Development and Implementation of a Mobile Phone–Based Prevention of Mother-To-Child Transmission of HIV Cascade Analysis Tool: Usability and Feasibility Testing in Kenya and Mozambique
Notice bibliographique
Résumé
BACKGROUND: Prevention of mother-to-child HIV transmission (PMTCT) care cascade failures drive pediatric HIV infections in sub-Saharan Africa. As nurses' clinical and management role in PMTCT expand, decision-support tools for nurses are needed to facilitate identification of cascade inefficiencies and solutions. The mobile phone-based PMTCT cascade analysis tool (mPCAT) provides health facility staff a quick summary of the number of patients and percentage drop-off at each step of the PMCTC care cascade, as well as how many women-infant pairs would be retained if a step was optimized. OBJECTIVE: The objective of this study was to understand and improve the mPCAT's core usability factors and assess the health workers' experience with using the mPCAT. METHODS: Overall, 2 rounds of usability testing were conducted with health workers from 4 clinics and leading experts in maternal and child health in Kenya and Mozambique using videotaped think aloud assessment techniques. Semistructured group interviews gauged the understanding of mPCAT's core usability factors, based on the Nielsen Usability Framework, followed by development of cognitive demand tables describing the needed mPCAT updates. Post adaptation, feasibility was assessed in 3 high volume clinics over 12 weeks. Participants completed a 5-point Likert questionnaire designed to measure ease of use, convenience of integration into work, and future intention to use the mPCAT. Focus group discussions with nurse participants at each facility and in-depth interviews with nurse managers were also conducted to assess the acceptability, use, and recommendations for adaptations of the mPCAT. RESULTS: Usability testing with software engineers enabled real-time feedback to build a tool following empathic design principles. The revised mPCAT had improved navigation and simplified data entry interface, with only 1 data entry field per page. Improvements to the results page included a data visualization feature and the ability to share results through WhatsApp. Coding was simplified to enable future revisions by nontechnical staff-critical for context-specific adaptations for scale-up. Health care workers and facility managers found the tool easy to use (mean=4.3), used the tool very often (mean=4.1), and definitely intended to continue to use the tool (mean=4.8). Ease of use was the most common theme identified, with emphasis on how the tool readily informed system improvement decision making. CONCLUSIONS: The mPCAT was well accepted by frontline health workers and facility managers. The collaborative process between software developer and user led to the development of a more user-friendly, context-specific tool that could be easily integrated into routine clinical practice and workflow. The mPCAT gave frontline health workers and facility managers an immediate, direct, and tangible way to use their clinical documentation and routinely reported data for decision making for their own clinical practice and facility-level improvements.
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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 | 0,017 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».