Decision support in diabetes Care: the challenge of supporting patients in their daily living using a mobile glucose predictor

Pérez Gandía, María Carmen; García Sáez, Gema; Subías, David; Rodríguez Herrero, Agustín; Gómez Aguilera, Enrique J.; Rigla Cros, Mercedes y Hernando Pérez, María Elena (2018). Decision support in diabetes Care: the challenge of supporting patients in their daily living using a mobile glucose predictor. "Journal of Diabetes Science and Technology", v. 12 (n. 2); pp. 243-250. ISSN 1932-2968. https://doi.org/10.1177/1932296818761457.

Descripción

Título: Decision support in diabetes Care: the challenge of supporting patients in their daily living using a mobile glucose predictor
Autor/es:
  • Pérez Gandía, María Carmen
  • García Sáez, Gema
  • Subías, David
  • Rodríguez Herrero, Agustín
  • Gómez Aguilera, Enrique J.
  • Rigla Cros, Mercedes
  • Hernando Pérez, María Elena
Tipo de Documento: Artículo
Título de Revista/Publicación: Journal of Diabetes Science and Technology
Fecha: 2018
Volumen: 12
Materias:
Palabras Clave Informales: Decision support; diabetes; m-health; glucose prediction
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Background: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-face visits. This work presents a decision support system (DSS), based on glucose prediction, to assist patients in a mobile environment. Methods: The system’s impact on therapeutic corrective actions has been evaluated in a randomized crossover pilot study focused on interprandial periods. Twelve people with type 1 diabetes treated with insulin pump participated in two phases: In the experimental phase (EP) patients used the DSS to modify initial corrective decisions in presence of hypoglycemia or hyperglycemia events. In the control phase (CP) patients were asked to follow decisions without knowing the glucose prediction. A telemedicine platform allowed participants to register monitoring data and decisions and allowed endocrinologists to supervise data at the hospital. The study period was defined as a postprediction (PP) time window. Results: After knowing the glucose prediction, participants modified the initial decision in 20% of the situations. No statistically significant differences were found in the PP Kovatchev’s risk index change (–1.23 ± 11.85 in EP vs –0.56 ± 6.06 in CP). Participants had a positive opinion about the DSS with an average score higher than 7 in a usability questionnaire. Conclusion: The DSS had a relevant impact in the participants’ decision making while dealing with T1DM and showed a high confidence of patients in the use of glucose prediction.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
Gobierno de EspañaPI14/00109, PI14/00010Sin especificarSin especificarSin especificar

Más información

ID de Registro: 49990
Identificador DC: http://oa.upm.es/49990/
Identificador OAI: oai:oa.upm.es:49990
Identificador DOI: 10.1177/1932296818761457
URL Oficial: http://journals.sagepub.com/doi/10.1177/1932296818761457
Depositado por: Memoria Investigacion
Depositado el: 07 May 2018 15:27
Ultima Modificación: 07 May 2018 15:27
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