Evidence map›Paper›PMID 36563043›Full record

ArticleJMIR formative research2022

Perceptions of a Secure Cloud-Based Solution for Data Sharing During Acute Stroke Care: Qualitative Interview Study.

Marcela Tuler de Oliveira, Lúcio Henrik Amorim Reis, Henk Marquering, Aeilko H Zwinderman, Sílvia Delgado Olabarriaga

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 29% of its field
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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
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

5 authors at 1 institution in 1 country.

Marcela Tuler de OliveiraAmsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0001-5739-5590
Lúcio Henrik Amorim ReisAmsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-8943-4600
Henk MarqueringAmsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-1414-6313
Aeilko H ZwindermanAmsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0003-0361-3139
Sílvia Delgado OlabarriagaAmsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.ORCID https://orcid.org/0000-0002-5935-4482
Amsterdam University Medical Centers · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute stroke care demands fast procedures performed through the collaboration of multiple professionals across multiple organizations. Cloud computing and the wide adoption of electronic medical records (EMRs) enable health care systems to improve data availability and facilitate sharing among professionals. However, designing a secure and privacy-preserving EMR cloud-based application is challenging because it must dynamically control the access to the patient's EMR according to the needs for data during treatment.

objectiveWe developed a prototype of a secure EMR cloud-based application. The application explores the security features offered by the eHealth cloud-based framework created by the Advanced Secure Cloud Encrypted Platform for Internationally Orchestrated Solutions in Health Care Horizon 2020 project. This study aimed to collect impressions, challenges, and improvements for the prototype when applied to the use case of secure data sharing among acute care teams during emergency treatment in the Netherlands.

methodsWe conducted 14 semistructured interviews with medical professionals with 4 prominent roles in acute care: emergency call centers, ambulance services, emergency hospitals, and general practitioner clinics. We used in-depth interviews to capture their perspectives about the application's design and functions and its use in a simulated acute care event. We used thematic analysis of interview transcripts. Participants were recruited until the collected data reached thematic saturation.

resultsThe participants' perceptions and feedback are presented as 5 themes identified from the interviews: current challenges (theme 1), quality of the shared EMR data (theme 2), integrity and auditability of the EMR data (theme 3), usefulness and functionality of the application (theme 4), and trust and acceptance of the technology (theme 5). The results reinforced the current challenges in patient data sharing during acute stroke care. Moreover, from the user point of view, we expressed the challenges of adopting the Advanced Secure Cloud Encrypted Platform for Internationally Orchestrated Solutions in Health Care Acute Stroke Care application in a real scenario and provided suggestions for improving the proposed technology's acceptability.

conclusionsThis study has endorsed a system that supports data sharing among acute care professionals with efficiency, but without compromising the security and privacy of the patient. This explorative study identified several significant barriers to and improvement opportunities for the future acceptance and adoption of the proposed system. Moreover, the study results highlight that the desired digital transformation should consider integrating the already existing systems instead of requesting migration to a new centralized system.

Indexed as

acute stroke carecloud-based applicationscross-organization data sharingdata access controldata privacyelectronic health recordsencryptionmobile phonequalitative interview study

Identifiers

PMID36563043
PMCPMC9823575
OpenAlexW4297135752

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.