P2.4: Quality improvement tools to manage deceased organ donation processes: a scoping review
Notice bibliographique
Résumé
Background: Deceased organ donation, both after circulatory determination of death (DCD) and after neurological determination of death (NDD), is a highly complex and multi-phased process. To ensure a proper flow of the donation process, appropriate quality improvement tools should be used. These tools allow better control over health activities with more reliable and predictable outcomes. However, there is still a paucity of comprehensive evidence about the use of these tools to manage deceased donation processes. Therefore, this scoping review aims to summarize the international literature on quality improvement tools developed to manage deceased organ donation processes (DCD/NDD). Methods: Scoping review using the JBI methodology. Published literature was searched on MEDLINE, Embase, PsycINFO, CINAHL, Web of Science and Academic Search Complete from inception to July 2021 (updated in June, 2022). Unpublished and gray literature included reports from organ donation organizations. Reports were considered if they described the use of quality improvement tools to manage deceased donation processes in any healthcare setting. Data were screened, extracted and analyzed by two independent reviewers. Results: The first search yielded over 10000 citations and 40 were included in this review. Most reports were written in English (n=38), from Canada (n=21), and published between 2016 and 2022 (n=22). The tools identified included checklists, algorithms, flow charts, charts, pathways, decision tree maps and mobile apps. These tools were applied in the following phases of the organ donation process: (1) potential donor identification, (2) donor referral, (3) donor assessment and risk, (4) donor management, (5) withdrawal of life-sustaining measures,(6) death determination, (7) organ retrieval and (8) overall organ donation process.Conclusion: The existing evidence lacks details in the report of methods used for the development, testing and impact of these tools, and we could not locate tools specific to some phases of the organ donation process. Lastly, by mapping existing tools, we aim to facilitate both clinician choices among available tools, as well as research work building on existing knowledge. The authors would like to acknowledge the Canadian Donation and Transplantation Research Programme (CDTRP), Canadian Blood Services (CBS) and Children’s Hospital of Eastern Ontario (CHEO) for all their support and guidance in the development of this research. We also thank Robin Featherstone, Cochrane Information Specialist, for developing and employing the main electronic search strategies, and Amanda Ross-White, from JBI Centre of Excellence, for peer-reviewing the search strategy.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,042 | 0,146 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,006 | 0,010 |
| Bibliométrie | 0,035 | 0,035 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,009 | 0,009 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,007 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».