Service Users’ Perspectives on an Integrated Electronic Care Record in Mental Health Care: Qualitative Vignette and Interview Study
Notice bibliographique
Résumé
BACKGROUND: There have been suggestions that electronic health records (EHRs) should be expanded beyond clinical mental health care services to a broader array of care services that support mental health service users, which we call an integrated electronic care record (IECR). Previous research has considered service users' general views on information being stored and shared via an EHR. However, little consideration has been given to service users' attitudes toward how EHRs should be used in the provision of care or the concept of an IECR. OBJECTIVE: This study aimed to understand mental health care service users' perspectives on an IECR and how it should be used in practice when receiving care. METHODS: Ten people with lived experience of accessing multiple services in Australia's mental health care system were provided with 2 vignettes that depicted fictional service users making decisions about an IECR. Participants were asked to respond to several scenarios that the fictional service users might experience in their journey through the mental health care system with an IECR. Participants provided written responses and took part in a semistructured interview to discuss their responses. An interpretative phenomenological analysis was undertaken, which led to 5 major themes and 15 subthemes being developed. RESULTS: Service users wanted an IECR that they had control over, supported them as equal partners in their care, and contributed toward more collaborative and proactive mental health care. However, participants were concerned that care professionals' perspectives would be privileged in the IECR and overshadow service users' needs. Participants also had concerns that stigmatizing and discriminatory information documented in their IECR would negatively impact their interactions with the mental health care system and their access to care. Participants saw value in an IECR bringing together information to support collaborative and proactive care. However, participants thought that the benefits of the IECR had to be balanced with potential risks to their privacy. Participants thought that the IECR should contain only information relevant to their care and should be shared only with relevant care professionals. There were concerns that service users might lack the skills, resources, and information required to manage their IECR. CONCLUSIONS: An IECR has the potential to fill the gaps in an increasingly complex and fragmented mental health care system but risks entrenching service users' experiences of stigma and discrimination unless service users are meaningfully involved in their IECR.
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 | 0,013 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,013 | 0,009 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».