Development and use of active clinical decision support for preemptive pharmacogenomics

Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC)

INTRODUCTION

Reporting and sharing pharmacogenetic test results across clinical laboratories and electronic health records is a crucial step toward the implementation of clinical pharmacogenetics, but allele function and phenotype terms are not standardized. Our goal was to develop terms that can be broadly applied to characterize pharmacogenetic allele function and inferred phenotypes.

MATERIALS AND METHODS

Terms currently used by genetic testing laboratories and in the literature were identified. The Clinical Pharmacogenetics Implementation Consortium (CPIC) used the Delphi method to obtain a consensus and agree on uniform terms among pharmacogenetic experts.

RESULTS

Experts with diverse involvement in at least one area of pharmacogenetics (clinicians, researchers, genetic testing laboratorians, pharmacogenetics implementers, and clinical informaticians; n = 58) participated. After completion of five surveys, a consensus (>70%) was reached with 90% of experts agreeing to the final sets of pharmacogenetic terms.

DISCUSSION

The proposed standardized pharmacogenetic terms will improve the understanding and interpretation of pharmacogenetic tests and reduce confusion by maintaining consistent nomenclature. These standard terms can also facilitate pharmacogenetic data sharing across diverse electronic health care record systems with clinical decision support.Genet Med 19 2, 215-223.

[Acute lymphoblastic leukemia: a genomic perspective]

In parallel to the human genome sequencing project, several technological platforms have been developed that let us gain insight into the genome structure of human entities, as well as evaluate their usefulness in the clinical approach of the patient. Thus, in acute lymphoblastic leukemia (ALL), the most common pediatric malignancy, genomic tools promise to be useful to detect patients at high risk of relapse, either at diagnosis or during treatment (minimal residual disease), and they also increase the possibility to identify cases at risk of adverse reactions to chemotherapy. Therefore, the physician could offer patient-tailored therapeutic schemes. A clear example of the useful genomic tools is the identification of single nucleotide polymorphisms (SNPs) in the thiopurine methyl transferase (TPMT) gene, where the presence of two null alleles (homozygous or compound heterozygous) indicates the need to reduce the dose of mercaptopurine by up to 90% to avoid toxic effects which could lead to the death of the patient. In this review, we provide an overview of the genomic perspective of ALL, describing some strategies that contribute to the identification of biomarkers with potential clinical application.

Educational strategies to enable expansion of pharmacogenomics-based care

PURPOSE

The current state of pharmacogenomics education for pharmacy students and practitioners is discussed, and resources and strategies to address persistent challenges in this area are reviewed.

SUMMARY

Consensus-based pharmacist competencies and guidelines have been published to guide pharmacogenomics knowledge attainment and application in clinical practice. Pharmacogenomics education is integrated into various pharmacy school courses and, increasingly, into Pharm.D. curricula in the form of required standalone courses. Continuing-education programs and a limited number of postgraduate training opportunities are available to practicing pharmacists. For colleges and schools of pharmacy, identifying the optimal structure and content of pharmacogenomics education remains a challenge; insufficient numbers of faculty members with pharmacogenomics expertise and the inadequate availability of practice settings for experiential education are other limiting factors. Strategies for overcoming those challenges include providing early exposure to pharmacogenomics through foundational courses and incorporating pharmacogenomics into practice-based therapeutics courses and introductory and advanced pharmacy practice experiences. For practitioner education, online resources, clinical decision support-based tools, and certificate programs can be used to supplement structured postgraduate training in pharmacogenomics. Recently published data indicate successful use of "shared curricula" and participatory education models involving opportunities for learners to undergo personal genomic testing.

CONCLUSION

The pharmacy profession has taken a leadership role in expanding student and practitioner education to meet the demand for increased pharmacist involvement in precision medicine initiatives. Effective approaches to teaching pharmacogenomics knowledge and driving its appropriate application in clinical practice are increasingly available.

Integrating Pharmacogenomics into Clinical Practice: Promise vs Reality

BACKGROUND

Limited information is available regarding primary care clinicians' response to pharmacogenomic clinical decision support (PGx-CDS) alerts integrated in the electronic health record.

