Hospital Costing Methods: Four Decades of Literature Review
Bibliographic record
Abstract
This study aims to identify and classify the costing methods used in hospitals in recent decades and to analyze the research carried out in this area, to identify and characterize the main lines of research and the research paradigms used. To this end, a systematic literature review was carried out, mapping 1067 articles collected from the ISI Web of Science and Scopus databases. The articles were selected by two independent researchers. To ensure the quality of the SLR, AMSTAR 2 was used as well as matrices for quantitative studies, and for qualitative articles. Additionally, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review process was followed to systematize the article selection process. Of the 1067 articles screened, 172 articles met the inclusion criteria. The results point to a growing interest among researchers and a predominance of the positive paradigm, albeit with an increase in interpretative research. There is a growing production of descriptive analyses of hospital processes and the costing of pathologies, with a predominance of the ABC method and analyses of costs and reimbursements for diagnosis-related groups. As a contribution, a conceptual model is proposed that aims to help the performance of hospital institutions, as well as a proposal for a future agenda based on this model.
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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 | 0.029 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.036 | 0.037 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".