Caseload management: an approach to making community needs visible
Bibliographic record
Abstract
AIM: To explore the process employed in the development of a population health framework and documentation for managing community nursing caseloads. BACKGROUND: No formal structure exists to validate and link local health information collected by Irish public health nurses to a wider epidemiological framework. Neglect of this bottom up information forfeits opportunities to resource and manage public health nursing services. DESIGN: Action research methods guided the development of the framework in one geographic area in Dublin and 34 participants engaged in Stringer's (1996) Look, Think and Act cycle. RESULTS: The framework identified four patient registers: family health, chronic sick/disability, older adults and acute care, which identify public health outcomes for discussion within the caseload analysis process and can predict risk factors in local populations. CONCLUSIONS: The use of the developed documentation identified a framework that describes caseloads in primary care and provides nurse managers with an evidence base to allocate resources, match skill mix to need, and estimate future workforce requirements.
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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 | 0.077 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.006 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.010 | 0.028 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".