James M. Hoffman

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.

Incorporation of pharmacogenomics into routine clinical practice: the Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline development process.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug therapy. CPIC has focused initially on well-known examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the development process of the CPIC guidelines and compares this process to the Institute of Medicine’s Standards for Developing Trustworthy Clinical Practice Guidelines.

Economic evaluations of clinical pharmacy services: 2006-2010.

Studies have consistently evidenced the positive clinical, economic, and humanistic benefits of pharmacist‐directed patient care in a variety of settings. Given the vast differences in clinical outcomes associated with evaluated clinical pharmacy services (CPS), more detail as to the nature of the CPS is needed to better understand observed differences in economic outcomes. With the growing trend of outpatient pharmacy services, these economic evaluations serve as viable decision‐making tools in choosing the most effective and cost‐effective pharmacy programs. We previously conducted three systematic reviews to evaluate the economic impact of CPS from 1988 to 2005. In this systematic review, our objectives were to describe and evaluate the quality of economic evaluations of CPS published between 2006 and 2010, with the goal of informing administrators and practitioners as to their cost‐effectiveness. We searched the scientific literature by using the Medline, International Pharmaceutical Abstracts, Embase, and Cumulative Index to Nursing and Allied Health Literature databases to identify studies describing CPS published from 2006 to 2010. Studies meeting our inclusion criteria (original research articles that evaluated CPS and described economic and clinical outcomes) were reviewed by two investigators. Methodology used, economic evaluation type, CPS setting and type, and clinical and economic outcome results were extracted. Results were informally compared with previous systematic reviews. Of 3587 potential studies identified, 25 met inclusion criteria. Common CPS settings were hospital (36%), community (32%), and clinic or hospital‐based ambulatory practices (28%). CPS types were disease state management (48%), general pharmacotherapeutic monitoring (24%), target drug programs (8%), and patient education (4%). Two studies (8%) listed CPS as medication therapy management. Costs were evaluated in 24 studies (96%) and sufficiently described in 13 (52%). Clinical or humanistic outcomes were evaluated in 20 studies (80%) and were sufficiently described in 18 (72%). Control groups were included in 16 (70%) of 23 studies not involving modeling. Study assumptions and limitations were stated and justified in eight studies (32%). Conclusions and recommendations were considered justified and based on results in 24 studies (96%). Eighteen studies (72%) involved full economic evaluation. The mean ± SD study quality score for full economic evaluations (18 studies) was 60.4 ± 22.3 of a possible 100 points. Benefit‐cost ratios from three studies ranged from 1.05:1 to 25.95:1, and incremental cost‐effectiveness ratios of five studies were calculated and reported. Fewer studies documented the economic impact of CPS from 2006–2010 than from 2001–2005, although a higher proportion involved controlled designs and were full economic evaluations. Evaluations of ambulatory practices were increasingly common. CPS were generally considered cost‐effective or provided a good benefit‐cost ratio.

Development and use of active clinical decision support for preemptive pharmacogenomics

Background Active clinical decision support (CDS) delivered through an electronic health record (EHR) facilitates gene-based drug prescribing and other applications of genomics to patient care. Objective We describe the development, implementation, and evaluation of active CDS for multiple pharmacogenetic test results reported preemptively. Materials and methods Clinical pharmacogenetic test results accompanied by clinical interpretations are placed into the patients EHR, typically before a relevant drug is prescribed. Problem list entries created for high-risk phenotypes provide an unambiguous trigger for delivery of post-test alerts to clinicians when high-risk drugs are prescribed. In addition, pre-test alerts are issued if a very-high risk medication is prescribed (eg, a thiopurine), prior to the appropriate pharmacogenetic test result being entered into the EHR. Our CDS can be readily modified to incorporate new genes or high-risk drugs as they emerge. Results Through November 2012, 35 customized pharmacogenetic rules have been implemented, including rules for TPMT with azathioprine, thioguanine, and mercaptopurine, and for CYP2D6 with codeine, tramadol, amitriptyline, fluoxetine, and paroxetine. Between May 2011 and November 2012, the pre-test alerts were electronically issued 1106 times (76 for thiopurines and 1030 for drugs metabolized by CYP2D6), and the post-test alerts were issued 1552 times (1521 for TPMT and 31 for CYP2D6). Analysis of alert outcomes revealed that the interruptive CDS appropriately guided prescribing in 95% of patients for whom they were issued. Conclusions Our experience illustrates the feasibility of developing computational systems that provide clinicians with actionable alerts for gene-based drug prescribing at the point of care.

