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Ramelson, Harley Z.

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Ramelson

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Harley Z.

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Ramelson, Harley Z.

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2012 - 20132

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Author's Publications: search.filters.isAuthorOfPublication.668f466e-9fc7-4bff-b6f3-ffdc5e23f8a4

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    Improving Completeness of Electronic Problem Lists through Clinical Decision Support: A Randomized, Controlled Trial
    (BMJ Group, 2012) Wright, Adam; Pang, Justine; Feblowitz, Joshua; Maloney, Francine L.; Wilcox, Allison R.; McLoughlin, Karen Sax; Ramelson, Harley Z.; Schneider, Louise; Bates, David
    Background: Accurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date. Objective: To determine whether a clinical alerting system, which uses inference rules to notify providers of undocumented problems, improves problem list documentation. Study Design and Methods: Inference rules for 17 conditions were constructed and an electronic health record-based intervention was evaluated to improve problem documentation. A cluster randomized trial was conducted of 11 participating clinics affiliated with a large academic medical center, totaling 28 primary care clinical areas, with 14 receiving the intervention and 14 as controls. The intervention was a clinical alert directed to the provider that suggested adding a problem to the electronic problem list based on inference rules. The primary outcome measure was acceptance of the alert. The number of study problems added in each arm as a pre-specified secondary outcome was also assessed. Data were collected during 6-month pre-intervention (11/2009–5/2010) and intervention (5/2010–11/2010) periods. Results: 17,043 alerts were presented, of which 41.1% were accepted. In the intervention arm, providers documented significantly more study problems (adjusted OR=3.4, p<0.001), with an absolute difference of 6,277 additional problems. In the intervention group, 70.4% of all study problems were added via the problem list alerts. Significant increases in problem notation were observed for 13 of 17 conditions. Conclusion: Problem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement.
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    Provider Use of and Attitudes Towards an Active Clinical Alert
    (Schattauer GmbH, 2013) Feblowitz, Joshua; Henkin, Stanislav; Pang, Justine; Ramelson, Harley Z.; Schneider, L.; Maloney, F. L.; Wilcox, A. R.; Bates, David; Wright, A.
    Background In a previous study, we reported on a successful clinical decision support (CDS) intervention designed to improve electronic problem list accuracy, but did not study variability of provider response to the intervention or provider attitudes towards it. The alert system accurately predicted missing problem list items based on health data captured in a patient’s electronic medical record. Objective To assess provider attitudes towards a rule-based CDS alert system as well as heterogeneity of acceptance rates across providers. Methods We conducted a by-provider analysis of alert logs from the previous study. In addition, we assessed provider opinions of the intervention via an email survey of providers who received the alerts (n = 140). Results Although the alert acceptance rate was 38.1%, individual provider acceptance rates varied widely, with an interquartile range (IQR) of 14.8%-54.4%, and many outliers accepting none or nearly all of the alerts they received. No demographic variables, including degree, gender, age, assigned clinic, medical school or graduation year predicted acceptance rates. Providers’ self-reported acceptance rate and perceived alert frequency were only moderately correlated with actual acceptance rates and alert frequency. Conclusions Acceptance of this CDS intervention among providers was highly variable but this heterogeneity is not explained by measured demographic factors, suggesting that alert acceptance is a complex and individual phenomenon. Furthermore, providers’ self-reports of their use of the CDS alerting system correlated only modestly with logged usage.