Prioritization of Randomized Clinical Trial Questions for Children Hospitalized With Common Conditions: A Consensus Statement.

Importance: There is a lack of randomized clinical trial (RCT) data to guide many routine decisions in the care of children hospitalized for common conditions. A first step in addressing the shortage of RCTs for this population is to identify the most pressing RCT questions for children hospitalized with common conditions. Objective: To identify the most important and feasible RCT questions for children hospitalized with common conditions. Design, Setting, and Participants: For this consensus statement, a 3-stage modified Delphi process was used in a virtual conference series spanning January 1 to September 29, 2022. Forty-six individuals from 30 different institutions participated in the process. Stage 1 involved construction of RCT questions for the 10 most common pediatric conditions leading to hospitalization. Participants used condition-specific guidelines and reviews from a structured literature search to inform their development of RCT questions. During stage 2, RCT questions were refined and scored according to importance. Stage 3 incorporated public comment and feasibility with the prioritization of RCT questions. Main Outcomes and Measures: The main outcome was RCT questions framed in a PICO (population, intervention, control, and outcome) format and ranked according to importance and feasibility; score choices ranged from 1 to 9, with higher scores indicating greater importance and feasibility. Results: Forty-six individuals (38 who shared demographic data; 24 women [63%]) from 30 different institutions participated in our modified Delphi process. Participants included children's hospital (n = 14) and community hospital (n = 13) pediatricians, parents of hospitalized children (n = 4), other clinicians (n = 2), biostatisticians (n = 2), and other researchers (n = 11). The process yielded 62 unique RCT questions, most of which are pragmatic, comparing interventions in widespread use for which definitive effectiveness data are lacking. Overall scores for importance and feasibility of the RCT questions ranged from 1 to 9, with a median of 5 (IQR, 4-7). Six of the top 10 selected questions focused on determining optimal antibiotic regimens for 3 common infections (pneumonia, urinary tract infection, and cellulitis). Conclusions and Relevance: This consensus statementhas identified the most important and feasible RCT questions for children hospitalized with common conditions. This list of RCT questions can guide investigators and funders in conducting impactful trials to improve care and outcomes for hospitalized children.

Associations between Social Adversity and Biomarkers of Inflammation, Stress, and Aging in Children.

BACKGROUND: Prior work has found relationships between childhood social adversity and biomarkers of stress, but knowledge gaps remain. To help address these gaps, we explored associations between social adversity and biomarkers of inflammation (interleukin-1ß [IL-1ß], IL-6, IL-8, tumor necrosis factor-alpha [TNF-α], and salivary cytokine hierarchical "clusters" based on the three interleukins), neuroendocrine function (cortisol, cortisone, dehydroepiandrosterone, testosterone, and progesterone), neuromodulation (N-arachidonoylethanolamine, stearoylethanolamine, oleoylethanolamide, and palmitoylethanolamide), and epigenetic aging (Pediatric-Buccal-Epigenetic clock). METHODS: We collected biomarker samples of children ages 0-17 recruited from an acute care pediatrics clinic and examined their associations with caregiver-endorsed education, income, social risk factors, and cumulative adversity. We calculated regression-adjusted means for each biomarker and compared associations with social factors using Wald tests. We used logistic regression to predict being in the highest cytokine cluster based on social predictors. RESULTS: Our final sample included 537 children but varied based on each biomarker. Cumulative social adversity was significantly associated with having higher levels of all inflammatory markers and with cortisol, displaying a U-shaped distribution. There were no significant relationships between cumulative social adversity and cortisone, neuromodulation biomarkers or epigenetic aging. CONCLUSION: Our findings support prior work suggesting that social stress exposures contribute to increased inflammation in children. IMPACT: Our study is one of the largest studies examining associations between childhood social adversity and biomarkers of inflammation, neuroendocrine function, neuromodulation, and epigenetic aging. It is one of the largest studies to link childhood social adversity to biomarkers of inflammation, and the first of which we are aware to link cumulative social adversity to cytokine clusters. It is also one of the largest studies to examine associations between steroids and epigenetic aging among children, and one of the only studies of which we are aware to examine associations between social adversity and endocannabinoids among children. CLINICAL TRIAL REGISTRATION: NCT02746393.

