Evolution of pharmacogenomic services and implementation of a multi-state pharmacogenomics clinic across a large rural healthcare system

Introduction: Pharmacogenomics (PGx) aims to maximize drug benefits while minimizing risk of toxicity. Although PGx has proven beneficial in many settings, clinical uptake lags. Lack of clinician confidence and limited availability of PGx testing can deter patients from completing PGx testing. A few novel PGx clinic models have been described as a way to incorporate PGx testing into the standard of care.Background: A PGx clinic was implemented to fill an identified gap in provider availability, confidence, and utilization of PGx across our health system. Through a joint pharmacist and Advanced Practice Provider (APP) collaborative clinic, patients received counseling and PGx medication recommendations both before and after PGx testing. The clinic serves patients both in-person and virtually across four states in the upper Midwest.Results: The majority of patients seen in the PGx clinic during the early months were clinician referred (77%, n = 102) with the remainder being self-referred. Patients were, on average, taking two medications with Clinical Pharmacogenetics Implementation Consortium guidelines. Visits were split almost equally between in-person and virtual visits.Conclusion: Herein, we describe the successful implementation of an interdisciplinary PGx clinic to further enhance our PGx program. Throughout the implementation of the PGx clinic we have learned valuable lessons that may be of interest to other implementors. Clinicians were actively engaged in clinic referrals and early adoption of telemedicine was key to the clinic’s early successes

Multi-site investigation of strategies for the implementation of CYP2C19 genotype-guided antiplatelet therapy

CYP2C19 genotype-guided antiplatelet therapy following percutaneous coronary intervention is increasingly implemented in clinical practice. However, challenges such as selecting a testing platform, communicating test results, building clinical decision support processes, providing patient and provider education, and integrating methods to support the translation of emerging evidence to clinical practice are barriers to broad adoption. In this report, we compare and contrast implementation strategies of 12 early adopters, describing solutions to common problems and initial performance metrics for each program. Key differences between programs included the test result turnaround time and timing of therapy changes which are both related to CYP2C19 testing model and platform used. Sites reported the need for new informatics infrastructure, expert clinicians such as pharmacists to interpret results, physician champions, and ongoing education. Consensus lessons learned are presented to provide a path forward for those seeking to implement similar clinical pharmacogenomics programs within their institutions. This article is protected by copyright

Multisite evaluation of institutional processes and implementation determinants for pharmacogenetic testing to guide antidepressant therapy.

There is growing interest in utilizing pharmacogenetic (PGx) testing to guide antidepressant use, but there is lack of clarity on how to implement testing into clinical practice. We administered two surveys at 17 sites that had implemented or were in the process of implementing PGx testing for antidepressants. Survey 1 collected data on the process and logistics of testing. Survey 2 asked sites to rank the importance of Consolidated Framework for Implementation Research (CFIR) constructs using best-worst scaling choice experiments. Of the 17 sites, 13 had implemented testing and four were in the planning stage. Thirteen offered testing in the outpatient setting, and nine in both outpatient/inpatient settings. PGx tests were mainly ordered by psychiatry (92%) and primary care (69%) providers. CYP2C19 and CYP2D6 were the most commonly tested genes. The justification for antidepressants selected for PGx guidance was based on Clinical Pharmacogenetics Implementation Consortium guidelines (94%) and US Food and Drug Administration (FDA; 75.6%) guidance. Both institutional (53%) and commercial laboratories (53%) were used for testing. Sites varied on the methods for returning results to providers and patients. Sites were consistent in ranking CFIR constructs and identified patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and the identification of champions as most important for implementation. Sites deployed similar implementation strategies and measured similar outcomes. The process of implementing PGx testing to guide antidepressant therapy varied across sites, but key drivers for successful implementation were similar and may help guide other institutions interested in providing PGx-guided pharmacotherapy for antidepressant management

Disease Control Among Patients With Diabetes and Severe Depressive Symptoms

Objective: Major depressive disorder and type 2 diabetes commonly co-occur and disease control tends to be poorer when both conditions are present. However, little research has examined the disease characteristics of patients with diabetes and more severe depressive symptoms. Methods: We report a retrospective observational study of 517 patients with diabetes from 2 primary care centers. Patients with diabetes and moderately-severe/severe depression symptoms (Patient Health Questionnaire [PHQ-9] score >15) were compared with patients with diabetes without moderate or severe depression symptoms (PHQ-9 score <15; the comparison group) with regard to control of diabetes, blood pressure, and lipid parameters. Frequency of HbA1c and PHQ-9 testing were also examined. Results: Patients with diabetes and moderately severe/severe depressive symptoms had higher HbA1c (7.56% vs 7.09%), diastolic blood pressure (78.43 vs 75.67 mm Hg), and low-density lipoprotein cholesterol (109.12 vs 94.22 mg/dL) versus the comparison group. Patients with diabetes and moderately-severe/severe depression underwent HbA1c and PHQ-9 testing with similar frequency to the comparison group. Conclusions: The presence of moderately severe/severe depressive symptoms was associated with poorer glucose, lipid, and blood pressure control among patients with diabetes. Further research should prospectively examine whether a targeted depression treatment goal (PHQ-9 score <15) in patients with diabetes results in improved control of these important disease parameters

Development and early evaluation of clinical decision support for long QT syndrome population screening

Aim: Long QT syndrome (LQTS) is an inherited condition that predisposes individuals to prolongation of the QT interval and increased risk for Torsade de Pointes. Pathogenic variants in three genes - KCNH2, KCNQ1 and SCN5A - are responsible for most cases of LQTS, and recent advances in genetic testing have improved knowledge of the disease, increased access to follow-up, and reduced adverse cardiovascular outcomes. Methods: Based around our preemptive genetic screening platform which includes the three long QT genes listed above, we developed and implemented a clinical decision support (CDS) module that alerts prescribers whenever a QT-prolonging medication is ordered for patients with a genetic predisposition to LQTS. Results: Of the 13,777 individuals screened, twenty-seven tested positive for a pathogenic or likely pathogenic variant of KCNH2, KCNQ1 or SCN5A. In a subsequent early evaluation of the CDS and clinical processes, the number of QT-prolonging medications in this cohort decreased by 20% and new QT-prolonging medications were avoided in approximately 1/3 of new prescription orders. Conclusions: While long-term evaluation is needed, early data support the benefit of utilizing CDS in expanded roles, such as drug-gene-disease interactions where rare genetic variants intersect with everyday prescribing

Moving Pharmacogenetics Into Practice: It’s All About the Evidence!

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/169310/1/cpt2327.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/169310/2/cpt2327_am.pd

Moving Pharmacogenetics into Practice: It’s All About the Evidence!

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/169310/1/cpt2327.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/169310/2/cpt2327_am.pd

Patient Satisfaction with Return of Pharmacogenomic Results Utilizing a Patient Portal Message - supplementary material

Supporting Materials: Table 1: List of all questions and answer options included in this survey. Figure Supporting Materials 2: Answers to the question: Who contacted you about your Pharmacogenomics (PGx) results? Figure Supporting Materials 3: Answers to the question I was given written information explaining what the results mean to me. Figure Supporting Materials 4: Answers to the question: I was given access to a video explaining what the results mean to me. Figure Supporting Materials 5: Answers to the question: If a friend was interested in having Pharmacogenomics (PGx) testing, how likely are you to recommend they have it done? Figure Supporting Materials 6: Discrete answers to the question: How do you prefer to be contacted with Pharmacogenomics (PGx) results? (Please select all that apply) Figure Supporting Materials 7: Comparison of the text of the PRM sent prior to adjusting the process of sending the message to all panel-based testing patients.</p