1701 Improving completion rates of routine mental health screening for depression and anxiety in paediatric lupus outpatient clinic to enhance patient mental health care
Notice bibliographique
Résumé
Background/Purpose Mental health (MH) problems are prevalent in adolescents with childhood-onset lupus (cSLE), with cross-sectional studies estimating prevalences of 20-60% for depression symptoms and 20-40% for anxiety symptoms. Despite this, MH screening rates are low. Identifying and treating MH symptoms early on is crucial as they are known to be associated with poor patient outcomes. A six-month chart audit (July 2021- Dec 2021) revealed a baseline median percentage of 17% of cSLE patients with documented MH screening in paediatric lupus outpatient clinic at The Hospital for Sick Children (Sickkids). In response, we aimed to: 1) increase percentage of cSLE patients (≥ 12-18 yo) with routine MH screening for depression (Patient Health Questionnaire-9 (PHQ-9)) and anxiety (Generalized Anxiety Disorder-7 (GAD-7)) from 17% to 80%, and if positive, 2) increase percentage of documented initial management (psychoeducation and/or referral to appropriate MH service(s)) from 22% to 80% in cSLE outpatient clinic by Sep 2022. Methods This is a time series study analyzed with run charts. Root cause analysis was performed using fishbone diagram, 5Whys, and pareto chart. Patient and parent satisfaction surveys were conducted to determine their baseline satisfaction. Plan-Do-Study Act (PDSA) method was used to systematically evaluate and adjust process in real time. Family of measures included outcome measure – percentage of positively screened cSLE patients with documented initial MH management, process measure – percentage of eligible cSLE patients screened, and balancing measure – number of referrals to MH services, and time till seen. Results Root causes identified included limited MH resources, lack of integration into clinic workflow, lack of standardized clinic algorithm for positive screens, lack of MH training of health care providers, and patient/family stigma and misconceptions. A series of site-specific change ideas (figure 1) were developed accordingly and implemented including 1) patients self-screened instead of administered by health care providers, 2) a standardized clinic algorithm, and 3) two 2-hour MH training workshops for health care providers. Over 50% of patients (n= 23) and parents (n=18) surveyed felt comfortable with routine MH screening, preferably in-person, and supported ongoing MH inquiry at future visits (figure 2). Patients emphasized privacy and confidentiality. Over six month period, 42 cSLE patients completed PHQ-9 and GAD-7 screens, increasing screening rate from 17 to 67%, of which 18 (43%) and 15 (36%) had positive screens respectively (figure 3). Of those, 10% (n=4) had moderate to severe scores and suicidal ideation. Six cSLE patients were referred and seen by appropriate MH service within 4-6 weeks. Majority screened (n=41) received psychoeducation and MH handout. Conclusion Routine formal depression and anxiety screening is feasible in a busy subspecialty clinic. Next steps include ongoing screening, and ensuring appropriate follow-up plan for positive screens.
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 | 0,004 | 0,017 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,002 |
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 ».