Structured and unstructured social risk factor documentation in the electronic health record underestimates patients' self-reported risks.

OBJECTIVES: National attention has focused on increasing clinicians' responsiveness to the social determinants of health, for example, food security. A key step toward designing responsive interventions includes ensuring that information about patients' social circumstances is captured in the electronic health record (EHR). While prior work has assessed levels of EHR "social risk" documentation, the extent to which documentation represents the true prevalence of social risk is unknown. While no gold standard exists to definitively characterize social risks in clinical populations, here we used the best available proxy: social risks reported by patient survey. MATERIALS AND METHODS: We compared survey results to respondents' EHR social risk documentation (clinical free-text notes and International Statistical Classification of Diseases and Related Health Problems [ICD-10] codes). RESULTS: Surveys indicated much higher rates of social risk (8.2%-40.9%) than found in structured (0%-2.0%) or unstructured (0%-0.2%) documentation. DISCUSSION: Ideally, new care standards that include incentives to screen for social risk will increase the use of documentation tools and clinical teams' awareness of and interventions related to social adversity, while balancing potential screening and documentation burden on clinicians and patients. CONCLUSION: EHR documentation of social risk factors currently underestimates their prevalence.

Parent and staff perceptions of racism in a single-center neonatal intensive care unit.

IMPACT: In alignment with previous literature, NICU parents reported experiencing racism and NICU staff reported witnessing racism in the NICU. Our study also uniquely describes personal experiences with racism by staff in the NICU. NICU staff reported witnessing and experiencing racism more often than parents reported. Black staff reported witnessing and experiencing more racism than white staff. Differences in reporting is likely influenced by variations in lived experience, social identities, psychological safety, and levels of awareness. Future studies are necessary to prevent and accurately measure racism in the NICU.

Hospital Characteristics Associated With Social Needs Activities in the US.

This study assesses what hospital characteristics, including hospital participation in payment and delivery reform, are associated with activities related to health-related social needs.

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.

Social and Medical Care Integration Practices Among Children's Hospitals.

OBJECTIVES: In response to evidence linking social risk factors and adverse health outcomes, new incentives have emerged for hospitals to screen for adverse social determinants of health (SDOH). However, little information is available about the current state of social risk-related care practices among children's hospitals. To address outstanding knowledge gaps, we sought to describe social risk-related care practices among a national sample of children's hospitals. METHODS: We analyzed responses to the 2020 American Hospital Association Annual Survey. Among children's hospitals, we calculated the prevalence of screening for social needs, strategies to address social risks/needs, partnerships with community-based organizations to address social risks/needs at the individual and community level, and rates of impact assessments of how social risk-related interventions affect outcomes. We also used χ2 tests to compare results by hospital characteristics. We weighted results to adjust for nonresponse. RESULTS: The sample included 82 children's hospitals. A total of 79.6% screened for and 96.0% had strategies to address at least 1 social risk factor, although rates varied by SDOH domain. Children's hospitals more commonly partnered with community-based organizations to address patient-level social risks than to participate in community-level initiatives. A total of 39.2% of hospitals assessed SDOH intervention effectiveness. Differences in social risk-related care practices commonly varied by hospital ownership and Medicaid population but not by region. CONCLUSIONS: We found wide variability in social risk-related care practices among children's hospitals based on the risk domain and hospital characteristics. Findings can be used to monitor whether social risk-related care practices change in the setting of new incentives.

Structural Racism Operationalized via Adverse Social Events in a Single-Center Neonatal Intensive Care Unit.

