The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation

Maria Beatriz Walter Costa; Mark Wernsdorfer; Alexander Kehrer; Markus Voigt; Carina Cundius; Martin Federbusch; Felix Eckelt; Johannes Remmler; Maria Schmidt; Sarah Pehnke; Christiane Gärtner; Markus Wehner; Berend Isermann; Heike Richter; Jörg Telle; Thorsten Kaiser

doi:10.2196/20407

The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation

JMIR Med Inform. 2021 Jun 3;9(6):e20407. doi: 10.2196/20407.

Authors

Maria Beatriz Walter Costa^#^{1

2}, Mark Wernsdorfer^#^{1

2}, Alexander Kehrer³, Markus Voigt⁴, Carina Cundius⁴, Martin Federbusch¹, Felix Eckelt¹, Johannes Remmler¹, Maria Schmidt^{1

2}, Sarah Pehnke¹, Christiane Gärtner^{1

2}, Markus Wehner⁵, Berend Isermann¹, Heike Richter⁵, Jörg Telle³, Thorsten Kaiser¹

Affiliations

¹ Institute of Laboratory Medicine, Clinical Chemistry und Molecular Diagnostics, University of Leipzig Medical Center, Leipzig, Germany.
² Faculty of Medicine, University of Leipzig, Leipzig, Germany.
³ Xantas AG, Leipzig, Germany.
⁴ Information Management, University of Leipzig Medical Center, Leipzig, Germany.
⁵ Muldental Clinics GmbH Non-Profit Company, Hospital Grimma and Wurzen, Grimma, Germany.

^# Contributed equally.

PMID: 34081013
PMCID: PMC8212627
DOI: 10.2196/20407

Abstract

Background: Laboratory results are of central importance for clinical decision making. The time span between availability and review of results by clinicians is crucial to patient care. Clinical decision support systems (CDSS) are computational tools that can identify critical values automatically and help decrease treatment delay.

Objective: With this work, we aimed to implement and evaluate a CDSS that supports health care professionals and improves patient safety. In addition to our experiences, we also describe its main components in a general manner to make it applicable to a wide range of medical institutions and to empower colleagues to implement a similar system in their facilities.

Methods: Technical requirements must be taken into account before implementing a CDSS that performs laboratory diagnostics (labCDSS). These can be planned within the functional components of a reactive software agent, a computational framework for such a CDSS.

Results: We present AMPEL (Analysis and Reporting System for the Improvement of Patient Safety through Real-Time Integration of Laboratory Findings), a labCDSS that notifies health care professionals if a life-threatening medical condition is detected. We developed and implemented AMPEL at a university hospital and regional hospitals in Germany (University of Leipzig Medical Center and the Muldental Clinics in Grimma and Wurzen). It currently runs 5 different algorithms in parallel: hypokalemia, hypercalcemia, hyponatremia, hyperlactatemia, and acute kidney injury.

Conclusions: AMPEL enables continuous surveillance of patients. The system is constantly being evaluated and extended and has the capacity for many more algorithms. We hope to encourage colleagues from other institutions to design and implement similar CDSS using the theory, specifications, and experiences described in this work.

Keywords: clinical decision support system (CDSS); computational architecture; digital health; laboratory medicine; reactive software agent.

©Maria Beatriz Walter Costa, Mark Wernsdorfer, Alexander Kehrer, Markus Voigt, Carina Cundius, Martin Federbusch, Felix Eckelt, Johannes Remmler, Maria Schmidt, Sarah Pehnke, Christiane Gärtner, Markus Wehner, Berend Isermann, Heike Richter, Jörg Telle, Thorsten Kaiser. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 03.06.2021.