Economic impact of pharmacists' interventions in asthma management: a systematic review
Bibliographic record
Abstract
Objective: The purpose of this study was to review in a systematically way the studies that investigated the economic impact of clinical pharmacist services delivered to asthma individuals. Methods: A systematic survey was conducted in the PubMed, Scopus, Lilacs and Cochrane databases aiming to grade the economic evaluations published until January 2020. English, Spanish, Portuguese or French language articles were included if they evaluated a pharmaceutical intervention aiming asthma patients and also reported economic data about these interventions. There was no limitation regarding the study design or type of economic analysis. Two independent authors assessed and selected the studies, extracted the data, and measured risk of bias. Risk of bias was measured through the Cochrane’s risk of bias tool for randomized controlled trials and the Newcastle-Ottawa quality assessment scale for cohort studies. Results: 2,832 references were identified through the search strategy, but only seven studies met the inclusion criteria to be selected into the final analysis. Out of these seven articles, four consisted of cohort studies, and three consisted of randomized controlled trials. Instructional programs and patient counseling were the most usual components of pharmaceutical care interventions. Six articles showed statistically significant positive economic outcomes of pharmaceutical care interventions in asthma management. Moreover, pharmaceutical interventions were found to decrease hospitalizations, emergency visits, symptoms, and increase adherence to pharmacotherapy. Conclusions: Studies included showed acceptable and satisfactory cost-saving ratios, demonstrating the potential benefit of inserting the pharmacist into the multidisciplinary team. Nevertheless, long-term studies and randomized clinical trials are needed to establish solid evidence in order to expand the results found in this review to broader and different contexts.
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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 | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".