Fast and frugal trees: translating population-based pharmacogenomics to medication prioritization

Will Precision Medicine Meet Digital Health? A Systematic Review of Pharmacogenomics Clinical Decision Support Systems Used in Clinical Practice

Digital health, an emerging scientific domain, attracts increasing attention as artificial intelligence and relevant software proliferate. Pharmacogenomics (PGx) is a core component of precision/personalized medicine driven by the overarching motto "the right drug, for the right patient, at the right dose, and the right time." PGx takes into consideration patients' genomic variations influencing drug efficacy and side effects. Despite its potentials for individually tailored therapeutics and improved clinical outcomes, adoption of PGx in clinical practice remains slow. We suggest that e-health tools such as clinical decision support systems (CDSSs) can help accelerate the PGx, precision/personalized medicine, and digital health emergence in everyday clinical practice worldwide. Herein, we present a systematic review that examines and maps the PGx-CDSSs used in clinical practice, including their salient features in both technical and clinical dimensions. Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and research of the literature, 29 relevant journal articles were included in total, and 19 PGx-CDSSs were identified. In addition, we observed 10 technical components developed mostly as part of research initiatives, 7 of which could potentially facilitate future PGx-CDSSs implementation worldwide. Most of these initiatives are deployed in the United States, indicating a noticeable lack of, and the veritable need for, similar efforts globally, including Europe.

eHealth: past and future perspectives

eHealth is an umbrella term incorporating any area that combines healthcare and technology to improve efficiencies and reduce costs. The ultimate goal of eHealth is to rationalize treatment selection to improve patient safety and outcomes. Telemedicine, first used in the 1920s, is the oldest form of eHealth. The introduction of broadband Internet, followed by wireless technologies, has allowed an explosion of mHealth applications within this field. Wearable technologies, such as smartwatches, are now being used for diagnostics and patient monitoring. Challenges remain to develop reusable Clinical Decision Support systems that will streamline the flow of data from clinical laboratories to point of care. This review explores the history of eHealth, and describes some of the remaining integration and implementation challenges.

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making

Background:

Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps.

Methods:

We combined Change Management with a three-tier information technology architecture to stimulate CDS app development.

Results:

A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app.

Conclusion:

Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens.

Medical information needs to be structured in a way that it can be used in a time-constrained environment. This project looked at the process of creating mobile applications (apps), to help medical professionals rapidly apply new knowledge to better treat patients. We developed a novel system that allowed medical professionals to have a leading role in development. With the input from a pharmacist we created an app to deal with pharmacy and patient-related decisions surrounding newly available anticancer pills. Other medical professionals could also use this method to make apps to provide information with relevance to their medical decisions.