Integrating genomic-based clinical decision support into electronic health records

Examination and diagnosis of electronic patient records and their associated ethics: a scoping literature review

Background

Electronic patient record (EPR) technology is a key enabler for improvements to healthcare service and management. To ensure these improvements and the means to achieve them are socially and ethically desirable, careful consideration of the ethical implications of EPRs is indicated. The purpose of this scoping review was to map the literature related to the ethics of EPR technology. The literature review was conducted to catalogue the prevalent ethical terms, to describe the associated ethical challenges and opportunities, and to identify the actors involved. By doing so, it aimed to support the future development of ethics guidance in the EPR domain.

Methods

To identify journal articles debating the ethics of EPRs, Scopus, Web of Science, and PubMed academic databases were queried and yielded 123 eligible articles. The following inclusion criteria were applied: articles need to be in the English language; present normative arguments and not solely empirical research; include an abstract for software analysis; and discuss EPR technology.

Results

The medical specialty, type of information captured and stored in EPRs, their use and functionality varied widely across the included articles. Ethical terms extracted were categorised into clusters ‘privacy’, ‘autonomy’, ‘risk/benefit’, ‘human relationships’, and ‘responsibility’. The literature shows that EPR-related ethical concerns can have both positive and negative implications, and that a wide variety of actors with rights and/or responsibilities regarding the safe and ethical adoption of the technology are involved.

Conclusions

While there is considerable consensus in the literature regarding EPR-related ethical principles, some of the associated challenges and opportunities remain underdiscussed. For example, much of the debate is presented in a manner more in keeping with a traditional model of healthcare and fails to take account of the multidimensional ensemble of factors at play in the EPR era and the consequent need to redefine/modify ethical norms to align with a digitally-enabled health service. Similarly, the academic discussion focuses predominantly on bioethical values. However, approaches from digital ethics may also be helpful to identify and deliberate about current and emerging EPR-related ethical concerns.

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.

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

Aim: Fast and frugal decision trees (FFTs) can simplify clinical decision making by providing a heuristic approach to contextual guidance. We wanted to use FFTs for pharmacogenomic knowledge translation at point-of-care. Materials & Methods: The Pharmacogenomics for Every Nation Initiative (PGENI), an international nonprofit organization, collects data on regional polymorphisms as a predictor of metabolism for individual drugs and dosages. We advanced FFTs to work with PGENI pharmacogenomic data to produce medication recommendations that are accurate, transparent and straightforward to automate. Results: By streamlining medication selection processes in the PGENI workflow, information technology applications can now be deployed. Conclusion: We developed a decision tree approach that can translate pharmacogenomic data to provide up-to-date recommended care for populations based on their medication-specific markers.

Mining electronic health records: towards better research applications and clinical care

Clinical data describing the phenotypes and treatment of patients represents an underused data source that has much greater research potential than is currently realized. Mining of electronic health records (EHRs) has the potential for establishing new patient-stratification principles and for revealing unknown disease correlations. Integrating EHR data with genetic data will also give a finer understanding of genotype-phenotype relationships. However, a broad range of ethical, legal and technical reasons currently hinder the systematic deposition of these data in EHRs and their mining. Here, we consider the potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality.

Improving oncology outcomes through targeted therapeutics will require electronic delivery systems

Typically, chemotherapy selection takes into account patient demographic data, including disease symptoms, family history, environmental factors and concurrent medications. Although validated and approved genomics tests are available for targeted therapeutics, a major challenge facing healthcare is the ability to process the genomic data in the patient’s context and to return clinically interpretable dosing guidance to the physician in a realistic time frame. Delivery of these targeted therapeutics, made possible by clinical decision support systems connected to an electronic health record may help drive both the acceptance and adaptation of an electronic health record system, as well as provide personalized information at point-of-care, as part of the routine workflow. The realization of targeted therapeutics will depend on the concerted efforts of stakeholder groups as they address political, ethical, socioeconomical and technical challenges to achieve personalized medicine adoption through real-world implementation.