Opportunities for genomic clinical decision support interventions

Bridging the Gap in Genomic Implementation: Identifying User Needs for Precision Nephrology

Introduction

Genomic medicine holds transformative potential for personalized nephrology care; however, its clinical integration poses challenges. Automated clinical decision support (CDS) systems in the electronic health record (EHR) offer a promising solution but have shown limited impact. This study aims to glean practical insights into nephrologists' challenges using genomic resources, informing precision nephrology decision support tools.

Methods

We conducted an anonymous electronic survey among US nephrologists from January 19, 2021 to May 19, 2021, guided by the Consolidated Framework for Implementation Research. It assessed practice characteristics, genomic resource utilization, attitudes, perceived knowledge, self-efficacy, and factors influencing genetic testing decisions. Survey links were primarily shared with National Kidney Foundation members.

Results

We analyzed 319 surveys, with most respondents specializing in adult nephrology. Although respondents generally acknowledged the clinical use of genomic resources, varying levels of perceived knowledge and self-efficacy were evident regarding precision nephrology workflows. Barriers to genetic testing included cost/insurance coverage and limited genomics experience.

Conclusion

The study illuminates specific hurdles nephrologists face using genomic resources. The findings are a valuable contribution to genomic implementation research, highlighting the significance of developing tailored interventions to support clinicians in using genomic resources effectively. These findings can guide the future development of CDS systems in the EHR. Addressing unmet informational and workflow support needs can enhance the integration of genomics into clinical practice, advancing personalized nephrology care and improving kidney disease outcomes. Further research should focus on interventions promoting seamless precision nephrology care integration.

Harnessing the power of clinical decision support systems: challenges and opportunities

Clinical decision support systems (CDSSs) are increasingly integrated into healthcare settings to improve patient outcomes, reduce medical errors and enhance clinical efficiency by providing clinicians with evidence-based recommendations at the point of care. However, the adoption and optimisation of these systems remain a challenge. This review aims to provide an overview of the current state of CDSS, discussing their development, implementation, benefits, limitations and future directions. We also explore the potential for enhancing their effectiveness and provide an outlook for future developments in this field. There are several challenges in CDSS implementation, including data privacy concerns, system integration and clinician acceptance. While CDSS have demonstrated significant potential, their adoption and optimisation remain a challenge.

The practice of genomic medicine: A delineation of the process and its governing principles

Genomic medicine, an emerging medical discipline, applies the principles of evolution, developmental biology, functional genomics, and structural genomics within clinical care. Enabling widespread adoption and integration of genomic medicine into clinical practice is key to achieving precision medicine. We delineate a biological framework defining diagnostic utility of genomic testing and map the process of genomic medicine to inform integration into clinical practice. This process leverages collaboration and collective cognition of patients, principal care providers, clinical genomic specialists, laboratory geneticists, and payers. We detail considerations for referral, triage, patient intake, phenotyping, testing eligibility, variant analysis and interpretation, counseling, and management within the utilitarian limitations of health care systems. To reduce barriers for clinician engagement in genomic medicine, we provide several decision-making frameworks and tools and describe the implementation of the proposed workflow in a prototyped electronic platform that facilitates genomic care. Finally, we discuss a vision for the future of genomic medicine and comment on areas for continued efforts.

Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis

We constructed a cost-effectiveness model to assess the clinical and economic value of a CDS alert program that provides pharmacogenomic (PGx) testing results, compared to no alert program in acute coronary syndrome (ACS) and atrial fibrillation (AF), from a health system perspective. We defaulted that 20% of 500,000 health-system members between the ages of 55 and 65 received PGx testing for CYP2C19 (ACS-clopidogrel) and CYP2C9, CYP4F2 and VKORC1 (AF-warfarin) annually. Clinical events, costs, and quality-adjusted life years (QALYs) were calculated over 20 years with an annual discount rate of 3%. In total, 3169 alerts would be fired. The CDS alert program would help avoid 16 major clinical events and 6 deaths for ACS; and 2 clinical events and 0.9 deaths for AF. The incremental cost-effectiveness ratio was $39,477/QALY. A PGx-CDS alert program was cost-effective, under a willingness-to-pay threshold of $100,000/QALY gained, compared to no alert program.

Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network

The complexity of genomic medicine can be streamlined by implementing some form of clinical decision support (CDS) to guide clinicians in how to use and interpret personalized data; however, it is not yet clear which strategies are best suited for this purpose. In this study, we used implementation science to identify common strategies for applying provider-based CDS interventions across six genomic medicine clinical research projects funded by an NIH consortium. Each project's strategies were elicited via a structured survey derived from a typology of implementation strategies, the Expert Recommendations for Implementing Change (ERIC), and follow-up interviews guided by both implementation strategy reporting criteria and a planning framework, RE-AIM, to obtain more detail about implementation strategies and desired outcomes. We found that, on average, the three pharmacogenomics implementation projects used more strategies than the disease-focused projects. Overall, projects had four implementation strategies in common; however, operationalization of each differed in accordance with each study's implementation outcomes. These four common strategies may be important for precision medicine program implementation, and pharmacogenomics may require more integration into clinical care. Understanding how and why these strategies were successfully employed could be useful for others implementing genomic or precision medicine programs in different contexts.