METHODS

In February 2015, 159 clinicians in the Mayo Clinic primary care practice were sent e-mail surveys to understand their perspectives on the implementation and use of pharmacogenomic testing in their clinical practice. Surveys assessed how the clinicians felt about pharmacogenomics and whether they thought electronic PGx-CDS alerts were useful. Information was abstracted on the number of CDS alerts the clinicians received between October 2013 and the date their survey was returned. CDS alerts were grouped into 2 categories: the alert recommended caution using the prescription, or the alert recommended an alternate prescription. Finally, data were abstracted regarding whether the clinician changed their prescription in response to the alert recommendation.

RESULTS

The survey response rate was 57% (n = 90). Overall, 52% of the clinicians did not expect to use or did not know whether they would use pharmacogenomic information in their future prescribing practices. Additionally, 53% of the clinicians felt that the alerts were confusing, irritating, frustrating, or that it was difficult to find additional information. Finally, only 30% of the clinicians that received a CDS alert changed their prescription to an alternative medication.

CONCLUSIONS

Our results suggest a lack of clinician comfort with integration of pharmacogenomic data into primary care. Further efforts to refine PGx-CDS alerts to make them as useful and user-friendly as possible are needed to improve clinician satisfaction with these new tools.

Multidisciplinary model to implement pharmacogenomics at the point of care

Purpose

Despite potential clinical benefits, implementation of pharmacogenomics (PGx) faces many technical and clinical challenges. These challenges can be overcome by a comprehensive and systematic implementation model.

Methods

The development and implementation of PGx was organized into eight interdependent components addressing resources, governance, clinical practice, education, testing, knowledge translation, clinical decision support (CDS) and maintenance. Several aspects of the implementation were assessed including adherence to the model, production of PGx-CDS interventions and access to educational resources.

Results

Between 8/2012 and 6/2015, 21 specific drug-gene interactions were reviewed and 18 of them were implemented in the electronic medical record as PGx-CDS interventions. There was complete adherence to the model with variable production time (98 to 392 days) and delay time (0 to 148 days). The implementation impacted approximately 1247 unique providers and 3788 unique patients. A total of 11 educational resources complementary to the drug-gene interactions and 5 modules specific for pharmacists were developed and implemented.

Conclusion

A comprehensive operational model can support PGx implementation into routine prescribing. Institutions can use this model as a roadmap to support similar efforts. However, we also identified challenges that will require major multidisciplinary and multi-institutional efforts to make PGx a universal reality.

Comparison of genome sequencing and clinical genotyping for pharmacogenes

We compared whole exome sequencing (WES, n = 176 patients) and whole genome sequencing (WGS, n = 68) and clinical genotyping (DMET array-based approach) for interrogating 13 genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. We focused on 127 CPIC important variants: 103 single nucleotide variations (SNV), 21 insertion/deletions (Indel), HLA-B alleles, and two CYP2D6 structural variations. WES and WGS provided interrogation of nonoverlapping sets of 115 SNV/Indels with call rate >98%. Among 68 loci interrogated by both WES and DMET, 64 loci (94.1%, confidence interval [CI]: 85.6-98.4%) showed no discrepant genotyping calls. Among 66 loci interrogated by both WGS and DMET, 63 loci (95.5%, CI: 87.2-99.0%) showed no discrepant genotyping calls. In conclusion, even without optimization to interrogate pharmacogenetic variants, WES and WGS displayed potential to provide reliable interrogation of most pharmacogenes and further validation of genome sequencing in a clinical lab setting is warranted.

Individualized Hydrocodone Therapy Based on Phenotype, Pharmacogenetics, and Pharmacokinetic Dosing

OBJECTIVES

(1) To quantify hydrocodone (HC) and hydromorphone (HM) metabolite pharmacokinetics with pharmacogenetics in CYP2D6 ultra-rapid metabolizer (UM), extensive metabolizer (EM), and poor metabolizer (PM) metabolizer phenotypes. (2) To develop an HC phenotype-specific dosing strategy for HC that accounts for HM production using clinical pharmacokinetics integrated with pharmacogenetics for patient safety.

SETTING

In silico clinical trial simulation.

