Measuring High-Risk Patients' Preferences for Pharmacogenetic Testing to Reduce Severe Adverse Drug Reaction: A Discrete Choice Experiment

Estimating preferences and willingness to pay for pharmacogenetic testing in populations who are medically underserved: a discrete choice experiment

Background: The implementation of pharmacogenetic (PGx) testing may contribute to health disparities if access to testing is inequitable, as medically underserved patients are prescribed higher rates of drugs with PGx guidelines and often experience the benefits of emerging health technologies last. Limited research has evaluated potential implementation of PGx testing in populations who are medically underserved and none have evaluated their preferences regarding PGx test characteristics and cost. Our study endeavored to assess the willingness to pay for PGx testing and key PGx test preferences in a nationwide cohort of medically underserved respondents. Methods: A survey was developed to assess willingness to pay and preferences for PGx testing through a discrete choice experiment (DCE). Five attributes of PGx tests were included in the DCE: doctor recommendation, wait time, number of actionable results, benefit of the test (avoid a side effect or address a health problem), and out-of-pocket cost. A convenience sample of U.S. adults with an average yearly household income of $42,000 or less was collected utilizing an online survey fielded by Qualtrics Research Services (Provo, UT). For the DCE analysis, conditional logit and mixed-logit regression models were utilized to determine relative utility of attributes and levels, conditional relative importance for each attribute, and marginal willingness to pay. Results: Respondents completed the survey with an 83.1% response completion rate. Following quality control procedures, 1,060 respondents were included in the final nationwide cohort. Approximately, 82% of respondents were willing to pay less than $100 for PGx testing, and a strong price ceiling was identified at $200. Out-of-pocket cost was the attribute identified as having the greatest relative importance on choice, while wait time had the lowest importance. Greater utility was observed if the PGx test was doctor recommended, had a higher number of actionable results, and resolved major or minor health problems compared with avoiding side effects. Conclusion: This first-of-its-kind study provides important insights into the willingness to pay for PGx testing and PGx test preferences of a large medically underserved population. Applying these findings can potentially lead to improvements in the successful implementation of PGx testing in this population.

Assessing the utility of measurement methods applied in economic evaluations of pharmacogenomics applications

An increasing number of economic evaluations are published annually investigating the economic effectiveness of pharmacogenomic (PGx) testing. This work was designed to provide a comprehensive summary of the available utility methods used in cost-effectiveness/cost-utility analysis studies of PGx interventions. A comprehensive review was conducted to identify economic analysis studies using a utility valuation method for PGx testing. A total of 82 studies met the inclusion criteria. A majority of studies were from the USA and used the EuroQol-5D questionnaire, as the utility valuation method. Cardiovascular disorders was the most studied therapeutic area while discrete-choice studies mainly focused on patients' willingness to undergo PGx testing. Future research in applying other methodologies in PGx economic evaluation studies would improve the current research environment and provide better results.

Cost-effectiveness of HLA-B*58:01 testing to prevent Stevens-Johnson syndrome/toxic epidermal necrolysis in Vietnam

Background: HLA-B*58:01 is strongly associated with allopurinol-induced Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) in Vietnam. This study assessed the cost-effectiveness of this testing to prevent SJS/TEN. Methods: A model was developed to compare three strategies: no screening, use allopurinol; HLA-B*58:01 screening; and no screening, use probenecid. A willingness-to-pay of three-times gross domestic product per capita was used. Results: Compared with 'no screening, use allopurinol', 'screening' increased quality-adjusted life-years by 0.0069 with the incremental cost of Vietnam dong (VND) 14,283,633 (US$617), yielding an incremental cost-effectiveness ratio of VND 2,070,459,122 (US$89,398) per quality-adjusted life-year. Therefore, 'screening' was unlikely to be cost-effective under the current willingness-to-pay. Testing's cost-effectiveness may change with targeted high-risk patients, reimbursed febuxostat or lower probenecid prices. Conclusion: The implementation of nationwide HLAB*58:01 testing before the use of allopurinol is not cost-effective, according to this analysis. This may be due to the lack of quality data on the effectiveness of testing and costing data in the Vietnamese population.

