Recording of Social Determinants in Computerized Medical Records in Primary Care Consultations: Quasi-Experimental Study
Notice bibliographique
Résumé
BACKGROUND: Social determinants of health may be more important than medical or lifestyle choices in influencing people's health. Even so, there is a deficit in recording these in patients' computerized medical histories. The Spanish administration and the World Health Organization are promoting the recording of diagnoses in computerized clinical histories with the aim of benefiting the individual, the professional, and the community. In most cases, professionals tend to record only clinical diagnoses despite evidence in the literature documenting that addressing the social determinants of health can lead to improvements in health and reductions in social disparities in disease. OBJECTIVE: This study aims to develop and evaluate the effectiveness of a mixed intervention (face-to-face-digital) aimed at improving the quantity and quality of the records of the social determinants of health in computerized medical records at primary care clinics. METHODS: A quasi-experimental, nonrandomized, controlled, multicenter study with 2 parallel study arms was conducted in the area of Central Catalonia (Spain) with primary care professionals of the Institut Català de la Salut (ICS), working from September 23, 2019, to March 31, 2020. All interested professionals were accepted. In total, 22 basic health areas were involved in the study. In Spain and Catalonia, the International Classification of Diseases is used, in which there is a coding of the social determinants of health. Five social determinants were selected by a physician, a nurse, and a social worker; these professionals had experience in primary care and were experts in community health. The choice was made taking into account the ease of use, benefit, and existing terminology. The intervention, based on the integration of a checklist, was integrated as part of the usual multidisciplinary clinical workflow in primary care consultations to influence the recording of these determinants in the patient's computerized medical record. RESULTS: After 6 months of implementing the intervention, the volume and quantity of records of 5 social determinants of health were compared, and a significant increase in the median number of pre- and postintervention diagnoses was observed (P≤.001). There was also an increase in the diversity of selected social determinants. Using the linear regression model, the significant mean increase of the experimental group with respect to the control group was estimated with a coefficient of 8.18 (95% CI 5.11-11.26). CONCLUSIONS: The intervention described in this study is an effective tool for coding the social determinants of health designed by a multidisciplinary team to be incorporated into the workflow of primary care practices. The effectiveness of its usability and the description of the intervention described here should be generalizable to any environment. TRIAL REGISTRATION: ClinicalTrials.gov NCT04151056; https://clinicaltrials.gov/ct2/show/NCT04151056.
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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 | 0,016 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».