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. It was indicated, however, that genetics is one of many characteristics that influence dose adjustments during pregnancy. This study motivates future research to help obstetric healthcare providers tailor drug dose to individual patients based upon models integrating multiple patient characteristics, including genetics.

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). There was general agreement (91%) that new content is needed for patients and providers specific to genomics, and that while aspects of this content could be shared across institutions there remain site-specific needs (73% in agreement). CONCLUSION: This work identifies a need for the improved access to and expansion of information resources to support genomic medicine, and opportunities for content developers and EHR vendors to partner with institutions to develop needed resources, and streamline their use - such as a central content site in multiple modalities while implementing approaches to allow for site-specific customization.

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. OBJECTIVES: To integrate genomic knowledge resources using the HL7 infobutton standard. Two tactics to achieve this objective were: (1) creating an HL7-compliant search interface for ClinGen, and (2) proposing guidance for genomic resources on achieving HL7 Infobutton standard accessibility and compliance. METHODS: We built a search interface utilizing OpenInfobutton, an open source reference implementation of the HL7 Infobutton standard. ClinGen resources were assessed for readiness towards HL7 compliance. Finally, based upon our experiences we provide recommendations for publishers seeking to achieve HL7 compliance. RESULTS: Eight genomic resources and two sub-resources were integrated with the ClinGen search engine via OpenInfobutton and the HL7 infobutton standard. Resources we assessed have varying levels of readiness towards HL7-compliance. Furthermore, we found that adoption of standard terminologies used by EHR systems is the main gap to achieve compliance. CONCLUSION: Genomic resources can be integrated with EHR systems via the HL7 Infobutton standard using OpenInfobutton. Full compliance of genomic resources with the Infobutton standard would further enhance interoperability with EHR systems.

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. Responses from focus group sessions were transcribed, coded and analyzed by two team members. Notification mechanisms and information resources preferred by participants from our first phase of focus groups were incorporated into scenarios and the design of a software prototype for delivering GS reports. The goal of our second phase of focus group, to gain input on the prototype software design, was accomplished through conducting task walkthroughs with GS reporting scenarios. Preferences for notification, content and consultation from genetics specialists appeared to depend upon familiarity with scenarios for ordering and delivering GS reports. Despite familiarity with some aspects of the scenarios we proposed, many of our participants agreed that they would likely seek consultation from a genetics specialist after viewing the test reports. In addition, participants offered design and content recommendations. Findings illustrated a need to support customized notification approaches, user-specific information, and access to genetics specialists with GS reports. These design principles can be incorporated into software applications that deliver GS reports. Our user-centered approach to conduct this assessment and the specific input we received from clinicians may also be relevant to others working on similar projects.

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 meeting outcome underscored the need to address a number of important policy and technical considerations in order to realize the potential of personalized or precision medicine in actual clinical contexts.

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.

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. Previous literature has established theoretical models for PGx CDS implementation and discussed a number of anticipated real-world challenges. However, work detailing actual PGx CDS implementation experiences has been limited. Anticipated challenges include data storage and management, system integration, physician acceptance, and more. METHODS: In this study, we analyzed the experiences of ten members of the Electronic Medical Records and Genomics (eMERGE) Network, and one affiliate, in their attempts to implement PGx CDS. We examined the resulting PGx CDS system characteristics and conducted a survey to understand the unanticipated implementation challenges sites encountered. RESULTS: Ten sites have successfully implemented at least one PGx CDS rule in the clinical setting. The majority of sites elected to create an Omic Ancillary System (OAS) to manage genetic and genomic data. All sites were able to adapt their existing CDS tools for PGx knowledge. The most common and impactful delays were not PGx-specific issues. Instead, they were general IT implementation problems, with top challenges including team coordination/communication and staffing. The challenges encountered caused a median total delay in system go-live of approximately two months. CONCLUSIONS: These results suggest that barriers to PGx CDS implementations are generally surmountable. Moreover, PGx CDS implementation may not be any more difficult than other healthcare IT projects of similar scope, as the most significant delays encountered were not unique to genomic medicine. These are encouraging results for any institution considering implementing a PGx CDS tool, and for the advancement of genomic medicine.

