The Integrated Population (I-POP) Health Trial (I-POP)

The Role of Community Health Workers to Reduce Health Disparities Using a Multi-Level Integrated Population Health Intervention

The primary aim of this study is to determine whether community health worker (CHW) navigation improves outcomes of chronic disease and chronic disease risk factors in a low-income, primarily ethnic minority population when combined with an evidence-based population health model as compared to usual care after 10 months.

The I-POP+CHW participants will be paired with a CHW at baseline to assist with navigation for 10-months between health and wellness services in the selected zip codes: 75210, 75215, 75216, 75217, 75223, or 75227. Participants will receive a multi-level intervention utilizing the current I-POP Health model that includes: 1) Access to health services (including oral health), 2) Access to clinical prevention services, 3) Access to education and facilities to increase physical activity and improved nutrition choices, and 4) Scheduled visits with CHWs for education and navigation. Individuals will complete study measures at baseline, 6-months, and 10-months. The control group participants will receive access to the same I-POP Health resources without CHW navigation until the end of 10-months (delayed CHW navigation). The current usual care model is outlined below (section 2.3) Participants will complete study measures at baseline, 6-months, and 10-months timepoints. Upon completion of 10-months measures, these individuals will be assigned a CHW and receive delayed navigation.

Control group participants will receive access to the same I-POP Health resources without CHW navigation until the end of 10-months (delayed CHW navigation). The current usual care model is outlined. Participants will complete study measures at baseline, 6-months, and 10-months timepoints. Upon completion of 10-months measures, these individuals will be assigned a CHW and receive delayed navigation.

I-POP+CHW participants will be paired with a CHW at baseline to assist with navigation for 10-months between health and wellness services in the selected zip codes: 75210, 75215, 75216, 75217, 75223, or 75227. Participants will receive a multi-level intervention utilizing the current I-POP Health model that includes: 1) Access to health services (including oral health), 2) Access to clinical prevention services, 3) Access to education and facilities to increase physical activity and improved nutrition choices, and 4) Scheduled visits with CHWs for education and navigation. Individuals will complete study measures at baseline, 6-months, and 10-months.

The current I-POP health model includes: 1) BSW HWC primary care medical home (for uninsured or Medicare patients), 2)BSW HWC providing diabetes prevention, nutrition education, weight loss, farm stands, physical activity programming (in collaboration with its onsite City of Dallas Park and Recreation Center), 3) BSW HWC programming at community sites in 75210, 4) Referrals to Parkland Hatcher Station clinic that provides health care to Medicaid patients, 5) Referrals between Parkland Hatcher Station and BSW HWC programming, 6) Community improvement in collaboration with Frazier Revitalization Inc. Individuals will have access to resources within our current, ongoing I-POP Health model, but without CHW navigation between BSW HWC and local service providers. Participants will complete follow-up visits for collection of study measures with study personnel at 6- and 10- months. At the end of the 10-month follow-up period, participants receive an assigned CHW and CHW-navigation.

Individuals randomized to this condition will be paired with a CHW to assist with navigation of I-POP Health resources at BSW HWC and entities in local zip codes. CHW navigation will occur through monthly one-on-one follow-up visits for a period of 10-months. Participants will complete study visits for collection of data measures at baseline, 6- and 10- month timepoints. Study participation ends with completion of 10-months data measures.

A composite score of 10 biomarkers to measure chronic stress and health outcomes. The biomarkers are BMI, waist-to-hip ratio, HDL, TC/HDL ratio, triglycerides, HbA1c, SBP, DBP, C-reactive protein, and cortisol. For each marker a value of 1 will be assigned if that exceed the third quartile except for HDL where a value of 1 will be assigned if lower than first quartile; otherwise a score of zero will be assigned. [scale: Count of risk factors. May be dichotomized as high risk = 6 to 10, low risk=0 to 5]

A composite score of 10 biomarkers to measure chronic stress and health outcomes. The biomarkers are BMI, waist-to-hip ratio, HDL, TC/HDL ratio, triglycerides, HbA1c, SBP, DBP, C-reactive protein, and cortisol. For each marker a value of 1 will be assigned if that exceed the third quartile except for HDL where a value of 1 will be assigned if lower than first quartile; otherwise a score of zero will be assigned. [scale: Count of risk factors. May be dichotomized as high risk = 6 to 10, low risk=0 to 5].