PARTICIPANTS

Healthy white men and women without comorbidities or history of opioid, or any other drug or nutraceutical use, age 26.3±5.7 years (mean±SD; range, 19 to 36 y) and weight 71.9±16.8 kg (range, 50 to 108 kg).

MAIN OUTCOME MEASURES

CYP2D6 phenotype-specific HC clinical pharmacokinetic parameter estimates and phenotype-specific percentages of HM formed from HC.

RESULTS

PMs had lower indices of HC disposition compared with UMs and EMs. Clearance was reduced by nearly 60% and the t1/2 was increased by about 68% compared with EMs. The canonical order for HC clearance was UM>EM>PM. HC elimination mainly by the liver, represented by ke, was reduced about 70% in PM. However, HC's apparent Vd was not significantly different among UMs, EMs, and PM. The canonical order of predicted plasma HM concentrations was UM>EM>PM. For each of the CYP2D6 phenotypes, the mean predicted HM levels were within HM's therapeutic range, which indicates HC has significant phenotype-dependent pro-drug effects.

CONCLUSIONS

Our results demonstrate that pharmacogenetics afford clinicians an opportunity to individualize HC dosing, while adding enhanced opportunity to account for its conversion to HM in the body.

Novel Disease-Drug Database Demonstrating Applicability for Pharmacogenomic-Based Prescribing

Significant advances have been made in the clinical implementation of pharmacogenomics in recent years with tools for clinical decision support (CDS) being developed and integrated in the electronic health record (EHR). In this issue, the article by Hussain et al. describes the creation of a disease-drug association tool that enables providers to search by disease indications to receive a list of treatment options marked with pharmacogenomics annotations at the point of prescribing.

Attitudes of clinicians following large-scale pharmacogenomics implementation

Clinician attitudes toward multiplexed genomic testing may be vital to the success of translational programs. We surveyed clinicians at an academic medical center about their views on a large pharmacogenomics implementation, the PREDICT (Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment) program. Participants were asked about test ordering, major factors influencing use of results, expectations of efficacy and responsibility for applying results to patient care. Virtually all respondents (99%) agreed that pharmacogenomics variants influence patients' response to drug therapy. The majority (92%) favored immediate, active notification when a clinically significant drug-genome interaction was present. However, clinicians were divided on which providers were responsible for acting on a result when a prescription change was indicated and whether patients should be directly notified of a significant result. We concluded genotype results were valued for tailoring prescriptions, but clinicians do not agree on how to appropriately assign clinical responsibility for actionable results from a multiplexed panel.The Pharmacogenomics Journal advance online publication, 11 August 2015; doi:10.1038/tpj.2015.57.

Pharmacologic Treatment of Pain

Adolescents and children are frequently affected by chronic pain conditions that can lead to disability and distress. The best approach to evaluation and treatment of these conditions involves use of the biopsychosocial model, which includes use of medication management. Chronic pain conditions are treated pharmacologically with a number of different medication classes via several routes of administration as drug delivery systems have progressed. These include anti-inflammatory drugs, muscle relaxants, antiepileptic medicines, antidepressants, opioids, and local anesthetics. Most are prescribed without regulatory body approval to treat specific pain syndromes as data to support their use are sparse. Medical decision making is guided by experience, empiric evidence, extrapolation from adult studies, and matching medication classes with the theorized mechanism of the pain condition. It is not recommended that nonpain practitioners prescribe opioid medications for treatment of chronic pain conditions, and pain management practitioners should seek to minimize their use. The appropriate and commonly used medications for pain conditions are presented in this narrative review.

Challenges of development and implementation of point of care pharmacogenetic testing

INTRODUCTION

Just as technology was the underlying driver of the sequencing of the human genome and subsequent generation of volumes of genome sequence data from healthy and affected individuals, animal, plant, and microbial species alike, so too will technology revolutionize diagnostic testing. One area of intense interest is the use of genetic data to inform decisions regarding drug selection and drug dosing, known as pharmacogenetic (PGx) testing, to improve likelihood of successful treatment outcomes with minimal risks.

