Ordering Cost-Effectiveness Management Studies in Healthcare: A PRISMA-Compliant Systematic Literature Review and Bibliometric Analysis
Bibliographic record
Abstract
The issue of effectiveness in healthcare plays a role in international debates. The search for adequate tools allowing management to evaluate the correct allocation of resources becomes increasingly necessary. Cost-effectiveness analysis responds to this need, but the variety of tools and solutions proposed makes their application and replicability complex. The aim of this study was to create a starting approach model useful to researchers and professionals to cost-effectiveness problem solving. The study integrates two approaches by unifying the PRISMA-Compliant Systematic Literature Review and Bibliometric Analysis. The results obtained from the analysis are manifold. Scientific production related to cost-effectiveness in healthcare has increased in the last ten years and is mainly concentrated in three sources. Researchers insert multiple keywords into the articles, but the main ones are cost effectiveness analysis, human, health care cost. The topics covered can be divided into two clusters, which can be further divided into several subgroups. PRISMA analysis reinforces and confirms what has been identified through bibliometric analysis: in cost-effectiveness analysis different methodological bases are applicable to specific individual topics; in particular, the most used approaches to evaluate cost-effectiveness are DES (discrete event simulation) and Mathematical-statistical analysis methodologies, whose applications need the highlighted data. The study also underlines the literature absence of some specific topics such as spillover from primary and secondary health prevention activities, organization of services, rehabilitation activities, centralization of services related to contracts and PPPs, evaluation of infra-hospital care pathways.
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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 | 0.346 | 0.560 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.021 |
| Bibliometrics | 0.117 | 0.099 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.009 | 0.012 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".