BACKGROUND AND OBJECTIVE: On March 11, 2009, the Veterans Health Administration (VA) implemented an electronic health record (EHR)-based intervention that required all pathology results to be transmitted to ordering providers by mandatory automated notifications. We examined the impact of this intervention on improving follow-up of abnormal outpatient pathology results. RESEARCH DESIGN AND SUBJECTS: We extracted pathology reports from the EHR of 2 VA sites. From 16,738 preintervention and 17,305 postintervention reports between 09/01/2008 and 09/30/2009, we randomly selected about 5% and evaluated follow-up outcomes using a standardized chart review instrument. Documented responses to the alerted report (eg, ordering follow-up tests or referrals, notifying patients, and prescribing/changing treatment) were recorded. MEASURES: Primary outcome measures included proportion of timely follow-up responses (within 30 d) and median time to direct response for abnormal reports. RESULTS: Of 816 preintervention and 798 postintervention reports reviewed, 666 (81.6%) and 688 (86.2%) were abnormal. Overall, there was no apparent intervention effect on timely follow-up (69% vs. 67.1%; P=0.4) or median time to direct response (8 vs. 8 d; P=0.7). However, logistic regression uncovered a significant intervention effect (preintervention odds ratio, 0.7; 95% confidence interval, 0.5-1.0) after accounting for site-specific differences in follow-up, with a lower likelihood of timely follow-up at one site (odds ratio, 0.4; 95% confidence interval, 0.2-0.7). CONCLUSIONS: An electronic intervention to improve test result follow-up at 2 VA institutions using the same EHR was found effective only after accounting for certain local contextual factors. Aggregating the effect of EHR interventions across different institutions and EHRs without controlling for contextual factors might underestimate their potential benefits.
BACKGROUND AND OBJECTIVE: On March 11, 2009, the Veterans Health Administration (VA) implemented an electronic health record (EHR)-based intervention that required all pathology results to be transmitted to ordering providers by mandatory automated notifications. We examined the impact of this intervention on improving follow-up of abnormal outpatient pathology results. RESEARCH DESIGN AND SUBJECTS: We extracted pathology reports from the EHR of 2 VA sites. From 16,738 preintervention and 17,305 postintervention reports between 09/01/2008 and 09/30/2009, we randomly selected about 5% and evaluated follow-up outcomes using a standardized chart review instrument. Documented responses to the alerted report (eg, ordering follow-up tests or referrals, notifying patients, and prescribing/changing treatment) were recorded. MEASURES: Primary outcome measures included proportion of timely follow-up responses (within 30 d) and median time to direct response for abnormal reports. RESULTS: Of 816 preintervention and 798 postintervention reports reviewed, 666 (81.6%) and 688 (86.2%) were abnormal. Overall, there was no apparent intervention effect on timely follow-up (69% vs. 67.1%; P=0.4) or median time to direct response (8 vs. 8 d; P=0.7). However, logistic regression uncovered a significant intervention effect (preintervention odds ratio, 0.7; 95% confidence interval, 0.5-1.0) after accounting for site-specific differences in follow-up, with a lower likelihood of timely follow-up at one site (odds ratio, 0.4; 95% confidence interval, 0.2-0.7). CONCLUSIONS: An electronic intervention to improve test result follow-up at 2 VA institutions using the same EHR was found effective only after accounting for certain local contextual factors. Aggregating the effect of EHR interventions across different institutions and EHRs without controlling for contextual factors might underestimate their potential benefits.
Authors: Sylvia J Hysong; Mona K Sawhney; Lindsay Wilson; Dean F Sittig; Donna Espadas; Traber Davis; Hardeep Singh Journal: J Am Med Inform Assoc Date: 2010 Jan-Feb Impact factor: 4.497
Authors: Paul G Shekelle; Peter J Pronovost; Robert M Wachter; Stephanie L Taylor; Sydney M Dy; Robbie Foy; Susanne Hempel; Kathryn M McDonald; John Ovretveit; Lisa V Rubenstein; Alyce S Adams; Peter B Angood; David W Bates; Leonard Bickman; Pascale Carayon; Liam Donaldson; Naihua Duan; Donna O Farley; Trisha Greenhalgh; John Haughom; Eileen T Lake; Richard Lilford; Kathleen N Lohr; Gregg S Meyer; Marlene R Miller; Duncan V Neuhauser; Gery Ryan; Sanjay Saint; Kaveh G Shojania; Stephen M Shortell; David P Stevens; Kieran Walshe Journal: Ann Intern Med Date: 2011-05-17 Impact factor: 25.391
Authors: Rachel B Issaka; Maneesh H Singh; Sachiko M Oshima; Victoria J Laleau; Carly D Rachocki; Ellen H Chen; Lukejohn W Day; Urmimala Sarkar; Ma Somsouk Journal: Am J Gastroenterol Date: 2016-12-13 Impact factor: 10.864
Authors: Adam Wright; Francine L Maloney; Matthew Wien; Lipika Samal; Srinivas Emani; Gianna Zuccotti Journal: J Am Med Inform Assoc Date: 2015-05-26 Impact factor: 4.497
Authors: Shailaja Menon; Michael W Smith; Dean F Sittig; Nancy J Petersen; Sylvia J Hysong; Donna Espadas; Varsha Modi; Hardeep Singh Journal: BMJ Open Date: 2014-11-11 Impact factor: 2.692
Authors: Andrew Georgiou; Julie Li; Judith Thomas; Maria R Dahm; Johanna I Westbrook Journal: J Am Med Inform Assoc Date: 2019-07-01 Impact factor: 4.497