OBJECTIVE: To evaluate structural racism in the neonatal intensive care unit (NICU) by determining if differences in adverse social events occur by racialized groups. STUDY DESIGN: Retrospective cohort study of 3290 infants hospitalized in a single center NICU between 2017 and 2019 in the Racial and Ethnic Justice in Outcomes in Neonatal Intensive Care (REJOICE) study. Demographics and adverse social events including infant urine toxicology screening, child protective services (CPS) referrals, behavioral contracts, and security emergency response calls were collected from electronic medical records. Logistic regression models were fit to test the association of race/ethnicity and adverse social events, adjusting for length of stay. Racial/ethnic groups were compared with a White referent group. RESULTS: There were 205 families (6.2%) that experienced an adverse social event. Black families were more likely to have experienced a CPS referral and a urine toxicology screen (OR, 3.6; 95% CI, 2.2-6.1 and OR, 2.2; 95% CI, 1.4-3.5). American Indian and Alaskan Native families were also more likely to experience CPS referrals and urine toxicology screens (OR, 15.8; 95% CI, 6.9-36.0 an OR, 7.6; 95% CI, 3.4-17.2). Black families were more likely to experience behavioral contracts and security emergency response calls. Latinx families had a similar risk of adverse events, and Asian families were less likely to experience adverse events. CONCLUSIONS: We found racial inequities in adverse social events in a single-center NICU. Investigation of generalizability is necessary to develop widespread strategies to address institutional and societal structural racism and to prevent adverse social events.

Unmet Social Needs and Patterns of Hair Cortisol Concentration in Mother-Child Dyads.

Background: Mothers and their children demonstrate dyadic synchrony of hypothalamic-pituitary-adrenal (HPA) axis function, likely influenced by shared genetic or environmental factors. Although evidence has shown that chronic stress exposure has physiologic consequences for individuals-including on the HPA axis-minimal research has explored how unmet social needs such as food and housing instability may be associated with chronic stress and HPA axis synchrony in mother-child dyads. Methods: We conducted a secondary analysis of data from 364 mother-child dyads with low-income recruited during a randomized trial conducted in an urban pediatric clinic. We used latent profile analysis (LPA) to identify subgroups based on naturally occurring patterns of within-dyad hair cortisol concentration (HCC). A logistic regression model predicted dyadic HCC profile membership as a function of summative count of survey-reported unmet social needs, controlling for demographic and health covariates. Results: LPA of HCC data from dyads revealed a 2-profile model as the best fit. Comparisons of log HCC for mothers and children in each profile group resulted in significantly "higher dyadic HCC" versus "lower dyadic HCC" profiles (median log HCC for mothers: 4.64 vs 1.58; children: 5.92 vs 2.79, respectively; P < .001). In the fully adjusted model, each one-unit increase in number of unmet social needs predicted significantly higher odds of membership in the higher dyadic HCC profile when compared to the lower dyadic HCC profile (odds ratio = 1.13; 95% confidence interval [1.04-1.23]; P = .01). Conclusion: Mother-child dyads experience synchronous patterns of physiologic stress, and an increasing number of unmet social needs is associated with a profile of higher dyadic HCC. Interventions aimed at decreasing family-level unmet social needs or maternal stress are, therefore, likely to affect pediatric stress and related health inequities; efforts to address pediatric stress similarly may affect maternal stress and related health inequities. Future research should explore the measures and methods needed to understand the impact of unmet social needs and stress on family dyads.

The association between prescription drug monitoring programs and controlled substance prescribing: a cross-sectional study using data from 2019 National Electronic Health Records Survey.

OBJECTIVE: The use of controlled medications such as opioids, stimulants, anabolic steroids, depressants, and hallucinogens has led to an increase in addiction, overdose, and death. Given the high attributes of abuse and dependency, prescription drug monitoring programs (PDMPs) were introduced in the United States as a state-level intervention. MATERIALS AND METHODS: Using cross-sectional data from the 2019 National Electronic Health Records Survey, we assessed the association between PDMP usage and reduced or eliminated controlled substance prescribing as well as the association between PDMP usage and changing a controlled substance prescription to a nonopioid pharmacologic therapy or nonpharmacologic therapy. We applied survey weights to produce physician-level estimates from the survey sample. RESULTS: Adjusting for physician age, sex, type of medical degree, specialty, and ease of PDMP, we found that physicians who reported "often" PDMP usage had 2.34 times the odds of reducing or eliminating controlled substance prescriptions compared to physicians who reported never using the PDMP (95% confidence interval [CI] 1.12-4.90). Adjusting for physician age, sex, type of doctor, and specialty, we found that physicians who reported "often" use of the PDMP had 3.65 times the odd of changing controlled substance prescriptions to a nonopioid pharmacologic therapy or nonpharmacologic therapy (95% CI: 1.61-8.26). DISCUSSION: These results support the continued use, investment, and expansion of PDMPs as an effective intervention for reducing controlled substance prescription and changing to nonopioid/pharmacologic therapy. CONCLUSION: Overall, frequent usage of PDMPs was significantly associated with reducing, eliminating, or changing controlled substance prescription patterns.

