Developing the Patient Falls Risk Report: A mixed-methods study on sharing falls-related clinical information from home care with primary care providers
Notice bibliographique
Résumé
Background: Only 24% of Canadian primary care providers communicate with home care providers about the needs and services of patients. This service gap puts vulnerable people at risk of adverse events. One tool that may enhance communication between home care and primary care is the interRAI home care (interRAI-HC), a mandated comprehensive geriatric assessment in home care. The focus of this study was on development of a one-page document for sharing falls-related clinical information from the interRAI-HC with primary care providers (i.e., the Patient Falls Risk Report). Target audience: Primary care providers who feel siloed from the rest of the health care system. About the intervention: The Patient Falls Risk Report is a structured, one-page, faxable form that contains falls-related patient information derived from interRAI-HC assessments. The report is evidence-based and includes personalized information on future falls risk, balance, cognition, pain, foot problems, medications, and physical activity levels, as well as recommendations for falls prevention in older persons. Stakeholder engagement and other research methods: This mixed-methods intervention development study began with one-on-one stakeholder engagement via semi-structured interviews with primary care providers. We first explored their views on falls-related information sharing. Then, we tested a prototype of the Patient Falls Risk Report for usability and utility, thematically analyzing the findings to iteratively to develop the tool. The report was then evaluated again with voluntary self-report surveys based on the System Usability Scale. Results: A sample of 9 interview participants co-developed the Patient Falls Risk Report to improve its clarity and level of detail. All participants stated that they would use the report in their practices and most believed that it could support care provision due to its inclusion of relevant, actionable information. In the end, a survey sample of 27 participants determined that the report was highly usable, with an overall usability score of 83.4 (95% CI = 78.7, 88.2). However, the need for improved shared care planning and community responsibility was also emphasized. Impact: This study demonstrates that information collected from existing clinical assessments can be shared with primary care providers in a useful manner. It also highlights criteria to inform the design of future information-sharing interventions, especially those harnessing interRAI assessments. Key Learning: Primary care providers need tailored and consistent streams of communication with other health care providers so that collaboration and integration can become a reality. Next Steps: We are at a turning point in health care, where the functionality of health information systems is improving, and fax is becoming increasingly obsolete. Based on the recently published results of this study [1], we are currently collaborating with government and eHealth organizations on an implementation plan for interRAI information sharing with patients and caregivers in Ontario, Canada. 1. Nova AA, Heckman G, Giangregorio LM, Alarakhia M. Developing the Patient Falls Risk Report: A Mixed-Methods Study on Sharing Falls-Related Clinical Information from Home Care with Primary Care Providers. Canadian Journal on Aging / La Revue canadienne du vieillissement. 2022;1–14.
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 | 0,062 | 0,070 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 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 ».