A New Standards-based Grammar for Linking Aggregate Datasets
Notice bibliographique
Résumé
The theme of this session is the linking and cross-referencing of disparate aggregate datasets that need to be combined for pruporses of reporting and/or analysis. The session leverages, as a global case study, the US Government's President's Emergency Plan for AIDS Relief (PEPFAR) programme. PEPFAR is a $7 billion per year programme supporting the delivery of HIV-related services, medicines, and commodities in 58 low and middle-income countries (www.pepfar.gov). PEPFAR has an immense datastore of monitoring, evaluation and reporting (MER) indicators that have been collected from all its supported countries over the course of its 15 years of operations.
 The goal of the session is to describe for attendees a newly-developed, standards-based grammar for describing interoperable aggregate data exchange and the message schemas needed to support it. The session facilitators are the primary authors of this new standard. Using the PEPFAR case study as a working example, the session explores how disparate HIV data elements and indicators from PEPFAR-supported countries are cross-referenced to each other and collected into a single central datastore to support analysis, management and reporting across the global programme. The specific HIV example will be elaborated upon to illustrate generalizable techniques that can be applied to linking aggregate datasets in other use cases (e.g. reporting to the annual WHO global health observatory, multiple provinces reporting to a federal health data institute, etc.).
 The session will be facilitated by Xenophon Santas and James Kariuki of the US CDC, Bob Jolliffe of the University of Oslo's Health Information Systems Programme (HISP) and Derek Ritz of ecGroup Inc (a Canadian health informatics consultancy). All four facilitators are members of the Quality, Research and Publich Health (QRPH) technical committee of the international digital health standards body, Integrating the Healthcare Enterprise (IHE; www.ihe.net). The session's content and examples will leverage the facilitators' first-hand experience working on HIV-related projects in low and middle-income countries (e.g. South Africa, Rwanda, Kenya, Malawi, Zimbabwe, Uganda, Sierre Leone, Vietnam, the Philippines and elsewhere).
 It is intended that the session will be conducted using an interactive workshop style. Attendees who wish it will have an opportunity to engage in participative (hands-on) learning. To get started, information will be provided about the standards-based grammar and how it works. Then, results from the facilitators' efforts leveraging this method to link multiple disparate HIV-related datasets will be presented. As a hands-on activity, attendees who have notebook computers will be able to connect to an open source software solution (www.dhis2.org) and "play in a sandbox" to try for themselves some of the techniques that have been described.
 As learning objectives, it is expected that attendees will:
 
 Be introduced to data linking use cases outside of their everyday experience
 Learn about a new technique for expressing aggregate content schema that supports interoperable data exhange
 Apply new skills in a hands-on, worked example.
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Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,014 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,007 | 0,001 |
| 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.
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