4mL saliva collected fasting in the morning. [Scale: measured in a continuous scale. Normal range 0.007 - 0.115 ug/dL. Value exceeded the normal range indicates higher level of stress.]

4mL saliva collected fasting in the morning. [Scale: measured in a continuous scale. Normal range 0.007 - 0.115 ug/dL. Value exceeded the normal range indicates higher level of stress.]

4mL saliva collected fasting in the morning. [Scale: measured in a continuous scale. Normal range 25 pg/mL - 1600 pg/mL. Value exceeded the normal range indicates higher level of inflammation.]

4mL saliva collected fasting in the morning. [Scale: measured in a continuous scale. Normal range 25 pg/mL - 1600 pg/mL. Value exceeded the normal range indicates higher level of inflammation.]

Weight in pounds (lbs) divided by height in inches (in) squared and multiplying by a conversion factor of 703

Weight in pounds (lbs) divided by height in inches (in) squared and multiplying by a conversion factor of 703

Weight in pounds (lbs) divided by height in inches (in) squared and multiplying by a conversion factor of 703

Measured by self report Dietary Screening questionnaire (DSQ). [scale: dietary nutrients will be calculated on a continuous scale based on NHANES guideline. Score: 0 to any positive value. A score above or below the threshold based on 2000 calories per day would indicate worse outcome.]

Measured by self report Dietary Screening questionnaire (DSQ). [scale: dietary nutrients will be calculated on a continuous scale based on NHANES guideline. Score: 0 to any positive value. A score above or below the threshold based on 2000 calories per day would indicate worse outcome.]

Measured by self report Dietary Screening questionnaire (DSQ). [scale: dietary nutrients will be calculated on a continuous scale based on NHANES guideline. Score: 0 to any positive value. A score above or below the threshold based on 2000 calories per day would indicate worse outcome.]

Measured by self-report survey. [scale: count the number visits at healthcare or wellness centers. A higher score would indicate better utilization.]

Measured by self-report survey. [scale: count the number visits at healthcare or wellness centers. A higher score would indicate better utilization.]

Measured by self-report survey. [scale: count the number visits at healthcare or wellness centers. A higher score would indicate better utilization.]

Inclusion Criteria: Age 18 years or older Ability to alter diet and/or physical activity Willing to participate in a 10-month study Resident of selected zip codes: 75210, 75215, 75216, 75217, 75223, or 75227 Not having utilized BSW HWC membership services within the past 12 months Not planning to move outside of the selected zip code area within the next 6 months Exclusion Criteria: Below the age of 18 years Unable or unwilling to alter diet and/or physical activity Not willing to participate in a 10-month study Not resident of local selected zip codes: 75210, 75215, 75216, 75217, 75223, or 75227 Currently using or have used BSW HWC membership services within the past 12 months Planning to move outside of the selected zip code area within the next 6 months

Kitzman H, Dodgen L, Mamun A, Slater JL, King G, Slater D, King A, Mandapati S, DeHaven M. Community-based participatory research to design a faith-enhanced diabetes prevention program: The Better Me Within randomized trial. Contemp Clin Trials. 2017 Nov;62:77-90. doi: 10.1016/j.cct.2017.08.003. Epub 2017 Aug 12.

Tan M, Mamun A, Kitzman H, Dodgen L. Longitudinal Changes in Allostatic Load during a Randomized Church-based, Lifestyle Intervention in African American Women. Ethn Dis. 2019 Apr 18;29(2):297-308. doi: 10.18865/ed.29.2.297. eCollection 2019 Spring.

