Patient Portal Implementation and Uptake: Qualitative Comparative Case Study
Notice bibliographique
Résumé
BACKGROUND: Giving patients access to their health information is a provincial and national goal, and it is critical to the delivery of patient-centered care. With this shift, patient portals have become more prevalent. In Alberta, the Alberta Health Services piloted a portal (MyChart). There was a need to identify factors that promoted the use of this portal. Furthermore, it was imperative to understand why there was variability in uptake within the various clinics that participated in the pilot. OBJECTIVE: This study aims to identify potential factors that could improve the uptake of MyChart from the perspectives of both users and nonusers at pilot sites. We focused on factors that promoted the use of MyChart along with related benefits and barriers to its use, with the intention that this information could be incorporated into the plan for its province-wide implementation. METHODS: A qualitative comparative case study was conducted to determine the feasibility, acceptability, and initial perceptions of users and to identify ways to increase uptake. Semistructured interviews were conducted with 56 participants (27 patients, 21 providers, 4 nonmedical staff, and 4 clinic managers) from 5 clinics. Patients were asked about the impact of MyChart on their health and health care. Providers were asked about the impact on the patient-provider relationship and workflow. Managers were asked about barriers to implementation. The interviews were recorded, transcribed verbatim, and entered into NVivo. A thematic analysis was used to analyze the data. RESULTS: Results from a comparison of factors related to uptake of MyChart in 5 clinics (2 clinics with high uptake, 1 with moderate uptake, 1 with low uptake, and 1 with no uptake) are reported. Some theoretical constructs in our study, such as intention to use, perceived value, similarity (novelty) of the technology, and patient health needs, were similar to findings published by other research teams. We also identified some new factors associated with uptake, including satisfaction or dissatisfaction with the current status quo, performance expectancy, facilitating conditions, behavioral intentions, and use behavior. All these factors had an impact on the level of uptake in each setting and created different opportunities for end users. CONCLUSIONS: There is limited research on factors that influence the uptake of patient portals. We identified some factors that were consistent with those reported by others but also several new factors that were associated with the update of MyChart, a new patient portal, in the clinics we studied. On the basis of our results, we posit that a shared understanding of the technology among patients, clinicians, and managers, along with dissatisfaction with nonportal-based communications, is foundational and must be addressed for patient portals to support improvements in care.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».