SOCIAL DRIVERS OF HEALTH IN A LARGE ACADEMIC LUPUS CLINIC
Bibliographic record
Abstract
PV097a / #117 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose Adverse social drivers of health (SDoH) in systemic lupus erythematosus (SLE) are associated with worse health outcomes and quality of life. The aim of this initiative was to provide support to SLE patients with SDoH needs. To respect patient autonomy, financial support was given as $100 cash to spend as they deemed best. Herein, we report the clinical characteristics of those who received financial support as well as the patient and staff perspective of the program. Methods Adult Duke Lupus Clinic (DLC) patients are screened annually for SDoH insecurities. From January 2024 to October 2024, SLE patients were with food and/or transportation insecurity by routine SDoH screening, lupus nephritis patients with federally funded (Medicare and/or Medicaid) or no insurance, and patients with a SDoH need as determined by the treating clinician’s discretion qualified for financial support. These patients were offered 1) $100 cash at the end of visit 2) a referral to NCCare360, a statewide community social support program, and 3) a referral to DukeWell, an internal healthcare navigation program. After the visit, patients completed an anonymous survey on barriers to healthcare and experience with the program. Feedback was obtained from the clinic team. The clinical and demographic data of participants in the Duke Lupus Registry (DLR) who did and did not receive cash assistance were analyzed. Results Cash was distributed to 101 DLC patients; 27 patients received cash at more than 1 visit. Of the 276 DLR patients seen during this time, 74 patients (26%) received cash assistance and underwent analysis. There was no difference in age, disease duration, gender, and Hispanic ethnicity between participants who had identified SDoH barriers and those who did not (Table 1). However, patients with identified SDoH barriers were more likely to have lower educational attainment, federally funded insurance or no health insurance, and a low annual income. Nearly half of patients with an identified SDoH barrier reported food insecurity and over a quarter reported transportation insecurity. Nearly three-quarters identified difficulty paying for a variety of basic needs such as food, housing, medical care, and heating. Participants with an identified SDoH barrier were more likely to have a history of brain fog, fatigue, waking unrefreshed, and anxiety in the previous 18 months. Over three-quarters of patients completed the anonymous survey. Over half of patients had never worked with a case manager or social worker. The most frequently reported barriers to managing and accessing healthcare included the cost of food (55%), cost of utilities (45%), and cost of medications (43%). Feedback from patients was overwhelmingly positive (Table 2), with patients frequently sharing emotions such as “grateful” or “blessed.” Quotes from the clinical team highlight the profound, positive impact of the program, with team members noting how the cash assistance has addressed tangible needs of patients with SLE. Table 1. Demographics and Disease Manifestations Table 2. Patient and clinical team quotes about the cash assistance program. Conclusions A financial support program was implemented to address SDoH needs that are identified upon routine clinic screening. A range of SDoH needs and financial difficulty affording food, utilities, and medications are not uncommon in SLE. Those with SDoH needs experienced a greater burden of fatigue, pain, and mental health suggesting a connection between social, environmental, and physical health. Patients and the clinical team expressed gratitude and appreciation for program. Sustainable programs that screen and address SDoH could impact disparities in lupus outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".