Browsing by Author "Pasternak, Amy L."

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Best-worst scaling methodology to evaluate constructs of the Consolidated Framework for Implementation Research: application to the implementation of pharmacogenetic testing for antidepressant therapy.
    (BMC, 2022-05-14) Salloum, Ramzi G.; Bishop, Jeffrey R.; Elchynski, Amanda L.; Smith, D. Max; Rowe, Elizabeth; Blake, Kathryn V.; Limdi, Nita A.; Aquilante, Christina L.; Bates, Jill; Beitelshees, Amber L.; Cipriani, Amber; Duong, Benjamin Q.; Empey, Philip E.; Formea, Christine M.; Hicks, J. Kevin; Mroz, Pawel; Oslin, David; Pasternak, Amy L.; Petry, Natasha; Ramsey, Laura B.; Schlichte, Allyson; Swain, Sandra M.; Ward, Kristen M.; Wiisanen, Kristin; Skaar, Todd C.; Van Driest, Sara L.; Cavallari, Larisa H.; Tuteja, Sony
    BACKGROUND: Despite the increased demand for pharmacogenetic (PGx) testing to guide antidepressant use, little is known about how to implement testing in clinical practice. Best-worst scaling (BWS) is a stated preferences technique for determining the relative importance of alternative scenarios and is increasingly being used as a healthcare assessment tool, with potential applications in implementation research. We conducted a BWS experiment to evaluate the relative importance of implementation factors for PGx testing to guide antidepressant use. METHODS: We surveyed 17 healthcare organizations that either had implemented or were in the process of implementing PGx testing for antidepressants. The survey included a BWS experiment to evaluate the relative importance of Consolidated Framework for Implementation Research (CFIR) constructs from the perspective of implementing sites. RESULTS: Participating sites varied on their PGx testing platform and methods for returning recommendations to providers and patients, but they were consistent in ranking several CFIR constructs as most important for implementation: patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and identification of champions. CONCLUSIONS: This study demonstrates the feasibility of using choice experiments to systematically evaluate the relative importance of implementation determinants from the perspective of implementing organizations. BWS findings can inform other organizations interested in implementing PGx testing for mental health. Further, this study demonstrates the application of BWS to PGx, the findings of which may be used by other organizations to inform implementation of PGx testing for mental health disorders.
  • Thumbnail Image
    Item
    Comparison of clinical pharmacogenetic recommendations across therapeutic areas
    (Wolters Kluwer, 2022) Shugg, Tyler; Pasternak, Amy L.; Luzum, Jasmine A.; Medicine, School of Medicine
    Objectives: Evaluations from pharmacogenetics implementation programs at major US medical centers have reported variability in the clinical adoption of pharmacogenetics across therapeutic areas. A potential cause for this variability may involve therapeutic area-specific differences in published pharmacogenetics recommendations to clinicians. To date, however, the potential for differences in clinical pharmacogenetics recommendations by therapeutic areas from prominent US guidance sources has not been assessed. Accordingly, our objective was to comprehensively compare essential elements from clinical pharmacogenetics recommendations contained within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and clinical practice guidelines from US professional medical organizations across therapeutic areas. Methods: We analyzed clinical pharmacogenetics recommendation elements within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and professional clinical practice guidelines through 05/24/19. Results: We identified 606 unique clinical pharmacogenetics recommendations, with the most recommendations involving oncology (217 recommendations), hematology (79), psychiatry (65), cardiovascular (43) and anesthetic (37) medications. Within our analyses, we observed considerable variability across therapeutic areas within the following essential pharmacogenetics recommendation elements: the recommended clinical management strategy; the relevant genetic biomarkers; the organizations providing pharmacogenetics recommendations; whether routine genetic screening was recommended; and the time since recommendations were published. Conclusions: On the basis of our results, we infer that observed differences in clinical pharmacogenetics recommendations across therapeutic areas may result from specific factors associated with individual disease states, the associated genetic biomarkers, and the characteristics of the organizations providing recommendations.
  • Thumbnail Image
    Item
    Multisite evaluation of institutional processes and implementation determinants for pharmacogenetic testing to guide antidepressant therapy.
    (Wiley, 2022-02) Tuteja, Sony; Salloum, Ramzi G.; Elchynski, Amanda L.; Smith, D. Max; Rowe, Elizabeth; Blake, Kathryn V.; Limdi, Nita A.; Aquilante, Christina L.; Bates, Jill; Beitelshees, Amber L.; Cipriani, Amber; Duong, Benjamin Q.; Empey, Philip E.; Formea, Christine M.; Hicks, J. Kevin; Mroz, Pawel; Oslin, David; Pasternak, Amy L.; Petry, Natasha; Ramsey, Allyson; Swain, Sandra M.; Ward, Kristen M.; Wiisanen, Kristin; Skaar, Todd C.; Van Driest, Sara L.; Cavallari, Larisa H.; Bishop, Jeffrey R.
    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.
