Digital Outcome Measurement to Improve Care for Patients With Immune-Mediated Inflammatory Diseases: Protocol for the IMID Registry
Notice bibliographique
Résumé
BACKGROUND: Despite enormous clinical improvements, due to better management strategies and the availability of biologicals, immune-mediated inflammatory diseases (IMIDs) still have a significant impact on patients' lives. To further reduce disease burden, provider- as well as patient-reported outcomes (PROs) should be taken into account during treatment and follow-up. Web-based collection of these outcomes generates valuable repeated measurements, which could be used (1) in daily clinical practice for patient-centered care, including shared decision-making; (2) for research purposes; and (3) as an essential step toward the implementation of value-based health care (VBHC). Our ultimate goal is that our health care delivery system is completely aligned with the principles of VBHC. For aforementioned reasons, we implemented the IMID registry. OBJECTIVE: The IMID registry is a digital system for routine outcome measurement that mainly includes PROs to improve care for patients with IMIDs. METHODS: The IMID registry is a longitudinal observational prospective cohort study within the departments of rheumatology, gastroenterology, dermatology, immunology, clinical pharmacy, and outpatient pharmacy of the Erasmus MC, the Netherlands. Patients with the following diseases are eligible for inclusion: inflammatory arthritis, inflammatory bowel disease, atopic dermatitis, psoriasis, uveitis, Behçet disease, sarcoidosis, and systemic vasculitis. Generic and disease-specific (patient-reported) outcomes, including adherence to medication, side effects, quality of life, work productivity, disease damage, and activity, are collected from patients and providers at fixed intervals before and during outpatient clinic visits. Data are collected and visualized through a data capture system, which is linked directly to the patients' electronic health record, which not only facilitates a more holistic care approach, but also helps with shared decision-making. RESULTS: The IMID registry is an ongoing cohort with no end date. Inclusion started in April 2018. From start until September 2022, a total of 1417 patients have been included from the participating departments. The mean age at inclusion was 46 (SD 16) years, and 56% of the patient population is female. The average percentage of filled out questionnaires at baseline is 84%, which drops to 72% after 1 year of follow-up. This decline may be due to the fact that the outcomes are not always discussed during the outpatient clinic visit or because the questionnaires were sometimes forgotten to set out. The registry is also used for research purposes and 92% of the patients with IMIDs gave informed consent to use their data for that. CONCLUSIONS: The IMID registry is a web-based digital system that collects provider- and PROs. The collected outcomes are used to improve care for the individual patient with an IMID and facilitate shared decision-making, and they are also used for research purposes. The measurement of these outcomes is an essential step toward the implementation of VBHC. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43230.
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 | 0,083 | 0,080 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,004 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,043 | 0,012 |
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 ».