A Turchin1, A Sawarkar2, Y A Dementieva3, E Breydo4, H Ramelson5. 1. Harvard Clinical Research Institute , Boston, MA ; Division of Endocrinology, Brigham and Women's Hospital , Boston, MA ; Harvard Medical School , Boston, MA. 2. Harvard Medical School , Boston, MA ; Division of General Internal Medicine, Brigham and Women's Hospital , Boston, MA. 3. Department of Mathematics, Emmanuel College , Boston, MA. 4. BE-Tech, Inc. , Brooklyn, NY ; Division of General Internal Medicine, Brigham and Women's Hospital , Boston, MA. 5. Harvard Medical School , Boston, MA ; Information Systems, Partners HealthCare , Boston, MA.
Abstract
OBJECTIVE: To determine whether specific design interventions (changes in the user interface (UI)) of an electronic health record (EHR) medication module are associated with an increase or decrease in the incidence of contradictions between the structured and narrative components of electronic prescriptions (internal prescription discrepancies). MATERIALS AND METHODS: We performed a retrospective analysis of 960,000 randomly selected electronic prescriptions generated in a single EHR between 01/2004 and 12/2011. Internal prescription discrepancies were identified using a validated natural language processing tool with recall of 76% and precision of 84%. A multivariable autoregressive integrated moving average (ARIMA) model was used to evaluate the effect of five UI changes in the EHR medication module on incidence of internal prescription discrepancies. RESULTS: Over the study period 175,725 (18.4%) prescriptions were found to have internal discrepancies. The highest rate of prescription discrepancies was observed in March 2006 (22.5%) and the lowest in March 2009 (15.0%). Addition of "as directed" option to the <Frequency> dropdown decreased prescription discrepancies by 195 / month (p = 0.0004). An non-interruptive alert that reminded providers to ensure that structured and narrative components did not contradict each other decreased prescription discrepancies by 145 / month (p = 0.03). Addition of a "Renew / Sign" button to the Medication module (a negative control) did not have an effect in prescription discrepancies. CONCLUSIONS: Several UI changes in the electronic medication module were effective in reducing the incidence of internal prescription discrepancies. Further research is needed to identify interventions that can completely eliminate this type of prescription error and their effects on patient outcomes.
OBJECTIVE: To determine whether specific design interventions (changes in the user interface (UI)) of an electronic health record (EHR) medication module are associated with an increase or decrease in the incidence of contradictions between the structured and narrative components of electronic prescriptions (internal prescription discrepancies). MATERIALS AND METHODS: We performed a retrospective analysis of 960,000 randomly selected electronic prescriptions generated in a single EHR between 01/2004 and 12/2011. Internal prescription discrepancies were identified using a validated natural language processing tool with recall of 76% and precision of 84%. A multivariable autoregressive integrated moving average (ARIMA) model was used to evaluate the effect of five UI changes in the EHR medication module on incidence of internal prescription discrepancies. RESULTS: Over the study period 175,725 (18.4%) prescriptions were found to have internal discrepancies. The highest rate of prescription discrepancies was observed in March 2006 (22.5%) and the lowest in March 2009 (15.0%). Addition of "as directed" option to the <Frequency> dropdown decreased prescription discrepancies by 195 / month (p = 0.0004). An non-interruptive alert that reminded providers to ensure that structured and narrative components did not contradict each other decreased prescription discrepancies by 145 / month (p = 0.03). Addition of a "Renew / Sign" button to the Medication module (a negative control) did not have an effect in prescription discrepancies. CONCLUSIONS: Several UI changes in the electronic medication module were effective in reducing the incidence of internal prescription discrepancies. Further research is needed to identify interventions that can completely eliminate this type of prescription error and their effects on patient outcomes.
Entities:
Keywords:
Medication errors; electronic medical records; electronic prescribing; user interface
Authors: Peter J Embi; Thomas R Yackel; Judith R Logan; Judith L Bowen; Thomas G Cooney; Paul N Gorman Journal: J Am Med Inform Assoc Date: 2004-04-02 Impact factor: 4.497
Authors: Nidhi R Shah; Andrew C Seger; Diane L Seger; Julie M Fiskio; Gilad J Kuperman; Barry Blumenfeld; Elaine G Recklet; David W Bates; Tejal K Gandhi Journal: J Am Med Inform Assoc Date: 2005-10-12 Impact factor: 4.497
Authors: Richard Hillestad; James Bigelow; Anthony Bower; Federico Girosi; Robin Meili; Richard Scoville; Roger Taylor Journal: Health Aff (Millwood) Date: 2005 Sep-Oct Impact factor: 6.301
Authors: G M Chertow; J Lee; G J Kuperman; E Burdick; J Horsky; D L Seger; R Lee; A Mekala; J Song; A L Komaroff; D W Bates Journal: JAMA Date: 2001-12-12 Impact factor: 56.272
Authors: Stephen E Ross; Laurie A Moore; Mark A Earnest; Loretta Wittevrongel; Chen-Tan Lin Journal: J Med Internet Res Date: 2004-05-14 Impact factor: 5.428
Authors: Sally L Baxter; Helena E Gali; Michael F Chiang; Michelle R Hribar; Lucila Ohno-Machado; Robert El-Kareh; Abigail E Huang; Heather E Chen; Andrew S Camp; Don O Kikkawa; Bobby S Korn; Jeffrey E Lee; Christopher A Longhurst; Marlene Millen Journal: Appl Clin Inform Date: 2020-02-19 Impact factor: 2.342
Authors: Evan W Orenstein; Daria F Ferro; Christopher P Bonafide; Christopher P Landrigan; Scott Gillespie; Naveen Muthu Journal: JAMIA Open Date: 2019-08-07
Authors: Robert J Romanelli; Naomi R M Schwartz; William G Dixon; Carla Rodriguez-Watson; Brian C Sauer; Dawn Albright; Zachary A Marcum Journal: Pharmacoepidemiol Drug Saf Date: 2021-07-28 Impact factor: 2.732