AREAS COVERED

This commentary will provide an overview of implementation research of PGx testing, the benefits of point-of-care (POC) testing and overview of POC testing platforms, available PGx tests, and barriers and facilitators to the development and integration of POC-PGx testing into clinical settings. Sources include the published literature, and databases from the Centers for Medicaid and Medicare Services, Food and Drug Administration. Expert commentary: The utilization of POC PGx testing may enable more routine test use, but the development and implementation of such tests will face some barriers before personalized medicine is available to every patient. In particular, provider training, availability of clinical decision supports, and connectivity will be key areas to facilitate routine use.

Pharmacogenetics for Safe Codeine Use in Sickle Cell Disease

After postoperative deaths in children who were prescribed codeine, several pediatric hospitals have removed it from their formularies. These deaths were attributed to atypical cytochrome P450 2D6 (CYP2D6) pharmacogenetics, which is also implicated in poor analgesic response. Because codeine is often prescribed to patients with sickle cell disease and is now the only Schedule III opioid analgesic in the United States, we implemented a precision medicine approach to safely maintain codeine as an option for pain control. Here we describe the implementation of pharmacogenetics-based codeine prescribing that accounts for CYP2D6 metabolizer status. Clinical decision support was implemented within the electronic health record to guide prescribing of codeine with the goal of preventing its use after tonsillectomy or adenoidectomy and in CYP2D6 ultra-rapid and poor metabolizer (high-risk) genotypes. As of June 2015, CYP2D6 genotype results had been reported for 2468 unique patients. Of the 830 patients with sickle cell disease, 621 (75%) had a CYP2D6 genotype result; 7.1% were ultra-rapid or possible ultra-rapid metabolizers, and 1.4% were poor metabolizers. Interruptive alerts recommended against codeine for patients with high-risk CYP2D6 status. None of the patients with an ultra-rapid or poor metabolizer genotype were prescribed codeine. Using genetics to tailor analgesic prescribing retained an important therapeutic option by limiting codeine use to patients who could safely receive and benefit from it. Our efforts represent an evidence-based, innovative medication safety strategy to prevent adverse drug events, which is a model for the use of pharmacogenetics to optimize drug therapy in specialized pediatric populations.

Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study

BACKGROUND

Inappropriate prescribing increases patient illness and death owing to adverse drug events. The inclusion of genetic information into primary care medication practices is one solution. Our aim was to assess the ability to obtain and genotype saliva samples and to determine the levels of use of a decision support tool that creates medication options adjusted for patient characteristics, drug-drug interactions and pharmacogenetics.

METHODS

We conducted a cohort study in 6 primary care settings (5 family practices and 1 pharmacy), enrolling 191 adults with at least 1 of 10 common diseases. Saliva samples were obtained in the physician's office or pharmacy and sent to our laboratory, where DNA was extracted and genotyped and reports were generated. The reports were sent directly to the family physician/pharmacist and linked to an evidence-based prescribing decision support system. The primary outcome was ability to obtain and genotype samples. The secondary outcomes were yield and purity of DNA samples, ability to link results to decision support software and use of the decision support software.

RESULTS

Genotyping resulted in linking of 189 patients (99%) with pharmacogenetic reports to the decision support program. A total of 96.8% of samples had at least 1 actionable genotype for medications included in the decision support system. The medication support system was used by the physicians and pharmacists 236 times over 3 months.

INTERPRETATION

Physicians and pharmacists can collect saliva samples of sufficient quantity and quality for DNA extraction, purification and genotyping. A clinical decision support system with integrated data from pharmacogenetic tests may enable personalized prescribing within primary care. Trial registration: ClinicalTrials.gov, NCT02383290.

Creating a scalable clinical pharmacogenomics service with automated interpretation and medical record result integration - experience from a pediatric tertiary care facility

OBJECTIVE

This paper outlines the implementation of a comprehensive clinical pharmacogenomics (PGx) service within a pediatric teaching hospital and the integration of clinical decision support in the electronic health record (EHR).

MATERIALS AND METHODS

An approach to clinical decision support for medication ordering and dispensing driven by documented PGx variant status in an EHR is described. A web-based platform was created to automatically generate a clinical report from either raw assay results or specified diplotypes, able to parse and combine haplotypes into an interpretation for each individual and compared to the reference lab call for accuracy.

