P599: An efficient alternative model of genetic counseling to deliver services at the Saguenay-Lac-Saint-Jean region in Quebec
Notice bibliographique
Résumé
Introduction: Utilization of genetic counseling (GC) clinics in pediatrics and general genetics has been presented as a model of care that increases access to genetic healthcare services.A number of these models require triage of specific indications for GC clinic appointments, while other indications are scheduled with physician geneticists with or without a GC.In our practice, initial genetic evaluations are primarily conducted with a physician or nurse practitioner (APRN) and GC and frequently exceed one hour.We evaluated potential outcomes of universal initial GC clinic appointments for patients seen in our pediatric and general genetics practice.Methods: A workflow for GC first appointments was created with our physician and GCs, starting with limited triage of referrals for appropriateness, followed by the initial GC visit.During this visit the GC would collect patient medical and family history and pick one of four choices: 1) select genetic testing and provide pre-test GC with follow up result disclosure and assessment with a GC and physician or APRN, 2) select genetic testing and provide pre-test GC with GC only follow up, 3) provide genetic counseling only with no testing or further evaluation needed, or 4) defer test selection to evaluation with physician or APRN and genetic counselor.Our team elected to have all GC-initiated exome and genome tests followed up with a physician or APRN and GC appointment for result disclosure and interpretation.Follow up appointments were categorized as: 1) GC not needed or 2) combined GC and physician/APRN care.Four GCs retrospectively reviewed 142 patients (79 new, 63 follow up) scheduled with physician or APRN providers in August, 2024, and provided their predicted assessment for these patients if they were instead seen by a GC first.Actual content of each visit was also noted and divided into 9 categories with the ability to select multiple categories for each visit: 1) GC medical/family/interval history, 2) GC pre-test counseling, 3) GC posttest counseling, 4) physician/ APRN medical/family/interval history, 5) physician/APRN pre-test counseling, 6) physician/APRN posttest counseling, 7) physician/APRN ordered nongenetic studies, 8) physician/APRN treating patient, 9) physician/APRN physical exam.Results: Among new patient appointments, 19 (24%) were predicted to receive care only from a GC with another 46 (58%) having testing initiated by a GC with result disclosure and interpretation provided with a physician/APRN in follow up.Further assessment and potential test selection with a physician/APRN and GC was the predicted outcome for 13 (17%) of new patient visits.One new patient seen for a positive newborn screen did not fit the proposed framework and required initial evaluation with an APRN and GC.GCs were determined not to be needed for 40 (63%) of follow up patients.With actual outcomes, GCs were involved with 11 patients whose needs could have been met by only seeing an MD/APRN, primarily collecting interval histories for established patients.The physician or APRN performed a physical exam in all but one visit.GCs were not involved in 33 (23%) patient encounters. Conclusion:The predicted outcomes of our model for universal GC first appointments is consistent with reports from other pediatric and general genetic counseling clinics, suggesting that even without filtering for specific indications, GCs are able to take on nearly a quarter of new patient referrals to a pediatric and general genetics clinic without further assessment needed by a physician, APRN, or physician assistant.Patients that do require additional care with the genetics team may benefit from having two separate, shorter appointments and testing completed by the second appointment for around half.Ongoing evaluations of patient and provider satisfaction, efficiency, and access are needed to more completely determine the value of this model.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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; un appel candidat d’une seule tête enseignante, pas un consensus.
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