Defining Quality Criteria for Success in Organ Donation Programs: A Scoping Review
Bibliographic record
Abstract
Background: Well-established performance measures for organ donation programs do not fully address the complexity and multifactorial nature of organ donation programs such as the influence of relationships and organizational attributes. Objective: To synthesize the current evidence on key organizational attributes and processes of international organ donation programs associated with successful outcomes and to generate a framework to categorize those attributes. Design: Scoping Review using a mixed methods approach for data extraction. Setting: Databases included PubMed, CINAHL, Embase, LILACS, ABI Business ProQuest, Business Source Premier, and gray literature (organ donation association websites, Google Scholar—first 8 pages), and searches for gray literature were performed, and relevant websites were perused. Sample: Organ donation programs or processes. Methods: We systematically searched the literature to identify any research design, including text and opinion papers and unpublished material (research data, reports, institutional protocols, government documents, etc). Searches were completed on January 2018, updated it in May 2019, and lastly in March 2020. Title, abstracts, and full texts were screened independently by 2 reviewers with disagreements resolved by a third. Data extraction followed a mixed method approach in which we extracted specific details about study characteristics such as type of research, year of publication, origin/country of study, type of journal published, and key findings. Studies included considered definitions and descriptions of success in organ donation programs in any country by considering studies that described (1) attributes associated with success or effectiveness, (2) organ donation processes, (3) quality improvement initiatives, (4) definitions of organ donation program effectiveness, (5) evidence-based practices in organ donation, and (6) improvements or success in such programs. We tabulated the type and frequency of the presence or absence of reported improvement quality indicators and used a qualitative thematic analysis approach to synthesize results. Results: A total of 84 articles were included. Quantitative analysis identified that most of the included articles originated from the United States (n = 32, 38%), used quantitative approaches (n = 46, 55%), and were published in transplant journals (n = 34, 40.5%). Qualitative analysis revealed 16 categories that were described as positively influencing success/effectiveness of organ donation programs. Our thematic analysis identified 16 attributes across the 84 articles, which were grouped into 3 categories influencing organ donation programs’ success: context (n = 39, 46%), process (n = 48, 57%), and structural (n = 59, 70%). Limitations: Consistent with scoping review methodology, the methodological quality of included studies was not assessed. Conclusions: This scoping review identified a number of factors that led to successful outcomes. However, those factors were rarely studied in combination representing a gap in the literature. Therefore, we suggest the development and reporting of primary research investigating and measuring those attributes associated with the performance of organ donation programs holistically. Trial Registration: Not applicable.
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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 | 0.216 | 0.515 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.062 | 0.054 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.006 | 0.004 |
| 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".