44 Finding the Onramp: Understanding Access to Neuropsychological Evaluation in New Onset Pediatric Epilepsy
Notice bibliographique
Résumé
Objective: Approximately half of all children and adults newly diagnosed with epilepsy also show behavioral and/or cognitive difficulties upon evaluation. While neuropsychological screening is recommended as a routine part of care at seizure onset, in reality, access to care is often restricted by many factors. In order to better define the extent of the problem, we developed a survey to understand how frequently youth with new onset epilepsy currently undergo neuropsychological evaluation or screening and whether virtual assessment tools are used to extend access to care. Participants and Methods: We created an online survey to better understand new onset epilepsy care provided within neuropsychological practice settings in the United States and Canada. The survey was disseminated via multiple listservs (e.g., AACN listservs, APPCN, PERF neuropsychologists) and respondents included 45 neuropsychologists. Survey questions were grouped by the following domains: 1) location characteristics (e.g., urban versus rural location, type of practice, affiliation with comprehensive epilepsy center); 2) volume of new onset epilepsy patient cases (e.g., number of neuropsychologists within practice who see new onset patients, percentage of new onset cases who received neuropsychological evaluations/screeners, wait time), and 3) tele-neuropsychology procedures (e.g., use of virtual testing, frequency of virtual testing, frequency of virtual intakes/feedbacks). Results: Practice locations of the 45 respondents included academic medical center (n=34, 75.6%), community medical center (n=10, 22.2%), and private practice (n=1, 2.2%). All but one respondent practiced in an urban setting. Respondents were generally affiliated with Comprehensive Epilepsy Centers (level 3 or 4) (n=39, 86.7%). Practice settings typically included < 3 epilepsy neuropsychologists (n=29, 65.9%). Of interest, neuropsychological evaluation of new onset pediatric epilepsy patients generally ranged from 0-25% of cases (n=32, 71%; mode=11-25%). Reported barriers included: insurance, poor access to rural populations, interdisciplinary communication, departmental referral patterns, limited number of providers, and need to prioritize pre-surgical patients. In terms of access, neuropsychology waitlist times for patients with nonsurgical epilepsy ranged from <1 to 6 months (n=34, 75%) with an equal proportion of patients waiting 1-3 months (33%) and 4-6 months (33%). Telehealth was not frequently utilized in non-surgical epilepsy test administration (Do not use, n=39; 86.7%), but frequently incorporated for non-testing purposes (i.e., intakes, feedbacks) (n=40, 88.9%). Conclusions: Results of this provider survey indicate that children with new-onset epilepsy do not routinely undergo neuropsychological evaluation (< 25%). Barriers included prioritizing presurgical workups, referral patterns, access to care, and limited provider bandwidth. Clearly, there is a need to improve access to care. Possible solutions include developing more time efficient screening batteries with measures most sensitive to early cognitive and psychosocial deficits, and incorporating the use of virtual technology all in the service of improving the lives of children with epilepsy.
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 | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».