Implementation Support for a Social Risk Screening and Referral Process in Community Health Centers

Gold, Rachel; Kaufmann, Jorge; Cottrell, Erika; Bunce, Arwen; Sheppler, Christina; Hoopes, Megan; Krancari, Molly; Gottlieb, Laura M.; Bowen, Meg; Bava, Julianne; Mossman, Ned; Yosuf, Nadia; Marino, Miguel

doi:10.1056/cat.23.0034

Cited by 11 publications

(16 citation statements)

References 52 publications

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“…For example, two recently released quality measures are available for a few payment programs that specifically focus on social risk screening and positivity [12,13]. Concurrently, we must support those care settings that serve populations with a high prevalence of these social risks in collecting these data [45]. A study strength is our use of data from a nationwide network of community-based healthcare organizations that have been innovators in social risk screening since 2016 [22,46,47].…”

Section: Discussionmentioning

confidence: 99%

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening

Bensken,

McGrath,

Gold

et al. 2023

J. Clin. Trans. Sci.

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Introduction: Area-level social determinants of health (SDoH) and individual-level social risks are different, yet area-level measures are frequently used as proxies for individual-level social risks. This study assessed whether demographic factors were associated with patients being screened for individual-level social risks, the percentage who screened positive for social risks, and the association between SDoH and patient-reported social risks in a nationwide network of community-based health centers. Methods: Electronic health record data from 1,330,201 patients with health center visits in 2021 were analyzed using multilevel logistic regression. Associations between patient characteristics, screening receipt, and screening positive for social risks (e.g., food insecurity, housing instability, transportation insecurity) were assessed. The predictive ability of three commonly used SDoH measures (Area Deprivation Index, Social Deprivation Index, Material Community Deprivation Index) in identifying individual-level social risks was also evaluated. Results: Of 244,155 (18%) patients screened for social risks, 61,414 (25.2%) screened positive. Sex, race/ethnicity, language preference, and payer were associated with both social risk screening and positivity. Significant health system-level variation in both screening and positivity was observed, with an intraclass correlation coefficient of 0.55 for social risk screening and 0.38 for positivity. The three area-level SDoH measures had low accuracy, sensitivity, and area under the curve when used to predict individual social needs. Conclusion: Area-level SDoH measures may provide valuable information about the communities where patients live. However, policymakers, healthcare administrators, and researchers should exercise caution when using area-level adverse SDoH measures to identify individual-level social risks.

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Section: Discussionmentioning

confidence: 99%

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening

Bensken,

McGrath,

Gold

et al. 2023

J. Clin. Trans. Sci.

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“…30 Reducing barriers to the adoption of social risk screening will require concurrent strategies, such as providing technical assistance and training to help FQHCs integrate screening into existing workflows, giving FQHCs additional grants, and encouraging more flexible value-based payment models. 52 Importantly, there is no clear evidence about the advantages and disadvantages of implementing a standardized versus non-standardized social risk screener, particularly in terms of patient outcomes. It is possible, for example, that standardized screening may benefit potential organizations partnering with multiple FQHCs.…”

Section: Discussionmentioning

confidence: 99%

“…Consequently, FQHCs' implementation of social risk screening tools or engagement in cross‐sector efforts may be limited if these activities require significant contribution of staff time and resources outside of care delivery that is explicitly covered under the current payment system 30 . Reducing barriers to the adoption of social risk screening will require concurrent strategies, such as providing technical assistance and training to help FQHCs integrate screening into existing workflows, giving FQHCs additional grants, and encouraging more flexible value‐based payment models 52 . Importantly, there is no clear evidence about the advantages and disadvantages of implementing a standardized versus non‐standardized social risk screener, particularly in terms of patient outcomes.…”

Section: Discussionmentioning

confidence: 99%

Use of and barriers to adopting standardized social risk screening tools in federally qualified health centers during the first year of the COVID‐19 pandemic

