Methodological Quality of Economic Evaluations in Integrated Care: Evidence from a Systematic Review
Bibliographic record
Abstract
INTRODUCTION: The aim of this review is to systematically assess the methodological quality of economic evaluations in integrated care and to identify challenges with conducting such studies. THEORY AND METHODS: Searches of grey-literature and scientific papers were performed, from January 2000 to December 2018. A checklist was developed to assess the quality of economic evaluations. Authors' statements of challenges encountered during their evaluations were qualitatively coded. RESULTS: Forty-four articles were eligible for inclusion. The review found that study design, measurement of cost and outcomes, statistical analysis and presentation of data were the areas with most quality variation. Authors identified challenges mostly related to time horizon of the evaluation, inadequate or lack of comparator group, contamination bias, and a post-hoc evaluation culture. DISCUSSION: Our review found significant differences in quality, with some studies showing poor methodological rigor; challenging conclusions on the cost-effectiveness of integrated care. CONCLUSION: It is essential for evaluators to use best-practice standards when planning and conducting economic evaluations, in order to build a reliable evidence base for decision-making in integrated care.
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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 | 0.030 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads 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".