Standardized and individualized care: do they complement or oppose each other?
Notice bibliographique
Résumé
EDITOR–The overall aim of the Common Data Elements (CDE) project1 was to standardize data collection and assessment in studies of children and young people with cerebral palsy (CP). Dr Fairhurst's commentary raised the following question: can standardized care coexist with personalized care without losing the flexible art of medicine?2 Standardization promotes the application of evidence-based medicine (or the best available evidence) in a systematic way, to ensure patients receive effective care. We need less variance in clinical practice to achieve more consistent outcomes and improve quality of care and patient safety. On the other hand, personalization of care relies on health professionals knowing their patients well and treating them as unique individuals. Personalization improves the patient experience and increases their engagement and health knowledge. While standardization of clinical care – using universal frameworks, CDEs, toolbox of measures, core sets, care pathways – is valuable to support evidence-based practices, the experience from the child's and his or her family's points of view can still be personalized. It is important to note that with standardized care there are still decisions to be made based on the child's and family's preferences and choices. Setting goals and priorities for intervention, pain management techniques, and type and time of introduction of assistive technologies are examples where clients' decision-making takes place to meet their personalized needs. Hence, we can standardize and personalize care at the same time. The recommended CDEs for children and young adults with CP standardize data collection for this population. In CP, standardization and personalization can complement each other. Most importantly, standardization can enhance personalization by eliminating the unnecessary time and cost of using low quality assessment tools, or ignoring opportunities to obtain relevant clinical information, which in turn minimizes complications or inappropriate treatment that does not adhere to best evidence-informed practices. Health professionals often make assessment and treatment decisions based on their unique clinical education and experiences. Standardization compensates for this variation in history and experience and harmonizes assessment, evaluation, and reporting of outcomes, ultimately facilitating informative comparisons across research studies and therapeutic interventions. Finally, we propose that the essence of good empathic care is based on the personal connection and mutual respect developed between health professionals and the child and family. While standardization of care has the potential to relieve actual workload and to allow for more positive and productive in-person connections. Future CP CDE revisions will incorporate additional information that includes client perspectives, preferences, and choices in a systematic way, to enhance the standardized tools proposed by the current recommendations in CP CDEs version 1.0.
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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 | 0,036 | 0,230 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,011 |
| Communication savante | 0,007 | 0,013 |
| Science ouverte | 0,008 | 0,003 |
| Intégrité de la recherche | 0,027 | 0,046 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,004 |
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 ».