The objective of the proposed research is to provide an evidence-base to better inform user centered design and implementation processes to improve health information technology (health IT) usability and safety. The proposed research is in direct response to special emphasis notice (NOT-HS-15-005). Utilizing a hybrid approach of expert manual review and machine learning techniques, specifically natural language processing, we will develop methods to rapidly analyze patient safety event data to determine which events are health IT related. We will then further categorize the health IT related safety events to determine which events could have been prevented by effective usability or implementation processes. Through this analysis we will be able to specify the usability and implementation processes that are critical to the safe and effective use of health IT. This project utilizes the extensive expertise of the research team in human factors and safety science, health IT, and computer science. The proposed research is based on unique insights that our team gleaned from previous research that we conducted focusing on health IT vendor design and implementation processes. The application addresses fundamental aspects of the call for applications by providing an evidence base to improve health IT usability and safety to better inform policy and practice. This research effort is being conducted in partnership with a health IT vendor and a patient safety organization to ensure that our results align with vendor needs and to ensure the results are generalizable. Contributions from this research will include a fundamental understanding of the critical user centered design and implementation processes to inform vendor and provider practice. Our research will also provide organizations like the Office of the National Coordinator with the information to better inform health IT policy.

Public Health Relevance

This project is relevant to public health because it applies the science of human factors and data analytics to improve the usability and safety of health information technology and ultimately improve patient care. Patient safety event data will be analyzed to support specific user centered design and implementation processes to better inform the design and development of health information technology.

National Institute of Health (NIH)
Agency for Healthcare Research and Quality (AHRQ)
Research Project (R01)
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Healthcare Information Technology Research (HITR)
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Dymek, Christine
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Medstar Health Research Institute
United States
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Fong, Allan; Adams, Katharine T; Gaunt, Michael J et al. (2018) Identifying health information technology related safety event reports from patient safety event report databases. J Biomed Inform 86:135-142
Howe, Jessica L; Adams, Katharine T; Hettinger, A Zachary et al. (2018) Electronic Health Record Usability Issues and Potential Contribution to Patient Harm. JAMA 319:1276-1278
Ratwani, Raj M; Savage, Erica; Will, Amy et al. (2018) Identifying Electronic Health Record Usability And Safety Challenges In Pediatric Settings. Health Aff (Millwood) 37:1752-1759
Ratwani, Raj M; Moscovitch, Ben; Rising, Josh P (2018) Improving Pediatric Electronic Health Record Usability and Safety Through Certification: Seize the Day. JAMA Pediatr 172:1007-1008
Ratwani, Raj (2017) Electronic Health Records and Improved Patient Care: Opportunities for Applied Psychology. Curr Dir Psychol Sci 26:359-365
Ratwani, Raj M; Hettinger, A Zachary; Fairbanks, Rollin J (2017) Barriers to comparing the usability of electronic health records. J Am Med Inform Assoc 24:e191-e193
Savage, Erica L; Fairbanks, Rollin J; Ratwani, Raj M (2017) Are informed policies in place to promote safe and usable EHRs? A cross-industry comparison. J Am Med Inform Assoc 24:769-775
Adams, Katharine T; Howe, Jessica L; Fong, Allan et al. (2017) An Analysis of Patient Safety Incident Reports Associated with Electronic Health Record Interoperability Appl Clin Inform 8:593-602
Kellogg, Kathryn M; Fairbanks, Rollin J; Ratwani, Raj M (2017) EHR Usability: Get It Right from the Start. Biomed Instrum Technol 51:197-199
Fong, Allan; Harriott, Nicole; Walters, Donna M et al. (2017) Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events. Int J Med Inform 104:120-125

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