Elizabeth L Tung1,2,3, Emily M Abramsohn4, Kelly Boyd4, Jennifer A Makelarski4, David G Beiser5,6, Chiahung Chou7,8, Elbert S Huang9,10,6, Jonathan Ozik11,12, Chaitanya Kaligotla11,12, Stacy Tessler Lindau4,6,13,14. 1. Section of General Internal Medicine, University of Chicago, Chicago, IL, USA. eliztung@uchicago.edu. 2. Center for Health and the Social Sciences, University of Chicago, Chicago, IL, USA. eliztung@uchicago.edu. 3. Chicago Center for Diabetes Translation Research, University of Chicago, Chicago, IL, USA. eliztung@uchicago.edu. 4. Department of Obstetrics and Gynecology, University of Chicago, Chicago, IL, USA. 5. Section of Emergency Medicine, University of Chicago, Chicago, IL, USA. 6. Center for Healthcare Delivery Science and Innovation, University of Chicago, Chicago, IL, USA. 7. Department of Health Outcomes Research and Policy, Auburn University, Auburn, AL, USA. 8. Department of Medical Research, China Medical University Hospital, Taichung, Taiwan. 9. Section of General Internal Medicine, University of Chicago, Chicago, IL, USA. 10. Chicago Center for Diabetes Translation Research, University of Chicago, Chicago, IL, USA. 11. Consortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA. 12. Decision and Infrastructure Sciences Division, Argonne National Laboratory, Lemont, IL, USA. 13. Department of Medicine-Geriatrics, University of Chicago, Chicago, IL, USA. 14. Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA.
Abstract
BACKGROUND: Connecting patients to community-based resources is now a cornerstone of modern healthcare that supports self-management of health. The mechanisms that link resource information to behavior change, however, remain poorly understood. OBJECTIVE: To evaluate the impact of CommunityRx, an automated, low-intensity resource referral intervention, on patients' knowledge, beliefs, and use of community resources. DESIGN: Real-world controlled clinical trial at an urban academic medical center in 2015-2016; participants were assigned by alternating week to receive the CommunityRx intervention or usual care. Surveys were administered at baseline, 1 week, 1 month, and 3 months. PARTICIPANTS: Publicly insured adults, ages 45-74 years. INTERVENTION: CommunityRx generated an automated, personalized list of resources, known as HealtheRx, near each participant's home using condition-specific, evidence-based algorithms. Algorithms used patient demographic and health characteristics documented in the electronic health record to identify relevant resources from a comprehensive, regularly updated database of health-related resources in the study area. MAIN MEASURES: Using intent-to-treat analysis, we examined the impact of HealtheRx referrals on (1) knowledge of the most commonly referred resource types, including healthy eating classes, individual counseling, mortgage assistance, smoking cessation, stress management, and weight loss classes or groups, and (2) beliefs about having resources in the community to manage health. KEY RESULTS: In a real-world controlled trial of 374 adults, intervention recipients improved knowledge (AOR = 2.15; 95% CI, 1.29-3.58) and beliefs (AOR = 1.68; 95% CI, 1.07-2.64) about common resources in the community to manage health, specifically gaining knowledge about smoking cessation (AOR = 2.76; 95% CI, 1.07-7.12) and weight loss resources (AOR = 2.26; 95% CI 1.05-4.84). Positive changes in both knowledge and beliefs about community resources were associated with higher resource use (P = 0.02). CONCLUSIONS: In a middle-age and older population with high morbidity, a low-intensity health IT intervention to deliver resource referrals promoted behavior change by increasing knowledge and positive beliefs about community resources for self-management of health. NIH TRIAL REGISTRY: NCT02435511.
BACKGROUND: Connecting patients to community-based resources is now a cornerstone of modern healthcare that supports self-management of health. The mechanisms that link resource information to behavior change, however, remain poorly understood. OBJECTIVE: To evaluate the impact of CommunityRx, an automated, low-intensity resource referral intervention, on patients' knowledge, beliefs, and use of community resources. DESIGN: Real-world controlled clinical trial at an urban academic medical center in 2015-2016; participants were assigned by alternating week to receive the CommunityRx intervention or usual care. Surveys were administered at baseline, 1 week, 1 month, and 3 months. PARTICIPANTS: Publicly insured adults, ages 45-74 years. INTERVENTION: CommunityRx generated an automated, personalized list of resources, known as HealtheRx, near each participant's home using condition-specific, evidence-based algorithms. Algorithms used patient demographic and health characteristics documented in the electronic health record to identify relevant resources from a comprehensive, regularly updated database of health-related resources in the study area. MAIN MEASURES: Using intent-to-treat analysis, we examined the impact of HealtheRx referrals on (1) knowledge of the most commonly referred resource types, including healthy eating classes, individual counseling, mortgage assistance, smoking cessation, stress management, and weight loss classes or groups, and (2) beliefs about having resources in the community to manage health. KEY RESULTS: In a real-world controlled trial of 374 adults, intervention recipients improved knowledge (AOR = 2.15; 95% CI, 1.29-3.58) and beliefs (AOR = 1.68; 95% CI, 1.07-2.64) about common resources in the community to manage health, specifically gaining knowledge about smoking cessation (AOR = 2.76; 95% CI, 1.07-7.12) and weight loss resources (AOR = 2.26; 95% CI 1.05-4.84). Positive changes in both knowledge and beliefs about community resources were associated with higher resource use (P = 0.02). CONCLUSIONS: In a middle-age and older population with high morbidity, a low-intensity health IT intervention to deliver resource referrals promoted behavior change by increasing knowledge and positive beliefs about community resources for self-management of health. NIH TRIAL REGISTRY: NCT02435511.
Entities:
Keywords:
community linkages; community resource referral; disease-management; health information technology; health-related social needs; self-care; self-management; social determinants of health
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Authors: Stacy Tessler Lindau; Jennifer A Makelarski; Chaitanya Kaligotla; Emily M Abramsohn; David G Beiser; Chiahung Chou; Nicholson Collier; Elbert S Huang; Charles M Macal; Jonathan Ozik; Elizabeth L Tung Journal: PLoS Comput Biol Date: 2021-10-25 Impact factor: 4.475