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Enregistrement W4200167513 · doi:10.1111/cen.14661

Patient experience of telemedicine for osteoporosis care during the COVID‐19 pandemic

2021· letter· en· W4200167513 sur OpenAlexaboutno aff
Alicia Jones, Peter R. Ebeling, Helena Teede, Frances Milat, Amanda Vincent

Notice bibliographique

RevueClinical Endocrinology · 2021
Typeletter
Langueen
DomaineMedicine
ThématiqueTelemedicine and Telehealth Implementation
Établissements canadiensnon disponible
Organismes subventionnairesNational Health and Medical Research Council
Mots-clésTelemedicineMedicineOsteoporosisPandemicFamily medicineHealth careTelephone interviewCoronavirus disease 2019 (COVID-19)Medical emergencyDiseaseInternal medicineInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

In response to the coronavirus disease 2019 (COVID-19) pandemic, expansion of telemedicine (telephone and video) billing numbers in March 2020 led to the rapid, widespread implementation of telemedicine across Australia, with minimal consumer involvement in service development. Osteoporosis predominantly affects older people, who are also at risk of more severe COVID-19. In response to reports that osteoporosis treatments were delayed during the COVID-19 pandemic, a number of professional societies released statements discouraging delaying certain therapies and underlying the importance of continuing best practice osteoporosis care.1, 2 In March 2020, osteoporosis clinics at our tertiary health service in Melbourne, Australia, moved to a telemedicine model of care. This study evaluated the patient experience of telemedicine for osteoporosis care and the impact on osteoporosis management. We invited patients attending osteoporosis clinics between 1 April 2020 and 28 February 2021, to complete an anonymous online survey, adapted from previous studies, regarding satisfaction and concerns using telemedicine, and changes to their management during the COVID-19 pandemic.3, 4 The clinics manage post-menopausal and secondary osteoporosis and include a paediatric transition service. We excluded patients aged <18 years, unable to consent, no mobile phone, and non-English speaking patients. The hospital's Human Research Ethics Committee approved the study (RES-20-0000-546L). Of 904 patients attending the clinics, 700 patients were eligible and sent text message invitations to the survey, and 129 completed surveys. The mean (SD) age was 61.6 (1.57) years and 77.3% were female. Most consultations were via telephone (89%). Only 15.5% of patients had previously used telemedicine. Although 83% used a smartphone, tablet or computer daily, only 56% rated themselves as confident with computers/technology. Most patients were satisfied with telemedicine, 70% thought it adequately addressed their needs, 72% thought it was convenient, and 83% thought the system was easy to use. However, 30% were concerned about inadequate treatment using telemedicine, and 19% thought the quality of care differed from in-person consultations. This differs from a study of telemedicine for osteoporosis in Canada before the COVID-19 pandemic, where only 5% thought the quality of care differed.4 Reasons given for the lack of satisfaction included communication barriers (missing body language cues, hearing difficulties), difficulty accessing paperwork such as referrals or prescriptions, and uncertainty about how to contact the clinician/clinic if they had further questions. Figure 1 shows patients' preferences for telemedicine or in-person consultations. If offered again, 68% of patients would use telemedicine for osteoporosis, while 22% would not. Using multiple logistic regression analysis, neither age, sex, nor confidence with technology was associated with either the overall preference for telemedicine or in-person consultations, or the likelihood of using telemedicine again. Unlike an international survey of clinicians, where 62% delayed osteoporosis imaging and 43% had difficulty arranging osteoporosis treatment during the COVID-19 pandemic, a minority of our patients had changes to their management.5 Only 11% of patients delayed blood tests or treatment, and 9% delayed imaging, likely reflecting the lower burden of COVID-19 in Australia. Limitations of our study include that it is single-centre and the low response rate. The findings may not be applicable to other cohorts, where the value of remote, out-of-hospital care in the form of telemedicine may differ. This includes countries with a greater COVID-19 burden, rural health services, and areas with poor telephone/internet access. Finally, due to the clinics sampled, our cohort was relatively young, which may influence the experience of telemedicine. Among patients treated at an Australian tertiary health service for osteoporosis, most had a positive experience with telemedicine. Although telemedicine was preferred to in-person consultation for travel and waiting time, only 27% prefer the overall experience of telemedicine. There was no association between age, sex, or confidence with technology, and preferences for telemedicine. Lack of personal interaction and system factors contributed to dissatisfaction with telemedicine; future studies should explore other contributing factors. Coproduction with consumers is needed to optimise telemedicine services for osteoporosis. Alicia R. Jones is the recipient of a National Health and Medical Research Council postgraduate research scholarship (Grant no. 1169192). The authors declare that there are no conflict of interests. Data are available from the corresponding author on reasonable request. Data are available from the corresponding author on reasonable request.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,306
Score d'incertitude au seuil0,976

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,134
Tête enseignante GPT0,448
Écart entre enseignants0,314 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2021
Routes d'admission1
Résumé présentoui

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