Comparing the performance of two social risk screening tools in a vulnerable subpopulation

Measuring social determinants of health in the All of Us Research Program

To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbach's alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Screening for Financial Hardship: Comparing Patient Survey Responses Using Two Different Screening Tools

BACKGROUND

Healthcare delivery organizations are increasingly screening patients for social risks using tools that vary in content and length.

OBJECTIVES

To compare two screening tools both containing questions related to financial hardship.

DESIGN

Cross-sectional survey.

PARTICIPANTS

Convenience sample of adult patients (n = 471) in three primary care clinics.

MAIN MEASURES

Participants randomly assigned to self-complete either: (1) a screening tool developed by the Centers for Medicare & Medicaid Services (CMS) consisting of six questions on financial hardship (housing stability, housing quality, food security, transportation security, utilities security); or (2) social and behavioral risk measures recommended by the National Academy of Medicine (NAM), including one question on financial hardship (financial strain). We compared patient acceptability of screening, positive screening rates for financial hardship, patient interest in assistance, and self-rated health.

RESULTS

Ninety-one percent of eligible/interested patients completed the relevant survey questions to be included in the study (N = 471/516). Patient acceptability was high for both tools, though more participants reported screening was appropriate when answering the CMS versus NAM questions (87% vs. 79%, p = 0.02). Of respondents completing the CMS tool, 57% (132/232) reported at least one type of financial hardship; on the NAM survey, 52% (125/239) reported financial hardship (p = 0.36). Nearly twice as many respondents indicated interest in assistance related to financial hardship after completing items on the CMS tool than on the NAM question (39% vs. 21%, p < 0.01).

CONCLUSIONS

Patients reported high acceptability of both social risk assessment tools. While rates of positive screens for financial hardship were similar across the two measures, more patients indicated interest in assistance after answering questions about financial hardship on the CMS tool. This might be because the screening questions on the CMS tool help patients to appreciate the types of assistance related to financial hardship that may be available after screening. Future research should assess the validity and comparative validity of individual measures and measure sets. Tool selection should be based on setting and population served, screening goals, and resources available.

Screening for Unstable Housing in a Healthcare Setting

Objectives: To describe existing tools for screening patients for unstable housing in a healthcare setting. Methods: A literature search was completed to retrieve articles published in the last 10 years on screening patients for unstable housing in a healthcare setting. Results: The current literature on screening patients for homelessness in healthcare settings describes a variety of tools administered by a range of healthcare providers, but all are based in the United States. Conclusion: The studies revealed the potential for effective screening in healthcare settings and positive engagement of patients and providers with screening. Key areas for future research include innovative methods of screening and evaluation of reliability and validity for a broader range of tools.

Developing a brief assessment of social risks for the Veterans Health Administration Survey of Healthcare Experiences of Patients

OBJECTIVE

To determine whether a 6- or 12-month look-back period affected rates of reported social risks in a social risk survey for use in the Veterans Health Administration and to assess associations of social risks with overall health and mental health.

STUDY DESIGN

Cross-sectional survey of respondents randomized to 6- or 12-month look-back period.

DATA SOURCES AND STUDY SETTING

Online survey with a convenience sample of Veterans in June and July 2021.

DATA COLLECTION/EXTRACTION METHODS

Veteran volunteers were recruited by email to complete a survey assessing social risks, including financial strain, adult caregiving, childcare, food insecurity, housing, transportation, internet access, loneliness/isolation, stress, discrimination, and legal issues. Outcomes included self-reported overall health and mental health. Chi-squared tests compared the prevalence of reported social risks between 6- and 12-month look-back periods. Spearman correlations assessed associations among social risks. Bivariate and multivariable logistic regression models estimated associations between social risks and fair/poor overall and mental health.

PRINCIPAL FINDINGS

Of 3418 Veterans contacted, 1063 (31.10%) responded (87.11% male; 85.61% non-Hispanic White; median age = 70, interquartile range [IQR] = 61-74). Prevalence of most reported social risks did not significantly differ by look-back period. Most social risks were weakly intercorrelated (median |r| = 0.24, IQR = 0.16-0.31). Except for legal issues, all social risks were associated with higher odds of fair/poor overall health and mental health in bivariate models. In models containing all significant social risks from bivariate models, adult caregiving and stress remained significant predictors of overall health; food insecurity, housing, loneliness/isolation, and stress remained significant for mental health.

CONCLUSIONS

Six- and 12-month look-back periods yielded similar rates of reported social risks. Although most individual social risks are associated with fair/poor overall and mental health, when examined together, only adult caregiving, stress, loneliness/isolation, food, and housing remain significant.

