Patient Wait Time Recall Accuracy for Gastroenterology Specialty Consultation in Nova Scotia
Notice bibliographique
Résumé
BACKGROUND: Inflammatory Bowel Disease (IBD) is a chronic disease with lifelong health, social, and economic burden. The province of Nova Scotia (NS) has the highest age-adjusted incidence and prevalence rates of IBD in Canada, with Canada having the highest prevalence rates of IBD in the world. The Canadian Association of Gastroenterology guidelines suggest wait times between two and 16 weeks for those with active IBD symptoms. Despite these guidelines, a 2015 audit of the NS Health Authority revealed that 50% of IBD referrals were seen within 12 weeks and 90% of referrals waiting longer (up to two years). Long wait times can lead to increased anxiety, decreased quality of life, and reduction in patient satisfaction and overall health. Estimating wait times is complex but essential in order to evaluate access to specialty care. Aims: 1) To determine whether patients referred to GI specialty services in NS can accurately estimate the length of time between GP referral and first GI specialty appointment; 2) To examine demographic, disease-related, and system factors which may influence the accuracy of patient wait time estimates. METHODS: Questionnaires were distributed to patients following their appointment with a luminal GI or IBD nurse practitioner. Patients were asked to estimate their wait time for seeing a GI specialist. They were also asked to report on factors that could influence their wait time recall (geographic locale, age, employment status, completed education, disease severity, and relevant comorbidities). Completed questionnaires were returned and retrospective chart reviews were performed to validate the patients' responses. Descriptive analyses (means, standard deviations) on disease phenotype, complications and surgeries, current and past medication use, distance travelled to appointment, and perceived acceptability of wait times were completed. Spearman's correlations were run on wait time estimates and actual wait times to determine level of estimate accuracy. RESULTS: A total of 70 patients were prospectively enrolled as of July 2017. Forty-three (61.4%) patients were female, with an average age of 45.3 years (SD=20.3 years). When patients were asked to estimate their wait time between referral and seeing a GI specialist, they reported an average of 35.7 weeks. Following retrospective chart reviews, the patient estimates were shown to be conservative. In reality, records showed the average patient waited 39.8 weeks from the time the referral was sent to seeing a GI specialist. Spearman's correlation was used to determine the relationship between patient estimates and referral dates. There was a strong positive correlation between patient estimates and referral dates (rs=0.8, N=67, P<0.0001). CONCLUSION(S): This study is the first of its kind to look at the accuracy of patient recall of wait times for gastroenterology. The initial pilot data highlights the reality of excessive wait times in NS for patients seeking GI speciality care and suggests that patient wait time recall may be used to provide estimates of specialist wait times for patients with IBD. Future research will look at access to GI care using a healthcare systems mapping approach using patient recall to estimate perceived wait times to better inform clinical care pathways in the province.
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 | 0,002 | 0,012 |
| 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 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».