RESULTS

Clinical decision support rules built within an EHR provided guidance to providers for 31 patients (100%) who had actionable PGx variants and were written for interacting medications. A breakdown of the PGx alerts by practitioner service, and alert response for the initial cohort of patients tested is described. In 90% (355/394) of the cases, thiopurine methyltranferase genotyping was ordered pre-emptively.

DISCUSSION

This paper outlines one approach to implementing a clinical PGx service in a pediatric teaching hospital that cares for a heterogeneous patient population. There is a focus on incorporation of PGx clinical decision support rules and a program to standardize report text within the electronic health record with subsequent exploration of clinician behavior in response to the alerts.

CONCLUSION

The incorporation of PGx data at the time of prescribing and dispensing, if done correctly, has the potential to impact the incidence of adverse drug events, a significant cause of morbidity and mortality.

Evaluation: A Qualitative Pilot Study of Novel Information Technology Infrastructure to Communicate Genetic Variant Updates

BACKGROUND

Partners HealthCare Personalized Medicine developed GeneInsight Clinic (GIC), a tool designed to communicate updated variant information from laboratory geneticists to treating clinicians through automated alerts, categorized by level of variant interpretation change.

OBJECTIVES

The study aimed to evaluate feedback from the initial users of the GIC, including the advantages and challenges to receiving this variant information and using this technology at the point of care.

METHODS

Healthcare professionals from two clinics that ordered genetic testing for cardiomyopathy and related disorders were invited to participate in one-hour semi-structured interviews and/ or a one-hour focus group. Using a Grounded Theory approach, transcript concepts were coded and organized into themes.

RESULTS

Two genetic counselors and two physicians from two treatment clinics participated in individual interviews. Focus group participants included one genetic counselor and four physicians. Analysis resulted in 8 major themes related to structuring and communicating variant knowledge, GIC's impact on the clinic, and suggestions for improvements. The interview analysis identified longitudinal patient care, family data, and growth in genetic testing content as potential challenges to optimization of the GIC infrastructure.

DISCUSSION

Participants agreed that GIC implementation increased efficiency and effectiveness of the clinic through increased access to genetic variant information at the point of care.

CONCLUSION

Development of information technology (IT) infrastructure to aid in the organization and management of genetic variant knowledge will be critical as the genetic field moves towards whole exome and whole genome sequencing. Findings from this study could be applied to future development of IT support for genetic variant knowledge management that would serve to improve clinicians' ability to manage and care for patients.

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.

Developing knowledge resources to support precision medicine: principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC)

To move beyond a select few genes/drugs, the successful adoption of pharmacogenomics into routine clinical care requires a curated and machine-readable database of pharmacogenomic knowledge suitable for use in an electronic health record (EHR) with clinical decision support (CDS). Recognizing that EHR vendors do not yet provide a standard set of CDS functions for pharmacogenetics, the Clinical Pharmacogenetics Implementation Consortium (CPIC) Informatics Working Group is developing and systematically incorporating a set of EHR-agnostic implementation resources into all CPIC guidelines. These resources illustrate how to integrate pharmacogenomic test results in clinical information systems with CDS to facilitate the use of patient genomic data at the point of care. Based on our collective experience creating existing CPIC resources and implementing pharmacogenomics at our practice sites, we outline principles to define the key features of future knowledge bases and discuss the importance of these knowledge resources for pharmacogenomics and ultimately precision medicine.

Merging Electronic Health Record Data and Genomics for Cardiovascular Research: A Science Advisory From the American Heart Association

The process of scientific discovery is rapidly evolving. The funding climate has influenced a favorable shift in scientific discovery toward the use of existing resources such as the electronic health record. The electronic health record enables long-term outlooks on human health and disease, in conjunction with multidimensional phenotypes that include laboratory data, images, vital signs, and other clinical information. Initial work has confirmed the utility of the electronic health record for understanding mechanisms and patterns of variability in disease susceptibility, disease evolution, and drug responses. The addition of biobanks and genomic data to the information contained in the electronic health record has been demonstrated. The purpose of this statement is to discuss the current challenges in and the potential for merging electronic health record data and genomics for cardiovascular research.

