Establishing a System for Medical Certification of Cause of Death for Noninstitutional Deaths in a Selected Area of Kolar District, Karnataka, India: Protocol for a Population-Based Feasibility and Validation Study
Notice bibliographique
Résumé
BACKGROUND: Medical Certification of Cause of Death (MCCD) coverage in India is only 22.5%, largely due to a significant proportion of deaths occurring outside hospitals (noninstitutional deaths). The cause of death (CoD) in such cases is unlikely to be certified by any doctor. This study attempts to address this gap by developing an MCCD system for noninstitutional deaths in India. OBJECTIVE: This study will assess the feasibility of a physician-derived cause of death (PhyCoD) approach for deducing CoD in noninstitutional deaths in a selected area of Kolar Taluk, Karnataka, and validate this approach. METHODS: This population-based feasibility and validation study will be conducted in 4 selected hospitals and 2 Primary Health Centre (PHC) areas in Kolar taluk, Kolar district, Karnataka, India. We developed 4 PhyCoD questionnaires: maternal, neonatal, child, and adult. Institutional deaths that occurred over the previous 10 months in these selected hospitals with detailed case records available were selected as "gold standard" cases. Trained investigators abstracted the history from these case records into the questionnaires and deduced the CoD sequence of events. The investigators then elicited the history from the deceased's relatives using the PhyCoD questionnaire and deduced the CoD sequence of events. This will be compared with the gold standard CoD sequence of events deduced from medical records. The extent of agreement will be measured. The tool will be revised based on the pilot phase experiences. For all brought dead cases to the 4 hospitals and home deaths in the 2 PHC areas over a 3-month period, doctors in these hospitals and PHC medical officers, respectively, will elicit the history from the deceased's kin using the PhyCoD questionnaires and arrive at a CoD sequence of events. This CoD sequence of events will be validated against the gold standard autopsy whenever possible (in brought dead cases). The PhyCoD approach will also be tested for inter-rater reliability by independent investigators on a random sample of noninstitutional deaths. RESULTS: Institutional ethics committee clearance (January 2024), recruitment and training of project staff (January 2024-January 2025), preparation of questionnaires and application (August 2024-February 2025), pilot phase data collection (48 cases; August 2024-December 2024), and training of the doctors in the participating hospitals and PHC medical officers (December 2024) are complete. A total of 48 cases (32 adult, 7 child, 3 maternal, and 6 neonatal) were included in the pilot phase. Data review and analysis of the pilot phase data are underway. CONCLUSIONS: The study is expected to provide information about the validity and feasibility of the PhyCoD approach. Depending on the study's outcomes, the tool may be adopted by more states, leading to increased coverage of noninstitutional deaths under MCCD, improved accuracy, and reduced delay of CoD reporting for noninstitutional deaths. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72330.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».