A qualitative study of prevalent laboratory information systems and data communication patterns for genetic test reporting

PURPOSE

The availability of genetic test data within the electronic health record (EHR) is a pillar of the US vision for an interoperable health IT infrastructure and a learning health system. Although EHRs have been highly investigated, evaluation of the information systems used by the genetic labs has received less attention-but is necessary for achieving optimal interoperability. This study aimed to characterize how US genetic testing labs handle their information processing tasks.

METHODS

We followed a qualitative research method that included interviewing lab representatives and a panel discussion to characterize the information flow models.

RESULTS

Ten labs participated in the study. We identified three generic lab system models and their relevant characteristics: a backbone system with additional specialized systems for interpreting genetic results, a brokering system that handles housekeeping and communication, and a single primary system for results interpretation and report generation.

CONCLUSION

Labs have heterogeneous workflows and generally have a low adoption of standards when sending genetic test reports back to EHRs. Core interpretations are often delivered as free text, limiting their computational availability for clinical decision support tools. Increased provision of genetic test data in discrete and standard-based formats by labs will benefit individual and public health.

Integrating Genomic Screening into Primary Care: Provider Experiences Caring for Latino Patients at a Community-Based Health Center

INTRODUCTION

Minority communities have had limited access to advances in genomic medicine. Mayo Clinic and Mountain Park Health Center, a Federally Qualified Health Center in Phoenix, Arizona, partnered to assess the feasibility of offering genomic screening to Latino patients receiving care at a community-based health center. We examined primary care provider (PCP) experiences reporting genomic screening results and integrating those results into patient care.

METHODS

We conducted open-ended, semi-structured interviews with PCPs and other members of the health care team charged with supporting patients who received positive genomic screening results. Interviews were recorded, transcribed, and analyzed thematically.

RESULTS

Of the 500 patients who pursued genomic screening, 10 received results indicating a genetic variant that warranted clinical management. PCPs felt genomic screening was valuable to patients and their families, and that genomic research should strive to include underrepresented minorities. Providers identified multiple challenges integrating genomic sequencing into patient care, including difficulties maintaining patient contact over time; arranging follow-up medical care; and managing results in an environment with limited genetics expertise. Providers also reflected on the ethics of offering genomic sequencing to patients who may not be able to pursue diagnostic testing or follow-up care due to financial constraints.

CONCLUSIONS

Our results highlight the potential benefits and challenges of bringing advances in precision medicine to community-based health centers serving under-resourced populations. By proactively considering patient support needs, and identifying financial assistance programs and patient-referral mechanisms to support patients who may need specialized medical care, PCPs and other health care providers can help to ensure that precision medicine lives up to its full potential as a tool for improving patient care.

Clinical Genomic Sequencing Reports in Electronic Health Record Systems Based on International Standards: Implementation Study

BACKGROUND

To implement standardized machine-processable clinical sequencing reports in an electronic health record (EHR) system, the International Organization for Standardization Technical Specification (ISO/TS) 20428 international standard was proposed for a structured template. However, there are no standard implementation guidelines for data items from the proposed standard at the clinical site and no guidelines or references for implementing gene sequencing data results for clinical use. This is a significant challenge for implementation and application of these standards at individual sites.

OBJECTIVE

This study examines the field utilization of genetic test reports by designing the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) for genomic data elements based on the ISO/TS 20428 standard published as the standard for genomic test reports. The goal of this pilot is to facilitate the reporting and viewing of genomic data for clinical applications. FHIR Genomics resources predominantly focus on transmitting or representing sequencing data, which is of less clinical value.

METHODS

In this study, we describe the practical implementation of ISO/TS 20428 using HL7 FHIR Genomics implementation guidance to efficiently deliver the required genomic sequencing results to clinicians through an EHR system.

RESULTS

We successfully administered a structured genomic sequencing report in a tertiary hospital in Korea based on international standards. In total, 90 FHIR resources were used. Among 41 resources for the required fields, 26 were reused and 15 were extended. For the optional fields, 28 were reused and 21 were extended.

CONCLUSIONS

To share and apply genomic sequencing data in both clinical practice and translational research, it is essential to identify the applicability of the standard-based information system in a practical setting. This prototyping work shows that reporting data from clinical genomics sequencing can be effectively implemented into an EHR system using the existing ISO/TS 20428 standard and FHIR resources.

Deploying Clinical Decision Support for Familial Hypercholesterolemia

Objective

Familial hypercholesterolemia (FH), a prevalent genomic disorder that increases risk of coronary heart disease, remains significantly underdiagnosed. Clinical decision support (CDS) tools have the potential to increase FH detection. We describe our experience in the development and implementation of a genomic CDS for FH at a large academic medical center.

