Clinical Decision Support systems: A step forward in establishing the clinical laboratory as a decision maker hubA CDS system protocol implementation in the clinical laboratory.
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 sy...
| Autores: | , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Instituto de Investigación Biomédica y Sanitaria de Alicante (ISABIAL) |
| Repositorio: | r-ISABIAL. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica y Sanitaria de Alicante |
| OAI Identifier: | oai:isabial.fundanetsuite.com:p10044 |
| Acceso en línea: | https://isabial.portalinvestigacion.com/publicaciones10044 |
| Access Level: | acceso abierto |
| Palabra clave: | Clinical Decision Support Systems Clinical laboratory Electronic health records Quality improvement Operational Management Artificial intelligence |
| Sumario: | 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. |
|---|