Evidence map›Paper›PMID 37266997›Full record

ArticleJMIR formative research2023

Assessing Health Care Professionals' Mindset in Adopting Telemedicine Post COVID-19: Pilot Questionnaire Study.

Rozhin Naghdi, Gianhu Nguyen, Cecile Maria Vazquez, Christian Mark Antonio, Carlos Cabrera, Austin Chandra, Jay Chok

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rozhin NaghdiKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0003-4691-1515
Gianhu NguyenKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0001-6806-8878
Cecile Maria VazquezKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0003-2827-5375
Christian Mark AntonioKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0001-7399-1616
Carlos CabreraKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0002-8269-5795
Austin ChandraKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0001-8699-965X
Jay ChokKeck Graduate Institute, Claremont, CA, United States.ORCID https://orcid.org/0000-0002-2082-0079

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAmidst 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.

objectiveThe 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.

methodsA 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.

resultsResponses 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.

conclusionsPreliminary 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.

Indexed as

accessibilitycreative destruction of medicinedelivery modeldigital healthimplementationpatient-centered healthpatient perspectivepilot studyquestionnairetelehealthwillingness

Identifiers

PMID37266997
PMCPMC10276314

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.