Modelling the Clinical and Economic Impacts of Foundation-Funded versus Staff-Driven Quality Improvement Mental Health Strategies
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND Employing a valid and reliable clinical measurement system established in 2002 within our regional Child and Adolescent, Addictions, Mental Health, and Psychiatry Program, we have been able to measure the effect of the general service system, a novel pre-admission initial family group session to orient families to treatment, and an acute at-home care service designed to divert admissions from emergency to in-home support rather than inpatient admission. Additionally, we modelled the clinical effect and economic impact of two community programs: one school-based mental health literacy program and one primary care physician training and education program focusing on the management of children's mental health problems. In this paper, we present an established clinical measurement system combined with a standardized cost evaluation strategy to assess the respective cost/benefit impacts of four service innovations. METHODS The clinical measurement system has been described in detail, as has its role in measuring the impact of community-level training on the quality of referrals. Our financial department developed standardized per diem cost references for levels of care within our system. The cost references permitted comparison of groups that were exposed and unexposed to the system innovations before and after the initiation of service and community innovations. The school-based mental health literacy program was a regional implementation of a national program (https://mentalhealthliteracy.org/). The primary care physician education was an internationally developed program from the United States (https://thereachinstitute.org). The other two projects were accomplished on a somewhat smaller local scale and at lower overall cost. The pre-admission initial family group session was a bottom-up, staff-designed and developed quality improvement project. The acute at-home project, while funded by the children’s hospital foundation as were the two national and international projects, was a top-down director-designed project with one manager and a coordinator. RESULTS The four innovations were evaluated employing the same model. In each case, the clinical space created by each innovation was measured in terms of the cost saved by comparing the same outcomes (re-admission rates and lengths of stay) over comparable time intervals between and within pre/post exposed and unexposed groups, whilst controlling for clinical effects of exposure and time. The clinical measurement system helped determine group effects to ensure that the target groups were comparable within each initiative’s exposed and unexposed groups and were appropriately distinct between initiatives (e.g., appropriate clinical groups were served by each initiative). While the four projects were different and served somewhat different patient groups, the pre-admission initial family group session was the most cost-effective. The physician training program was both effective and cost-neutral. The school-based mental health literacy program was the least evaluable due to the direction of implementation and tended to increase referrals rather than create clinical space for more affected youth, as might be expected. The acute at-home project successfully diverted less suicidal patients away from inpatient readmission over the evaluation period. DISCUSSION The main implications for mental health policy derive from linking standardized cost and clinical measurement models, permitting economic evaluation of system and community-level innovations. Pre- and post-clinical and cost measurements within and between exposed and unexposed groups for each innovation or project permitted estimation of benefits and costs. CONCLUSIONS The projects varied in focus together with the evaluability of each project, yet this provided important information for health system innovation and renewal within the context of fiscal constraint. The ranking of the projects in terms of their overall benefits and costs may guide decision-making where maximum return on investment makes the most sense.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it