High-value, data-informed, and team-based care for multimorbidity
Notice bibliographique
Résumé
In most settings, care is traditionally physician-centred, but trends are shifting towards a patient-centred health-care system.1NEJM CatalystWhat is value-based health care?.https://catalyst.nejm.org/what-is-value-based-healthcare/Date: Jan 1, 2017Date accessed: December 4, 2019Google Scholar Patient-centred care focuses on the health-care needs and preferences of patients, by allowing patients to become active participants and ensuring that their values guide clinical decisions.1NEJM CatalystWhat is value-based health care?.https://catalyst.nejm.org/what-is-value-based-healthcare/Date: Jan 1, 2017Date accessed: December 4, 2019Google Scholar Jonathan Pearson-Stuttard and colleagues2Pearson-Stuttard J Ezzati M Gregg EW Multimorbidity—a defining challenge for health systems.Lancet Public Health. 2019; 4: e599-e600Summary Full Text Full Text PDF PubMed Scopus (63) Google Scholar called for a patient-centred approach of multimorbidity in the previous issue of The Lancet Public Health. However, we would like to stress that for such an approach to be truly implemented, health-care systems must be designed for the provision of high-value, data-informed, and team-based care. Firstly, the promotion of high-value care is needed for the long-term sustainability of health-care systems. Value-based health care aims to increase the value that is derived from the resources available for a population.3Gray M Value based healthcare.BMJ. 2017; 356: j437Crossref PubMed Scopus (75) Google Scholar Overdiagnosis, overtreatment, and more subtle forms of low-value care and waste are recognised as major threats. However, one major challenge is distinguishing high-value care from low-value care; a hierarchy of evidence-based recommendations needs to be generated through health technological assessments that integrate patients’ preferences. Secondly, the management of multimorbidity should be transformed through data-informed care. Care for multimorbidity is complex, calling for monitoring at the individual level with new health information technology, including through a better use of electronic health records. A surveillance system is also needed at the population level, and we agree with Pearson-Stuttard and colleagues that existing disease surveillance systems have not been used optimally to guide effective action for the management of multimorbidity. The digital transformation of health-care systems will help to improve health surveillance, but these systems have to use data effectively to avoid being “data rich but information poor”.4OECDHealth in the 21st century: putting data to work for stronger health systems. Organisation for Economic Co-operation and Development, Paris2019Crossref Google Scholar Thirdly, team-based care is needed for the integrated and coordinated management of chronic diseases and multimorbidity. Although several types of team-based intervention exist for the management of chronic diseases, such as diabetes or hypertension,5Santschi V Wuerzner G Chiolero A et al.Team-based care for improving hypertension management among outpatients (TBC-HTA): study protocol for a pragmatic randomized controlled trial.BMC Cardiovasc Disord. 2017; 17: 39Crossref PubMed Scopus (14) Google Scholar studies are now needed to evaluate how team-based care can help manage multimorbidity within a patient-centred approach. Digital transformation of health care can also offer opportunities to ease the implementation of team-based care through information systems leveraging data from shared electronic health records. In conclusion, we agree with Pearson-Stuttard and colleagues that several challenges need to be addressed to work towards the provision of high-value, data-informed, team-based, and patient-centred care of multimorbidity; overcoming these challenges will be necessary for the long-term sustainability of health-care systems in aging populations. We declare no competing interests. Multimorbidity—a defining challenge for health systemsMultimorbidity has emerged as one of the greatest challenges facing health services, both presently and in coming decades. Surveillance data on chronic diseases in Scotland, UK, estimate around one in four of their adult population to have two or more long-term conditions.1 By 2035, approximately 17% of the UK population is projected to have four or more chronic conditions, which is almost double the current prevalence (9·8%).2 Hypertension (prevalence 18·2%), depression or anxiety (10·3%), and chronic pain (10·1%) are among the leading contributors to the increasing prevalence of multimorbidity,3 demonstrating the breadth, heterogeneity, and interlinked nature of physical and mental health conditions. Full-Text PDF Open Access
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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 | 0,011 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».