Socioeconomic Factors Are Associated With Severity of Hospitalization in Pediatric Lupus: An Analysis of the 2016 Kids' Inpatient Database.

OBJECTIVE: Health disparities in adult lupus, including higher disease severity and activity among those in poverty, have been identified. Similar associations in pediatric lupus have not been clearly established. This study was undertaken to investigate the relationship of income level and other socioeconomic factors with length of stay (LOS) in the hospital and severe lupus features using the 2016 Kids' Inpatient Database (KID). METHODS: Lupus hospitalizations were identified in children ages 2-20 years in the 2016 KID using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes (M32). Univariate and multivariate negative binomial regression analyses were used to analyze the association of income level, race and ethnicity, and insurance status with LOS in the hospital. Univariate and multivariate logistic regression analyses were used to analyze the association of the same predictors with the presence of severe lupus features, defined using ICD-10 codes associated with lupus sequelae (e.g., lupus nephritis). RESULTS: A total of 3,367 unweighted (4,650 weighted) lupus hospitalizations were identified. Income level was found to be a statistically significant predictor of increased LOS in the hospital for those in the lowest income quartile (adjusted incidence rate ratio 1.12 [95% confidence interval (95% CI) 1.02-1.23]). Black race, "other" race, and public insurance were also associated with severe lupus features (adjusted odds ratio [ORadj ] 1.51 [95% CI 1.11-2.06]; ORadj 1.61 [95% CI 1.01-2.55]; and ORadj 1.51 [95% CI 1.17-2.55], respectively). CONCLUSION: Using a nationally representative data set, income level was found to be a statistically significant predictor of LOS in the hospital among those with the lowest reported income, highlighting a potential target population for intervention. Additionally, Black race and public insurance were associated with severe lupus features.

Structural racism is associated with adverse postnatal outcomes among Black preterm infants.

BACKGROUND: Structural racism contributes to racial disparities in adverse perinatal outcomes. We sought to determine if structural racism is associated with adverse outcomes among Black preterm infants postnatally. METHODS: Observational cohort study of 13,321 Black birthing people who delivered preterm (gestational age 22-36 weeks) in California in 2011-2017 using a statewide birth cohort database and the American Community Survey. Racial and income segregation was quantified by the Index of Concentration at the Extremes (ICE) scores. Multivariable generalized estimating equations regression models were fit to test the association between ICE scores and adverse postnatal outcomes: frequent acute care visits, readmissions, and pre- and post-discharge death, adjusting for infant and birthing person characteristics and social factors. RESULTS: Black birthing people who delivered preterm in the least privileged ICE tertiles were more likely to have infants who experienced frequent acute care visits (crude risk ratio [cRR] 1.3 95% CI 1.2-1.4), readmissions (cRR 1.1 95% CI 1.0-1.2), and post-discharge death (cRR 1.9 95% CI 1.2-3.1) in their first year compared to those in the privileged tertile. Results did not differ significantly after adjusting for infant or birthing person characteristics. CONCLUSION: Structural racism contributes to adverse outcomes for Black preterm infants after hospital discharge. IMPACT STATEMENT: Structural racism, measured by racial and income segregation, was associated with adverse postnatal outcomes among Black preterm infants including frequent acute care visits, rehospitalizations, and death after hospital discharge. This study extends our understanding of the impact of structural racism on the health of Black preterm infants beyond the perinatal period and provides reinforcement to the concept of structural racism contributing to racial disparities in poor postnatal outcomes for preterm infants. Identifying structural racism as a primary cause of racial disparities in the postnatal period is necessary to prioritize and implement appropriate structural interventions to improve outcomes.

Characterizing the relative frequency of clinician engagement with structured social determinants of health data.