Evaluating the comparability of patient-level social risk data extracted from electronic health records: A systematic scoping review

Objective: To evaluate how and from where social risk data are extracted from EHRs for research purposes, and how observed differences may impact study generalizability. Methods: Systematic scoping review of peer-reviewed literature that used patient-level EHR data to assess 1 ± 6 social risk domains: housing, transportation, food, utilities, safety, social support/isolation. Results: 111/9022 identified articles met inclusion criteria. By domain, social support/isolation was most often included (N = 68/111), predominantly defined by marital/partner status (N = 48/68) and extracted from structured sociodemographic data (N = 45/48). Housing risk was defined primarily by homelessness (N = 39/49). Structured housing data was extracted most from billing codes and screening tools (N = 15/30, 13/30, respectively). Across domains, data were predominantly sourced from structured fields (N = 89/111) versus unstructured free text (N = 32/111). Conclusion: We identified wide variability in how social domains are defined and extracted from EHRs for research. More consistency, particularly in how domains are operationalized, would enable greater insights across studies.

Collection and Use of Social Determinants of Health Data in Inpatient General Internal Medicine Wards: A Scoping Review

BACKGROUND

There is growing interest in incorporating social determinants of health (SDoH) data collection in inpatient hospital settings to inform patient care. However, there is limited information on this data collection and its use in inpatient general internal medicine (GIM). This scoping review sought to describe the current state of the literature on SDoH data collection and its application to patient care in inpatient GIM settings.

METHODS

English-language searches on MedLine, Embase, Web of Science, CINAHL, Cochrane, and PsycINFO were conducted from 2000 to April 2021. Studies reporting systematic data collection or use of at least three SDoH, sociodemographic, or social needs variables in inpatient hospital GIM settings were included. Four independent reviewers screened abstracts, and two reviewers screened full-text articles.

RESULTS

A total of 8190 articles underwent abstract screening and eight were included. A range of SDoH tools were used, such as THRIVE, PRAPARE, WHO-Quality of Life, Measuring Health Equity, and a biopsychosocial framework. The most common SDoH were food security or malnutrition (n=7), followed by housing, transportation, employment, education, income, functional status and disability, and social support (n=5 each). Four of the eight studies applied the data to inform patient care, and three provided community resource referrals.

DISCUSSION

There is limited evidence to guide the collection and use of SDoH data in inpatient GIM settings. This review highlights the need for integrated care, the role of the electronic health record, and social history taking, all of which may benefit from more robust SDoH data collection. Future research should examine the feasibility and acceptability of SDoH integration in inpatient GIM settings.

Social risks and social needs in a health insurance exchange sample: a longitudinal evaluation of utilization

Background

Health systems are increasingly attempting to intervene on social adversity as a strategy to improve health care outcomes. To inform health system efforts to screen for social adversity, we sought to explore the stability of social risk and interest in assistance over time and to evaluate whether the social risk was associated with subsequent healthcare utilization.

Methods

We surveyed Kaiser Permanente members receiving subsidies from the healthcare exchange in Southern California to assess their social risk and desire for assistance using the Accountable Health Communities instrument. A subset of initial respondents was randomized to be re-surveyed at either three or six months later.

Results

A total of 228 participants completed the survey at both time points. Social risks were moderate to strongly stable across three and six months (Kappa range = .59-.89); however, social adversity profiles that included participants’ desire for assistance were more labile (3-month Kappa = .52; 95% CI = .41-.64 & 6-month Kappa = .48; 95% CI = .36-.6). Only housing-related social risks were associated with an increase in acute care (emergency, urgent care) six months after initial screening; no other associations between social risk and utilization were observed.

Conclusions

This study suggests that screening for social risk may be appropriate at intervals of six months, or perhaps longer, but that assessing desire for assistance may need to occur more frequently. Housing risks were associated with increases in acute care. Health systems may need to engage in screening and referral to resources to improve overall care and ultimately patient total health.

Low housing quality, unmet social needs, stress and depression among low-income smokers

•

Over 60% of low-income smokers reported housing quality problems.

•

Problems with housing quality were among the most common social needs.

•

Housing quality problems were associated with worse measures of health.

•

Poor housing quality may exacerbate health disparities for low-income smokers.