Preferences for pharmacogenomic testing in polypharmacy patients: a discrete choice experiment

Aim: To elicit preferences for pharmacogenomic (PGx) testing in polypharmacy patients. Materials & methods: A face-to-face discrete choice experiment survey was designed and administered to adult polypharmacy patients recruited at a local retail pharmacy in Albuquerque (NM, USA). Results: A total of 128 eligible polypharmacy patients completed the discrete choice experiment survey and significantly preferred a PGx test with lower cost, better confidentiality and higher certainty of identifying best medication/dose and side effects and one that can be used to advocate for their treatment needs (all p < 0.01). Conclusion: This is the first study eliciting preferences for PGx testing among polypharmacy patients. The study found most polypharmacy patients were willing to take a PGx test and their preferences were mostly influenced by test cost.

Physicians’ preferences and willingness to pay for artificial intelligence-based assistance tools: a discrete choice experiment among german radiologists

Background

Artificial Intelligence (AI)-based assistance tools have the potential to improve the quality of healthcare when adopted by providers. This work attempts to elicit preferences and willingness to pay for these tools among German radiologists. The goal was to generate insights for tool providers and policymakers regarding the development and funding of ideally designed and priced tools. Ultimately, healthcare systems can only benefit from quality enhancing AI when provider adoption is considered.

Methods

Since there is no established market for AI-based assistance tools in radiology yet, a discrete choice experiment was conducted. Respondents from the two major German professional radiology associations chose between hypothetical tools composed of five attributes and a no-choice option. The attributes included: provider, application, quality impact, time savings and price. A conditional logit model was estimated identifying preferences for attribute levels, the no-choice option, and significant subject-related interaction effects.

Results

114 respondents were included for analysis of which 46% were already using an AI-based assistance tool. Average adoption probability for an AI-based tool was 81% (95% CI 77.1% − 84.4%). Radiologists preferred a tool that assists in routine diagnostics performing at above-radiologist-level quality and saves 50% in diagnostics time at a price-point of €3 per study. The provider is not a significant factor in the decisions. Time savings were considered more important than quality improvements (i.e., detecting more anomalies).

Conclusions

Radiologists are overall willing to invest in AI-based assistance tools. Development, funding, and research regarding these tools should, however, consider providers’ preferences for features of immediate everyday and economic relevance like time savings to optimize adoption.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07769-x.

Factors affecting willingness to pay for NHS-based orthodontic treatment

Objective To assess factors affecting willingness to pay for orthodontic treatment.Methods An online discrete choice experiment and willingness to pay study was conducted on a convenience sample of 250 participants aged 16 and above over a four-month period. Participants completed a series of stated-preference tasks, in which they viewed choice sets with two orthodontic treatment options involving different combinations of attributes: family income; cost to patient; cause of problem; prevention of future problems; age; severity of the problem; and self-esteem/confidence.Results Family income, cost to patient, cause of the problem, age and self-esteem/confidence were the most important attributes influencing participants' decisions to have orthodontic treatment. Participants felt that free NHS-based orthodontic provision should be prioritised for those under 18, regardless of family income, for those with developmental anomalies, particularly where self-esteem and confidence are affected, with younger participants (aged 16-24 years) strongly preferring full NHS funding for those under 18 years old (p = 0.007, 95% CI: 0.57-0.09) who dislike smiling in public, especially where self-esteem and confidence are impaired (p = 0.002, 95% CI: 0.16-0.71). Participants with high annual income had the highest preference for the NHS to fund treatment regardless of income (p = 0.02, 95% CI: 0.13-1.47) and placed an onus on addressing developmental anomalies (p = 0.004, 95% CI: 0.22-1.15). In total, 159 (63.6%) of those who would undergo treatment were willing to pay for it, with the majority (88%) open to paying up to £2,000 and only three participants stating the NHS should not contribute towards the cost of orthodontic treatment.Conclusions Based on this pilot study, key factors influencing the decision to undergo treatment included family income, cost, the aetiology of malocclusion, age and self-esteem/confidence. It was felt that free NHS-based treatment should be given priority where self-esteem and confidence are impaired among young people. Further research to inform the priorities underpinning the provision of dental care and orthodontic treatment within the NHS is required.

