Assessment of Stakeholder Perceptions and Attitudes Toward Health Data Governance Principles in Botswana: Web-Based Survey
Notice bibliographique
Résumé
BACKGROUND: The use of information and communication technologies for health-eHealth-is described as having potential to improve the quality of health care service delivery. Consequently, there is an increased global trend toward adoption of eHealth interventions by health care systems worldwide. Despite the proliferation of eHealth solutions, many health care institutions especially in transitioning countries are struggling to attain effective data governance approaches. The Ministry of Health in Botswana is an exemplar institution continually seeking better approaches to strengthen health data governance (HDG) approaches following the adoption of eHealth solutions. Recognizing the need for a global HDG framework, the Transform Health coalition conceptualized HDG principles that are structured around 3 interconnected objectives: protecting people, promoting the value of health, and prioritizing equity. OBJECTIVE: The aim of the study is to solicit and evaluate perceptions and attitudes of health sector workers in Botswana toward the HDG principles by Transform Health and derive any future guidance. METHODS: Purposive sampling was used to select participants. A total of 23 participants from various health care organizations in Botswana completed a web-based survey and 10 participated in a follow-up remote round-table discussion. The aim of the round-table discussion was to gain further insight into participants' responses from the web-based survey. Participants were from the following health care cadres: nurses, doctors, information technology professionals, and health informaticians. Both validity and reliability testing were performed for the survey tool before sharing it with study participants. An analysis of participants' close-ended responses from the survey was performed using descriptive statistics. Thematic analysis of open-ended responses from the questionnaire and the round-table discussion was achieved using the Delve software and the widely accepted principles of thematic analysis. RESULTS: Although some participants highlighted having measures in place similar to the HDG principles, there were some who either did not know or disagreed that their organizations already had in place mechanisms similar to the proposed HDG principles. Participants further expressed relevance and importance of the HDG principles in the context of Botswana. However, some modifications to the principles were also suggested. CONCLUSIONS: This study highlights the necessity of data governance in health care particularly toward meeting the requirements for Universal Health Coverage. The existence of other health data governance frameworks calls for a critical analysis to assess the most appropriate and applicable framework in the context of Botswana and similar transitioning countries. An organization-centered approach may be most appropriate, as well as strengthening of existing organizations' HDG practices with the Transform Health principles.
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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 | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».