Accepted for/Published in: JMIR Formative Research
Date Submitted: Sep 16, 2020
Date Accepted: Jan 10, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Using Information Technology to Assess Patient Risk Factors in Primary Care Clinics: A Pragmatic Evaluation
ABSTRACT
Background:
Tobacco use, physical inactivity and poor diet are associated with morbidity and premature death. Health promotion and primary prevention counseling, advice and support by a primary care provider leads to behaviour change attempts among patients. However, although physicians consider preventative health important the focus on symptoms presentation, acute care and medication review often overshadows primary prevention counseling.
Objective:
This study evaluates feasibility, adoption and integration of the tablet-based Risk Factor Identification Tool (RFIT) that uses algorithmic information technology to support obtainment of patient risk factor information in primary care clinics.
Methods:
This is a pragmatic developmental evaluation. Each clinic developed a site-specific implementation plan adapted to their workflow. RFIT was implemented in two primary care clinics located in Manitoba. Perceptions of 10 clinic staff and 8 primary care clinicians informed this evaluation.
Results:
Clinicians reported a smooth and fast transfer of RFIT responses to an EMR encounter note. Two hundred seven patients used the RFIT with a completion rate of 86%. Clinic staff reported that very few patients declined the use of RFIT or required assistance to use the tablet. Among the patients that used RFIT 12.1% smoked, 21.2% felt their diet could be improved, 9.3% reported high alcohol consumption, 56.4% reported less than 150 minutes of PA a week, and 8.2% lived in poverty. Clinicians suggested that although a wide variety of patients were able to use the tablet-based RFIT, implemented surveys should be tailored to patient subgroups.
Conclusions:
Clinicians and clinic staff positively reviewed the use of information technology in primary care. Algorithmic information technology can collect, organize and synthesize individual health information to inform and tailor primary care counseling to the patients’ context and readiness to change. RFIT is a user-friendly tool that provides an effective method for obtaining risk factor information from patients. It is particularly useful for subsets of patients lacking continuity in the care they receive. When implemented within a context that can support practical interventions to address identified risk factors, RFIT can inform brief interventions within primary care.
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