Perceived fairness of direct-to-consumer genetic testing business models

Although consumers and experts often express concerns regarding the questionable business practices of direct-to-consumer (DTC) genetic testing services (e.g., reselling of consumers' genetic data), the DTC genetic testing market keeps expanding rapidly. We employ retail fairness as our theoretical lens to address this seeming paradox and conduct a discrete choice experiment with 16 attributes to better understand consumers' fairness perceptions of DTC genetic testing business models. Our results suggest that, while consumers perceive privacy-preserving DTC genetic testing services fairer, price is the main driver for fairness perception. We contribute to research on consumer perceptions of DTC genetic testing by investigating consumer preferences of DTC genetic testing business models and respective attributes. Further, this research contributes to knowledge about disruptive business models in healthcare and retail fairness by contextualizing the concept of retail fairness in the DTC genetic testing market. We also demonstrate how to utilize discrete choice experiments to elicit perceived fairness.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12525-022-00571-x.

A Systematic Review of Discrete Choice Experiments and Conjoint Analysis on Genetic Testing

BACKGROUND

Although genetic testing has the potential to offer promising medical benefits, concerns regarding its potential negative impacts may influence its acceptance. Users and providers need to weigh the benefits, costs and potential harms before deciding whether to take up or recommend genetic testing. Attribute-based stated-preference methods, such as discrete choice experiment (DCE) or conjoint analysis, can help to quantify how individuals value different features of genetic testing.

OBJECTIVES

The aim of this paper was to conduct a systematic review of DCE and conjoint analysis studies on genetic testing, including genomic tests.

METHODS

A systematic search was conducted in seven databases: Web of Science, CINAHL Plus with Full Text (EBSCO), PsycINFO, PubMed, Embase, The Cochrane Library and SCOPUS. The search was conducted in February 2021 and was limited to English peer-reviewed articles published until the search date. The search keywords included relevant keywords such as 'genetic testing', 'genomic testing', 'pharmacogenetic testing', 'discrete choice experiment' and 'conjoint analysis'. Narrative synthesis of the studies was conducted on survey population, testing type, recruitment and data collection, survey development, questionnaire content, survey validity, analysis, outcomes and other design features.

RESULTS

Of the 292 articles retrieved, 38 full-text articles were included in this review. Nearly two-thirds of the studies were published since 2015 and all were conducted in high-income countries. Survey samples included patients, parents, general population and healthcare providers. The articles assessed preferences for pharmacogenetic testing (28.9%), predictive testing and diagnostic testing (18.4%), while only one (2.6%) study investigated preferences for carrier testing. The most common sampling method was convenience sampling (57.9%) and the majority recruited participants via web-enabled surveys (60.5%). Review of literature (84.6%), discussions with healthcare professionals (71.8%) and cognitive interviews (53.8%) were commonly used for attribute identification. A survey validity test was included in only one-quarter of the studies (28.2%). Cost attributes were the most studied attribute type (76.9%), followed by risk attributes (61.5%). Among those that reported relative attribute importance, attributes related to benefits were the most commonly reported attributes with the highest relative attribute importance. Preference heterogeneity was investigated in most studies by modelling, such as via mixed logit analysis (82.1%) and/or by using interaction effects with respondent characteristics (74.4%). Willingness to pay was the most commonly estimated outcome and was presented in about two-thirds (n = 25; 64.1%) of the studies.

CONCLUSION

With the continuous advancement in genetic technology resulting in expanding options for genetic testing and improvements in delivery methods, the application of genetic testing in clinical care is expected to rise. DCEs and conjoint analysis remain robust and useful methods to elicit preferences of potential stakeholders. This review serves as a summary for future researchers when designing similar studies.

