Marmot M. Economic and social determinants of disease. Bull World Health Organ. 2001;79:988–9.
CAS
PubMed
PubMed Central
Google Scholar
Booske BC, Athens JK, Kindig DA, Park H, Remington PL. Different perspectives for assigning weights to determinants of health. Madison: University of Wisconsin: Population Health Institute; 2010.
Google Scholar
Beck AF, Cohen AJ, Colvin JD, Fichtenberg CM, Fleegler EW, Garg A, et al. Perspectives from the society for pediatric research: interventions targeting social needs in pediatric clinical care. Pediatr Res. 2018;84(1):10.
Article
Google Scholar
Alley DE, Asomugha CN, Conway PH, Sanghavi DM. Accountable health communities—addressing social needs through Medicare and Medicaid. N Engl J Med. 2016;374(1):8–11.
Article
CAS
Google Scholar
Gottlieb L, Tobey R, Cantor J, Hessler D, Adler NE. Integrating social and medical data to improve population health: opportunities and barriers. Health Aff. 2016;35(11):2116–23.
Article
Google Scholar
Fraze TK, Brewster AL, Lewis VA, Beidler LB, Murray GF, Colla CH. Prevalence of screening for food insecurity, housing instability, utility needs, transportation needs, and interpersonal violence by US physician practices and hospitals. JAMA Netw Open. 2019;2(9):1911514.
Article
Google Scholar
Moore J, Adams C, Tuck K. Medicaid access and coverage to care in 2018: results from the Institute for Medicaid Innovation's 2019 annual Medicaid managed care survey. 2018.
Weir RC, Proser M, Jester M, Li V, Hood-Ronick CM, Gurewich D. Collecting social determinants of health data in the clinical setting: findings from national PRAPARE implementation. J Health Care Poor Underserved. 2020;31(2):1018–35.
Article
Google Scholar
National Association of Community Health Centers AoAPCHO, Association OPC. PRAPARE implementation and action toolkit. Author Bethesda, MD; 2016.
Weir CR, Jester M. Assessing the relationship between social determinants of health and outcomes: findings from the PRAPARE pilot. nachc.org: National Association of Community Health Centers; 2018 June 25, 2018.
Henrikson NB, Blasi PR, Dorsey CN, Mettert KD, Nguyen MB, Walsh-Bailey C, et al. Psychometric and pragmatic properties of social risk screening tools: a systematic review. Am J Prev Med. 2019;57(6):S13–24.
Article
Google Scholar
Cantor J, Cohen L, Mikkelsen L, Pañares R, Srikantharajah J, Valdovinos E. Community-centered health homes. Oakland: Prevention Institute; 2011.
Google Scholar
Neuwirth EEB, Schmittdiel JA, Tallman K, Bellows J. Understanding panel management: a comparative study of an emerging approach to population care. Perm J. 2007;11(3):12.
Article
Google Scholar
National Academies of Sciences E, Medicine. Accounting for social risk factors in Medicare payment: criteria, factors, and methods: National Academies Press; 2016.
Joynt KE, De Lew N, Sheingold SH, Conway PH, Goodrich K, Epstein AM. Should Medicare value-based purchasing take social risk into account? N Engl J Med. 2017;376(6):510–3.
Article
Google Scholar
Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, et al. Heart disease and stroke statistics—2020 update: a report from the American Heart Association. Circulation. 2020;141(9):e139–596.
Article
Google Scholar
Drake C, Eisenson H. Assessing and addressing social needs in primary care. N Engl J Med Catal. 2019;5(6):1–12.
PRAPARE Validation Using 8 “Gold Standard” Stages of Measure Development: National Association of Community Health Centers; 2019 [July 3, 2020]. http://www.nachc.org/wp-content/uploads/2019/10/prapare_validation-fact-sheet-2019-9-26.pdf.
People H. Healthy people 2020 objectives. US Department of Health and Human Services. 2020.
Hedis N. Healthcare effectiveness data and information set. Washington: NCQA; 2009.
Google Scholar
Kreatsoulas C, Anand SS. The impact of social determinants on cardiovascular disease. Can J Cardiol. 2010;26:8C-13C.
Article
Google Scholar
Whelton P, Carey R, Aronow W, Casey D Jr, Collins K, Himmelfarb DC, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: executive summary: a report of the American college of cardiology/American heart association task force on clinical practice guidelines (vol 71, pg 2199, 2018). J Am Coll Cardiol. 2018;71(19):2273–5.
Article
Google Scholar
Lloyd-Jones DM, Huffman MD, Karmali KN, Sanghavi DM, Wright JS, Pelser C, et al. Estimating longitudinal risks and benefits from cardiovascular preventive therapies among medicare patients: the Million Hearts Longitudinal ASCVD Risk Assessment Tool: a special report from the American Heart Association and American College of Cardiology. J Am Coll Cardiol. 2017;69(12):1617–36.
