Health Care Utilization and Expenditures in Persons Receiving Social Assistance in 2012 Evidence From Switzerland
Bibliographic record
Abstract
INTRODUCTION: Lower socioeconomic position and measures of social and material deprivation are associated with morbidity and mortality. These inequalities in health among groups of various statuses remain one of the main challenges for public health. The aim of the study was to investigate differences in health care use and costs between recipients of social assistance and non-recipients aged 65 years and younger within the Swiss healthcare system. METHODS: We analyzed claims data of 13 492 individuals living in Bern, Switzerland of which 391 received social assistance. For the year 2012, we compared the number of physician visits, hospitalizations, prescribed drugs, and total health care costs as covered by mandatory health insurance. Linear and logistic adjusted regression analyses were made to estimate the effect of receipt of social assistance on health service use and costs. RESULTS: Multivariate linear regression analysis revealed that health care costs increased on average by 1 666 CHF if individuals received social assistance. Recipients of social assistance had on average 1.2 more ambulatory consultations than non-recipients and got 1.65 more different medications prescribed as compared to non-recipients. The chance for recipients of social assistance to be hospitalized was almost twice that of non-recipients (Odds Ratio 1.96, 95% confidence interval 1.49-2.59). CONCLUSIONS: Recipients of social assistance demonstrate an exceedingly high use of health services. The need for interventions to alleviate the identified inequalities in health and health care needs is obvious.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".