Giron,

Cole,

Nguyen

2023

Health Services Research

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ObjectiveTo describe the national rate of social risk factor screening adoption among federally qualified health centers (FQHCs), examine organizational factors associated with social risk screening adoption, and identify barriers to utilizing a standardized screening tool in 2020.Data Source2020 Uniform Data System, a 100% sample of all US FQHCs (N = 1375).Study DesignWe used multivariable linear probability models to assess the association between social risk screening adoption and key FQHC characteristics. We used descriptive statistics to describe variations in screening tool types and barriers to utilizing standardized tools. We thematically categorized open‐ended responses about tools and barriers.Data CollectionNone.Principal FindingsIn 2020, 68.9% of FQHCs screened patients for any social risk factors. Characteristics associated with a greater likelihood of screening adoption included having high proportions of patients best served in a language other than English (18.8 percentage point [PP] increase, 95% CI: 6.0, 31.6) and being larger in size (10.3 PP increase, 95% CI: 0.7, 20.0). Having higher proportions of uninsured patients (14.2 PP decrease, 95% CI: −25.5, −0.3) and participating in Medicaid‐managed care contracts (7.3 PP decrease, 95% CI: −14.2, −0.3) were associated with lower screening likelihood. Among screening FQHCs, the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) was the most common tool (47.1%). Among non‐screening FQHCs, common barriers to using a standardized tool included lack of staff training to discuss social issues (25.2%), inability to include screening in patient intake (21.7%), and lack of funding for addressing social needs (19.2%).ConclusionsThough most FQHCs screened for social risk factors in 2020, various barriers have prevented nearly 1 in 3 FQHCs from adopting a screening tool. Policies that provide FQHCs with resources to support training and workflow changes may increase screening uptake and facilitate engagement with other sectors.

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“…The OCHIN ASCEND study provided 26 clinical sites (not all based in Oregon and not all providing primary care) 6 months of implementation supports to facilitate clinic uptake of relevant EHR tools that were also available to all OCHIN clinics. The EHR tools have been described in previous publications 31,32 ; they included tools for identifying patients due for social risk screening, documenting and reviewing screening results, and ordering social service referrals 33,34 . The EHR infrastructure (including the screening tools but also patient social risk summaries and population‐level data dashboards) was available to all OCHIN member clinics and remained available after the ASCEND study ended.…”

Section: Methodsmentioning

confidence: 99%

“…The EHR tools have been described in previous publications 31,32 ; they included tools for identifying patients due for social risk screening, documenting and reviewing screening results, and ordering social service referrals. 33,34 The EHR infrastructure (including the screening tools but also patient social risk summaries and population-level data dashboards) was available to all OCHIN member clinics and remained available after the ASCEND study ended. The implementation supports specific to the AS-CEND trial included practice coaching in how to use or adapt these tools in clinic workflows.…”

Section: Study Setting and Designmentioning

confidence: 99%

Community Health Center Staff Perspectives on Financial Payments for Social Care

LOPEZ,

WING,

ACKERMAN

et al. 2023

Milbank Quarterly

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Policy Points State and federal payers are actively considering strategies to increase the adoption of social risk screening and interventions in health care settings, including through the use of financial incentives. Activities related to social care in Oregon community health centers (CHCs) provided a unique opportunity to explore whether and how fee‐for‐service payments for social risk screening and navigation influence CHC activities. CHC staff, clinicians, and administrative leaders were often unaware of existing financial payments for social risk screening and navigation services. As currently designed, fee‐for‐service payments are unlikely to strongly influence CHC social care practices. ContextA growing crop of national policies has emerged to encourage health care delivery systems to ask about and try to address patients’ social risks, e.g., food, housing, and transportation insecurity, in care delivery contexts. In this study, we explored how community health center (CHC) staff perceive the current and potential influence of fee‐for‐service payments on clinical teams’ engagement in these activities.MethodsWe interviewed 42 clinicians, frontline staff, and administrative leaders from 12 Oregon CHC clinical sites about their social care initiatives, including about the role of existing or anticipated financial payments intended to promote social risk screening and referrals to social services. Data were analyzed using both inductive and deductive thematic analysis approaches.FindingsWe grouped findings into three categories: participants’ awareness of existing or anticipated financial incentives, uses for incentive dollars, and perceived impact of financial incentives on social care activities in clinical practices. Lack of awareness of existing incentives meant these incentives were not perceived to influence the behaviors of staff responsible for conducting screening and providing referrals. Current or anticipated meaningful uses for incentive dollars included paying for social care staff, providing social services, and supporting additional fundraising efforts. Frontline staff reported that the strongest motivator for clinic social care practices was the ability to provide responsive social services. Clinic leaders/managers noted that for financial incentives to substantively change CHC practices would require payments sizable enough to expand the social care workforce as well.ConclusionsSmall fee‐for‐service payments to CHCs for social risk screening and navigation services are unlikely to markedly influence CHC social care practices. Refining the design of financial incentives—e.g., by increasing clinical teams’ awareness of incentives, linking screening to well‐funded social services, and changing incentive amounts to support social care staffing needs—may increase the uptake of social care practices in CHCs.

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Implementation Support for a Social Risk Screening and Referral Process in Community Health Centers

Cited by 11 publications

References 52 publications

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening

Use of and barriers to adopting standardized social risk screening tools in federally qualified health centers during the first year of the COVID‐19 pandemic

Community Health Center Staff Perspectives on Financial Payments for Social Care

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