014; 133 (03) e738-e746
• 11 Shaw SJ, Jacobs B, Stockwell DC, Futterman C, Spaeder MC. Effect of a real-time pediatric ICU safety bundle dashboard on quality improvement measures. Jt Comm J Qual Patient Saf 2015; 41 (09) 414-420
• 12 Schall Jr. MC, Cullen L, Pennathur P, Chen H, Burrell K, Matthews G. Usability evaluation and implementation of a health information technology dashboard of evidence-based quality indicators. Comput Inform Nurs 2017; 35 (06) 281-288
• 13 Brown N, Eghdam A, Koch S. Usability evaluation of visual representation formats for emergency department records. Appl Clin Inform 2019; 10 (03) 454-470
• 14 Tan Y-M, Hii J, Chan K, Sardual R, Mah B. An electronic dashboard to improve nursing care. Stud Health Technol Inform 2013; 192: 190-194
• 15 Bates DW, Kuperman GJ, Wang S. , et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc 2003; 10 (06) 523-530
• 16 Mlaver E, Schnipper JL, Boxer RB. , et al. User-centered collaborative design and development of an inpatient safety dashboard. Jt Comm J Qual Patient Saf 2017; 43 (12) 676-685
• 17 Few S. Data Visualization for human perception. Available at: https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception . Accessed December 17, 2019
• 18 Khasnabish S, Burns Z, Couch M, Mullin M, Newmark R, Dykes PC. Best practices for data visualization: creating and evaluating a report for an evidence-based fall prevention program. J Am Med Inform Assoc 2019 Doi: 10.1093/jamia/ocz190
• 19 Yen PY, Sousa KH, Bakken S. Examining construct and predictive validity of the Health-IT Usability Evaluation Scale: confirmatory factor analysis and structural equation modeling results. J Am Med Inform Assoc 2014; 21 (e2): e241-e248
• 20 Carayon P, Wetterneck TB, Rivera-Rodriguez AJ. , et al. Human factors systems approach to healthcare quality and patient safety. Appl Ergon 2014; 45 (01) 14-25
• 21 Khan S, Richardson S, Liu A. , et al. Improving provider adoption with adaptive clinical decision support surveillance: an observational study. JMIR Human Factors 2019; 6 (01) e10245
• 22 Kurtzman G, Dine J, Epstein A. , et al. Internal medicine resident engagement with a laboratory utilization dashboard: mixed methods study. J Hosp Med 2017; 12 (09) 743-746