PG4KDS: A model for the clinical implementation of pre‐emptive pharmacogenetics

Pharmacogenetics is frequently cited as an area for initial focus of the clinical implementation of genomics. Through the PG4KDS protocol, St. Jude Childrens Research Hospital pre‐emptively genotypes patients for 230 genes using the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array supplemented with a CYP2D6 copy number assay. The PG4KDS protocol provides a rational, stepwise process for implementing gene/drug pairs, organizing data, and obtaining consent from patients and families. Through August 2013, 1,559 patients have been enrolled, and four gene tests have been released into the electronic health record (EHR) for clinical implementation: TPMT, CYP2D6, SLCO1B1, and CYP2C19. These genes are coupled to 12 high‐risk drugs. Of the 1,016 patients with genotype test results available, 78% of them had at least one high‐risk (i.e., actionable) genotype result placed in their EHR. Each diplotype result released to the EHR is coupled with an interpretive consult that is created in a concise, standardized format. To support‐gene based prescribing at the point of care, 55 interruptive clinical decision support (CDS) alerts were developed. Patients are informed of their genotyping result and its relevance to their medication use through a letter. Key elements necessary for our successful implementation have included strong institutional support, a knowledgeable clinical laboratory, a process to manage any incidental findings, a strategy to educate clinicians and patients, a process to return results, and extensive use of informatics, especially CDS. Our approach to pre‐emptive clinical pharmacogenetics has proven feasible, clinically useful, and scalable.

Projecting future drug expenditures—2012

PURPOSE Factors likely to influence drug expenditures, drug expenditure trends in 2010 and 2011, and projected drug expenditures for 2012 are discussed. SUMMARY Data were analyzed to provide drug expenditure trends for total drug expenditures and the hospital and clinic sectors. Data were obtained from the IMS Health National Sales Perspectives database. From 2009 to 2010, total U.S. drug expenditures increased by 2.7%, with total spending rising from

A Clinician-Driven Automated System for Integration of Pharmacogenetic Interpretations Into an Electronic Medical Record

299.2 billion to

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

307.5 billion. Drug expenditures in clinics grew by 6.0% from 2009 to 2010. Hospital drug expenditures increased at the moderate rate of 1.5% from 2009 to 2010; through the first nine months of 2011, hospital drug expenditures increased by only 0.3% compared with the same period in 2010. The dominant trend over the past several years is substantial moderation in expenditure growth for widely used drugs, primarily due to the ongoing introduction and wide use of generic versions of high-cost, frequently used medications. At the end of 2010, generic drugs accounted for 78% of all retail prescriptions dispensed. Another pattern is substantial increases in expenditures for specialized medications, particularly in the outpatient setting as growth in prescription drug expenditures for clinic-administered drugs consistently outpaces growth in total expenditures. Various factors are likely to influence drug expenditures in 2012, including drugs in development, the diffusion of new drugs, generic drugs, drug shortages, and biosimilars. CONCLUSION For 2012, we project a 3-5% increase in total drug expenditures across all settings, a 5-7% increase in expenditures for clinic-administered drugs, and a 0-2% increase in hospital drug expenditures.

Clinical Pharmacogenetics Implementation Consortium Guidelines for HLA-B Genotype and Abacavir Dosing: 2014 Update

Advances in pharmacogenetic testing will expand the number of clinically important pharmacogenetic variants. Communication and interpretation of these test results are critical steps in implementation of pharmacogenetics into the clinic. Computational tools that integrate directly into the electronic medical record (EMR) are needed to translate the growing number of genetic variants into interpretive consultations to facilitate gene‐based drug prescribing. Herein, we describe processes for incorporating pharmacogenetic tests and interpretations into the EMR for clinical practice.

National survey on the effect of oncology drug shortages on cancer care

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.