Tan M, Mamun A, Kitzman H, Mandapati SR, Dodgen L. Neighborhood Disadvantage and Allostatic Load in African American Women at Risk for Obesity-Related Diseases. Prev Chronic Dis. 2017 Nov 22;14:E119. doi: 10.5888/pcd14.170143.

Kim K, Choi JS, Choi E, Nieman CL, Joo JH, Lin FR, Gitlin LN, Han HR. Effects of Community-Based Health Worker Interventions to Improve Chronic Disease Management and Care Among Vulnerable Populations: A Systematic Review. Am J Public Health. 2016 Apr;106(4):e3-e28. doi: 10.2105/AJPH.2015.302987. Epub 2016 Feb 18.

Nelson HD, Cantor A, Wagner J, Jungbauer R, Quinones A, Fu R, Stillman L, Kondo K. Achieving Health Equity in Preventive Services [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2019 Dec. Report No.: 20-EHC002-EF. Available from http://www.ncbi.nlm.nih.gov/books/NBK550958/

Wesson D, Kitzman H, Halloran KH, Tecson K. Innovative Population Health Model Associated With Reduced Emergency Department Use And Inpatient Hospitalizations. Health Aff (Millwood). 2018 Apr;37(4):543-550. doi: 10.1377/hlthaff.2017.1099.

Wesson DE, Kitzman HE. How Academic Health Systems Can Achieve Population Health in Vulnerable Populations Through Value-Based Care: The Critical Importance of Establishing Trusted Agency. Acad Med. 2018 Jun;93(6):839-842. doi: 10.1097/ACM.0000000000002140.

Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in Obesity Among Adults in the United States, 2005 to 2014. JAMA. 2016 Jun 7;315(21):2284-91. doi: 10.1001/jama.2016.6458.

Howard JT, Sparks PJ. Does allostatic load calculation method matter? Evaluation of different methods and individual biomarkers functioning by race/ethnicity and educational level. Am J Hum Biol. 2016 Sep 10;28(5):627-35. doi: 10.1002/ajhb.22843. Epub 2016 Feb 15.

Upchurch DM, Stein J, Greendale GA, Chyu L, Tseng CH, Huang MH, Lewis TT, Kravitz HM, Seeman T. A Longitudinal Investigation of Race, Socioeconomic Status, and Psychosocial Mediators of Allostatic Load in Midlife Women: Findings From the Study of Women's Health Across the Nation. Psychosom Med. 2015 May;77(4):402-12. doi: 10.1097/PSY.0000000000000175.

Chang A, Patberg E, Cueto V, Li H, Singh B, Kenya S, Alonzo Y, Carrasquillo O. Community Health Workers, Access to Care, and Service Utilization Among Florida Latinos: A Randomized Controlled Trial. Am J Public Health. 2018 Sep;108(9):1249-1251. doi: 10.2105/AJPH.2018.304542. Epub 2018 Jul 19.

Johnson TL, Van Der Heijde M, Davenport S, et al. Population health in primary care: Cost, quality and experience impact. The American Journal of Accountable Care. 2017;5(3):10-20.

Kindig D, Stoddart G. What is population health? Am J Public Health. 2003 Mar;93(3):380-3. doi: 10.2105/ajph.93.3.380.

Lushniak BD, Alley DE, Ulin B, Graffunder C. The National Prevention Strategy: leveraging multiple sectors to improve population health. Am J Public Health. 2015 Feb;105(2):229-31. doi: 10.2105/AJPH.2014.302257. No abstract available.

Paskett E, Thompson B, Ammerman AS, Ortega AN, Marsteller J, Richardson D. Multilevel Interventions To Address Health Disparities Show Promise In Improving Population Health. Health Aff (Millwood). 2016 Aug 1;35(8):1429-34. doi: 10.1377/hlthaff.2015.1360.