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Front Public Health. 2014 Nov 24;2:247. doi: 10.3389/fpubh.2014.00247. eCollection 2014.

Quality Assurance of Teleconsultations in a Store-and-Forward Telemedicine Network - Obtaining Patient Follow-up Data and User Feedback.

Author information

1
Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway , Tromsø , Norway ; Faculty of Health Sciences, University of Tromsø , Tromsø , Norway.
2
Médecins Sans Frontières (MSF) International , Geneva , Switzerland.
3
Department of Medical Ethics and Legal Medicine (EA 4569), Paris Descartes University , Paris , France ; Fondation Médecins Sans Frontières , Paris , France.

Abstract

User surveys in telemedicine networks confirm that follow-up data are essential, both for the specialists who provide advice and for those running the system. We have examined the feasibility of a method for obtaining follow-up data automatically in a store-and-forward network. We distinguish between follow-up, which is information about the progress of a patient and is based on outcomes, and user feedback, which is more general information about the telemedicine system itself, including user satisfaction and the benefits resulting from the use of telemedicine. In the present study, we were able to obtain both kinds of information using a single questionnaire. During a 9-month pilot trial in the Médecins Sans Frontières telemedicine network, an email request for information was sent automatically by the telemedicine system to each referrer exactly 21 days after the initial submission of the case. A total of 201 requests for information were issued by the system and these elicited 41 responses from referrers (a response rate of 20%). The responses were largely positive. For example, 95% of referrers found the advice helpful, 90% said that it clarified their diagnosis, 94% said that it assisted with management of the patient, and 95% said that the telemedicine response was of educational benefit to them. Analysis of the characteristics of the referrers who did not respond, and their cases, did not suggest anything different about them in comparison with referrers who did respond. We were not able to identify obvious factors associated with a failure to respond. Obtaining data by automatic request is feasible. It provides useful information for specialists and for those running the network. Since obtaining follow-up data is essential to best practice, one proposal to improve the response rate is to simplify the automatic requests so that only patient follow-up information is asked for, and to restrict user feedback requests to the cases being assessed each month by the quality assurance panel.

KEYWORDS:

LMICs; quality assurance; quality control; telehealth; telemedicine

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