Rebekah Ryanne Wu

Background: Pharmacogenetic (PGx) testing could identify actionable drug–gene interactions, reducing the risks of inappropriate prescribing of certain medications in some patients. An area of growing public health concern is rising global rates of depression and antidepressant use over the last two decades. Prior research has elucidated perspectives of healthcare providers who prescribe antidepressants regarding the clinical utility of genetic information, including PGx testing, but there is a gap in understanding how individual perspectives and systemic contextual factors may combine to influence PGx testing adoption. Objective: The objective of this study was to elucidate combinations of individual and contextual conditions associated with willingness to adopt PGx testing for Cytochrome P450 Subfamily IID, Polypeptide 6 (CYP2D6) and Subfamily IIC, Polypeptide 19 (CYP2C19) among antidepressant prescribers. Methods: We conducted a cross-sectional, mixed-methods study using structured questionnaires and semi-structured interviews with healthcare providers who prescribe antidepressants within their scope of practice across four healthcare systems in the United States. We collected data on implementation science concepts from the Theoretical Domains Framework, the Consolidated Framework for Implementation Research (CFIR), and the Implementation Outcomes Framework. Coincidence analysis (CNA), a case-based, Boolean logic-based method that identifies minimally sufficient combinations of conditions that lead to a particular outcome, was used to identify combinations of conditions for PGx test adoption among antidepressant prescribers. Interviews were also conducted with 10 patients who received pharmacogenetic testing within these healthcare systems to contextualize findings with patient perspectives. Results: Prescribers adopted PGx testing when they believed it would be beneficial to patients and were not deterred by cost-related concerns; the combination of these conditions led to PGx adoption in the most highly supported CNA model. Patient perspectives were also consistent with the selected model, with data suggesting they may have greater willingness to tolerate costs when they perceived or experienced benefits from testing. Conclusions: Insights from this study may be used by health system administrators and public health policymakers to inform future PGx implementation strategies that enhance uptake and awareness of existing evidence for clinical benefits of PGx testing and mitigate cost-related barriers to adoption.

The majority of individuals receiving treatment for major depressive disorder (MDD) do not achieve remission from the first medication they try, and over 80% subsequently discontinue pharmacotherapy or switch to a different medication. SSRI discontinuation due to side effects is common. We evaluated the effect of CYP2C19 genotype on SSRI response using self-reported data from 114,627 direct-to-consumer genetics research participants who were prescribed an SSRI primarily metabolized by CYP2C19 (citalopram, escitalopram, or sertraline). Among participants taking citalopram or escitalopram, slower metabolizers experienced side effects significantly more often than faster metabolizers (OR=1.04 per grade, from 0 for poor metabolizers to 5 for ultrarapid metabolizers, 95%CI=[1.02-1.06] and OR=1.05 per grade, 95%CI=[1.02-1.07]) and were more likely to discontinue treatment due to side effects (OR=1.05, 95%CI=[1.03-1.08], e.g. 29.7% of poor vs. 21.6% of ultrarapid metabolizers, and OR=1.07, 95%CI=[1.04-1.11], e.g. 25.7% vs. 20.2%). Slower metabolizers taking escitalopram were more likely to suffer from sleep problems and sexual problems than faster metabolizers. Slower metabolizers taking sertraline reported tremor more often than faster metabolizers. Overall, we find substantial differences in side effect risk between individuals with different CYP2C19 genotypes in a large sample, supporting the notion that individuals seeking treatment for MDD may benefit from preemptive pharmacogenetic testing and genotype-guided dosing recommendations to minimize side effects and reduce discontinuations.

Aim: Understanding barriers and facilitators to pharmacogenomics (PGx) implementation and how to structure a clinical program with the Veterans Health Administration (VA). Materials & methods: Heal...

We applied implementation science frameworks to identify barriers and facilitators to veterans’ acceptance of pharmacogenomic testing (PGx), which was made available as a part of clinical care at 25 VA medical centers. We conducted 30 min interviews with veterans who accepted (n = 14), declined (n = 9), or were contemplating (n = 8) PGx testing. Six team members coded one transcript from each participant group to develop the codebook and finalize definitions. Three team members coded the remaining 28 transcripts and met regularly with the larger team to reach a consensus. The coders generated a matrix of implementation constructs by testing status to identify the similarities and differences between accepters, decliners, and contemplators. All groups understood the PGx testing procedures and possible benefits. In the decision-making, accepters prioritized the potential health benefits of PGx testing, such as reducing side effects or the number of medications. In contrast, decliners prioritized the possibilities of data breach or the negative impact on healthcare insurance or Veterans Affairs benefits. Contemplators desired to speak to a provider to learn more before making a decision. Efforts to improve the clarity of data security and the impact on benefits may improve veterans’ abilities to make more informed decisions about whether to undergo PGx testing.