Perspective on CYP2C19 genotyping test among patients with acute coronary syndrome - a qualitative study

Aim: Identify factors patients consider regarding CYP2C19 genotyping test to guide choice of antiplatelet therapy. Patients & methods: Patient's perception and attitude toward use of CYP2C19 genotyping test was gathered according to an interview guide. Thematic analysis was conducted. Results: A total of 14 patients were interviewed. The main factors found to influence uptake of CYP2C19 genotyping test are, convenience of genotyping test (n = 4), physician's recommendation (n = 11), prior explanation of genetic testing by medical personnel (n = 5) and inclination toward clopidogrel, with three sub-factors; less frequent dosing (n = 3), lower cost (n = 7) and lower risk of bleeding (n = 9). Conclusion: This study provided the information needed to develop a discrete choice experiment to empirically quantify patients' preference and willingness to pay for genetic testing and to simulate uptake.

Measuring preferences for CYP2C19 genotyping in patients with acute coronary syndrome - a discrete choice experiment

Aim: To evaluate the relative importance of CYP2C19 genotype-guided treatment attributes to patients. Patients & methods: A discrete choice experiment questionnaire was administered to 63 patients with acute coronary syndrome. Attributes examined in the discrete choice experiment questionnaire were: cost of genetic testing (S$50, S$100, S$200); cost of antiplatelet medication (S$100, S$500, S$1000); heart attack or stroke risk (5 in 100, 15 in 100, 25 in 100); bleeding risk (5 in 100, 15 in 100, 25 in 100); doctor's recommendation (yes, neutral). Mixed logit model was used for analysis. Results & conclusion: All attributes were important in patients' decision-making. Most displayed strong preference for doctor's recommendation and reduced heart attack or stroke risk. Genotyping was chosen by 63.5% of the patients.

Is HLA-B*58:01 genotyping cost effective in guiding allopurinol use in gout patients with chronic kidney disease?

Aim: Concerns for fatal severe cutaneous adverse reactions (SCARs) hamper allopurinol use. Methods and material: We adopted a health system perspective to evaluate the cost-effectiveness of HLA-B*58:01 genotyping before allopurinol initiation. A decision tree compared three treatment strategies in gout patients with chronic kidney disease who have higher risk for SCAR. They were standard allopurinol treatment followed by febuxostat in nonresponders, test-positive patients receive febuxostat while test-negative receive allopurinol and universal use of febuxostat. Results: The first strategy was the most cost effective. Genotyping dominated universal febuxostat use. Time horizon and SCAR incidence were the most influential factors on the incremental cost-effectiveness ratio. Conclusion: HLA-B*58:01 genotyping compared with standard allopurinol-febuxostat sequential treatment does not provide good value for money in gout with chronic kidney disease.

Pharmacogenomic Testing In Pediatrics: Navigating The Ethical, Social, And Legal Challenges

For the past several years, the implementation of pharmacogenetic (PGx) testing has become widespread in several centers and clinical practice settings. PGx testing may be ordered at the point-of-care when treatment is needed or in advance of treatment for future use. The potential benefits of PGx testing are not limited to adult patients, as children are increasingly using medications more often and at earlier ages. This review provides some background on the use of PGx testing in children as well as mothers (prenatally and post-natally) and discusses the challenges, benefits, and the ethical, legal, and social implications of providing PGx testing to children.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.

Economic burden of adverse drug reactions and potential for pharmacogenomic testing in Singaporean adults

Adverse drug reactions (ADRs) contribute to hospitalization but data on its economic burden is scant. Pre-emptive pharmacogenetic (PGx) testing can potentially reduce ADRs and its associated costs. The objectives of this study were to quantify the economic burden of ADRs and to estimate the breakeven cost of pre-emptive PGx testing in Singapore. We collected itemized costs for 1000 random non-elective hospitalizations of adults admitted to a tertiary-care general hospital in Singapore. The presence of ADRs at admission and their clinical characteristics were reported previously. The economic burden of ADRs was assessed from two perspectives: (1) Total cost and (2) incremental costs. The breakeven cost of PGx testing was estimated by dividing avoidable hospitalization costs for ADRs due to selected drugs by the number of patients taking those drugs. The total cost of 81 admissions caused by ADRs was US$570,404. Costs were significantly higher for bleeding/elevated international normalized ratio (US$9906 vs. US$2251, p = 6.58 × 10^-3) compared to other ADRs, and for drugs acting on the blood coagulation system (US$9884 vs. US$2229, p = 4.41 × 10^-3) compared to other drug classes. There were higher incremental laboratory costs due to ADRs causing or being present at admission. The estimated breakeven cost of a pre-emptive PGx test for patients taking warfarin, clopidogrel, chemotherapeutic and neuropsychiatric drugs was US$114 per patient. These results suggest that future studies designed to directly measure the clinical and cost impact of a pre-emptive genotyping program will help inform clinical practice and health policy decisions.

