Michael K Rakotz1, Bernard G Ewigman2, Menaka Sarav2, Ruth E Ross2, Ari Robicsek2, Chad W Konchak3, Thomas F Gavagan4, David W Baker5, David J Hyman6, Kenneth P Anderson2, Christopher M Masi2. 1. Feinberg School of Medicine, Northwestern University, Chicago, Illinois mrakotz@nmh.org. 2. NorthShore University HealthSystem, Evanston, Illinois Pritzker School of Medicine, The University of Chicago, Chicago, Illinois. 3. NorthShore University HealthSystem, Evanston, Illinois. 4. College of Medicine, University of Illinois, Chicago, Illinois. 5. Feinberg School of Medicine, Northwestern University, Chicago, Illinois. 6. Baylor College of Medicine, Baylor University, Houston, Texas.
Abstract
PURPOSE: The goal of this study was to develop a technology-based strategy to identify patients with undiagnosed hypertension in 23 primary care practices and integrate this innovation into a continuous quality improvement initiative in a large, integrated health system. METHODS: In phase 1, we reviewed electronic health records (EHRs) using algorithms designed to identify patients at risk for undiagnosed hypertension. We then invited each at-risk patient to complete an automated office blood pressure (AOBP) protocol. In phase 2, we instituted a quality improvement process that included regular physician feedback and office-based computer alerts to evaluate at-risk patients not screened in phase 1. Study patients were observed for 24 additional months to determine rates of diagnostic resolution. RESULTS: Of the 1,432 patients targeted for inclusion in the study, 475 completed the AOBP protocol during the 6 months of phase 1. Of the 1,033 at-risk patients who remained active during phase 2, 740 (72%) were classified by the end of the follow-up period: 361 had hypertension diagnosed, 290 had either white-coat hypertension, prehypertension, or elevated blood pressure diagnosed, and 89 had normal blood pressure. By the end of the follow-up period, 293 patients (28%) had not been classified and remained at risk for undiagnosed hypertension. CONCLUSIONS: Our technology-based innovation identified a large number of patients at risk for undiagnosed hypertension and successfully classified the majority, including many with hypertension. This innovation has been implemented as an ongoing quality improvement initiative in our medical group and continues to improve the accuracy of diagnosis of hypertension among primary care patients.
PURPOSE: The goal of this study was to develop a technology-based strategy to identify patients with undiagnosed hypertension in 23 primary care practices and integrate this innovation into a continuous quality improvement initiative in a large, integrated health system. METHODS: In phase 1, we reviewed electronic health records (EHRs) using algorithms designed to identify patients at risk for undiagnosed hypertension. We then invited each at-risk patient to complete an automated office blood pressure (AOBP) protocol. In phase 2, we instituted a quality improvement process that included regular physician feedback and office-based computer alerts to evaluate at-risk patients not screened in phase 1. Study patients were observed for 24 additional months to determine rates of diagnostic resolution. RESULTS: Of the 1,432 patients targeted for inclusion in the study, 475 completed the AOBP protocol during the 6 months of phase 1. Of the 1,033 at-risk patients who remained active during phase 2, 740 (72%) were classified by the end of the follow-up period: 361 had hypertension diagnosed, 290 had either white-coat hypertension, prehypertension, or elevated blood pressure diagnosed, and 89 had normal blood pressure. By the end of the follow-up period, 293 patients (28%) had not been classified and remained at risk for undiagnosed hypertension. CONCLUSIONS: Our technology-based innovation identified a large number of patients at risk for undiagnosed hypertension and successfully classified the majority, including many with hypertension. This innovation has been implemented as an ongoing quality improvement initiative in our medical group and continues to improve the accuracy of diagnosis of hypertension among primary care patients.
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