Mark Chun Moon1, Rebecca Hills2, George Demiris3. 1. Rush University Medical Center. mrmoon@uw.edu. 2. University of Washington. hillsr@uw.edu. 3. University of Pennsylvania. gdemiris@nursing.upenn.edu.
Abstract
BACKGROUND: Little is known about optimization of electronic health records (EHR) systems in the hospital setting while adoption of EHR systems continues in the United States. OBJECTIVE: To understand optimization processes of EHR systems undertaken in leading healthcare organizations in the United States. METHODS: Informed by grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organizations across the United States. RESULTS: The study describes EHR optimization processes characterized by prioritizing exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimization teams or advisory groups, and standardization. The study discusses 16 types of optimization that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimization. CONCLUSION: The study describes overall experiences of optimizing electronic health records in select high performing healthcare organizations in the US. The findings highlight the importance of optimizing the EHR after, and even before, go-live and dedicating resources exclusively for optimization.
BACKGROUND: Little is known about optimization of electronic health records (EHR) systems in the hospital setting while adoption of EHR systems continues in the United States. OBJECTIVE: To understand optimization processes of EHR systems undertaken in leading healthcare organizations in the United States. METHODS: Informed by grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organizations across the United States. RESULTS: The study describes EHR optimization processes characterized by prioritizing exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimization teams or advisory groups, and standardization. The study discusses 16 types of optimization that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimization. CONCLUSION: The study describes overall experiences of optimizing electronic health records in select high performing healthcare organizations in the US. The findings highlight the importance of optimizing the EHR after, and even before, go-live and dedicating resources exclusively for optimization.
Keywords:
Clinical Information systems; Electronic health records and systems; Facilitators and barriers; Inpatient (inpatient CPOE); System improvement
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