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Automatic messaging for improving patients engagement in diabetes management: an exploratory study

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Abstract

Mobile health systems aiming to promote adherence may cost-effectively improve the self-management of chronic diseases like diabetes, enhancing the compliance to the medical prescription, encouraging and stimulating patients to adopt healthy life styles and promoting empowerment. This paper presents a strategy for m-health applications in diabetes self-management that is based on automatic generation of feedback messages. A feedback assistant, representing the core of architecture, delivers dynamic and automatically updated text messages set up on clinical guideline and patient’s lifestyle. Based on this strategy, an m-health adherence system was designed, developed and tested in a small-scale exploratory study with T1DM and T2DM patients. The results indicate that the system could be feasible and well accepted and that its usage increased along with adherence to prescriptions during the 4 weeks of the study. A more extensive research is pending to corroborate these outcomes and to establish a clear benefit of the proposed solution.

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Acknowledgments

The authors acknowledge the METABO consortium for their valuable contributions to this work. This project is partially funded by the European Commission (Contract No. 216270) under the 7th Framework Program, Theme ICT-2007.5.1, personal health systems for monitoring and point-of-care diagnostics—personalized monitoring.

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Authors and Affiliations

  1. Life Supporting Technologies (LifeSTech) Group, Universidad Politécnica de Madrid (UPM), 28040, Madrid, Spain

    Alessio Fioravanti, Giuseppe Fico, Dario Salvi, Rebeca I. García-Betances & Maria Teresa Arredondo

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  1. Alessio Fioravanti
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  2. Giuseppe Fico
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  3. Dario Salvi
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  4. Rebeca I. García-Betances
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  5. Maria Teresa Arredondo
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Correspondence to Alessio Fioravanti.

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Fioravanti, A., Fico, G., Salvi, D. et al. Automatic messaging for improving patients engagement in diabetes management: an exploratory study. Med Biol Eng Comput 53, 1285–1294 (2015). https://doi.org/10.1007/s11517-014-1237-8

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  • DOI: https://doi.org/10.1007/s11517-014-1237-8

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