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.

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. outpatient practices were invited to watch a video and complete a survey about a new biobank initiative. We used: Chi-square to assess the relationship between willingness to join the biobank and participant characteristics, other potentially mutable attitudes and opinions, and trust in the UMD. We also used t-test to assess the relationship with trust in medical research. We also prioritize proposed actions to improve attitudes and opinions about joining biobanks according to perceived responsiveness. RESULTS: 169 participants completed the study, 51% of whom indicated a willingness to join the biobank. Willingness to join the biobank was not associated with age, gender, race, or education but was associated with respondent comfort sharing samples and clinical information, concerns related to confidentiality, potential for misuse of information, trust in UMD, and perceived health benefit. In ranked order, potential actions we surveyed that might alleviate some of these concerns include: increase chances to learn more about the biobank, increase opportunities to be updated, striving to put community concerns first, including involving community members as leaders of biobank research, and involving community members in decision making. CONCLUSIONS: This study identified several attitudes and opinions that influence decisions to join a biobank, including many concerns that could potentially be addressed by engaging community members. We also demonstrate our method of prioritizing ways to improve attitudes and opinions about joining a biobank according to perceived responsiveness.

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. Twenty-two physicians completed the study. The proportion of physicians that saw a relative advantage to using PGx-CDS was 83% at the start and 94% at the conclusion of our study. Physicians used semi-active alerts 74-88% of the time. There was no association between previous experience with, awareness of, and belief in a relative advantage of using PGx-CDS and improved uptake. The proportion of physicians reporting confidence in their prescribing decisions decreased significantly after using the prototype PGx-CDS system (p=0.02). Despite decreases in confidence, physicians perceived a relative advantage to using PGx-CDS, viewed semi-active alerts on most occasions, and more frequently changed doses toward doses supported by published evidence. Specifically, sixty-five percent of physicians reduced their dosing, significantly for capecitabine (p=0.002) and mercaptopurine/thioguanine (p=0.03). These findings suggest a need to improve our prototype such that PGx CDS content is more useful and delivered in a way that improves physician's confidence in their prescribing decisions. The greatest increases in communication effectiveness and clinical impact of PGx-CDS are likely to be realized through continued focus on content, content delivery, and tailoring to physician characteristics.

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. We propose a business process model and notation (BPMN) representation of this process for a Translational Pharmacogenomics Project being implemented at the University of Maryland Medical Center, so that personalized medicine program implementers can identify areas to improve genetic testing processes. We found that the current process could be improved to reduce input errors, better inform and notify clinicians about the implications of certain genetic tests, and make results more easily understood. We demonstrate our use of BPMN to improve this important clinical process for CYP2C19 genetic testing in patients undergoing invasive treatment of coronary heart disease.

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. However, optimal design of further genetic studies is hindered by uncertain overall heritability of DILI. This is a common problem for low-prevalence pharmacological traits, since it is difficult to obtain clinical outcome data in families. Here we estimated the heritability (h(2)) of DILI from case-control genome-wide single nucleotide polymorphism data using a method based on random effect models. We estimated the proportion of h(2) captured by common SNPs for DILI to be between 0.3 and 0.5. For co-amoxiclav induced DILI, chromosome 6 explained part of the heritability, indicating additional contributions from common variants yet to be found. We performed simulations to assess the robustness of the h(2) estimate with limited sample size under low prevelance, a condition typical to studies on idiosyncratic pharmacological traits. Our findings suggest that common variants outside of HLA contribute to DILI susceptability; therefore, it is valuable to conduct further GWAS with expanded case collection.