OBJECTIVE: Electronic health records (EHRs) are increasingly used to capture social determinants of health (SDH) data, though there are few published studies of clinicians' engagement with captured data and whether engagement influences health and healthcare utilization. We compared the relative frequency of clinician engagement with discrete SDH data to the frequency of engagement with other common types of medical history information using data from inpatient hospitalizations. MATERIALS AND METHODS: We created measures of data engagement capturing instances of data documentation (data added/updated) or review (review of data that were previously documented) during a hospitalization. We applied these measures to four domains of EHR data, (medical, family, behavioral, and SDH) and explored associations between data engagement and hospital readmission risk. RESULTS: SDH data engagement was associated with lower readmission risk. Yet, there were lower levels of SDH data engagement (8.37% of hospitalizations) than medical (12.48%), behavioral (17.77%), and family (14.42%) history data engagement. In hospitalizations where data were available from prior hospitalizations/outpatient encounters, a larger proportion of hospitalizations had SDH data engagement than other domains (72.60%). DISCUSSION: The goal of SDH data collection is to drive interventions to reduce social risk. Data on when and how clinical teams engage with SDH data should be used to inform informatics initiatives to address health and healthcare disparities. CONCLUSION: Overall levels of SDH data engagement were lower than those of common medical, behavioral, and family history data, suggesting opportunities to enhance clinician SDH data engagement to support social services referrals and quality measurement efforts.

Cumulative Social Disadvantage Associated with Childhood Arthritis: A Cross-Sectional Analysis of the National Survey of Children's Health.

OBJECTIVE: Health disparities in juvenile idiopathic arthritis (JIA) remain poorly understood. Social disadvantage may have a cumulative impact on health, with recent analyses using combined scoring systems to measure their impact on outcomes. Our aim was to investigate cumulative social disadvantage on childhood arthritis by using a cumulative score to analyze its association with arthritis among a nationally representative sample of children. METHODS: A cross-sectional analysis of the National Survey of Children's Health (2016-2019) was performed. A cumulative social disadvantage score was generated (1 point each, with a maximum score of 4): low guardian education (high school or less), low household income level (0-199% of federal poverty level), underinsured status (public or uninsured), and high adverse childhood experience (ACE) score (≥4). Univariate and multivariable (adjusting for age, sex, and race and ethnicity) logistic regression models were used to measure the association between cumulative social risk and the odds of an arthritis diagnosis and moderate-to-severe parent-reported arthritis severity. RESULTS: Of 131,774 surveys completed, a total of 365 children reported current arthritis. Cumulative social disadvantage was associated with an arthritis diagnosis, with the highest odds among those with a score of 4 (adjusted odds ratio [ORadj ] 12.4 [95% confidence interval (95% CI) 2.9-53.3]). Cumulative social disadvantage also was associated with increased odds of moderate-to-severe arthritis severity (ORadj 12.4 [95% CI 1.8-82.6]). CONCLUSION: In this nationally representative sample, accumulated social disadvantage, measured via a cumulative social disadvantage score based on income level, guardian education, insurance status, and ACE exposure, was associated with an arthritis diagnosis and moderate-to-severe arthritis severity.

Social Risk Factor Documentation in Emergency Departments.

STUDY OBJECTIVE: Social Z codes are International Classification of Diseases, Tenth Revision, Clinical Modification codes that provide one way of documenting social risk factors in electronic health records. Despite the utility and availability of these codes, no study has examined social Z code documentation prevalence in emergency department (ED) settings. METHODS: In this descriptive, cross-sectional study of all ED visits included in the 2018 Nationwide Emergency Department Sample, we estimated the prevalence of social Z code documentation and used logistic regression to examine the association between documentation and patient and hospital characteristics. RESULTS: Of more than 35.8 million adult and pediatric ED visits, there was a 1.21% weighted prevalence (n=452,499) of at least 1 documented social Z code. Social Z codes were significantly more likely to be documented in ED visits among patients aged 35 to 64 compared to patients aged 18 to 34 (18.6/1000 [16.9 to 20.4] versus 12.7/1000 [11.5 to 14.0], odds ratio (OR) 1.47 [1.42 to 1.53]), male patients (16.6/1000 [15.1 to 18.2] versus female 8.5/1000 [7.8 to 9.2], OR 1.97 [1.89 to 2.06]), patients with Medicaid compared to patients with private insurance (15.9/1000 [14.4 to 17.6] versus (6.6/1000 [6.0 to 7.2], OR 2.45 [1.30 to 1.63]), and patients who had a Charlson Comorbidity Index≥1 compared to those with a Charlson Comorbidity Index of 0 (ranges 15.0 to 16.6/1000 versus 10.6/1000 [9.6 to 11.7], ORs ranging 1.43 to 1.58). ED visits with a primary diagnosis of mental, behavioral, and neurodevelopmental illness had the strongest positive association with social Z code documentation (85.6/1000 [78.4 to 93.4], OR 10.75 [9.88 to 11.70]) compared to ED visits without this primary diagnosis. CONCLUSION: We found a very low prevalence of social Z code documentation in ED visits nationwide. More systematic social Z code documentation could support targeted social interventions, social risk payment adjustments, and future policy reforms.

