Der Einfluss von HTA-Berichten auf die gesundheitspolitische Entscheidungsfindung
Bibliographic record
Abstract
Research Question The objective of health technology assessment (HTA) is to support decision-making in the health sector by assessing health technologies systematically under medical, economic, social, and ethical aspects. The present study aims at identifying ways of enabling the impact of HTA on decision-making processes in the German health sector. The authors formulate three research questions: (1) Can methods be identified that allow a valid assessment of the impact of HTA reports on the decision-making processes? (2) Has been shown an impact of HTA reports on decision-making processes in the health sector? (3) Which are the factors responsible for a high or a low impact of HTA? Methods The authors include studies that present a methodology to assess the impact of HTA, that investigate the impact of HTA on decision-making processes, or study the factors that might enhance or hinder the impact of HTA. Medical and social science electronic databases, lists of publications and projects of the European, North American, Canadian, and Australian HTA agencies, as well as the bibliography of the identified articles and documents are looked through. The writers do a handsearch of the International Journal of Technology Assessment in Health Care and contact 64 HTA agencies by a letter, requesting information on investigations that might not have been published. Results Abstracts from about 5,000 articles are read. 57 articles are ordered as full-text, 43 are finally included and 14 excluded. (1) In eight studies interviews with decision-makers are used to elicit the information, in three studies document analysis is employed, and in six surveys the results rely only on the observations and interpretations of the authors. One study analyses service data and in nine examinations more than one of the methods listed above are employed. Only in two studies pre-defined indicators were used and only in one clinical trial a prospective design is chosen. (2) In nine studies the impact of a population of HTA reports is analysed: Among these, seven find that more than 70% of the reports have an impact on the decision-making process, in one study 50% of the reports have none or only a minimal impact. In one study on the impact of 50 short HTA reports, it is found that they contribute valuable information but do not influence decisions. However, because of methodological flaws the evidence base for these results is rather limited. Most of the conclusions presented in the publications are based on the appraisal of the authors who are often related to the program of which the impact has been "evaluated". (3) The writers divide the factors that are identified as modifying the degree of impact of the HTA reports in two groups: context factors and factors that are connected to the developing process, the subject, the format, the content, or the quality of the reports. However, the relevance of these factors has to be assessed with caution: none of the publications has the relevance for a primary research question and in none of the studies is the relevance of the factors investigated in a prospective and systematic manner. Conclusion There is little experience with study designs or methods that allow a valid assessment of the impact of HTA reports on the decision-making process in the health sector. However, some approaches, such as the use of pre-defined indicators, were identified that should be pursued and elaborated in further studies. Due to the lack of a developed methodology only limited conclusions related to the impact of HTA reports can be drawn. Among the studies that show a relevant impact, most are methodological. However, results from qualitative studies caution against assuming a causal relationship where a mere coincidence between the recommendations of an HTA report and health policy is identified. In order to produce evidence-based conclusions regarding the impact of HTA reports, validated indicators should be used. Study design should also aim at controlling for other influencing factors. None of the studies explicitly aim at examining the role of the factors that might be responsible for a low or high impact of the HTA reports. The non-systematic retrospective analyses do not allow reliable conclusions regarding the relevance of these factors. Therefore the factors identified here should only serve for hypothesis formation. On the basis of these studies it is not possible to give evidence-based recommendations on the way how to increase the impact of HTA on decision-making in Germany. Instead a concept for evaluation should be developed that combines quantitative and qualitative methods and considers the following questions: (1) What kind of impact should be measured? (2) Which are the target groups and at which level of the health system are they located? (3) Which are the outcome parameters and how can they be measured? (4) Which are the potential impact enhancing or limiting factors?
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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 | 0.204 | 0.620 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.019 | 0.015 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.023 | 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".