A Decision Support System for Diabetes Chronic Care Models Based on General Practitioner Engagement and EHR Data Sharing.
Cloud computing
decision support system
electronic health records
general practice
type 2 diabetes
Journal
IEEE journal of translational engineering in health and medicine
ISSN: 2168-2372
Titre abrégé: IEEE J Transl Eng Health Med
Pays: United States
ID NLM: 101623153
Informations de publication
Date de publication:
2020
2020
Historique:
received:
13
05
2020
revised:
16
09
2020
accepted:
10
10
2020
entrez:
5
11
2020
pubmed:
6
11
2020
medline:
6
11
2020
Statut:
epublish
Résumé
Objective Decision support systems (DSS) have been developed and promoted for their potential to improve quality of health care. However, there is a lack of common clinical strategy and a poor management of clinical resources and erroneous implementation of preventive medicine. Methods To overcome this problem, this work proposed an integrated system that relies on the creation and sharing of a database extracted from GPs' Electronic Health Records (EHRs) within the Netmedica Italian (NMI) cloud infrastructure. Although the proposed system is a pilot application specifically tailored for improving the chronic Type 2 Diabetes (T2D) care it could be easily targeted to effectively manage different chronic-diseases. The proposed DSS is based on EHR structure used by GPs in their daily activities following the most updated guidelines in data protection and sharing. The DSS is equipped with a Machine Learning (ML) method for analyzing the shared EHRs and thus tackling the high variability of EHRs. A novel set of T2D care-quality indicators are used specifically to determine the economic incentives and the T2D features are presented as predictors of the proposed ML approach. Results The EHRs from 41237 T2D patients were analyzed. No additional data collection, with respect to the standard clinical practice, was required. The DSS exhibited competitive performance (up to an overall accuracy of 98%±2% and macro-recall of 96%±1%) for classifying chronic care quality across the different follow-up phases. The chronic care quality model brought to a significant increase (up to 12%) of the T2D patients without complications. For GPs who agreed to use the proposed system, there was an economic incentive. A further bonus was assigned when performance targets are achieved. Conclusions The quality care evaluation in a clinical use-case scenario demonstrated how the empowerment of the GPs through the use of the platform (integrating the proposed DSS), along with the economic incentives, may speed up the improvement of care.
Identifiants
pubmed: 33150095
doi: 10.1109/JTEHM.2020.3031107
pii: 3000112
pmc: PMC7605604
doi:
Types de publication
Journal Article
Langues
eng
Pagination
3000112Références
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