Integrating electronic health record genotype and phenotype datasets to transform patient care

The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 mandates the development and implementation of electronic health record (EHR) systems across the country. While a primary goal is to improve the care of individual patients, EHRs are also key enabling resources for a vision of individualized (or personalized or precision) medicine: the aggregation of multiple EHRs within or across healthcare systems should allow discovery of patient subsets that have unusual and definable clinical trajectories that deviate importantly from the expected response in a "typical" patient. The spectrum of such personalized care can then extend from prevention to choice of medication to intensity or nature of follow-up.

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.

Physician response to implementation of genotype-tailored antiplatelet therapy

Physician responses to genomic information are vital to the success of precision medicine initiatives. We prospectively studied a pharmacogenomics implementation program for the propensity of clinicians to select antiplatelet therapy based on CYP2C19 loss-of-function variants in stented patients. Among 2,676 patients, 514 (19.2%) were found to have a CYP2C19 variant affecting clopidogrel metabolism. For the majority (93.6%) of the cohort, cardiologists received active and direct notification of CYP2C19 status. Over 12 months, 57.6% of poor metabolizers and 33.2% of intermediate metabolizers received alternatives to clopidogrel. CYP2C19 variant status was the most influential factor impacting the prescribing decision (hazard ratio [HR] in poor metabolizers 8.1, 95% confidence interval [CI] [5.4, 12.2] and HR 5.0, 95% CI [4.0, 6.3] in intermediate metabolizers), followed by patient age and type of stent implanted. We conclude that cardiologists tailored antiplatelet therapy for a minority of patients with a CYP2C19 variant and considered both genomic and nongenomic risks in their clinical decision-making.

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.

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.

Trends in biomedical informatics: automated topic analysis of JAMIA articles

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a "generalist" journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years.

Is there a "magic" hemoglobin number? Clinical decision support promoting restrictive blood transfusion practices

Blood transfusion has been identified as one of the most frequently performed therapeutic procedures, with a significant percentage of transfusions identified to be inappropriate. Recent key clinical trials in adults have provided Level 1 evidence to support restrictive red blood cell (RBC) transfusion practices. However, some advocates have attempted to identify a "correct" Hb threshold for RBC transfusion; whereas others assert that management of anemia, including transfusion decisions, must take into account clinical patient variables, rather than simply one diagnostic laboratory test. The heterogeneity of guidelines for blood transfusion by a number of medical societies reflects this controversy. Clinical decision support (CDS) uses a Hb threshold number in a smart Best Practices Alert (BPA) upon physician order, to trigger a concurrent utilization self-review for whether blood transfusion therapy is appropriate. This review summarizes Level 1 evidence in seven key clinical trials in adults that support restrictive transfusion practices, along strategies made possible by CDS that have demonstrated value in improving blood utilization by promoting restrictive transfusion practices.

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.

Computerized Clinical Decision Support: Contributions from 2014

OBJECTIVE

To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.

METHOD

A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers.

RESULTS

Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy.

CONCLUSIONS

As health information technologies spread more and more meaningfully, CDSSs are improving to answer users' needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

Cardiovascular pharmacogenomics: current status and future directions

Drugs are widely used and highly effective in the treatment of heart disease. Nevertheless, in some instances, even drugs effective in a population display lack of efficacy or adverse drug reactions in individual patients, often in an apparently unpredictable fashion. This review summarizes the genomic factors now known to influence variability in responses to widely used cardiovascular drugs such as clopidogrel, warfarin, heparin and statins. Genomic approaches being used to discover new pathways in common cardiovascular diseases and thus potential new targets for drug development are described. Finally, the way in which this new information is likely to be used in an electronic medical record environment is discussed.

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.

Electronic health records: current and future use

This paper provides an overview of the current state of the electronic medical record, including benefits and shortcomings, and presents key factors likely to drive development in the next decade and beyond. The current electronic medical record to a large extent represents a digital version of the traditional paper legal record, owned and maintained by the practitioner. The future electronic health record is expected to be a shared tool, engaging patients in decision making, wellness and disease management and providing data for individual decision support, population management and analytics. Many drivers will determine this path, including payment model reform, proliferation of mobile platforms, telemedicine, genomics and individualized medicine and advances in 'big data' technologies.

