Development of a cervical cancer/screening database in Newfoundland and Labrador, Canada: A multi-linkage approach
Notice bibliographique
Résumé
B2 Rationale: Cervical cancer is an almost entirely preventable cancer, yet statistics have consistently shown higher incidence and mortality rates due to cervical cancer in the province of Newfoundland and Labrador (NL) compared to Canada overall. NL has a large rural population and previous research indicates that rural women have suboptimal cervical screening rates, more advanced disease at diagnosis, and higher cervical cancer mortality rates. An initiative was untaken by the Provincial Cervical Screening Initiatives Program and the Newfoundland & Labrador Centre for Health Information (The Centre) to develop a comprehensive longitudinal administrative database for the study of cervical cancer and cervical cancer screening in NL. The present abstract describes the creation, characteristics, and potential of this province-wide database. Methods: Based on a unique provincial medical care plan number, administrative data were linked regarding information on cervical cancer, cytology screening, hospitalizations, mortality and fee-for-service physician claims. The database covers the period from 1995 to 2005. Cervical cancer and cytology data came from the Provincial Cancer Registry and Provincial Cervical Cytology Registry, provided by the Newfoundland & Labrador Cancer Treatment and Research Foundation. The Cancer Registry contains information on demographics, diagnosis, method of diagnosis, site, stage, morphology and behavior of cancer, patient status, as well as treatment and provider information. The Cytology Registry collects demographic information and cytology findings for Pap smears. Information on hospitalizations came from the Clinical Database Management System (CDMS) maintained by the Centre. The CDMS is the provincial discharge abstract database containing demographic, clinical and procedural data on all acute care and surgical day care hospitalizations in the Province. Mortality data came from the provincial Mortality Surveillance System also maintained by the Centre. The physician claims data came from the provincial Medical Care Plan which includes information on services provided, diagnosis and physician demographics. In the first step of the linkage, cytology data were merged with the cervical cancer cases. In the second and third steps, the cancer and cytology data were linked to the hospitalization and mortality data, respectively. In the fourth and final step in the linkage, the cancer and cytology data were linked to the physician claims records. The database was created in Microsoft Access format. Discussion: The comprehensive cervical cancer/screening database offers a unique opportunity for epidemiological research in the area of cervical cancer and cervical cancer screening. The approach used in this project is an innovative model for studying cervical cancer epidemiology, prevention and control, enabling researchers to investigate risk factors, health care services utilization, and other outcomes for cervical cancer and cervical screening at the population level.
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 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 | 0,006 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,013 | 0,021 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
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 ».