Methods

CDS development and implementation were conducted in four phases: (1) development and validation of an algorithm to identify "possible FH"; (2) obtaining approvals from institutional committees to develop the CDS; (3) development of the initial prototype; and (4) use of an implementation science framework to evaluate the CDS.

Results

The timeline for this work was approximately 4 years; algorithm development and validation occurred from August 2018 to February 2020. During this 4-year period, we engaged with 15 stakeholder groups to build and integrate the CDS, including health care providers who gave feedback at each stage of development. During CDS implementation six main challenges were identified: (1) need for multiple institutional committee approvals; (2) need to align the CDS with institutional knowledge resources; (3) need to adapt the CDS to differing workflows; (4) lack of institutional guidelines for CDS implementation; (5) transition to a new institutional electronic health record (EHR) system; and (6) limitations of the EHR related to genomic medicine.

Conclusion

We identified multiple challenges in different domains while developing CDS for FH and integrating it with the EHR. The lessons learned herein may be helpful in streamlining the development and deployment of CDS to facilitate genomic medicine implementation.

Returning genomic results in a Federally Qualified Health Center: the intersection of precision medicine and social determinants of health

Purpose:

This report describes the return of sequencing results to low-income Latino participants recruited through a Federally Qualified Health Center (FQHC). We describe challenges in returning research results secondary to social determinants of health and present lessons learned to guide future genomic medicine implementation studies in low resource settings.

Methods:

500 Latino adults (76% women) consented to research sequencing for a predetermined panel of actionable genes. Providers and staff from the FQHC were engaged to align processes with the practice and a Community Advisory Board grounded the project in the local community.

Results:

A pathogenic/likely pathogenic variant was present in 10 participants (2%). Challenges in return of results included the time lag (582±53 days) between enrollment and returning actionable results, difficulty reaching participants, missed appointments, low health literacy, lack of health insurance, and reconciling results with limited information on family history. Return of one actionable result was deferred due to acute emotional distress secondary to recent traumatic life events.

Conclusion:

The social determinants of health influence the implementation of genomic medicine in low-income populations in low-resource settings. Considering non-biological factors that contribute to disparities will be necessary to better appreciate how genomic medicine may fit within the context of health equity.

Implementing the VMC Specification to Reduce Ambiguity in Genomic Variant Representation

Current methods used for representing biological sequence variants allow flexibility, which has created redundancy within variant archives and discordance among variant representation tools. While research methodologies have been able to adapt to this ambiguity, strict clinical standards make it difficult to use this data in what would otherwise be useful clinical interventions. We implemented a specification developed by the GA4GH Variant Modeling Collaboration (VMC), which details a new approach to unambiguous representation of variants at the allelic level, as a haplotype, or as a genotype. Our implementation, called the VMC Test Suite (http://vcfclin.org), offers web tools to generate and insert VMC identifiers into a VCF file and to generate a VMC bundle JSON representation of a VCF file or HGVS expression. A command line tool with similar functionality is also introduced. These tools facilitate use of this standard-an important step toward reliable querying of variants and their associated annotations.

The Implementation Chasm Hindering Genome-informed Health Care

The promises of precision medicine are often heralded in the medical and lay literature, but routine integration of genomics in clinical practice is still limited. While the "last mile' infrastructure to bring genomics to the bedside has been demonstrated in some healthcare settings, a number of challenges remain - both in the receptivity of today's health system and in its technical and educational readiness to respond to this evolution in care. To improve the impact of genomics on health and disease management, we will need to integrate both new knowledge and new care processes into existing workflows. This change will be onerous and time-consuming, but hopefully valuable to the provision of high quality, economically feasible care worldwide.

Genomic Information for Clinicians in the Electronic Health Record: Lessons Learned From the Clinical Genome Resource Project and the Electronic Medical Records and Genomics Network

Genomic knowledge is being translated into clinical care. To fully realize the value, it is critical to place credible information in the hands of clinicians in time to support clinical decision making. The electronic health record is an essential component of clinician workflow. Utilizing the electronic health record to present information to support the use of genomic medicine in clinical care to improve outcomes represents a tremendous opportunity. However, there are numerous barriers that prevent the effective use of the electronic health record for this purpose. The electronic health record working groups of the Electronic Medical Records and Genomics (eMERGE) Network and the Clinical Genome Resource (ClinGen) project, along with other groups, have been defining these barriers, to allow the development of solutions that can be tested using implementation pilots. In this paper, we present “lessons learned” from these efforts to inform future efforts leading to the development of effective and sustainable solutions that will support the realization of genomic medicine.

