Abstract

This randomized clinical trial examines the feasibility and acceptability of a decision-making tool for increasing patient interest in individualized recommendations for preventive care services. To pilot a tool to help patients compare life expectancy gains from evidence-based preventive services. This randomized clinical trial examined patient and physician responses to a pilot decision tool incorporating personalized risk factors at 3 US primary care clinics between 2017 and 2020. Eligible patients were between ages 45 to 70 years with 2 or more high-risk factors. Patients were followed-up after 1 year. The gain in life expectancy associated with guideline adherence to each recommended preventive service was estimated. Personalized estimates incorporating risk factors in electronic health records were displayed in a physician-distributed visual aid. During development, physicians discussed individualized results with patients using shared decision-making (SDM). During the trial, patients were randomized to receive individualized recommendations or usual care (nonmasked, parallel, 1:1 ratio). Primary outcome was patient interest in individualized recommendations, assessed by survey. Secondary outcomes were use of SDM, decisional comfort, readiness to change, and preventive services received within 1 year. The study enrolled 104 patients (31 development, 39 intervention, 34 control), of whom 101 were included in analysis (mean [SD] age, 56.5 [5.3] years; 73 [72.3%] women; 80 [79.2%] Black patients) and 20 physicians. Intervention patients found the tool helpful and wanted to use it again, rating it a median 9 of 10 (IQR, 8-10) and 10 of 10 (8-10), respectively. Compared with the control group, intervention patients more often correctly identified the service least likely (18 [46%] vs 0; P = .03) to improve their life expectancy. A greater number of patients also identified the service most likely to improve their life expectancy (26 [69%] vs 10 [30%]; P = .07), although this result was not statistically significant. Intervention patients reported greater mean [SD] improvement in SDM (4.7 [6.9] points) and near-term readiness to change (13.8 points for top-3-ranked recommendations). Point estimates indicated that patients in the intervention group experienced greater, although non-statistically significant, reductions in percentage of body weight (-2.96%; 95% CI, -8.18% to 2.28%), systolic blood pressure (-6.42 mm Hg; 95% CI, -16.12 to 3.27 mm Hg), hemoglobin A1c (-0.68%; 95% CI, -1.82% to 0.45%), 10-year atherosclerotic cardiovascular disease risk score (-1.20%; 95% CI, -3.65% to 1.26%), and low-density lipoprotein cholesterol (-8.46 mg/dL; 95% CI, -26.63 to 9.70 mg/dL) than the control group. Nineteen of 20 physicians wanted to continue using the decision tool in the future. In this clinical trial, an individualized preventive care decision support tool improved patient understanding of primary prevention and demonstrated promise for improved shared decision-making and preventive care utilization. ClinicalTrials.gov Identifier: NCT03023813.

Highlights

  • Preventable risk factors contributed to an estimated 61% of US deaths in 2019,1,2 and health risks increase with age.[3]

  • Point estimates indicated that patients in the intervention group experienced greater, non–statistically significant, reductions in percentage of body weight (−2.96%; 95% CI, −8.18% to 2.28%), systolic blood pressure (−6.42 mm Hg; 95% CI, −16.12 to 3.27 mm Hg), hemoglobin A1c (−0.68%; 95% CI, −1.82% to 0.45%), 10-year atherosclerotic cardiovascular disease risk score (−1.20%; 95% CI, −3.65% to 1.26%), and low-density lipoprotein cholesterol

  • We evaluated the potential of an individualized decision tool to help patients and physicians better understand the net benefits of all major, US Preventive Services Task Force (USPSTF)-recommended preventive services and improve preventive care delivery

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Summary

Introduction

Preventable risk factors contributed to an estimated 61% of US deaths in 2019,1,2 and health risks increase with age.[3]. They scarcely account for individuals’ unique characteristics, such as comorbid conditions, which affect 70% of middle-aged adults.[8] This standardized approach hinders physicians’ ability to identify which preventive services provide maximum benefit for a specific patient. Few guidelines consider patient preferences, including views about side effects, convenience, lifestyle, and cost.[9,10,11] This generic approach may contribute to low attainment of prevention targets.[8,12] Third, clinical time is limited, forcing physicians to prioritize among recommended guidelines without having tools to do so. A physician may know that both mammograms and colonoscopies are “life-saving,” but not understand their relative benefits.[13]

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