Patient perspectives following pharmacogenomics results disclosure in an integrated health system

Aim: To assess patient perceptions and utilization of pharmacogenomics (PGx) testing in an integrated community health system. Methods: Fifty-seven patients completed an online survey assessing their experiences with PGx testing offered through two methods: a designated PGx clinic or direct access in-home testing. Results: The majority of participants perceived PGx testing as helpful in their healthcare and reported understanding their results. Some had concerns about privacy and discrimination; most lacked familiarity with the Genetic Information Nondiscrimination Act. There were no significant differences in views between participants tested through either model. Conclusion: Participants reported value in both methods of PGx testing. Patient experiences, understanding and result utilization will play an important role in informing future development and implementation of PGx programs.

Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review

BACKGROUND

Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood.

OBJECTIVE

We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications.

METHODS

We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist.

RESULTS

We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p > 0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences between classes. Less than half of the studies reported that individual characteristics were included in the segmentation models, and 30% reported that post-estimation analyses were conducted to examine class characteristics. While a higher percentage of studies discussed clinical implications of the segmentation results, an increasing number of studies proposed policy recommendations based on segmentation results since 2010.

CONCLUSIONS

LCA is increasingly used to study preference heterogeneity in health and support decision-making. However, there is little consensus on best practices as its application in health is relatively new. With an increasing demand to study preference heterogeneity, guidance is needed to improve the quality of applications of segmentation methods in health to support policy development and clinical practice.

Women's preferences, willingness-to-pay, and predicted uptake for single-nucleotide polymorphism gene testing to guide personalized breast cancer screening strategies: a discrete choice experiment

BACKGROUND

Single-nucleotide polymorphism (SNP) gene test is a potential tool for improving the accuracy of breast cancer risk prediction. We seek to measure women's preferences and marginal willingness-to-pay (mWTP) for this new technology.

MATERIALS AND METHODS

We administered a discrete choice experiment (DCE) to English-speaking Singaporean women aged 40-69 years without any history of breast cancer, enrolled via door-to-door recruitment with quota sampling by age and ethnicity. DCE attributes comprise: 1) sample type (buccal swab and dried blood spot), 2) person conducting pretest discussion (specialist doctor, non-specialist doctor, and nurse educator), 3) test location (private family clinic, public primary-care clinic, and hospital), and 4) out-of-pocket cost (S$50, S$175, and S$300). Mixed logit model was used to estimate the effect of attribute levels on women's preferences and mWTP. Interactions between significant attributes and respondent characteristics were investigated. Predicted uptake rates for various gene testing scenarios were studied.

RESULTS

A total of 300 women aged 52.6±7.6 years completed the survey (100 Chinese, Malay, and Indian women, respectively). Sample type (P=0.046), person conducting pretest discussion, and out-of-pocket cost (P<0.001) are significantly associated with going for SNP gene testing. Women with higher income and education levels are more willing to pay higher prices for the test. Preferences in terms of mWTP across ethnic groups appear similar, but Chinese women have greater preference heterogeneity for the attributes. Predicted uptake for a feasible scenario consisting of buccal swab, pretest discussion with nurse educator at the hospital costing S$50 is 60.5%. Only 3.3% of women always opted out of the SNP gene test in real life. Reasons include high cost, poor awareness, and indifference toward test results.

CONCLUSION

SNP gene testing may be tailored according to individual preferences to encourage uptake. Future research should focus on outcomes and cost-effectiveness of personalized breast cancer screening using SNP gene testing.