Implementation and obstacles of pharmacogenetics in clinical practice: An international survey

AIMS

Eight years ago, a paper-based survey was administered during the World Pharma 2010 meeting, asking about the challenges of implementing pharmacogenetics (PGx) in clinical practice. The data collected at the time gave an idea about the progress of this implementation and what still needs to be done. Since then, although there have been major initiatives to push PGx forward, PGx clinical implementation may still be facing different challenges in different parts of the world. Our aim was therefore to distribute a follow-up international survey in electronic format to elucidate an overview on the current stage of implementation, acceptance and challenges of PGx in academic institutions around the world.

METHODS

This is an online anonymous LimeSurvey-based study launched on 11 November 2018. Survey questions were adapted from the initially published manuscript in 2010. An extensive web search for worldwide scientists potentially involved in PGx research resulted in a total of 1973 names. Countries were grouped based on the Human Development Index.

RESULTS

There were 204 respondents from 43 countries. Despite the wide availability of PGx tests, the consistently positive attitude towards their applications and advances in the field, progress of the clinical implementation of PGx still faces many challenges all around the globe.

CONCLUSIONS

Clinical implementation of PGx started over a decade ago but there is a gap in progress around the globe and discrepancies between the challenges reported by different countries, despite some challenges being universal. Further studies on ways to overcome these challenges are warranted.

Physician Communication of Genomic Results in a Diagnostic Odyssey Case Series

BACKGROUND AND OBJECTIVES

The availability of whole genome sequencing (WGS) is increasing in clinical care, and WGS is a promising tool in diagnostic odyssey cases. Physicians' ability to effectively communicate genomic information with patients, however, is unclear. In this multiperspective study, we assessed physicians' communication of patient genome sequencing information in a diagnostic odyssey case series.

METHODS

We evaluated physician communication of genome sequencing results in the context of an ongoing study of the utility of WGS for the diagnosis of rare and idiopathic diseases. A modified version of the Medical Communication Competence Scale was used to compare patients' ratings of their physicians' communication of general medical information to communication of genome sequencing information. Physician self-ratings were also compared with patient ratings.

RESULTS

A total of 47 patients, parents, and physicians across 11 diagnostic odyssey cases participated. In 6 of 11 cases (54%), the patient respondent rated the physician's communication of genome sequencing information as worse than that of general medical information. In 9 of 11 cases (82%), physician self-ratings of communication of genome sequencing information were worse than the patient respondent's rating. Identification of a diagnosis via WGS was positively associated with physician self-ratings (P = .021) but was not associated with patient respondent ratings (P = .959).

CONCLUSIONS

These findings reveal that even in diagnostic odyssey cases, in which genome sequencing may be clinically beneficial, physicians may not be well-equipped to communicate genomic information to patients. Future studies may benefit from multiperspective approaches to assessing and understanding physician-patient communication of genome-sequencing information.

Barriers to the identification of familial hypercholesterolemia among primary care providers

Familial hypercholesterolemia (FH) is severely underdiagnosed in the USA. Primary care providers are well-positioned to identify FH cases; however, universal FH screening is not routinely implemented in practice. The aim of the present study was to identify perceived barriers to FH screening among primary care physicians in Minnesota. A questionnaire assessed FH screening practices, knowledge, and perceived barriers to FH screening. The questionnaire, sent electronically to internal and family medicine physicians in Minnesota (N = 1932) yielded a conservative estimated response rate of 9% (N = 173). Although 92% of participants reported themselves responsible for identifying individuals with FH, 30% did not routinely perform screening in practice. Only 50% of participants were able to correctly identify the risk of FH to first-degree relatives of individuals with FH. Challenges incorporating lipid and family history data was the most frequently endorsed barrier to FH screening (34%). A majority of participants endorsed a clinical decision support system that flags individuals at high risk for FH (62%) and an algorithm with cholesterol levels and lipid disorders (56%) as means of facilitating FH screening. Although the generalizability of the findings is unknown, the results underscore the need for increased provider education regarding FH and suggest an FH screening strategy incorporating a clinical decision support system, screening algorithm, and support from other healthcare providers.

A New Era, New Strategies: Education and Communication Strategies to Manage Greater Access to Genomic Information

As next-generation genomic sequencing, including whole-genome sequencing information, becomes more common in research, clinical, and public health contexts, there is a need for comprehensive communication strategies and education approaches to prepare patients and clinicians to manage this information and make informed decisions about its use, and nowhere is that imperative more pronounced than when genomic sequencing is applied to newborns. Unfortunately, in-person counseling is unlikely to be applicable or cost-effective when parents obtain genomic risk information directly via the Internet. As a rule, communication strategies should match how people are accessing health information. Today, many people can obtain health information in a variety of settings, including through direct-to-consumer services, via websites, and through other digital channels or settings. In response to these changes, new communication strategies need to be considered. Adopting a comprehensive communication model means understanding the multiple levels of influence experienced by parents and the clinicians who serve them. In addition, applying communication-science principles can help in addressing some key challenges to effectively communicating genomic information to parents.

