Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development

Abstract

BackgroundPharmacogenomic clinical decision support systems (CDSS) have the potential to help overcome some of the barriers for translating pharmacogenomic knowledge into clinical routine. Before developing a prototype it is crucial for developers to know which pharmacogenomic CDSS features and user-system interactions have yet been developed, implemented and tested in previous pharmacogenomic CDSS efforts and if they have been successfully applied. We address this issue by providing an overview of the designs of user-system interactions of recently developed pharmacogenomic CDSS.MethodsWe searched PubMed for pharmacogenomic CDSS published between January 1, 2012 and November 15, 2016. Thirty-two out of 118 identified articles were summarized and included in the final analysis. We then compared the designs of user-system interactions of the 20 pharmacogenomic CDSS we had identified.ResultsAlerts are the most widespread tools for physician-system interactions, but need to be implemented carefully to prevent alert fatigue and avoid liabilities. Pharmacogenomic test results and override reasons stored in the local EHR might help communicate pharmacogenomic information to other internal care providers. Integrating patients into user-system interactions through patient letters and online portals might be crucial for transferring pharmacogenomic data to external health care providers. Inbox messages inform physicians about new pharmacogenomic test results and enable them to request pharmacogenomic consultations. Search engines enable physicians to compare medical treatment options based on a patient’s genotype.ConclusionsWithin the last 5 years, several pharmacogenomic CDSS have been developed. However, most of the included articles are solely describing prototypes of pharmacogenomic CDSS rather than evaluating them. To support the development of prototypes further evaluation efforts will be necessary. In the future, pharmacogenomic CDSS will likely include prediction models to identify patients who are suitable for preemptive genotyping.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-017-0480-y) contains supplementary material, which is available to authorized users.

Nature of adverse events with opioids in hospitalised patients: a post-hoc analysis of three patient record review studies

“…Finally, a CDSS could also be used to identify patients who might be suitable for pre-emptive genotyping, which involves metabolic testing prior to prescribing. 42 Patients with high levels of pain despite using high doses of pain medication or patients who experience severe side effects while using common dosing schedules may especially benefit from such an intervention. 43 …”

MIRACUM: Medical Informatics in Research and Care in University Medicine

“…In the MIRACUM conceptual phase, we have already performed an in-depth analysis of the clinician experiences and attitudes towards genome-guided therapy support [ 46 ] as well as analysis of activities, processes and IT solutions at all MIRACUM sites [ 47 ] to gain a comprehensive understanding of the requirements and the processes involved in MTBs across these institutions. Further, a comprehensive literature review was performed to learn from experiences of previous research towards the integration of pharmacogenomics testing and molecular-guided therapy decisions in clinical care environments [ 48 ]. To cope with the complexity of the generated tumor sequencing data all MIRACUM sites have commenced in efforts to implement multi-disciplinary MTBs.…”

Pharmacogenetics and Psychiatric Care: A Review and Commentary

“…Incorporating pharmacogenomics into clinical decision support systems (CDSS) and translating knowledge into practice is challenging. These systems will help the clinician by transferring pharmacogenomics data to other health care providers and by informing physicians of patient’s results enabling them to request consultations based on the patient’s genotype 37 .…”