Smokers are at greater risk of multiple health conditions that are exacerbated by environmental hazards associated with low housing quality. However, little is known about the prevalence of low housing quality among low-income smokers. Using correlations and logistic regression, we examined associations among eight housing quality indicators – pests, water leaks, mold, lead paint, and working smoke detectors, appliances, heating, and air conditioning – and between housing quality and social needs, depressive symptoms, perceived stress, sleep problems, and self-rated health in a community-based sample of 786 low-income smokers from 6 states. Most participants were female (68%), and White (45%) or African-American (43%). One in four (27%) completed less than high school education, and 41% reported annual pre-tax household income of less than $10,000. Housing quality problems were common. Most participants (64%) reported at least one problem in their home, and 41% reported two or more problems, most commonly pest infestations (40%), water leaks (22%), lack of air conditioning (22%) and mold (18%). Lack of heat and air conditioning were correlated, as were water leaks and mold. Using logistic regression analyses controlling for participant demographic characteristics, we found that reporting more housing quality problems was associated with greater odds of worse mental and physical health outcomes. Multiple health threats, including housing quality, depressive symptoms, stress, poor sleep, and financial strain may be mutually reinforcing and compound the health consequence of smoking. Future research should seek to replicate these findings in other samples, and examine associations longitudinally to better understand causality.

Predicting health-related social needs in Medicaid and Medicare populations using machine learning

Providers currently rely on universal screening to identify health-related social needs (HRSNs). Predicting HRSNs using EHR and community-level data could be more efficient and less resource intensive. Using machine learning models, we evaluated the predictive performance of HRSN status from EHR and community-level social determinants of health (SDOH) data for Medicare and Medicaid beneficiaries participating in the Accountable Health Communities Model. We hypothesized that Medicaid insurance coverage would predict HRSN status. All models significantly outperformed the baseline Medicaid hypothesis. AUCs ranged from 0.59 to 0.68. The top performance (AUC = 0.68 CI 0.66–0.70) was achieved by the “any HRSNs” outcome, which is the most useful for screening prioritization. Community-level SDOH features had lower predictive performance than EHR features. Machine learning models can be used to prioritize patients for screening. However, screening only patients identified by our current model(s) would miss many patients. Future studies are warranted to optimize prediction of HRSNs.

Social Risk Factors and Desire for Assistance Among Patients Receiving Subsidized Health Care Insurance in a US-Based Integrated Delivery System

PURPOSE

Because social conditions such as food insecurity and housing instability shape health outcomes, health systems are increasingly screening for and addressing patients' social risks. This study documented the prevalence of social risks and examined the desire for assistance in addressing those risks in a US-based integrated delivery system.

METHODS

A survey was administered to Kaiser Permanente members on subsidized exchange health insurance plans (2018-2019). The survey included questions about 4 domains of social risks, desire for help, and attitudes. We conducted a descriptive analysis and estimated multivariate modified Poisson regression models.

RESULTS

Of 438 participants, 212 (48%) reported at least 1 social risk factor. Housing instability was the most common (70%) factor reported. Members with social risks reported more discomfort being screened for social risks (14.2% vs 5.4%; P = .002) than those without risks, although 90% of participants believed that health systems should assist in addressing social risks. Among those with 1-2 social risks, however, only 27% desired assistance. Non-Hispanic Black participants who reported a social risk were more than twice as likely to desire assistance compared with non-Hispanic White participants (adjusted relative risk [RR] 2.2; 95% CI, 1.3-3.8).

CONCLUSIONS

Athough most survey participants believed health systems have a role in addressing social risks, a minority of those reporting a risk wanted assistance and reported more discomfort being screened for risk factors than those without risks. Health systems should work to increase the comfort of patients in reporting risks, explore how to successfully assist them when desired, and offer resources to address these risks outside the health care sector.VISUAL ABSTRACT.

Association Between Unmet Essential Social Needs and Influenza Vaccination in US Adults

BACKGROUND

Although social factors influence uptake of preventive services, the association between social needs and influenza vaccination has not been comprehensively evaluated for adults seeking primary care in the USA.

OBJECTIVE

To determine the association between unmet social needs and influenza vaccination.

DESIGN

Retrospective, cross-sectional, multivariable logistic regression.

PARTICIPANTS

Persons completing ambulatory visits in a primary care department at a midwestern, urban, multispecialty, academic medical center between July 2017 and July 2019 (N = 7955 individuals included).

MAIN MEASURES

Completion of influenza vaccination in the 2018-2019 influenza season (primary outcome) or any year (secondary outcome) against 11 essential social needs (childcare, companionship, food security, health literacy, home safety, neighborhood safety, housing, health care provider costs, prescription costs, transportation, and utilities). Demographics, diabetic status, COPD, smoking status, office visit frequency, and hierarchical condition category risk scores were included as covariates.

