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Mobile Clinical Decision Support Systems and Applications: A Literature and Commercial Review

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Abstract

The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.

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Abbreviations

CDSS:

Clinical decision support system

CSW:

Clinical standard work

CVD:

Cardiovascular disease

eGaIT:

Embedded gait analysis using intelligent technology

ESKD:

Endstage kidney disease

GOe:

Global observatory for eHealth

H&Y:

Hoehn & Yahr

IAAP:

Imperial antibiotic prescribing policy

IgAN:

IgA nephropathy

PD:

Parkinson’s disease

PDA:

Personal digital assistant

PTT:

Partial thromboplastin time

QoE:

Quality of experience

RFID:

Radio-frequency identification

SCORE:

Systematic coronary risk evaluation

UPDRS:

Unified Parkinson disease rating scale

WHO:

World health organization

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Acknowledgments

This research has been partially supported by Ministerio de Economía y Competitividad, Spain. This research has been partially supported by the ICT-248765 EU-FP7 Project. This research has been partially supported by the IPT-2011-1126-900000 project under the INNPACTO 2011 program, Ministerio de Ciencia e Innovación.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15., 47011, Valladolid, Spain

    Borja Martínez-Pérez, Isabel de la Torre-Díez, Miguel López-Coronado & Beatriz Sainz-de-Abajo

  2. Biomedical Informatics Group, Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Camino de Vera s/n., 46022, Valencia, Spain

    Montserrat Robles & Juan Miguel García-Gómez

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  1. Borja Martínez-Pérez
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  2. Isabel de la Torre-Díez
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Correspondence to Borja Martínez-Pérez.

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Martínez-Pérez, B., de la Torre-Díez, I., López-Coronado, M. et al. Mobile Clinical Decision Support Systems and Applications: A Literature and Commercial Review. J Med Syst 38, 4 (2014). https://doi.org/10.1007/s10916-013-0004-y

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