How Primary Care Providers Talk to Patients about Genome Sequencing Results: Risk, Rationale, and Recommendation

BACKGROUND

Genomics will play an increasingly prominent role in clinical medicine.

OBJECTIVE

To describe how primary care physicians (PCPs) discuss and make clinical recommendations about genome sequencing results.

DESIGN

Qualitative analysis.

PARTICIPANTS

PCPs and their generally healthy patients undergoing genome sequencing.

APPROACH

Patients received clinical genome reports that included four categories of results: monogenic disease risk variants (if present), carrier status, five pharmacogenetics results, and polygenic risk estimates for eight cardiometabolic traits. Patients' office visits with their PCPs were audio-recorded, and summative content analysis was used to describe how PCPs discussed genomic results.

KEY RESULTS

For each genomic result discussed in 48 PCP-patient visits, we identified a "take-home" message (recommendation), categorized as continuing current management, further treatment, further evaluation, behavior change, remembering for future care, or sharing with family members. We analyzed how PCPs came to each recommendation by identifying 1) how they described the risk or importance of the given result and 2) the rationale they gave for translating that risk into a specific recommendation. Quantitative analysis showed that continuing current management was the most commonly coded recommendation across results overall (492/749, 66%) and for each individual result type except monogenic disease risk results. Pharmacogenetics was the most common result type to prompt a recommendation to remember for future care (94/119, 79%); carrier status was the most common type prompting a recommendation to share with family members (45/54, 83%); and polygenic results were the most common type prompting a behavior change recommendation (55/58, 95%). One-fifth of recommendation codes associated with monogenic results were for further evaluation (6/24, 25%). Rationales for these recommendations included patient context, family context, and scientific/clinical limitations of sequencing.

CONCLUSIONS

PCPs distinguish substantive differences among categories of genome sequencing results and use clinical judgment to justify continuing current management in generally healthy patients with genomic results.

Leveraging the Learning Health Care Model to Improve Equity in the Age of Genomic Medicine

To fully achieve the goals of a genomics-enabled learning health care system, purposeful efforts to understand and reduce health disparities and improve equity of care are essential. This paper highlights three major challenges facing genomics-enabled learning health care systems, as they pertain to ancestrally diverse populations: inequality in the utility of genomic medicine; lack of access to pharmacogenomics in clinical care; and inadequate incorporation of social and environmental data into the electronic health care record (EHR). We advance a framework that can not only be used to directly improve care for all within the learning health system, but can also be used to focus on the needs to address racial and ethnic health disparities and improve health equity.

Understanding the Bioinformatics Challenges of Integrating Genomics into Healthcare

Genomic data is paving the way towards personalized healthcare. By unveiling genetic disease-contributing factors, genomic data can aid in the detection, diagnosis, and treatment of a wide range of complex diseases. Integrating genomic data into healthcare is riddled with a wide range of challenges spanning social, ethical, legal, educational, economic, and technical aspects. Bioinformatics is a core integration aspect presenting an overwhelming number of unaddressed challenges. In this paper we tackle the fundamental bioinformatics integration concerns including: genomic data generation, storage, representation, and utilization in conjunction with clinical data. We divide the bioinformatics challenges into a series of seven intertwined integration aspects spanning the areas of informatics, knowledge management, and communication. For each aspect, we provide a detailed discussion of the current research directions, outstanding challenges, and possible resolutions. This paper seeks to help narrow the gap between the genomic applications, which are being predominantly utilized in research settings, and the clinical adoption of these applications.

Compatibility of Family History Cancer Guidelines With Meaningful Use Standards

Purpose

To evaluate the potential of implementing established family cancer guidelines as clinical decision support within meaningful use (MU)-compliant health information technology systems. Methods We conducted a systematic analysis of cancer guidelines involving family health history (FHx) published before 2015. By comparing existing cancer guideline statements to current MU FHx standard requirements, we determined whether the cancer guideline statements could be implemented as clinical decision support. For guidelines that could not implemented, we determined the primary reasons for incompatibility.

Results

A total of 531 statements from 55 guidelines published by 11 different organizations were reviewed and analyzed. Overall, 18% to 66% of guideline statements could or could not be implemented in MU-compliant health information technology systems, depending on which MU standard was used. Health Level Seven (HL7) models performed better than SNOMED models. Implementability of guideline statements varied by cancer type and guideline organizations. The greatest deficiencies in implementability of statements were largely a result of the fact that MU standards required only first-degree relatives and that FHx terms used in guidelines statements were ambiguous.

Conclusion

FHx cancer guidelines and MU-based systems vary widely and are mostly incompatible. We identified sources of incompatibility and made recommendations that could improve the implementability of FHx cancer guidelines. Our findings and recommendations can enhance the use of established FHx cancer risk guidelines in routine clinical workflows.