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. OBJECTIVES: The study objectives were to: (1) evaluate an early prototype, commercial CPOE system with PGx-CDS alerts in a simulated environment, (2) identify potential improvements to the system user interface, and (3) understand the contexts under which PGx knowledge embedded in an electronic health record is useful to prescribers. METHODS: Using a mixed methods approach, we presented seven cardiologists and three oncologists with five hypothetical clinical case scenarios. Each scenario featured a drug for which a gene encoding drug metabolizing enzyme required consideration of dosage adjustment. We used Morae(®) to capture comments and on-screen movements as participants prescribed each drug. In addition to PGx-CDS alerts, 'Infobutton(®)' and 'Evidence' icons provided participants with clinical knowledge resources to aid decision-making. RESULTS: Nine themes emerged. Five suggested minor improvements to the CPOE user interface; two suggested presenting PGx information through PGx-CDS alerts using an 'Infobutton' or 'Evidence' icon. The remaining themes were strong recommendations to provide succinct, relevant guidelines and dosing recommendations of phenotypic information from credible and trustworthy sources; any more information was overwhelming. Participants' median rating of PGx-CDS system usability was 2 on a Likert scale ranging from 1 (strongly agree) to 7 (strongly disagree). CONCLUSIONS: Usability evaluation results suggest that participants considered PGx information important for improving prescribing decisions; and that they would incorporate PGx-CDS when information is presented in relevant and useful ways.

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. Now with a working template for PAP3, implementation of other drug-gene pairs is in process. Lessons learned as described in this article may prove useful to other medical centers as they implement pharmacogenetics into patient care, a critical step in the pathway to personalized and genomic medicine.

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. We surveyed 101 General Internal Medicine physicians from the Icahn School of Medicine at Mount Sinai (ISMMS). The majority were residency program trainees (~88%). Prior to enlisting into CLIPMERGE PGx, most physicians were aware of and had used decision support aids. Few physicians, however, were aware of and had used genome-guided prescribing. The majority of physicians viewed decision support aids and genotype data as being useful for making prescribing decisions. Most physicians had not heard of, but were willing to use, PGT services and felt comfortable interpreting PGT results. Most physicians were comfortable with technology. Physicians who perceived genotype data to be useful in making prescribing decisions, had more positive attitudes toward adopting genome-guided prescribing through CDS. Our findings suggest that internal medicine physicians have a deficit in their familiarity and comfort interpreting and using genomic information. This has reinforced the importance of gathering feedback and guidance from our enrolled physicians when designing genome-guided CDS and the importance of prioritizing genomic medicine education at our 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. 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.

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. This was an analysis of a qualitative data set from interviews of eight cancer genetic counselors, recruited from three institutions. Genetic counselors at each site were interviewed using a semi-structured, open-ended questionnaire. A selective coding approach was used to determine major themes associated with genetic counseling information needs for communicating risk. We generated a model for understanding categories of genetic counseling information needs to support risk communication activities. Common activities for risk communication included risk assessment and tailoring communication. Categories of information needs included: (a) clinical patient characteristics, (b) social and cognitive patient characteristics and (c) patient motivation and goals for the genetic counseling session. A logical next step is for this model to inform the design of software systems for pre-visit patient planning and delivering just-in-time educational information to facilitate cancer risk communication activities.

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. Depending on the complexity of an algorithm, interim refinements may be required to improve measurement methods. Therefore, we develop an evaluation framework that incorporates both measurement and demonstration studies. We evaluate a baseline EHR phenotyping algorithm for drug induced liver injury (DILI) developed in collaboration with electronic Medical Records Genomics (eMERGE) network participants. We conduct a measurement study and report qualitative (i.e., perceptions of evaluation approach effectiveness) and quantitative (i.e., inter-rater reliability) measures. We also conduct a demonstration study and report qualitative (i.e., appropriateness of results) and quantitative (i.e., positive predictive value) measures. Given results from the measurement study, our evaluation approach underwent multiple changes including the addition of laboratory value visualization and an expanded review of clinical notes. Results from the demonstration study informed changes to our algorithm. For example, given the goal of eMERGE to identify patients who may have a genetic susceptibility to DILI, we excluded overdose patients.

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." This article discusses barriers to implementing genomics applications and current progress toward overcoming barriers, describes lessons learned from early experiences of institutions engaged in personalized medicine and provides example areas for translational bioinformatics research inquiry.