Jennifer S Haas1, Heather J Baer2, Katyuska Eibensteiner3, Elissa V Klinger3, Stella St Hubert3, George Getty3, Phyllis Brawarsky3, E John Orav4, Tracy Onega5, Anna N A Tosteson5, David W Bates6, Graham Colditz7. 1. Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts; Department of Medicine, Harvard University Medical School, Boston, Massachusetts; Department of Social and Behavioral Sciences, Harvard University School of Public Health, Boston, Massachusetts. Electronic address: jhaas@partners.org. 2. Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts; Department of Medicine, Harvard University Medical School, Boston, Massachusetts; Department of Epidemiology, Harvard University School of Public Health, Boston, Massachusetts. 3. Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts. 4. Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts; Department of Medicine, Harvard University Medical School, Boston, Massachusetts; Department of Biostatistics, Harvard University School of Public Health, Boston, Massachusetts. 5. Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon, New Hampshire. 6. Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts; Department of Medicine, Harvard University Medical School, Boston, Massachusetts; Department of Health Policy and Management, Harvard University School of Public Health, Boston, Massachusetts. 7. Institute for Public Health, Washington University School of Medicine, St. Louis, Missouri.
Abstract
INTRODUCTION: Personal risk for multiple conditions should be assessed in primary care. This study evaluated whether collection of risk factors to generate electronic health record (EHR)-linked health risk appraisal (HRA) for coronary heart disease, diabetes, breast cancer, and colorectal cancer was associated with improved patient-provider communication, risk assessment, and plans for breast cancer screening. METHODS: This pragmatic trial recruited adults with upcoming visits to 11 primary care practices during 2013-2014 (N=3,703). Pre-visit, intervention patients completed a risk factor and perception assessment and received an HRA; coded risk factor data were sent to the EHR. Post-visit, intervention patients reported risk perception. Pre-visit, control patients only completed the risk perception assessment; post-visit they also completed the risk factor assessment and received the HRA. No data were sent to the EHR for controls. Accuracy/improvement of self-perceived risk was assessed by comparing self-perceived to calculated risk. RESULTS: The intervention was associated with improvement of patient-provider communication of changes to improve health (78.5% vs 74.1%, AOR=1.67, 99% CI=1.07, 2.60). There was a similar trend for discussion of risk (54.1% vs 45.5%, AOR=1.34, 95% CI=0.97, 1.85). The intervention was associated with greater improvement in accuracy of self-perceived risk for diabetes (16.0% vs 12.6%, p=0.006) and colorectal cancer (27.9% vs 17.2%, p<0.001) with a similar trend for coronary heart disease and breast cancer. There were no changes in plans for breast cancer screening. CONCLUSIONS: Patient-reported risk factors and EHR-linked multi-condition HRAs in primary care can modestly improve communication and promote accuracy of self-perceived risk.
RCT Entities:
INTRODUCTION: Personal risk for multiple conditions should be assessed in primary care. This study evaluated whether collection of risk factors to generate electronic health record (EHR)-linked health risk appraisal (HRA) for coronary heart disease, diabetes, breast cancer, and colorectal cancer was associated with improved patient-provider communication, risk assessment, and plans for breast cancer screening. METHODS: This pragmatic trial recruited adults with upcoming visits to 11 primary care practices during 2013-2014 (N=3,703). Pre-visit, intervention patients completed a risk factor and perception assessment and received an HRA; coded risk factor data were sent to the EHR. Post-visit, intervention patients reported risk perception. Pre-visit, control patients only completed the risk perception assessment; post-visit they also completed the risk factor assessment and received the HRA. No data were sent to the EHR for controls. Accuracy/improvement of self-perceived risk was assessed by comparing self-perceived to calculated risk. RESULTS: The intervention was associated with improvement of patient-provider communication of changes to improve health (78.5% vs 74.1%, AOR=1.67, 99% CI=1.07, 2.60). There was a similar trend for discussion of risk (54.1% vs 45.5%, AOR=1.34, 95% CI=0.97, 1.85). The intervention was associated with greater improvement in accuracy of self-perceived risk for diabetes (16.0% vs 12.6%, p=0.006) and colorectal cancer (27.9% vs 17.2%, p<0.001) with a similar trend for coronary heart disease and breast cancer. There were no changes in plans for breast cancer screening. CONCLUSIONS:Patient-reported risk factors and EHR-linked multi-condition HRAs in primary care can modestly improve communication and promote accuracy of self-perceived risk.
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