Virtual Medical Modality Implementation Strategies for Patient-Aligned Care Teams to Promote Veteran-Centered Care: Protocol for a Mixed-Methods Study
Notice bibliographique
Résumé
BACKGROUND: The Veterans Health Administration (VHA) is making system-wide efforts to increase integrated use of health information technology (HIT), including My HealtheVet (MHV), the Veterans Affairs (VA) electronic patient portal, Vet Link kiosks, telehealth, and mobile apps. Integrated use of HIT can increase individual and system efficiency, maximize resources, and enhance patient outcomes. Prior research indicates that provider endorsement and reinforcement are key determinants of patient adoption of HIT. HIT implementation strategies need to reflect providers' perspectives to promote adoption and endorsement of these tools; however, providers often lack awareness or are unmotivated to incorporate HIT into clinical care with their patients. When these modalities are used by patients, the approach is often fragmented rather than integrated within and across care settings. Research is needed to identify effective implementation strategies for increasing patient-aligned care team (PACT) member (ie, the VHA's Patient Centered Medical Home) awareness and motivation to use HIT in a proactive and integrated approach with patients. OBJECTIVE: This paper describes the rationale, design, and methods of the PACT protocol to promote proactive integrated use of HIT. METHODS: In Aim 1, focus groups (n=21) were conducted with PACT members (n=65) along with questionnaires and follow-up individual interviews (n=16). In Aim 2, the team collaborated with VA clinicians, electronic health researchers and operational partners to conduct individual expert interviews (n=13), and an environmental scan to collect current and emerging provider-focused implementation tools and resources. Based on Aim 1 findings, a gap analysis was conducted to determine what implementation strategies and content needed to be adapted or developed. Following the adaptation or development of resources, a PACT expert panel was convened to evaluate the resultant content. In Aim 3, a local implementation of PACT-focused strategies to promote integrated use of HIT was evaluated using pre- and postquestionnaire surveys, brief structured interviews, and secondary data analysis with PACT members (n=63). RESULTS: Study enrollment for Aim 1 has been completed. Aims 1 and 2 data collection and analysis are underway. Aim 3 activities are scheduled for year 3. CONCLUSIONS: This work highlights the practical, technological, and participatory factors involved in facilitating implementation research designed to engage PACT clinical members in the proactive integrated use of HIT. These efforts are designed to support the integrated and proactive use of VA HIT to support clinical care coordination in ways that are directly aligned with PACT member preferences. This study evaluated integrated VA HIT use employing mixed-methods and multiple data sources. Deliverables included PACT-focused strategies to support integrated use of HIT in the ambulatory care setting that will also inform strategy development in other systems of care and support subsequent implementation efforts at regional and national levels. REGISTERED REPORT IDENTIFIER: RR1-10.2196/11262.
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 | 0,059 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,007 | 0,007 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,006 | 0,003 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,005 | 0,004 |
| Intégrité de la recherche | 0,006 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,060 | 0,010 |
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 ».