Patient perspectives on wait times and the impact on their life: A waiting room survey in a chronic pain clinic
Notice bibliographique
Résumé
BACKGROUND AND AIMS: Chronic pain is a debilitating condition that requires prompt access to care for effective treatment. Wait times for care often exceed benchmark recommendations, with potential consequences to patient health outcomes. The goal of this paper is to gain the perspectives of patients attending a chronic pain clinic regarding the acceptability of current wait times and the impact of their experiences of waiting for chronic pain care. METHODS: The study took place in a chronic pain clinic at an academic-affiliated teaching hospital in Ottawa, Canada, which housed seven clinicians at the time of the study. New patients attending the chronic pain clinic between July 14, 2014 and August 5, 2015 were eligible to participate based on the availability of the research and clerical staff who administered the survey on a variety of days over the course of the study. Patients completed a self-administered 29-item survey. The survey took approximately five to ten minutes to complete. Questions pertained to patients' socioeconomic factors, chronicity and burden of pain symptoms, and satisfaction with current wait times. Actual wait times were self-reported. Survey results were entered into an Excel spreadsheet, exported to SPSS, and coded numerically to facilitate descriptive analyses using comparative graphs and tables. Open-text responses were reviewed by the authors. RESULTS: Sixty-six patients completed the survey. While 83% of patients stated that their ideal wait time was less than three months, 32% reported receiving an appointment within this period, and 31% reported waiting a year or more. Only 37% of patients felt the wait time for their appointment was appropriate. During their wait, 41% of patients reported receiving written information about chronic pain and 47% were referred to a local chronic pain management group. 94% reported interference with social/recreational activities and normal activities of daily living, 31% had to miss work or school due to the frequency of ongoing symptoms, and 22% reported being unable to attend work or school altogether. Furthermore, 37% of patients reported visiting the emergency room within the previous year and 65% worried about having a serious undiagnosed disease. CONCLUSIONS: Our study found that wait times for chronic pain care, even those triaged as urgent cases, far exceeded what patients considered ideal. Only a third of patients received care within three months of making their appointment, while nearly another third waited over a year. During the waiting period, nearly all patients experienced some impact on their day-to-day activities and work or school attendance, half were unemployed, and nearly a quarter reported a complete inability to attend work or school because of pain. IMPLICATIONS: Wait times for chronic pain care exceed timelines deemed acceptable by patients, causing anxiety and reducing function. The patient perspective must be considered in initiatives attempting to improve access to care for this population with specific needs and goals. Innovative solutions, such as electronic consultation and shared care models, hold promise.
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 | 0,009 |
| 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 | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».