Projection of Health Sector Workforce Requirement: Vision 2025
Bibliographic record
Abstract
BACKGROUND: This study was conducted with a long-term vision (2014-2025) targeted workforce requirement projection by occupational groups in Iran's health sector. METHODS: The "modified & combined model" used including Hall Model and Australian health workforce estimation model. It was a need-based approach with three components of estimation; requirements, supply with current growth and net required workforce. Requirement estimated by three assumptions: active workforce calculation; the growth of health service delivery resources and facilities; and daily individual working hours, created eight different scenarios. Economic feasibility of each scenario determined. To forecast the supply, used accurate numbers of the existing pool of practicing workforce in addition to inflows, minus losses from the profession. To calculate total recruits required, base year stock deducted from projected requirement and by adding Net flow, recruits required calculated. RESULTS: The health sector will need 781,887 workforces to realize service's needs. Workforce supply with the existing trend in the target year was 799,347. Therefore, workforce balance would be 17,460 surpluses. Moreover, to estimate required workforce and substitution number for the exited ones during the study periods till the target year, 547,136 individuals should be recruited mostly nurses and physicians. CONCLUSION: Limiting the workforce required to economic feasibility challenge workforce accessibility in the future as it is sensed in present tense as well. Therefore, in addition augmenting GDP and health funds, it is necessary alternative policies such as increasing share of health sector from GDP, prioritization of workforce needs or moving towards other proper policies.
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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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".