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Clinical Decision Support systems: A step forward in establishing the clinical laboratory as a decision maker hub - A CDS system protocol implementation in the clinical laboratory

Authors :
Emilio Flores
José María Salinas
Álvaro Blasco
Maite López-Garrigós
Ruth Torreblanca
Rosa Carbonell
Laura Martínez-Racaj
Maria Salinas
Source :
Computational and Structural Biotechnology Journal, Vol 22, Iss , Pp 27-31 (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Background: New tools for health information technology have been developed in recent times, such as Clinical Decision Support (CDS) systems, which are any digital solutions designed to help healthcare professionals when making clinical decisions. The study aimed to show how we have adopted a CDS system in the San Juan de Alicante Clinical Laboratory and facilitate the implementation of our protocol in other clinical laboratories. We have user experience and the motivation to improve healthcare tools. The improvement, measurement, and monitoring of interventions and laboratory tests has been our motto for years. Materials and methods: A descriptive research was conducted. All stages in the design of the project are as follows: 1. Set up a multidisciplinary workgroup. 2. Review patients’ data. 3. Identify relevant data from main sources. 4. Design the likely outcomes. 5. Define a complete integration scenario. 6. Monitor and track the impact. To set up this protocol, two new software systems were implemented in our laboratory: AlinIQ CDS v8.2 as Rule Engine, and AlinIQ AIP Integrated Platform v1.6 as Business Intelligence (BI) tool. Results: Our protocol shows the workflow and actions that can be done with a CDS system and also how it could be integrated with other monitoring systems, as well as some examples of KPIs and their outcomes. Conclusions: CDS could be a great strategic asset for clinical laboratories to improve the integration of care, optimize the use of laboratory tests, and add more clinical value to physicians in the interpretation of results.

Details

Language :
English
ISSN :
20010370
Volume :
22
Issue :
27-31
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.b13e34482ae4c4bbd8730f2c9eb24e2
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2023.08.006