A Review of Recent Advances in Translational Bioinformatics: Bridges from Biology to Medicine

Objectives: To highlight and provide insights into key developments in translational bioinformatics between 2014 and 2016. Methods: This review describes some of the most influential bioinformatics papers and resources that have been published between 2014 and 2016 as well as the national genome sequencing initiatives that utilize these resources to routinely embed genomic medicine into healthcare. Also discussed are some applications of the secondary use of patient data followed by a comprehensive view of the open challenges and emergent technologies. Results: Although data generation can be performed routinely, analyses and data integration methods still require active research and standardization to improve streamlining of clinical interpretation. The secondary use of patient data has resulted in the development of novel algorithms and has enabled a refined understanding of cellular and phenotypic mechanisms. New data storage and data sharing approaches are required to enable diverse biomedical communities to contribute to genomic discovery. Conclusion: The translation of genomics data into actionable knowledge for use in healthcare is transforming the clinical landscape in an unprecedented way. Exciting and innovative models that bridge the gap between clinical and academic research are set to open up the field of translational bioinformatics for rapid growth in a digital era.

Genomic decision support needs in pediatric primary care

Clinical genome and exome sequencing can diagnose pediatric patients with complex conditions that often require follow-up care with multiple specialties. The American Academy of Pediatrics emphasizes the role of the medical home and the primary care pediatrician in coordinating care for patients who need multidisciplinary support. In addition, the electronic health record (EHR) with embedded clinical decision support is recognized as an important component in providing care in this setting. We interviewed 6 clinicians to assess their experience caring for patients with complex and rare genetic findings and hear their opinions about how the EHR currently supports this role. Using these results, we designed a candidate EHR clinical decision support application mock-up and conducted formative exploratory user testing with 26 pediatric primary care providers to capture opinions on its utility in practice with respect to a specific clinical scenario. Our results indicate agreement that the functionality represented by the mock-up would effectively assist with care and warrants further development.

Pharmacogenomics in the clinic

After decades of discovery, inherited variations have been identified in approximately 20 genes that affect about 80 medications and are actionable in the clinic. And some somatically acquired genetic variants direct the choice of 'targeted' anticancer drugs for individual patients. Current efforts that focus on the processes required to appropriately act on pharmacogenomic variability in the clinic are moving away from discovery and towards implementation of an evidenced-based strategy for improving the use of medications, thereby providing a cornerstone for precision medicine.

A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine

Introduction:

In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework.

Framework:

We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the “Clinical Mendeliome” as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the “Archival Value Criterion” as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework.

Conclusion:

The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other ‘-omics’ fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.

How to know when physicians are ready for genomic medicine

Despite perceptions to the contrary, physicians are as prepared for genomic medicine as they are for other medical innovations; educational initiatives and support from genetics specialists can enhance clinical practice.

The genomic CDS sandbox: An assessment among domain experts

Genomics is a promising tool that is becoming more widely available to improve the care and treatment of individuals. While there is much assertion, genomics will most certainly require the use of clinical decision support (CDS) to be fully realized in the routine clinical setting. The National Human Genome Research Institute (NHGRI) of the National Institutes of Health recently convened an in-person, multi-day meeting on this topic. It was widely recognized that there is a need to promote the innovation and development of resources for genomic CDS such as a CDS sandbox. The purpose of this study was to evaluate a proposed approach for such a genomic CDS sandbox among domain experts and potential users. Survey results indicate a significant interest and desire for a genomic CDS sandbox environment among domain experts. These results will be used to guide the development of a genomic CDS sandbox.

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.

Physician perspectives of CYP2C19 and clopidogrel drug-gene interaction active clinical decision support alerts

OBJECTIVE

To determine if physicians find clinical decision support alerts for pharmacogenomic drug-gene interactions useful and assess their perceptions of usability aspects that impact usefulness.

MATERIALS AND METHODS

52 physicians participated in an online simulation and questionnaire involving a prototype alert for the clopidogrel and CYP2C19 drug-gene interaction.

RESULTS

Only 4% of participants stated they would override the alert. 92% agreed that the alerts were useful. 87% found the visual interface appropriate, 91% felt the timing of the alert was appropriate and 75% were unfamiliar with the specific drug-gene interaction. 80% of providers preferred the ability to order the recommended medication within the alert. Qualitative responses suggested that supplementary information is important, but should be provided as external links, and that the utility of pharmacogenomic alerts depends on the broader ecosystem of alerts.

PRINCIPAL CONCLUSIONS

Pharmacogenomic alerts would be welcomed by many physicians, can be built with minimalist design principles, and are appropriately placed at the end of the prescribing process. Since many physicians lack familiarity with pharmacogenomics but have limited time, information and educational resources within the alert should be carefully selected and presented in concise ways.

