CONSIGNELA: A multidisciplinary patient-centered project to improve drug prescription comprehension and execution in elderly people and parkinsonian patients
2017
Abstract Many older patients and patients with Parkinson’s disease (PD) do not respect medication prescriptions. Non-adherence is caused by several factors among which three play an important role: Treatment complexity, cognitive decline, and patient-provider communication. This article presents an ongoing multidisciplinary project, the CONSIGNELA project, which adopts a patient-centered approach for improving medication adherence in these patients. The first objective of the project is to identify the best way to communicate medication prescriptions with tablets and touch-screen devices. The second objective is to improve medication adherence by creating a collaborative application (app) designed both for older and PD patients and for healthcare professionals in charge of them. Two solutions are combined: A cognitive and a technological solutions. The cognitive solution consists in studying in real time older and PD patients while consulting and executing prescriptions presented in different formats to select the most efficient one. The technological solution aims to improve collaboration between health professionals and patients by developing System of Systems (SoS). The research model used in the project includes three phases. Only the results of phase 1 are presented in the article. A research app, CONSIGNELA-Appli-R was programmed to analyze patient cognitive processes while consulting a prescription on a tablet. A pilot study was carried out with young adults to test it. It confirmed a facilitating effect of table format. In parallel, the prototype of a second app, CONSIGNELA-Appli-P, for patients and healthcare providers was developed. It is based on an SoS architecture connecting a virtual pillbox, a Multi-Agent System (MAS) and a knowledge platform. The virtual pillbox is used by patients and providers to improve mutual understanding of medication prescriptions. The MAS provides agents that extract and analyze indicators, actions and information resulting from the interaction between patients and virtual pillboxes. All the information is capitalized and stored in the knowledge platform. Providers can receive charts and dashboards showing information about the following of the medication regimen, for instance, if patients are following it correctly or not.
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