Building remote care management on the foundations of integrated care: A review of Connected Care Halton Ontario Health Team experience
Notice bibliographique
Résumé
Background: The call for population segmentation and management from the Ontario Ministry of Health requires Ontario Health Teams (OHTs) to identify priority population for targeted interventions. For Connected Care Halton Ontario Health Team (CCHOHT), patients with respiratory diseases, diabetes, end-stage cancer - palliative, and those in need of wound care were identified and individual remote care management programs around these health conditions were established. While these programs rest upon some of the pillars of integrated care (namely, population health, people as partners in care, digital solutions and transparency of progress), they have not been previously evaluated based on evidence-based principles and best practices. Where this type of analysis bears value is in ensuring that RCM programs are rooted in the foundations of integrated care and are well placed to benefit from its rewards. The respiratory diseases RCM program is highlighted in this analysis because it is the most established of the RCM programs at CCHOHT and it provides an opportunity for program organizers to provide deep reflections on its establishment and overall performance. The program is a digital-based remote monitoring service geared towards patients with respiratory diseases. Objective: The objective of this study is to evaluate the core structure of the RCM model developed by the Connected Care Halton Ontario Health Team (CCHOHT) according to best practices for establishing such programs as they relate to values of integrated care. The results of the program’s first evaluation exercise are also provided to assess its initial performance. Method: This study adopts a qualitative approach to compare the RCM model established by the CCHOHT with best practice principles for building RCM programs outlined by Ontario Ministry of Health. These principles are touch, technology, integration and equity. The authors also proposed a fifth principle called, outcomes to measure the main achievements of its RCM programs. Results: From its inception, the respiratory diseases RCM program continues to be shaped by engagements and collaborations with patients, clinicians and caregivers, which ultimately influence the administration of remote monitoring. The program also meets Ontario Health RCM taxonomy criteria of technology touch, integration and equity. It is a digital solution to remotely monitor patients, provide follow-up communication and escalate critical cases through a more connected clinical pathway of services and care partners. The program is delivered through the Aetonix monitoring software, which is available electronically on tablets that are distributed to the target population. Preliminary outcomes of the program include a 69% and a 79% reduction in emergency department visits and hospital admission, respectively, with participants expressing favorable experiences while on the program. Conclusion: The CCHOHT’s RCM model and by extension its respiratory diseases RCM program are built on intersecting principles of RCM and integrated care articulated by the Ontario Ministry of Health, and a retrospective evaluation of this program revealed notable benefits to its target population and other stakeholders. Moreover, the adaptable nature of the RCM model allows it to be extended to other clinical conditions like diabetes, palliative and wound care, which are also currently being explored.
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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 | 0,015 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,010 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 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 ».