KEY RESULTS

Individuals with transportation vulnerability were less likely to be vaccinated against influenza (current-year aOR 0.65, 95% CI: 0.53-0.78, p < 0.001; any-year aOR 0.58, 95% CI: 0.47-0.71, p < 0.001). Poor health literacy promoted any-year, but not current-year, influenza vaccination (any-year aOR 1.30, 95% CI: 1.01-1.69, p = 0.043). Older age, female sex, diabetes, more comorbidities, and more frequent primary care visits were associated with greater influenza vaccination. Persons with Black or other/multiple race and current smokers were less frequently vaccinated.

CONCLUSIONS

Transportation vulnerability, health literacy, smoking, age, sex, race, comorbidity, and office visit frequency are associated with influenza vaccination. Primary care-led interventions should consider these factors when designing outreach interventions.

TRIAL REGISTRATION

Not applicable.

Evaluation of a social determinants of health screening questionnaire and workflow pilot within an adult ambulatory clinic

BACKGROUND

There is increased recognition in clinical settings of the importance of documenting, understanding, and addressing patients' social determinants of health (SDOH) to improve health and address health inequities. This study evaluated a pilot of a standardized SDOH screening questionnaire and workflow in an ambulatory clinic within a large integrated health network in Northern California.

METHODS

The pilot screened for SDOH needs using an 11-question Epic-compatible paper questionnaire assessing eight SDOH and health behavior domains: financial resource, transportation, stress, depression, intimate partner violence, social connections, physical activity, and alcohol consumption. Eligible patients for the pilot receiving a Medicare wellness, adult annual, or new patient visits during a five-week period (February-March, 2020), and a comparison group from the same time period in 2019 were identified. Sociodemographic data (age, sex, race/ethnicity, and payment type), visit type, length of visit, and responses to SDOH questions were extracted from electronic health records, and a staff experience survey was administered. The evaluation was guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.

RESULTS

Two-hundred eighty-nine patients were eligible for SDOH screening. Responsiveness by domain ranged from 55 to 67%, except for depression. Half of patients had at least one identified social need, the most common being stress (33%), physical activity (22%), alcohol (12%), and social connections (6%). Physical activity needs were identified more in females (81% vs. 19% in males, p < .01) and at new patient/transfer visits (48% vs. 13% at Medicare wellness and 38% at adult wellness visits, p < .05). Average length of visit was 39.8 min, which was 1.7 min longer than that in 2019. Visit lengths were longer among patients 65+ (43.4 min) and patients having public insurance (43.6 min). Most staff agreed that collecting SDOH data was relevant and accepted the SDOH questionnaire and workflow but highlighted opportunities for improvement in training and connecting patients to resources.

CONCLUSION

Use of evidence-based SDOH screening questions and associated workflow was effective in gathering patient SDOH information and identifying social needs in an ambulatory setting. Future studies should use qualitative data to understand patient and staff experiences with collecting SDOH information in healthcare settings.

Association of Financial Worry and Material Financial Risk with Short-Term Ambulatory Healthcare Utilization in a Sample of Subsidized Exchange Patients

BACKGROUND

Financial burden can affect healthcare utilization. Few studies have assessed the short-term associations between material (debt, trouble paying rent) and psychological (worry or distress about affording future healthcare) financial risks, and subsequent outpatient and emergency healthcare use. Worry was defined as concerns about affording future healthcare.

OBJECTIVE

Examine whether worry about affording healthcare is associated with healthcare utilization when controlling for material risk and general anxiety DESIGN: Longitudinal observational study PARTICIPANTS: Kaiser Permanente members with exchange-based federally subsidized health insurance (n = 450, 45% response rate) MAIN MEASURES: Survey measures of financial risks (material difficulty paying for medical care and worry about affording healthcare) and general anxiety. Healthcare use (primary care, urgent care, emergency department, and outpatient specialty visits) in the 6 months following survey completion.

KEY RESULTS

Emergency department and primary care visits were not associated with material risk, worry about affording care, or general anxiety in individual and pooled analyses (all 95% confidence intervals (CI) for relative risk (RR) included 1). Although no individual predictor was associated with urgent care use (all 95% CIs for RR included 1), worry about affording prescriptions (relative risk (RR) = 2.01; 95% CI 1.14, 3.55) and general anxiety (RR = 0.38; 95% CI 0.15, 0.95) were significant when included in the same model, suggesting the two confounded each other. Worry about affording healthcare services was associated with fewer specialty care visits (RR = 0.40; 95% CI 0.25, 0.64) even when controlling for material risk and general anxiety, although general anxiety was also associated with more specialty care visits (RR = 1.98; 95% CI, 1.23, 3.18).

CONCLUSIONS

Screening for both general anxiety and financial worry may assist with specialty care utilization. Identifying these concerns may provide more opportunities to assist patients. Future research should examine interventions to reduce worry about cost of care.