Discussion of "Combining Health Data Uses to Ignite Health System Learning"

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Combining Health Data Uses to Ignite Health System Learning" written by John D. Ainsworth and Iain E. Buchan [1]. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Ainsworth and Buchan. In subsequent issues the discussion can continue through letters to the editor. With these comments on the paper "Combining Health Data Uses to Ignite Health System Learning", written by John D. Ainsworth and Iain E. Buchan [1], the journal seeks to stimulate a broad discussion on new ways for combining data sources for the reuse of health data in order to identify new opportunities for health system learning. An international group of experts has been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.

CSER and eMERGE: current and potential state of the display of genetic information in the electronic health record

OBJECTIVE

Clinicians' ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS).

MATERIALS AND METHODS

The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement.

RESULTS

There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information enters the EHR through multiple laboratory sources and through clinician notes. For laboratory-based data, the source laboratory was the main determinant of the location of genetic information in the EHR. The highest priority recommendation was to address the need to implement CDS mechanisms and content for decision support for medically actionable genetic information.

CONCLUSION

Heterogeneity of genetic information flow and importance of source laboratory, rather than clinical content, as a determinant of information representation are major barriers to using genetic information optimally in patient care. Greater effort to develop interoperable systems to receive and consistently display genetic and/or genomic information and alert clinicians to genomic-dependent improvements to clinical care is recommended.

Global implementation of genomic medicine: We are not alone

Around the world, innovative genomic-medicine programs capitalize on singular capabilities arising from local health care systems, cultural or political milieus, and unusual selected risk alleles or disease burdens. Such individual efforts might benefit from the sharing of approaches and lessons learned in other locales. The U.S. National Human Genome Research Institute and the National Academy of Medicine recently brought together 25 of these groups to compare projects, to examine the current state of implementation and desired near-term capabilities, and to identify opportunities for collaboration that promote the responsible practice of genomic medicine. Efforts to coalesce these groups around concrete but compelling signature projects should accelerate the responsible implementation of genomic medicine in efforts to improve clinical care worldwide.

Perspectives on genetic and genomic technologies in an academic medical center: the duke experience

In this age of personalized medicine, genetic and genomic testing is expected to become instrumental in health care delivery, but little is known about its actual implementation in clinical practice.

METHODS

We surveyed Duke faculty and healthcare providers to examine the extent of genetic and genomic testing adoption. We assessed providers' use of genetic and genomic testing options and indications in clinical practice, providers' awareness of pharmacogenetic applications, and providers' opinions on returning research-generated genetic test results to participants. Most clinician respondents currently use family history routinely in their clinical practice, but only 18 percent of clinicians use pharmacogenetics. Only two respondents correctly identified the number of drug package inserts with pharmacogenetic indications. We also found strong support for the return of genetic research results to participants. Our results demonstrate that while Duke healthcare providers are enthusiastic about genomic technologies, use of genomic tools outside of research has been limited. Respondents favor return of research-based genetic results to participants, but clinicians lack knowledge about pharmacogenetic applications. We identified challenges faced by this institution when implementing genetic and genomic testing into patient care that should inform a policy and education agenda to improve provider support and clinician-researcher partnerships.

The need for clinical decision support integrated with the electronic health record for the clinical application of whole genome sequencing information

Whole genome sequencing (WGS) is rapidly approaching widespread clinical application. Technology advancements over the past decade, since the first human genome was decoded, have made it feasible to use WGS for clinical care. Future advancements will likely drive down the price to the point wherein WGS is routinely available for care. However, were this to happen today, most of the genetic information available to guide clinical care would go unused due to the complexity of genetics, limited physician proficiency in genetics, and lack of genetics professionals in the clinical workforce. Furthermore, these limitations are unlikely to change in the future. As such, the use of clinical decision support (CDS) to guide genome-guided clinical decision-making is imperative. In this manuscript, we describe the barriers to widespread clinical application of WGS information, describe how CDS can be an important tool for overcoming these barriers, and provide clinical examples of how genome-enabled CDS can be used in the clinical setting.

A proposed clinical decision support architecture capable of supporting whole genome sequence information

Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine.

Information technology and precision medicine

OBJECTIVES

To provide oncology nurses with an overview of clinical decision support (CDS) and explore opportunities for genomic CDS interventions. The nation's first personalized cancer decision support tool, My Cancer Genome, is presented as an exemplar of a novel CDS tool.

DATA SOURCES

Published nursing and medical literature and the internet for an exemplar.

CONCLUSION

CDS is a sophisticated health information technology that can translate and integrate genomic knowledge with patient information, providing recommendations at the point of care.

IMPLICATIONS FOR NURSING PRACTICE

Nurses, as key stakeholders, must have an understanding of CDS interventions and their application to fully participate in all stages of CDS development and implementation.

The intelligent use and clinical benefits of electronic medical records in multiple sclerosis

Electronic medical records (EMRs) are being quickly adopted in clinics around the world. This advancement can greatly enhance the clinical care of patients with multiple sclerosis (MS) by providing formats that allow easier review of medical documents and more structured avenues to store relevant information. MS clinicians should be involved with implementing and updating EMRs at their institutions to ensure EMR formats that benefit MS clinics. EMRs also provide opportunities for research studies of MS to access detailed, longitudinal data of MS disease course that would otherwise be difficult to collect.

