Analysis of the effects of EHR implementation on timeliness of care in a dermatology clinic: a simulation study. (4th April 2018)

• Record Type: Journal Article
• Authors: Vahdat, Vahab; Griffin, Jacqueline A; Stahl, James E; Yang, F Clarissa
• Is Part Of: Journal of the American Medical Informatics Association. Volume 25:Number 7(2018)
• Page Start: 827
• Page End: 832
• Publication Date: 2018-04-04
• Subjects: Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocy024
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective: Quantify the downstream impact on patient wait times and overall length of stay due to small increases in encounter times caused by the implementation of a new electronic health record (EHR) system. Methods: A discrete-event simulation model was created to examine the effects of increasing the provider-patient encounter time by 1, 2, 5, or 10 min, due to an increase in in-room documentation as part of an EHR implementation. Simulation parameters were constructed from an analysis of 52 000 visits from a scheduling database and direct observation of 93 randomly selected patients to collect all the steps involved in an outpatient dermatology patient care visit. Results: Analysis of the simulation results demonstrates that for a clinic session with an average booking appointment length of 15 min, the addition of 1, 2, 5, and 10 min for in-room physician documentation with an EHR system would result in a 5.2 (22%), 9.8 (41%), 31.8 (136%), and 87.2 (373%) minute increase in average patient wait time, and a 6.2 (12%), 11.7 (23%), 36.7 (73%), and 96.9 (193%) minute increase in length of stay, respectively. To offset the additional 1, 2, 5, or 10 min, patient volume would need to decrease by 10%, 20%, 40%, and >50%, respectively. Conclusions: Small changes to processes, such as the addition of a few minutes of extra documentation time in the exam room, can cause significant delays in the timeliness of patient care. Simulation models can assist in quantifying the downstream effects and help analyze the impact of these operational changes.