Stuart Wright

Cost-effectiveness analyses of genetic and genomic diagnostic tests

Developments in next-generation sequencing technologies have driven the clinical application of diagnostic tests that interrogate the whole genome, which offer the chance to diagnose rare inherited diseases or inform the targeting of therapies. New genomic diagnostic tests compete with traditional approaches to diagnosis, including the genetic testing of single genes and other clinical strategies, for finite health-care budgets. In this context, decision analytic model-based cost-effectiveness analysis is a useful method to help evaluate the costs versus consequences of introducing new health-care interventions. This Perspective presents key methodological, technical, practical and organizational challenges that must be considered by decision-makers responsible for the allocation of health-care resources to obtain robust and timely information about the relative cost-effectiveness of the increasing numbers of emerging genomic tests.

Scale Heterogeneity in Healthcare Discrete Choice Experiments: A Primer

Discrete choice experiments (DCEs) are used to quantify the preferences of specified sample populations for different aspects of a good or service and are increasingly used to value interventions and services related to healthcare. Systematic reviews of healthcare DCEs have focussed on the trends over time of specific design issues and changes in the approach to analysis, with a more recent move towards consideration of a specific type of variation in preferences within the sample population, called taste heterogeneity, noting rises in the popularity of mixed logit and latent class models. Another type of variation, called scale heterogeneity, which relates to differences in the randomness of choice behaviour, may also account for some of the observed ‘differences’ in preference weights. The issue of scale heterogeneity becomes particularly important when comparing preferences across subgroups of the sample population as apparent differences in preferences could be due to taste and/or choice consistency. This primer aims to define and describe the relevance of scale heterogeneity in a healthcare context, and illustrate key points, with a simulated data set provided to readers in the Online appendix.

Identifying variation in models of care for the genomic-based diagnosis of inherited retinal dystrophies in the United Kingdom.

PurposeAdvances in genomic technologies are prompting a realignment of diagnostic and management pathways for rare inherited disease. New models of care are being developed as genomic-based diagnostic testing becomes increasingly relevant within more and more aspects of medicine. This study describes current care models for the provision of a genomic-based diagnosis for patients with inherited retinal dystrophy (IRD) in UK clinical practice.MethodsA structured telephone survey, conducted (in 2014) with all 23 UK Regional Genetics Centres and a sample of specialist ophthalmology centres (n=4), was used to describe models of service delivery and current levels of genomic-based diagnostic testing. Quantitative data were summarised using descriptive statistics. Responses to open-ended questions were summarised using thematic analysis.ResultsOf the 27 centres 10 of them saw IRD patients in ‘generic’ clinics and 17 centres offered ophthalmic-specific clinics. Extensive regional variation was observed in numbers of patients seen and in how care for the diagnosis and management of IRD was provided.ConclusionsUnderstanding current practice is a necessary first step in the development and evaluation of complex interventions, such as care models for the genomic-based diagnosis of inherited eye conditions. Presented findings here relating to disparities in care provision are potentially linked to previously reported evidence of perceived unmet needs and expectations of IRD service users. This work provides a foundation for the integration of new care models in mainstream medicine.

Understanding barriers to the introduction of precision medicines in non-small cell lung cancer: A qualitative interview protocol

Background: While precision medicines targeting genetic mutations and alterations in non-small cell lung cancer (NSCLC) have been available since 2010, their adoption into clinical practice has been slow. Evidence suggests that a number of barriers, such as insufficient clinician knowledge, a need for training of test providers, or a lack of specific clinical guidelines, may slow the implementation of precision in general. However, little attention has been given to the barriers to providing precision medicines in NSCLC. The purpose of this protocol is to outline the design for a qualitative interview study to identify the barriers and facilitators to the provision of precision medicines for NSCLC. Methods: This study will use semi-structured interviews with clinicians (n=10), test providers (n=10), and service commissioners (n=10) to identify the perceived barriers and facilitators to providing historical, current, and future precision medicines in NSCLC. Participants will be identified through mailing list advertisements and snowball sampling. Recruitment will continue until data saturation, indicated by no new themes arising from the data. Interviews will be conducted by telephone to facilitate geographical diversity. The qualitative data will be analysed using a framework analysis with themes anticipated to relate to; relevant barriers to providing precision medicines, the impact of different barriers on medicine provision, changes in the ability to provide precision medicines over time, and strategies to facilitate the provision of precision medicines. Ethics: This study has been approved by the University of Manchester Proportionate Review Research Ethics Committee (Reference number: 2017-1885-3619). Written consent will be obtained from all participants. Conclusion: This study is the first to explore the barriers and facilitators to providing precision medicines for NSCLC in the English NHS. The findings will inform strategies to improve the implementation of future precision medicines. These findings will be disseminated in peer-reviewed publications and national and international conferences.

Understanding Midwives’ Preferences for Providing Information About Newborn Bloodspot Screening

Background: Understanding preferences for information provision in the context of health care service provision is challenging because of the number of potential attributes that may influence preferences. This study aimed to identify midwives’ preferences for the process and outcomes of information provision in an expanded national newborn bloodspot screening program. Design: A sample of practicing midwives completed a hybrid-stated preference survey including a conjoint analysis (CA) and discrete choice experiment to quantify preferences for the types of, and way in which, information should be provided in a newborn bloodspot screening program. Six conjoint analysis questions captured the impact of different types of information on parents’ ability to make a decision, and 10 discrete choice experiment questions identified preferences for four process attributes (including parents’ ability to make a decision). Results: Midwives employed by the UK National Health Service (n = 134) completed the survey. All types of information content were perceived to improve parents’ ability to make a decision except for the possibility of false-positive results. Late pregnancy was seen to be the best time to provide information, followed by day 3 postbirth. Information before 20 weeks of pregnancy was viewed as reducing parents’ ability to make a decision. Midwives preferred information to be provided by an individual discussion and did not think parents should receive information on the Internet. Conclusion: A hybrid stated preference survey design identified that a wide variety of information should be provided to maximize parents’ ability to make a decision ideally provided late in pregnancy or on day 3 postbirth.

Accounting for Capacity Constraints In Economic Evaluations of Stratified Medicine: A Systematic Review

Background and Objective Precision (stratified or personalised) medicine is underpinned by the premise that it is feasible to identify known heterogeneity using a specific test or algorithm in patient populations and to use this information to guide patient care to improve health and well-being. This study aimed to understand if, and how, previous economic evaluations of precision medicine had taken account of the impact of capacity constraints.

DECISION MAKING IN EXPANDED NEWBORN SCREENING; A QUALITATIVE STUDY EXAMINING CONSENT AND COMMUNICATION PREFERENCES OF PARENTS IN THE UK

WEB-ONLY ABSTRACTS E79 PS1-3 OVERTREATMENT AND COST-EFFECTIVENESS OF SEE-AND-TREAT APPROACH IN MANAGING CERVICAL SQUAMOUS INTRAEPITHELIAL LESIONS IN THE US SETTING Applied Health Economics (AHE) Kalatu R. Davies, Ph.D., Van T. Nghiem, M.S.P.H., J. Robert Beck, M.D., Michele Follen, MD, PhD and Scott B. Cantor, Ph.D., (1)The University of Texas MD Anderson Cancer Center, Department of Health Services Research, Houston, TX, (2)Fox Chase Cancer Center, Philadelphia, PA, (3)Department of Obstetrics & Gynecology, Brookdale University Hospital & Medical Center, Brooklyn, NY, (4)The University of Texas MD Anderson Cancer Center, Houston, TX