Joshua R Vest1, Nir Menachemi2, Shaun J Grannis3, Jennifer L Ferrell4, Suranga N Kasthurirathne5, Ying Zhang6, Yan Tong6, Paul K Halverson7. 1. Department of Health Policy and Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana; Regenstrief Institute, Indianapolis, Indiana. Electronic address: joshvest@iu.edu. 2. Department of Health Policy and Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana; Regenstrief Institute, Indianapolis, Indiana. 3. Regenstrief Institute, Indianapolis, Indiana; Department of Family Medicine, School of Medicine, Indiana University, Indianapolis, Indiana. 4. Eskenazi Health, Indianapolis, Indiana. 5. Regenstrief Institute, Indianapolis, Indiana; Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana. 6. Department of Biostatistics, School of Medicine and Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana. 7. Department of Health Policy and Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana; Regenstrief Institute, Indianapolis, Indiana; Department of Family Medicine, School of Medicine, Indiana University, Indianapolis, Indiana.
Abstract
INTRODUCTION: Social determinants of health are critical drivers of health status and cost, but are infrequently screened or addressed in primary care settings. Systematic approaches to identifying individuals with unmet social determinants needs could better support practice workflows and linkages of patients to services. A pilot study examined the effect of a risk-stratification tool on referrals to services that address social determinants in an urban safety-net population. METHODS: An intervention that risk stratified patients according to the need for wraparound was evaluated in a stepped wedge design (i.e., phased implementation at the clinic level during 2017). Staff at nine federally qualified health centers received a daily report predicting patients' needs for social worker, dietitian, behavioral health, and other wraparound services (categorized as low, rising, or high risk). Outcomes included referrals and uptake of appointments to wraparound services. RESULTS: Among 238,087 encounters, providing clinic staff with risk-stratification scores increased the odds that a patient would be referred to a social worker. For patients categorized as high risk, the odds of a social work referral was 65% higher than controls and similar patients, but lower effect sizes were observed for individuals categorized with rising and low risk. Among referred patients, the intervention was generally associated with increased odds of kept appointments. CONCLUSIONS: This study provided preliminary evidence that risk-stratification interventions to identify patients in need of wraparound services to address social determinants can increase referrals and uptake of services that may address social drivers of disease burden.
INTRODUCTION: Social determinants of health are critical drivers of health status and cost, but are infrequently screened or addressed in primary care settings. Systematic approaches to identifying individuals with unmet social determinants needs could better support practice workflows and linkages of patients to services. A pilot study examined the effect of a risk-stratification tool on referrals to services that address social determinants in an urban safety-net population. METHODS: An intervention that risk stratified patients according to the need for wraparound was evaluated in a stepped wedge design (i.e., phased implementation at the clinic level during 2017). Staff at nine federally qualified health centers received a daily report predicting patients' needs for social worker, dietitian, behavioral health, and other wraparound services (categorized as low, rising, or high risk). Outcomes included referrals and uptake of appointments to wraparound services. RESULTS: Among 238,087 encounters, providing clinic staff with risk-stratification scores increased the odds that a patient would be referred to a social worker. For patients categorized as high risk, the odds of a social work referral was 65% higher than controls and similar patients, but lower effect sizes were observed for individuals categorized with rising and low risk. Among referred patients, the intervention was generally associated with increased odds of kept appointments. CONCLUSIONS: This study provided preliminary evidence that risk-stratification interventions to identify patients in need of wraparound services to address social determinants can increase referrals and uptake of services that may address social drivers of disease burden.
Authors: Steven J Korzeniewski; Carla Bezold; Jason T Carbone; Shooshan Danagoulian; Bethany Foster; Dawn Misra; Maher M El-Masri; Dongxiao Zhu; Robert Welch; Lauren Meloche; Alex B Hill; Phillip Levy Journal: Online J Public Health Inform Date: 2020-05-16
Authors: Michael J Kleiman; Abbi D Plewes; Arthur Owora; Randall W Grout; Paul Richard Dexter; Nicole R Fowler; James E Galvin; Zina Ben Miled; Malaz Boustani Journal: Trials Date: 2022-10-11 Impact factor: 2.728
Authors: Shelley-Ann M Girwar; Robert Jabroer; Marta Fiocco; Stephen P Sutch; Mattijs E Numans; Marc A Bruijnzeels Journal: Health Sci Rep Date: 2021-07-23
Authors: Titus Schleyer; Linda Williams; Jonathan Gottlieb; Christopher Weaver; Michele Saysana; Jose Azar; Josh Sadowski; Chris Frederick; Siu Hui; Areeba Kara; Laura Ruppert; Sarah Zappone; Michael Bushey; Randall Grout; Peter J Embi Journal: Learn Health Syst Date: 2021-06-23