Using telerehabilitation for the initial remote evaluation and diagnosis of musculoskeletal disorders: perceptions of patients and health care providers
Notice bibliographique
Résumé
To explore, using semi-structured interviews, the perceptions of patients, clinicians and other stakeholders involved in telehealth regarding the perceived strengths and limitations of an initial remote evaluation for the diagnosis of MSKDs and the current environment of telehealth in the province of Quebec, Canada. The identified barriers, facilitators, and needs of patients and health care providers are important to acknowledge as they need to be taken into account to allow the development of effective strategies to implement remote evaluation to assess new patients with MSKDs. The main themes were: 1- Several participants felt that telehealth, including a remote evaluation, is a solution to improve access to care by reducing travel, wait times and time away from usual activities. 2- Patients and health care providers reported that a remote evaluation was more suitable for simple MSKD presentations. 3- Some clinicians expressed concerns about the potential increase in diagnostic errors and the feasibility of performing all usual components of a MSK physical examination. 4- Patients expressed doubts regarding their ability to perform some of the tasks or tests on themselves during the remote MSK physical examination and 5- More common issues related to the use of telerehabilitation were also highlighted by all such as the impact on the patient-clinician relationship, access to adequate hardware, general digital literacy, data management and issues with confidentiality. The perceived challenges of remote evaluation, specifically those related to the remote physical examination and the increased risk of diagnostic errors, must be weighed against the opportunities for improving access to care. Providing specific training for health care providers and patients on the proper use of telehealth, including how to perform a remote physical examination and how to communicate and collaborate effectively in a virtual setting, is essential to facilitate successful remote evaluation. Semi-structured interviews were conducted in the province of Quebec with patients (n=11), health care providers (physiotherapists [n=10] and physicians [n=11]), telehealth software specialists (n=2) and regulatory organizations (n=4). Five interview guides, adapted to the different types of participants, were developed using the Consolidated Framework of Implementation Research and the framework of Mathieu-Fritz et al. for the study of telehealth interventions. The themes explored included participants’ previous experiences with telehealth, their perceived strengths and limitations of telehealth, particularly regarding the initial evaluation and diagnosis of new patients, and the current global environment of telehealth use. All semi-structured interviews were transcribed and inductive thematic analysis was performed. The framework of Mathieu-Fritz et al. was used as the template for analyses.
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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 | 0,006 | 0,014 |
| 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 | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».