Article
Google Scholar
Karmali KN, Goff DC, Ning H, Lloyd-Jones DM. A systematic examination of the 2013 ACC/AHA pooled cohort risk assessment tool for atherosclerotic cardiovascular disease. J Am Coll Cardiol. 2014;64(10):959–68.
Article
Google Scholar
Wells BJ, Chagin KM, Nowacki AS, Kattan MW. Strategies for handling missing data in electronic health record derived data. Egems. 2013;1(3):1035.
Article
Google Scholar
Hosmer DW, Lemeshow S. Applied logistic regression. New York: Wiley; 2000.
Book
Google Scholar
Heinze G, Wallisch C, Dunkler D. Variable selection–a review and recommendations for the practicing statistician. Biom J. 2018;60(3):431–49.
Article
Google Scholar
Ahrens A, Hansen CB, Schaffer ME. lassopack: model selection and prediction with regularized regression in Stata. arXiv:190105397. 2019.
Kennedy P. A guide to econometrics. Cambridge: MIT press; 2003.
Google Scholar
DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–45.
Article
CAS
Google Scholar
Steyerberg EW, Harrell FE Jr, Borsboom GJ, Eijkemans M, Vergouwe Y, Habbema JDF. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54(8):774–81.
Article
CAS
Google Scholar
StataCorp L. Stata statistical software: release 16. College Station, TX. 2019.
Gold R, Bunce A, Cowburn S, Dambrun K, Dearing M, Middendorf M, et al. Adoption of social determinants of health EHR tools by community health centers. Ann Fam Med. 2018;16(5):399–407.
Article
Google Scholar
Theiss J, Regenstein M. Facing the need: screening practices for the social determinants of health. J Law Med Ethics. 2017;45(3):431–41.
Article
Google Scholar
Doyle SK, Chang AM, Levy P, Rising KL. Achieving health equity in hypertension management through addressing the social determinants of health. Curr Hypertens Rep. 2019;21(8):58.
Article
Google Scholar
Byhoff E, Taylor LA. Massachusetts community-based organization perspectives on Medicaid redesign. Am J Prev Med. 2019;57(6):S74–81.
Article
Google Scholar
Billioux A, Verlander K, Anthony S, Alley D. Standardized screening for health-related social needs in clinical settings: the accountable health communities screening tool. NAM Perspectives. 2017.
Thomas-Henkel C, Schulman M. Screening for social determinants of health in populations with complex needs: implementation considerations. Available from: The Robert Wood Johnson Foundation and the Center for Health Care Strategies, New York, NY. 2017.
Garg A, Toy S, Tripodis Y, Silverstein M, Freeman E. Addressing social determinants of health at well child care visits: a cluster RCT. Pediatrics. 2015;135(2):e296–304.
Article
Google Scholar
Gottlieb LM, Wing H, Adler NE. A systematic review of interventions on patients’ social and economic needs. Am J Prev Med. 2017;53(5):719–29.
Article
Google Scholar
Bennett GG, Wolin KY, Duncan DT. Social determinants of obesity. In: Obesity epidemiology: methods and applications. 2008. pp. 342–76.
Frizzell JD, Liang L, Schulte PJ, Yancy CW, Heidenreich PA, Hernandez AF, et al. Prediction of 30-day all-cause readmissions in patients hospitalized for heart failure: comparison of machine learning and other statistical approaches. JAMA Cardiol. 2017;2(2):204–9.
Article
Google Scholar
Miller PE, Pawar S, Vaccaro B, McCullough M, Rao P, Ghosh R, et al. Predictive abilities of machine learning techniques may be limited by dataset characteristics: insights from the UNOS database. J Cardiac Fail. 2019;25(6):479–83.
Article
Google Scholar
van der Ploeg T, Steyerberg EW. Feature selection and validated predictive performance in the domain of Legionella pneumophila: a comparative study. BMC Res Notes. 2016;9(1):1–7.
Article
Google Scholar
Chen M, Tan X, Padman R. Social determinants of health in electronic health records and their impact on analysis and risk prediction: a systematic review. J Am Med Inform Assoc. 2020;27(11):1764–73.
Article
Google Scholar
Cohen MK. North Carolina’s transformation to Medicaid managed care. N C Med J. 2019;80(5):277–9.
PubMed
Google Scholar
Bachrach D. Addressing patients' social needs: an emerging business case for provider investment: Commonwealth Fund; 2014.
Anderson AC, O’Rourke E, Chin MH, Ponce NA, Bernheim SM, Burstin H. Promoting health equity and eliminating disparities through performance measurement and payment. Health Aff. 2018;37(3):371–7.
Article
Google Scholar