  • Thumbnail Image
    Item
    Multisite investigation of strategies for the clinical implementation of pre-emptive pharmacogenetic testing
    (Elsevier, 2021) Duarte, Julio D.; Dalton, Rachel; Elchynski, Amanda L.; Smith, D. Max; Cicali, Emily J.; Lee, James C.; Duong, Benjamin Q.; Petry, Natasha J.; Aquilante, Christina L.; Beitelshees, Amber L.; Empey, Philip E.; Johnson, Julie A.; Obeng, Aniwaa Owusu; Pasternak, Amy L.; Pratt, Victoria M.; Ramsey, Laura B.; Tuteja, Sony; Van Driest, Sara L.; Wiisanen, Kristin; Hicks, J. Kevin; Cavallari, Larisa H.; IGNITE Network Pharmacogenetics Working Group; Medical and Molecular Genetics, School of Medicine
    Purpose: The increased availability of clinical pharmacogenetic (PGx) guidelines and decreasing costs for genetic testing have slowly led to increased utilization of PGx testing in clinical practice. Pre-emptive PGx testing, where testing is performed in advance of drug prescribing, is one means to ensure results are available at the time of prescribing decisions. However, the most efficient and effective methods to clinically implement this strategy remain unclear. Methods: In this report, we compare and contrast implementation strategies for pre-emptive PGx testing by 15 early-adopter institutions. We surveyed these groups, collecting data on testing approaches, team composition, and workflow dynamics, in addition to estimated third-party reimbursement rates. Results: We found that while pre-emptive PGx testing models varied across sites, institutions shared several commonalities, including methods to identify patients eligible for testing, involvement of a precision medicine clinical team in program leadership, and the implementation of pharmacogenes with Clinical Pharmacogenetics Implementation Consortium guidelines available. Finally, while reimbursement rate data were difficult to obtain, the data available suggested that reimbursement rates for pre-emptive PGx testing remain low. Conclusion: These findings should inform the establishment of future implementation efforts at institutions considering a pre-emptive PGx testing program.
  • Thumbnail Image
    Item
    Prevalence and types of inconsistencies in clinical pharmacogenetic recommendations among major U.S. sources
    (Nature, 2020-10-30) Shugg, Tyler; Pasternak, Amy L.; London, Bianca; Luzum, Jasmine A.; Pharmacology and Toxicology, School of Medicine
    Clinical implementation of pharmacogenomics (PGx) is slow. Previous studies have identified some inconsistencies among clinical PGx recommendations, but the prevalence and types of inconsistencies have not been comprehensively analyzed among major PGx guidance sources in the U.S. PGx recommendations from the Clinical Pharmacogenetics Implementation Consortium, U.S. Food and Drug Administration drug labels, and major U.S. professional medical organizations were analyzed through May 24, 2019. Inconsistencies were analyzed within the following elements: recommendation category; whether routine screening was recommended; and the specific biomarkers, variants, and patient groups involved. We identified 606 total clinical PGx recommendations, which contained 267 unique drugs. Composite inconsistencies occurred in 48.1% of clinical PGx recommendations overall, and in 93.3% of recommendations from three sources. Inconsistencies occurred in the recommendation category (29.8%), the patient group (35.4%), and routine screening (15.2%). In conclusion, almost one-half of clinical PGx recommendations from prominent U.S. guidance sources contain inconsistencies, which can potentially slow clinical implementation.
  • Thumbnail Image
    Item
    The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation
    (Wolters Kluwer, 2025) Cavallari, Larisa H.; Hicks, J. Kevin; Patel, Jai N.; Elchynski, Amanda L.; Smith, D. Max; Bargal, Salma A.; Fleck, Ashley; Aquilante, Christina L.; Killam, Shayna R.; Lemke, Lauren; Ochi, Taichi; Ramsey, Laura B.; Haidar, Cyrine E.; Ho, Teresa; El Rouby, Nihal; Monte, Andrew A.; Allen, Josiah D.; Beitelshees, Amber L.; Bishop, Jeffrey R.; Bousman, Chad; Campbell, Ronald; Cicali, Emily J.; Cook, Kelsey J.; Duong, Benjamin; Tsermpini, Evangelia Eirini; Girdwood, Sonya Tang; Gregornik, David B.; Grimsrud, Kristin N.; Lamb, Nathan; Lee, James C.; Lopez, Rocio Ortiz; Mazhindu, Tinashe Adrian; Morris, Sarah A.; Nagy, Mohamed; Nguyen, Jenny; Pasternak, Amy L.; Petry, Natasha; van Schaik, Ron H. N.; Schultz, April; Skaar, Todd C.; Al Alshaykh, Hana; Stevenson, James M.; Stone, Rachael M.; Tran, Nam K.; Tuteja, Sony; Woodahl, Erica L.; Yuan, Li-Chi; Lee, Craig R.; Medicine, School of Medicine
    Pharmacogenetics promises to optimize treatment-related outcomes by informing optimal drug selection and dosing based on an individual's genotype in conjunction with other important clinical factors. Despite significant evidence of genetic associations with drug response, pharmacogenetic testing has not been widely implemented into clinical practice. Among the barriers to broad implementation are limited guidance for how to successfully integrate testing into clinical workflows and limited data on outcomes with pharmacogenetic implementation in clinical practice. The Pharmacogenomics Global Research Network Implementation Working Group seeks to engage institutions globally that have implemented pharmacogenetic testing into clinical practice or are in the process or planning stages of implementing testing to collectively disseminate data on implementation strategies, metrics, and health-related outcomes with the use of genotype-guided drug therapy to ultimately help advance pharmacogenetic implementation. This paper describes the goals, structure, and initial projects of the group in addition to implementation priorities across sites and future collaborative opportunities.