Imputation and quality control steps for combining multiple genome-wide datasets

The electronic MEdical Records and GEnomics (eMERGE) network brings together DNA biobanks linked to electronic health records (EHRs) from multiple institutions. Approximately 51,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R² (estimated correlation between the imputed and true genotypes), and the relationship between allelic R² and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2) were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.

A Template for Authoring and Adapting Genomic Medicine Content in the eMERGE Infobutton Project

The Electronic Medical Records and Genomics (eMERGE) Network is a national consortium that is developing methods and best practices for using the electronic health record (EHR) for genomic medicine and research. We conducted a multi-site survey of information resources to support integration of pharmacogenomics into clinical care. This work aimed to: (a) characterize the diversity of information resource implementation strategies among eMERGE institutions; (b) develop a master template containing content topics of important for genomic medicine (as identified by the DISCERN-Genetics tool); and (c) assess the coverage of content topics among information resources developed by eMERGE institutions. Given that a standard implementation does not exist and sites relied on a diversity of information resources, we identified a need for a national effort to efficiently produce sharable genomic medicine resources capable of being accessed from the EHR. We discuss future areas of work to prepare institutions to use infobuttons for distributing standardized genomic content.

Clinical decision support for whole genome sequence information leveraging a service-oriented architecture: a prototype

Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time.

Preemptive clinical pharmacogenetics implementation: current programs in five US medical centers

Although the field of pharmacogenetics has existed for decades, practioners have been slow to implement pharmacogenetic testing in clinical care. Numerous publications describe the barriers to clinical implementation of pharmacogenetics. Recently, several freely available resources have been developed to help address these barriers. In this review, we discuss current programs that use preemptive genotyping to optimize the pharmacotherapy of patients. Array-based preemptive testing includes a large number of relevant pharmacogenes that impact multiple high-risk drugs. Using a preemptive approach allows genotyping results to be available prior to any prescribing decision so that genomic variation may be considered as an inherent patient characteristic in the planning of therapy. This review describes the common elements among programs that have implemented preemptive genotyping and highlights key processes for implementation, including clinical decision support.

Developing genomic knowledge bases and databases to support clinical management: current perspectives

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

Pragmatic and Ethical Challenges of Incorporating the Genome into the Electronic Medical Record

Recent successes in the use of gene sequencing for patient care highlight the potential of genomic medicine. For genomics to become a part of usual care, pertinent elements of a patient's genomic test must be communicated to the most appropriate care providers. Electronic medical records may serve as a useful tool for storing and disseminating genomic data. Yet, the structure of existing EMRs and the nature of genomic data pose a number of pragmatic and ethical challenges in their integration. Through a review of the recent genome-EMR integration literature, we explore concrete examples of these challenges, categorized under four key questions: What data will we store? How will we store it? How will we use it? How will we protect it? We conclude that genome-EMR integration requires a rigorous, multi-faceted and interdisciplinary approach of study. Problems facing the field are numerous, but few are intractable.

The future of genomic testing in primary care: the changing face of personalized medicine

Primary care is recognized worldwide as a key component for improving health outcomes in the population. At the same time, healthcare systems are rapidly changing with increasing expectations from technological advances. Genomics is a major driver in changing how medicine is being practiced; however, the importance for primary care has been under-appreciated. Strategically implementing genomics in a way that accounts for the unique characteristics of the primary care context is essential. In this perspective, we present important areas that we believe are critical in consideration of both the future of genomic medicine and primary healthcare delivery.

A survey of informatics approaches to whole-exome and whole-genome clinical reporting in the electronic health record

PURPOSE

Genome-scale clinical sequencing is being adopted more broadly in medical practice. The National Institutes of Health developed the Clinical Sequencing Exploratory Research (CSER) program to guide implementation and dissemination of best practices for the integration of sequencing into clinical care. This study describes and compares the state of the art of incorporating whole-exome and whole-genome sequencing results into the electronic health record, including approaches to decision support across the six current CSER sites.

METHODS

The CSER Medical Record Working Group collaboratively developed and completed an in-depth survey to assess the communication of genome-scale data into the electronic health record. We summarized commonalities and divergent approaches.

RESULTS

Despite common sequencing platform (Illumina) adoptions, there is a great diversity of approaches to annotation tools and workflow, as well as to report generation. At all sites, reports are human-readable structured documents available as passive decision support in the electronic health record. Active decision support is in early implementation at two sites.

CONCLUSION

The parallel efforts across CSER sites in the creation of systems for report generation and integration of reports into the electronic health record, as well as the lack of standardized approaches to interfacing with variant databases to create active clinical decision support, create opportunities for cross-site and vendor collaborations.