Primary care physician experiences with integrated pharmacogenomic testing in a community health system

Aim: To explore primary care physicians’ views of the utility and delivery of direct access to pharmacogenomics (PGx) testing in a community health system. Methods: This descriptive study assessed the perspectives of 15 healthcare providers utilizing qualitative individual interviews. Results: Three main themes emerged: perceived value and utility of PGx testing; challenges to implementation in practice; and provider as well as patient needs. Conclusion: While providers in this study viewed benefits of PGx testing as avoiding side effects, titrating doses more quickly, improving shared decision-making and providing psychological reassurance, challenges will need to be addressed such as privacy concerns, cost, insurance coverage and understanding the complexity of PGx test results.

Tailoring of recommendations to reduce serious cutaneous adverse drug reactions: a pharmacogenomics approach

The Health Sciences Authority launched a pharmacogenetics initiative in 2008 to facilitate evaluation of pharmacogenetics associations pertinent for Chinese, Malays and Indians in Singapore. The aim was to reduce the incidence and unpredictability of serious adverse drug reactions, with a focus on serious skin adverse drug reactions. This paper describes the gathering of evidence and weighing of factors that led to different genotyping recommendations for HLA-B*15:02 with carbamazepine and HLA-B*58:01 with allopurinol, despite both having strong genetic associations. Translation of pharmacogenomics at a national level requires careful deliberation of the prevalence of at-risk allele, strength of genetic associations, positive predictive value, cost-effectiveness and availability of alternative therapies. Our experience provides a perspective on translating genomic discoveries in advancing drug safety.

Predicted patient demand for a new delivery system for glaucoma medicine

Sustained-release drug delivery systems that replace the need for daily glaucoma medications will improve outcomes for those who are nonadherent and reduce the inconvenience of having to take medications on a recurring basis.The objective is to estimate uptake (i.e., demand) for a new technology that delivers sustained-release glaucoma medication and to investigate how uptake varies by product attributes, physician recommendations, peer adoption (i.e., percentage of patients seen in a clinic using the new technology), and patient characteristics.In a web-enabled discrete-choice experiment survey, glaucoma patients in the United States were asked to choose between continuing eye drop use or purchasing the new delivery system. In a cross-sectional web-enabled survey, ophthalmologists were asked their likelihood of recommending the new technology based on product and patient characteristics.Study participants were 500 glaucoma patients who were on topical administration of daily eye drops and 155 ophthalmologists who practice in the US.Main outcomes were predicted uptake for patients and likelihood of recommending a new drug delivery system for ophthalmologists. Logistic models were used to analyze the choice data.Uptake was estimated to be 18% at an annual cost of $1000 and to be 24% when the cost was $500. A physician's recommendation increased uptake by 6% to 12%, whereas an increase in peer adoption from 5% to 50% increased uptake by 3% to 7%. Patients aged ≥ 65 and those with lower income were more likely to remain on eye drops. Physicians were more likely to recommend a product if the interval between administrations is 6 months or longer and when long-term safety and efficacy data are available. They were less likely to recommend it to patients with lower income and no adherence problems.Results suggest a significant interest in an injectable solution or other sustained-release alternatives to daily eye drops. However, in this survey, patient uptake was greatly influenced by out-of-pocket cost and the interval between treatment administrations. Few physicians were willing to recommend sustained-release technology if the treatment interval was less than 3 months.

Assessing feasibility of delivering pharmacogenetic testing in a community pharmacy setting

AIM

To describe the rationale and design of a study evaluating the delivery of pharmacogenetic (PGx) testing in community pharmacies. Study rationale: Pharmacists have expressed interest in offering PGx testing; however, their lack of knowledge and experience, patients' acceptance and feasibility are unknown in this setting.

STUDY DESIGN

Through a cluster randomized trial, we will assess pharmacist and patient experiences with delivery of PGx testing as a standalone service or integrated into medication therapy management services. Anticipated results: We anticipate that PGx testing can be delivered in a community pharmacy setting and accepted and valued by patients.

CONCLUSION

This study is expected to provide valuable evidence about the real-world feasibility and acceptance of a community pharmacist-delivered approach of PGx testing.