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.

Development of clinical decision support alerts for pharmacogenomic incidental findings from exome sequencing

PURPOSE

Electronic health records (EHRs) and their associated decision support tools are potentially important means of disseminating a patient's pharmacogenomic profile to his or her health-care providers. We sought to create a proof-of-concept decision support alert system generated from pharmacogenomic incidental findings from exome sequencing.

METHODS

A pipeline for alerts from exome sequencing tests was created for patients in the New EXome Technology in (NEXT) Medicine study at the University of Washington. Decision support rules using discrete, machine-readable incidental finding results were programmed into a commercial EHR rules engine. An evaluation plan to monitor the alerts in real medical interactions was established.

RESULTS

Alerts were created for 48 actionable pharmacogenomic variants in 11 genes and were launched on 24 September 2014 for University of Washington inpatient care. Of the 94 participants enrolled in the NEXT Medicine study, 49 had one or more pharmacogenomic variants identified for return.

CONCLUSION

Reflections on the process reveal that while incidental findings can be used to generate decision support alerts, substantial resources are required to ensure that each alert is consistent with rapidly evolving pharmacogenomic literature and is customized to fit in the clinical workflow unique to each incidental finding.

An inter-professional approach to personalized medicine education: one institution's experience

Personalized medicine offers the promise of better diagnoses, targeted therapies and individualized treatment plans. Pharmacogenomics is an integral component of personalized medicine; it aids in the prediction of an individual's response to medications. Despite growing public acceptance and emerging clinical evidence, this rapidly expanding field of medicine is slow to be adopted and utilized by healthcare providers, although many believe that they should be knowledgeable and able to apply pharmacogenomics in clinical practice. Institutional infrastructure must be built to support pharmacogenomic implementation. Multidisciplinary education for healthcare providers is a critical component for pharmacogenomics to achieve its full potential to optimize patient care. We describe our recent experience at the Mayo Clinic implementing pharmacogenomics education in a large, academic healthcare system facilitated by the Mayo Clinic Center for Individualized Medicine.

Closing the gap between knowledge and clinical application: challenges for genomic translation

Despite early predictions and rapid progress in research, the introduction of personal genomics into clinical practice has been slow. Several factors contribute to this translational gap between knowledge and clinical application. The evidence available to support genetic test use is often limited, and implementation of new testing programs can be challenging. In addition, the heterogeneity of genomic risk information points to the need for strategies to select and deliver the information most appropriate for particular clinical needs. Accomplishing these tasks also requires recognition that some expectations for personal genomics are unrealistic, notably expectations concerning the clinical utility of genomic risk assessment for common complex diseases. Efforts are needed to improve the body of evidence addressing clinical outcomes for genomics, apply implementation science to personal genomics, and develop realistic goals for genomic risk assessment. In addition, translational research should emphasize the broader benefits of genomic knowledge, including applications of genomic research that provide clinical benefit outside the context of personal genomic risk.

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.

Clinician Perspectives on Using Pharmacogenomics in Clinical Practice

AIM

To describe the knowledge and attitudes of clinicians participating in a large pharmacogenomics implementation program.

MATERIALS & METHODS

Semi-structured interviews with 15 physicians and nurse practitioners were conducted.

RESULTS

Three categories of themes were identified: preparation and knowledge, pharmacogenomics usage in practice, and future management of genomic variants. Providers expressed an inability to keep up with the rapid pace of evidence generation and indicated strong support for clinical decision support to assist with genotype-tailored therapies. Concerns raised by clinicians included effectively communicating results, long-term responsibility for actionable results and hand-offs with providers outside the implementation program.

CONCLUSIONS

Clinicians identified their own knowledge deficits, workflow integration, and longitudinal responsibility as challenges to successful usage of pharmacogenomics in clinical practice.

