Telemedicine in addictions feasibility RCT – staff and patient qualitative satisfaction
Notice bibliographique
Résumé
Aims Opioid dependence has high risks. Opioid substitution treatment (OST) improves outcomes. Addiction specialist prescribers prescribe OST and monitor safety, but nonattendance may lead to worse outcomes. Telemedicine can reduce travel and improve attendance at appointments. Before COVID-19, we started a telemedicine in addictions trial to see if this helped in addictions. We present the qualitative patient and staff experience results. Method Health Research Authority approval for randomized controlled feasibility trial of Telemedicine versus Face-to-Face (control) consultations at community addictions semirural service (2500km2) using a modified Hub-and-Spoke (outreach) model. Adult opioid dependent patients prescribed OST and attending outreach were recruited. Participants received two appointments in randomized group. Telemedicine was delivered using Skype-for-business videoconferencing. Patients attended outreach, saw keyworker for drug testing first, and telemedicine conducted via keyworker's laptop. Addiction prescribers located remotely at Hub. Post-trial research interview conducted assessing patient and staff experience of Telemedicine versus Face-to-Face consultations. Data transcribed, inputted to RedCap Cloud and free-text analysed using qualitative thematic analysis. Result Of fifty-nine patient participants, 58 completed a research interview. Patient participants reported similar levels of satisfaction between the Telemedicine and Face to Face groups. The themes generated in relation to Face-to-Face were no difference, easy, kind staff and liking being part of research. For Telemedicine, themes were less travel, good experience, easier to access, good communication, saves time and saves money. For instance, one patient stated ‘Clear, easy to access less travel’ and another patient stated ‘I struggle with travel. I found it easier’. Of 19 staff participant research interviews completed, Staff reported Good or Very Good experience with telemedicine which was equivalent for Face-to-Face consultations. Eleven staff had experience of telemedicine consultations during the trial. They reported similar themes to patients with telemedicine leading to less travel, beneficial to patient care, improves attendance and was innovative technology. One staff member reported satisfaction with telemedicine due to ‘Time, travel and money reduction’. When questioned on the downsides to telemedicine, technological issues were mainly related to connection issues and sound issues. Conclusion In the first known RCT of Telemedicine versus Face-to-Face consultations for patients with opioid dependence attending prescriber review, we found that both patients and staff were satisfied with telemedicine as compared to face-to-face consultations. Overall themes were reduced travel, saving time and more convenience. This will be very important given the impact of COVID-19 on access to addictions services. Financial Sponsorship East Riding CCG Academic Health Science Network
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 | 0,047 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 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) | 0,013 | 0,001 |
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 ».