Value of Genetics-informed Drug Dosing Guidance in Pregnant Women: A Needs Assessment with Obstetric Healthcare Providers at Johns Hopkins.

In order to better understand the potential value of genetics-informed drug dose guidance to obstetric healthcare providers at Johns Hopkins we administered a web-based needs assessment survey. The survey included questions about: 1) experience with adjusting drug doses during pregnancy; 2) comfort prescribing medications to pregnant women with chronic conditions; 3) awareness and use of genetics-informed dosing guidance; and 4) perceived value of access to services to provide genetics-informed dosing guidance. Among thirty-one respondents, 81% indicated an interest in access to genetics-informed drug dose guidance, particularly a mobile or electronic health record (EHR) application.

User-centered design of multi-gene sequencing panel reports for clinicians.

The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center.

Practical considerations for implementing genomic information resources. Experiences from eMERGE and CSER.

Objectives: To understand opinions and perceptions on the state of information resources specifically targeted to genomics, and approaches to delivery in clinical practice.

Methods: We conducted a survey of genomic content use and its clinical delivery from representatives across eight institutions in the electronic Medical Records and Genomics (eMERGE) network and two institutions in the Clinical Sequencing Exploratory Research (CSER) consortium in 2014.

Results: Eleven responses representing distinct projects across ten sites showed heterogeneity in how content is being delivered, with provider-facing content primarily delivered via the electronic health record (EHR) (n=10), and paper/pamphlets as the leading mode for patient-facing content (n=9).

Integrating Genomic Resources with Electronic Health Records using the HL7 Infobutton Standard.

Background: The Clinical Genome Resource (ClinGen) Electronic Health Record (EHR) Workgroup aims to integrate ClinGen resources with EHRs. A promising option to enable this integration is through the Health Level Seven (HL7) Infobutton Standard. EHR systems that are certified according to the US Meaningful Use program provide HL7-compliant infobutton capabilities, which can be leveraged to support clinical decision-making in genomics.

Harnessing next-generation informatics for personalizing medicine: a report from AMIA's 2014 Health Policy Invitational Meeting.

The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting to develop recommendations for updates to current policies and to establish an informatics research agenda for personalizing medicine. In particular, the meeting focused on discussing informatics challenges related to personalizing care through the integration of genomic or other high-volume biomolecular data with data from clinical systems to make health care more efficient and effective. This report summarizes the findings (n = 6) and recommendations (n = 15) from the policy meeting, which were clustered into 3 broad areas: (1) policies governing data access for research and personalization of care; (2) policy and research needs for evolving data interpretation and knowledge representation; and (3) policy and research needs to ensure data integrity and preservation.

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.

Practical considerations in genomic decision support: The eMERGE experience.

Background: Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presence of well-characterized drug-gene interactions. Clinical Decision Support (CDS) is an ideal avenue by which to implement PGx at the bedside.

Prioritizing Approaches to Engage Community Members and Build Trust in Biobanks: A Survey of Attitudes and Opinions of Adults within Outpatient Practices at the University of Maryland.

Background: Achieving high participation of communities representative of all sub-populations is needed in order to ensure broad applicability of biobank study findings. This study aimed to understand potentially mutable attitudes and opinions commonly correlated with biobank participation in order to inform approaches to promote participation in biobanks.

Methods: Adults from two University of Maryland (UMD) Faculty Physicians, Inc.

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.

Making pharmacogenomic-based prescribing alerts more effective: A scenario-based pilot study with physicians.

To facilitate personalized drug dosing (PDD), this pilot study explored the communication effectiveness and clinical impact of using a prototype clinical decision support (CDS) system embedded in an electronic health record (EHR) to deliver pharmacogenomic (PGx) information to physicians. We employed a conceptual framework and measurement model to access the impact of physician characteristics (previous experience, awareness, relative advantage, perceived usefulness), technology characteristics (methods of implementation-semi-active/active, actionability-low/high) and a task characteristic (drug prescribed) on communication effectiveness (usefulness, confidence in prescribing decision), and clinical impact (uptake, prescribing intent, change in drug dosing). Physicians performed prescribing tasks using five simulated clinical case scenarios, presented in random order within the prototype PGx-CDS system.

Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support.

This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS), prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx). We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII). The survey also includes items to measure physicians' characteristics (awareness, experience, and perceived usefulness), attitudes about personal genome testing (PGT) services, and comfort using technology.

Using Workflow Modeling to Identify Areas to Improve Genetic Test Processes in the University of Maryland Translational Pharmacogenomics Project.

Delivering genetic test results to clinicians is a complex process. It involves many actors and multiple steps, requiring all of these to work together in order to create an optimal course of treatment for the patient. We used information gained from focus groups in order to illustrate the current process of delivering genetic test results to clinicians.

Estimating heritability of drug-induced liver injury from common variants and implications for future study designs.

Recent genome-wide association studies identified certain human leukocyote antigen (HLA) alleles as the major risk factors of drug-induced liver injuries (DILI). While these alleles often cause large relative risk, their predictive values are quite low due to low prevalence of idiosyncratic DILI. Finding additional risk factors is important for precision medicine.

