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Am J Prev Med. 2017 Jan;52(1):100-105. doi: 10.1016/j.amepre.2016.07.013. Epub 2016 Sep 14.

A Cluster Randomized Trial of a Personalized Multi-Condition Risk Assessment in Primary Care.

Author information

  • 1Division 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.
  • 2Division 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.
  • 3Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts.
  • 4Division 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.
  • 5Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon, New Hampshire.
  • 6Division 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.
  • 7Institute 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.

PMID:
27639785
PMCID:
PMC5167657
[Available on 2018-01-01]
DOI:
10.1016/j.amepre.2016.07.013
[PubMed - in process]
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