The next chapter in patient blood management: real-time clinical decision support

OBJECTIVES

Blood transfusion was identified by the American Medical Association as one of the top five most frequently overused therapies. Utilization review has been required by accreditation agencies, but retrospective review has been ineffective due to labor-intense resources applied to only a sampling of transfusion events. Electronic medical records have allowed clinical decision support (CDS) to occur via a best practices alert at the critical decision point concurrently with physician order entry.

METHODS

We review emerging strategies for improving blood utilization.

RESULTS

Implementation of CDS at our institution decreased the percentage of transfusions in patients with a hemoglobin level of more than 8 g/dL from 60% to less than 30%. Annual RBC transfusions were reduced by 24%, despite concurrent increases in patient discharge volumes and case mix complexity. This resulted in acquisition costs savings (direct blood product purchase costs) of $6.4 million over 4 years.

CONCLUSIONS

We have been able to significantly reduce inappropriate blood transfusions and related costs through an educational initiative coupled with real-time CDS. In deriving increased value out of health care, CDS can be applied to a number of overuse measures in laboratory testing, radiology, and therapy such as antibiotics, as outlined by the American Board of Internal Medicine's Choosing Wisely campaign.

Pharmacogenetics of cancer drugs

The variability in treatment outcomes among patients receiving the same therapy for seemingly similar tumors can be attributed in part to genetics. The tumor's (somatic) genome largely dictates the effectiveness of the therapy, and the patient's (germline) genome influences drug exposure and the patient's sensitivity to toxicity. Many potentially clinically useful associations have been discovered between common germline genetic polymorphisms and outcomes of cancer treatment. This review highlights the germline pharmacogenetic associations that are currently being used to guide cancer treatment decisions, those that are most likely to someday be clinically useful, and associations that are well known but their roles in clinical management are not yet certain. In the future, germline genetic information will likely be available from tumor genetic analyses, creating an efficient opportunity to integrate the two genomes to optimize treatment outcomes for each individual cancer patient.

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.

Pharmacogenetics and immunosuppressive drugs in solid organ transplantation

The transplantation literature includes numerous papers that report associations between polymorphisms in genes encoding metabolizing enzymes and drug transporters, and pharmacokinetic data on immunosuppressive drugs. Most of these studies are retrospective in design, and although a substantial number report significant associations, pharmacogenetic tests are hardly used in clinical practice. One of the reasons for this poor implementation is the current lack of evidence of improved clinical outcome with pharmacogenetic testing. Furthermore, with efficient therapeutic drug monitoring it is possible to rapidly correct for the effect of genotypic deviations on pharmacokinetics, thereby decreasing the utility of genotype-based dosing. The future of pharmacogenetics will be in treatment models in which patient characteristics are combined with data on polymorphisms in multiple genes. These models should focus on pharmacodynamic parameters, variations in the expression of drug transporter proteins, and predictors of toxicity. Such models will provide more information than the relatively small candidate gene studies performed so far. For implementation of these models into clinical practice, linkage of genotype data to medication prescription systems within electronic health records will be crucial.

Primary-care providers' perceived barriers to integration of genetics services: a systematic review of the literature

PURPOSE

We aimed to systematically review the literature to identify primary-care providers' perceived barriers against provision of genetics services.

METHODS

We systematically searched PubMed and ERIC using key and Boolean term combinations for articles published from 2001 to 2012 that met inclusion/exclusion criteria. Specific barriers were identified and aggregated into categories based on topic similarity. These categories were then grouped into themes.

RESULTS

Of the 4,174 citations identified by the search, 38 publications met inclusion criteria. There were 311 unique barriers that were classified into 38 categories across 4 themes: knowledge and skills; ethical, legal, and social implications; health-care systems; and scientific evidence. Barriers most frequently mentioned by primary-care providers included a lack of knowledge about genetics and genetic risk assessment, concern for patient anxiety, a lack of access to genetics, and a lack of time.

CONCLUSION

Although studies reported that primary-care providers perceive genetics as being important, barriers to the integration of genetics medicine into routine patient care were identified. The promotion of practical guidelines, point-of-care risk assessment tools, tailored educational tools, and other systems-level strategies will assist primary-care providers in providing genetics services for their patients.