Usability evaluation of pharmacogenomics clinical decision support aids and clinical knowledge resources in a computerized provider order entry system: a mixed methods approach.

Background: Pharmacogenomics (PGx) is positioned to have a widespread impact on the practice of medicine, yet physician acceptance is low. The presentation of context-specific PGx information, in the form of clinical decision support (CDS) alerts embedded in a computerized provider order entry (CPOE) system, can aid uptake. Usability evaluations can inform optimal design, which, in turn, can spur adoption.

Implementation of pharmacogenetics: the University of Maryland Personalized Anti-platelet Pharmacogenetics Program.

Despite a substantial evidence base, implementation of pharmacogenetics into routine patient care has been slow due to a number of non-trivial practical barriers. We implemented a Personalized Anti-platelet Pharmacogenetics Program (PAP3) for cardiac catheterization patients at the University of Maryland Medical Center and the Baltimore Veterans Administration Medical Center Patients' are offered CYP2C19 genetic testing, which is performed in our Clinical Laboratory Improvement Amendment (CLIA)-certified Translational Genomics Laboratory. Results are returned within 5 hr along with clinical decision support that includes interpretation of results and prescribing recommendations for anti-platelet therapy based on the Clinical Pharmacogenetics Implementation Consortium guidelines.

Practical choices for infobutton customization: experience from four sites.

Context-aware links between electronic health records (EHRs) and online knowledge resources, commonly called "infobuttons" are being used increasingly as part of EHR "meaningful use" requirements. While an HL7 standard exists for specifying how the links should be constructed, there is no guidance on what links to construct. Collectively, the authors manage four infobutton systems that serve 16 institutions.

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.

Cancer genetic counselor information needs for risk communication: a qualitative evaluation of interview transcripts.

Personalized medicine is a model of healthcare that is predictive, personalized, preventive and participatory ("P4 Medicine"). Genetic counselors are an ideal group to study when designing tools to support cancer P4 Medicine activities more broadly. The goal for this work was to gain a better understanding of the information cancer genetic counselors seek from their patients to facilitate effective information exchange for discussing risk.

Evaluation considerations for EHR-based phenotyping algorithms: A case study for drug-induced liver injury.

Developing electronic health record (EHR) phenotyping algorithms involves generating queries that run across the EHR data repository. Algorithms are commonly assessed within demonstration studies. There remains, however, little emphasis on assessing the precision and accuracy of measurement methods during the evaluation process.

Personalized medicine: challenges and opportunities for translational bioinformatics.

Personalized medicine can be defined broadly as a model of healthcare that is predictive, personalized, preventive and participatory. Two US President's Council of Advisors on Science and Technology reports illustrate challenges in personalized medicine (in a 2008 report) and in use of health information technology (in a 2010 report). Translational bioinformatics is a field that can help address these challenges and is defined by the American Medical Informatics Association as "the development of storage, analytic and interpretive methods to optimize the transformation of increasing voluminous biomedical data into proactive, predictive, preventative and participatory health.

Disseminating context-specific access to online knowledge resources within electronic health record systems.

Clinicians' patient care information needs are frequent and largely unmet. Online knowledge resources are available that can help clinicians meet these information needs. Yet, significant barriers limit the use of these resources within the clinical workflow.

A collaborative approach to developing an electronic health record phenotyping algorithm for drug-induced liver injury.

Objective: To describe a collaborative approach for developing an electronic health record (EHR) phenotyping algorithm for drug-induced liver injury (DILI).

Methods: We analyzed types and causes of differences in DILI case definitions provided by two institutions-Columbia University and Mayo Clinic; harmonized two EHR phenotyping algorithms; and assessed the performance, measured by sensitivity, specificity, positive predictive value, and negative predictive value, of the resulting algorithm at three institutions except that sensitivity was measured only at Columbia University.

Results: Although these sites had the same case definition, their phenotyping methods differed by selection of liver injury diagnoses, inclusion of drugs cited in DILI cases, laboratory tests assessed, laboratory thresholds for liver injury, exclusion criteria, and approaches to validating phenotypes.

Developing a prototype system for integrating pharmacogenomics findings into clinical practice.

Findings from pharmacogenomics (PGx) studies have the potential to be applied to individualize drug therapy to improve efficacy and reduce adverse drug events. Researchers have identified factors influencing uptake of genomics in medicine, but little is known about the specific technical barriers to incorporating PGx into existing clinical frameworks. We present the design and development of a prototype PGx clinical decision support (CDS) system that builds on existing clinical infrastructure and incorporates semi-active and active CDS.

Deriving rules and assertions from pharmacogenomics knowledge resources in support of patient drug metabolism efficacy predictions.

Objective: Pharmacogenomics evaluations of variability in drug metabolic processes may be useful for making individual drug response predictions. We present an approach to deriving 'phenotype scores' based on existing pharmacogenomics knowledge and a patient's genomics data. Pharmacogenomics plays an important role in the bioactivation of tamoxifen, a prodrug administered to patients for breast cancer treatment.