Assessing Health Care Professionals' Mindset in Adopting Telemedicine Post COVID-19: Pilot Questionnaire Study
Notice bibliographique
Résumé
BACKGROUND: Amidst the COVID-19 pandemic, the traditional health care model has evolved toward a more patient-centric model. In relation to this trend, digital health services have seen an acceleration, which may have significant implications for the health care model. Due to the impact of COVID-19 on health care facilities, it is important to explore health professionals' willingness to adopt a patient-centric digital health delivery model for medicine and health care. OBJECTIVE: The aim of this study was to pilot a survey that assesses the impact and implementation of telehealth in view of health care providers prior to and post COVID-19. METHODS: A total of 26 volunteer health care professionals participated in the pilot study, of which 19/26 (73%) completed the general demographics portion. Among these respondents, 9/26 (35%) completed the entirety of the survey. The questionnaire included questions relating to general demographics, accessibility and benefits, usability, and engagements with telemedicine. Participants were randomly assigned to 1 of the 4 questionnaire designs (A-D) based on their expertise in telehealth. Of the 9 total participants who completed their randomly assigned questionnaire, 1 (11%) was randomly assigned to A, 3 (33%) were randomly assigned to B, 2 (22%) were randomly assigned to C, and 3 (33%) were randomly assigned to D. RESULTS: Responses and data from the study questionnaire were collected from Qualtrics. Microsoft Excel was used for data organization. Due to limited responses and data, no advanced statistical software was implemented. From the 9 participants who completed the entirety of the survey, responses from those with telehealth experience (n=4) showed that telehealth was preferred for follow-ups, lab results, and consultations, and that with telehealth, there was greater flexibility with appointment times and a decrease in the number of patients seen. Among the 4 health care providers with telehealth experience, all of them believed it improved accessibility and reduced physical barriers; health care professionals believed telehealth reduced translational barriers with patients. Among health care professionals without telehealth experience (n=5), 60% (3/5) reported a decrease in appointments for in-office visits post COVID-19 and strongly agreed or agreed that telehealth could influence the quality of care for patients. All 5 participants also reported no general concerns about telehealth prior to the pandemic and agreed that it would provide accessibility for patients. CONCLUSIONS: Preliminary findings of our pilot study showed initial support of a dynamical shift within the health care model due to the rise in the use of telehealth services between health care providers and patients but no statistically significant results. Further research and investigation with a larger sample size is warranted to better understand the mindset of health care professionals in adopting telemedicine post COVID-19.
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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 | 0,011 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».