Browsing by Author "Lai, Albert"
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Item Electronic health record-based assessment of cardiovascular health: The stroke prevention in healthcare delivery environments (SPHERE) study(Elsevier, 2016) Foraker, Randi; Shoben, Abigail; Kelley, Marjorie; Lai, Albert; Lopetegui, Marcelo; Jackson, Rebecca; Langan, Michael; Payne, Philip< 3% of Americans have ideal cardiovascular health (CVH). The primary care encounter provides a setting in which to conduct patient-provider discussions of CVH. We implemented a CVH risk assessment, visualization, and decision-making tool that automatically populates with electronic health record (EHR) data during the encounter in order to encourage patient-centered CVH discussions among at-risk, yet under-treated, populations. We quantified five of the seven CVH behaviors and factors that were available in The Ohio State University Wexner Medical Center's EHR at baseline (May–July 2013) and compared values to those ascertained at one-year (May–July 2014) among intervention (n = 109) and control (n = 42) patients. The CVH of women in the intervention clinic improved relative to the metrics of body mass index (16% to 21% ideal) and diabetes (62% to 68% ideal), but not for smoking, total cholesterol, or blood pressure. Meanwhile, the CVH of women in the control clinic either held constant or worsened slightly as measured using those same metrics. Providers need easy-to-use tools at the point-of-care to help patients improve CVH. We demonstrated that the EHR could deliver such a tool using an existing American Heart Association framework, and we noted small improvements in CVH in our patient population. Future work is needed to assess how to best harness the potential of such tools in order to have the greatest impact on the CVH of a larger patient population. Abbreviations: 95% CI, 95% confidence interval; ACC, American College of Cardiology; AHA, American Heart Association; CDS, clinical decision support; CVH, cardiovascular health; EHR, electronic health record; GEE, generalized estimation equation; OSUWMC, Ohio State University Wexner Medical Center; SD, standard deviation; SPHERE, stroke prevention in healthcare delivery environments.Item Textual inference for eligibility criteria resolution in clinical trials.(Elsevier Inc, 2015) Shivade, Chaitanya; Hebert, Courtney; Lopetegui, Marcelo; De Marneffe, Marie-Catherine; Fosler-Lussier, Eric; Lai, AlbertClinical trials are essential for determining whether new interventions are effective. In order to determine the eligibility of patients to enroll into these trials, clinical trial coordinators often perform a manual review of clinical notes in the electronic health record of patients. This is a very time-consuming and exhausting task. Efforts in this process can be expedited if these coordinators are directed toward specific parts of the text that are relevant for eligibility determination. In this study, we describe the creation of a dataset that can be used to evaluate automated methods capable of identifying sentences in a note that are relevant for screening a patient's eligibility in clinical trials. Using this dataset, we also present results for four simple methods in natural language processing that can be used to automate this task. We found that this is a challenging task (maximum F-score=26.25), but it is a promising direction for further research.