Razai, MS; Khawaja, M; Shah, Z; Kuhn, I; Dambha-Miller, H; Oakeshott, P; Griffin, SJ
(2025)
Digital Information Sharing Before Consultations in General Practice: Protocol for a Scoping Review.
JMIR Research Protocols, 14.
e82649-e82649.
ISSN 1929-0748
https://doi.org/10.2196/82649
SGUL Authors: Razai, Mohammad Sharif Oakeshott, Philippa
|
PDF
Published Version
Available under License Creative Commons Attribution. Download (178kB) |
|
|
Microsoft Word (.docx) (Multimedia Appendix 1)
Supporting information
Download (118kB) |
|
|
Microsoft Word (.docx) (Multimedia Appendix 2)
Supporting information
Download (19kB) |
Abstract
Background Digital tools that enable patients to submit information before consultations, such as Accurx and eConsult, are increasingly used in general practice. These systems aim to streamline workflows, improve documentation, and optimize consultation efficiency. However, evidence about their implementation, impact on health inequalities, and health care outcomes remains limited and fragmented. Objective This study aims to map and synthesize the evidence on digital tools used for preconsultation information sharing in family or general practice. Methods This scoping review will follow the Joanna Briggs Institute framework and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Searches were conducted on May 12, 2025, in MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCOhost), and the Cochrane Library. Gray literature will be identified via Google Scholar and the National Health Service or government websites. Eligible studies will describe or evaluate digital tools used to collect information from patients before general practice consultations. Two independent reviewers will conduct screening and data extraction. Data will be analyzed using narrative synthesis. Results Database searches identified 6991 records, with 4536 (64.88%) remaining after deduplication. Screening began in June 2025. Full-text screening was completed in November 2025, with data extraction and synthesis planned for completion by February 2026. Results will be submitted for publication in early 2026. Conclusions This review will summarize evidence concerning the use of digital tools for preconsultation information sharing in general practice. Findings will inform implementation, research priorities, and service improvement in digitally supported care. International Registered Report Identifier (IRRID) DERR1-10.2196/82649
| Item Type: | Article | ||||||
|---|---|---|---|---|---|---|---|
| Additional Information: | ©Mohammad S Razai, Mikail Khawaja, Zahir Shah, Isla Kuhn, Hajira Dambha-Miller, Pippa Oakeshott, Simon J Griffin. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 03.Dec.2025. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included. | ||||||
| Keywords: | AI, Accurx, artificial intelligence, asynchronous communication, digital health, eConsult, general practice, online consultation, preconsultation information sharing, primary care, scoping review, telehealth, Humans, General Practice, Scoping Review as Topic, Information Dissemination, Research Design, Referral and Consultation | ||||||
| SGUL Research Institute / Research Centre: | Academic Structure > Population Health Research Institute (INPH) | ||||||
| Journal or Publication Title: | JMIR Research Protocols | ||||||
| ISSN: | 1929-0748 | ||||||
| Language: | en | ||||||
| Media of Output: | Electronic | ||||||
| Related URLs: | |||||||
| Publisher License: | Creative Commons: Attribution 4.0 | ||||||
| PubMed ID: | 41337744 | ||||||
| Dates: |
|
||||||
| Go to PubMed abstract | |||||||
| URI: | https://openaccess.sgul.ac.uk/id/eprint/118110 | ||||||
| Publisher's version: | https://doi.org/10.2196/82649 |
Statistics
Actions (login required)
![]() |
Edit Item |