Background: Systematically assessing disease risk can improve population health by identifying those eligible for enhanced prevention/screening strategies. This study aims to determine the clinical impact of a systematic risk assessment in diverse primary care populations. Methods: Hybrid implementation-effectiveness trial of a family health history-based health risk assessment (HRA) tied to risk-based guideline recommendations enrolling from 2014–2017 with 12 months of post-intervention survey data and 24 months of electronic medical record (EMR) data capture. Setting:19 primary care clinics at four geographically and culturally diverse U.S. healthcare systems. Participants: any English or Spanish-speaking adult with an upcoming appointment at an enrolling clinic. Methods: A personal and family health history based HRA with integrated guideline-based clinical decision support (CDS) was completed by each participant prior to their appointment. Risk reports were provided to patients and providers to discuss at their clinical encounter. Outcomes: provider and patient discussion and provider uptake (i.e. ordering) and patient uptake (i.e. recommendation completion) of CDS recommendations. Measures: patient and provider surveys and EMR data. Results: One thousand eight hundred twenty nine participants (mean age 56.2 [SD13.9], 69.6% female) completed the HRA and had EMR data available for analysis. 762 (41.6%) received a recommendation (29.7% for genetic counseling (GC); 15.2% for enhanced breast/colon cancer screening). Those with recommendations frequently discussed disease risk with their provider (8.7%-38.2% varied by recommendation, p-values ≤ 0.004). In the GC subgroup, provider discussions increased referrals to counseling (44.4% with vs. 5.9% without, P < 0.001). Recommendation uptake was highest for colon cancer screening (provider = 67.9%; patient = 86.8%) and lowest for breast cancer chemoprevention (0%). Conclusions: Systematic health risk assessment revealed that almost half the population were at increased disease risk based on guidelines. Risk identification resulted in shared discussions between participants and providers but variable clinical action uptake depending upon the recommendation. Understanding the barriers and facilitators to uptake by both patients and providers will be essential for optimizing HRA tools and achieving their promise of improving population health. Trial registration: Clinicaltrials.gov number NCT01956773, registered 10/8/2013.

Using a patient’s genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers—the cases—at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.

A family health history-based risk assessment is particularly valuable for guiding cancer screening and treatment strategies, yet an optimal implementation depends upon end-users’ values and needs. This is not only true prior to disease development, but also for those already affected. The aim of this study is to explore perceptions of the value of knowing one’s family health history (FHH)-based risk, experience using a patient-facing FHH tool and the potential of the tool for wider implementation. Twenty multi-ethnic Asian patients undergoing breast cancer treatment in Singapore completed an FHH-based risk assessment. Semi-structured one-on-one interviews were conducted and data were thematically analyzed. All participants were female and slightly more than half were Chinese. The acceptance and usage of an FHH risk assessment tool for cancers and its broader implementation was affected by a perceived importance of personal control over early detection, patient concerns of anxiety for themselves and their families due to risk results, concerns for genetic discrimination, adequacy of follow-up care plans and Asian cultural beliefs toward disease and dying. This study uniquely sheds light on the factors affecting Asian breast cancer patients’ perceptions about undergoing an FHH-based risk assessment, which should inform steps for a broader implementation in Asian healthcare systems.

Background: The presence of hereditary cancer syndromes in cancer patients can have an impact on current clinical care and post-treatment prevention and surveillance measures. Several barriers inhibit identification of hereditary cancer syndromes in routine practice. This paper describes the impact of using a patient-facing family health history risk assessment platform on the identification and referral of breast cancer patients to genetic counselling services. Methods: This was a hybrid implementation-effectiveness study completed in breast cancer clinics. English-literate patients not previously referred for genetic counselling and/or gone through genetic testing were offered enrollment. Consented participants were provided educational materials on family health history collection, entered their family health history into the platform and completed a satisfaction survey. Upon completion, participants and their clinicians were given personalized risk reports. Chart abstraction was done to identify actions taken by patients, providers and genetic counsellors. Results: Of 195 patients approached, 102 consented and completed the study (mean age 55.7, 100 % women). Sixty-six (65 %) met guideline criteria for genetic counseling of which 24 (36 %) were referred for genetic counseling. Of those referred, 13 (54 %) participants attended and eight (33 %) completed genetic testing. On multivariate logistic regression, referral was not associated with age, cancer stage, or race but was associated with clinical provider (p = 0.041). Most providers (71 %) had higher referral rates during the study compared to prior. The majority of participants found the experience useful (84 %), were more aware of their health risks (83 %), and were likely to recommend using a patient-facing platform to others (69 %). Conclusions: 65 % of patients attending breast cancer clinics in this study are at-risk for hereditary conditions based on current guidelines. Using a patient-facing risk assessment platform enhances the ability to identify these patients systematically and with widespread acceptability and recognized value by patients. As only a third of at-risk participants received referrals for genetic counseling, further understanding barriers to referral is needed to optimize hereditary risk assessment in oncology practices. Trial Registration: NIH Clinical Trials registry, NCT04639934. Registered Nov 23, 2020 -- Retrospectively registered.