Assessing Alignment of Patient and Clinician Perspectives on Community Health Resources for Chronic Disease Management.

Addressing social determinants of health (SDoH) is associated with improved clinical outcomes for patients with chronic diseases in safety-net settings. This qualitative study supplemented by descriptive quantitative analysis investigates the degree of alignment between patient and clinicians' perceptions of SDoH resources and referrals in clinics within the public healthcare delivery system in San Francisco. We conducted a qualitative analysis of in-depth interviews, patient-led neighborhood tours, and in-person clinic visit observations with 10 patients and 7 primary care clinicians. Using a convergent parallel mixed methodology, we also completed a descriptive quantitative analysis comparing the categories of neighborhood health resources mentioned by patients or community leaders to the resources integrated into the electronic health record. We found that patients held a wealth of knowledge about neighborhood resources relevant to SDoH that were highly localized and specific to their communities. In addition, multiple stakeholders were involved in conducting SDoH screenings and referrals, including clinicians, system navigators such as case workers, and community-based organizations. Yet, the information flow between these stakeholders and patients lacked systematization, and the prioritization of social needs by patients and clinicians was misaligned, as represented by qualitative themes as well as quantitative differences in resource category distribution analysis (p < 0.001). Our results shed light upon opportunities for strengthening social care delivery in safety-net healthcare settings by improving patient engagement, clinic workflow, EHR engagement, and resource dissemination.

Physician awareness of social determinants of health documentation capability in the electronic health record.

Healthcare organizations are increasing social determinants of health (SDH) screening and documentation in the electronic health record (EHR). Physicians may use SDH data for medical decision-making and to provide referrals to social care resources. Physicians must be aware of these data to use them, however, and little is known about physicians' awareness of EHR-based SDH documentation or documentation capabilities. We therefore leveraged national physician survey data to measure level of awareness and variation by physician, practice, and EHR characteristics to inform practice- and policy-based efforts to drive medical-social care integration. We identify higher levels of social needs documentation awareness among physicians practicing in community health centers, those participating in payment models with social care initiatives, and those aware of other advanced EHR functionalities. Findings indicate that there are opportunities to improve physician education and training around new EHR-based SDH functionalities.

Applying a socioecological framework to chronic disease management: implications for social informatics interventions in safety-net healthcare settings.

Objective: Vulnerable populations face numerous barriers in managing chronic disease(s). As healthcare systems work toward integrating social risk factors into electronic health records and healthcare delivery, we need better understanding of the interrelated nature of social needs within patients' everyday lives to inform effective informatics interventions to advance health equity. Materials and Methods: We conducted in-depth interviews, participant-led neighborhood tours, and clinic visit observations involving 10 patients with diabetes in underserved San Francisco neighborhoods and 10 community leaders serving those neighborhoods. We coded health barriers and facilitators using a socioecological framework. We also linked these qualitative data with early persona development, focusing on patients' experiences in these communities and within the healthcare system, as a starting place for our future informatics design. Results: We identified social risk and protective factors across almost every socioecological domain and level-from physical disability to household context to neighborhood environment. We then detailed the complex interplay across domains and levels within two critical aspects of patients' lives: housing and food. Finally, from these data we generated 3 personas that capture the intersectional nature of these determinants. Conclusion: Drawing from different disciplines, our study provides a socioecological approach to understanding health promotion for patients with chronic disease in a safety-net healthcare system, using multiple methodologies. Future digital health research should center the lived experiences of marginalized patients to effectively design and implement informatics solutions for this audience.