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.

Quantifying the effects of risk-stratified breast cancer screening when delivered in real time as routine practice versus usual screening: the BC-Predict non-randomised controlled study (NCT04359420).

BACKGROUND: Risk stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) could provide a better balance of benefits and harms. We developed BC-Predict, to offer women when invited to the NHSBSP, which collects standard risk factor information; mammographic density; and in a sub-sample, a Polygenic Risk Score (PRS). METHODS: Risk prediction was estimated primarily from self-reported questionnaires and mammographic density using the Tyrer-Cuzick risk model. Women eligible for NHSBSP were recruited. BC-Predict produced risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5-<8% 10-year) to have appointments to discuss prevention and additional screening. RESULTS: Overall uptake of BC-Predict in screening attendees was 16.9% with 2472 consenting to the study; 76.8% of those received risk feedback within the 8-week timeframe. Recruitment was 63.2% with an onsite recruiter and paper questionnaire compared to <10% with BC-Predict only (P < 0.0001). Risk appointment attendance was highest for those at high risk (40.6%); 77.5% of those opted for preventive medication. DISCUSSION: We have shown that a real-time offer of breast cancer risk information (including both mammographic density and PRS) is feasible and can be delivered in reasonable time, although uptake requires personal contact. Preventive medication uptake in women newly identified at high risk is high and could improve the cost-effectiveness of risk stratification. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420).

How do women want to receive information about non-invasive prenatal testing? Evidence from a discrete choice experiment.

OBJECTIVE: Non-invasive prenatal testing (NIPT) identifies the risk of abnormalities in pregnancy, potentially reducing the risk of miscarriage associated with invasive tests. This study aimed to understand the preferences of current and future mothers about the content, format and timing of information provision about NIPT. METHODS: An online discrete choice experiment was designed comprising four attributes: when in the pregnancy information is provided (4 levels); degree of detail (2 levels); information format (6 levels); cost to women for gathering information (5 levels). Respondents included women identified by an online-panel company in Sweden. The mathematical design was informed by D-efficient criteria. Choice data were analysed using uncorrelated random parameters logit and latent class models. RESULTS: One thousand Swedish women (56% current mothers) aged 18-45 years completed the survey. On average, women preferred extensive information provided at/before 9 weeks of pregnancy. There was heterogeneity in preferences about the desired format of information provision (website, mobile app or individual discussion with a midwife) in the population. CONCLUSION: Women had clear preferences about the desired content, format and timing of information provision about NIPT. It is important to tailor information provision to enable informed choices about NIPT.

Testing for changes in biomass dynamics in large-scale forest datasets.

Tropical forest responses to climate and atmospheric change are critical to the future of the global carbon budget. Recent studies have reported increases in estimated above-ground biomass (EAGB) stocks, productivity, and mortality in old-growth tropical forests. These increases could reflect a shift in forest functioning due to global change and/or long-lasting recovery from past disturbance. We introduce a novel approach to disentangle the relative contributions of these mechanisms by decomposing changes in whole-plot biomass fluxes into contributions from changes in the distribution of gap-successional stages and changes in fluxes for a given stage. Using 30 years of forest dynamic data at Barro Colorado Island, Panama, we investigated temporal variation in EAGB fluxes as a function of initial EAGB (EAGBi ) in 10 × 10 m quadrats. Productivity and mortality fluxes both increased strongly with initial quadrat EAGB. The distribution of EAGB (and thus EAGBi ) across quadrats hardly varied over 30 years (and seven censuses). EAGB fluxes as a function of EAGBi varied largely and significantly among census intervals, with notably higher productivity in 1985-1990 associated with recovery from the 1982-1983 El Niño event. Variation in whole-plot fluxes among census intervals was explained overwhelmingly by variation in fluxes as a function of EAGBi , with essentially no contribution from changes in EAGBi distributions. The high observed temporal variation in productivity and mortality suggests that this forest is very sensitive to climate variability. There was no consistent long-term trend in productivity, mortality, or biomass in this forest over 30 years, although the temporal variability in productivity and mortality was so strong that it could well mask a substantial trend. Accurate prediction of future tropical forest carbon budgets will require accounting for disturbance-recovery dynamics and understanding temporal variability in productivity and mortality.

Eliciting Preferences for Information Provision in Newborn Bloodspot Screening Programs.

BACKGROUND: The national newborn bloodspot screening programs (NBSPs) are continually expanding to screen for more conditions. OBJECTIVES: To quantify parents' preferences for information and the way in which this is provided in example NBSPs. METHODS: A hybrid choice experiment, combining a conjoint analysis and a discrete choice experiment, was designed. A sample of current and future parents between the ages of 18 and 45 years was identified via an Internet panel. Respondents completed one of two survey versions (9 conditions and 20 conditions) comprising a validated measure of attitudes toward involvement in decision making, 6 CA questions (11 information attributes), 10 DCE questions (4 attributes: 3 process and the ability to make an informed decision), and demographic questions. RESULTS: Of the 702 respondents who completed the survey, 58% were women, 48% were between 25 and 34 years old, and 48% were current parents. All types of information were identified to statistically significantly improve parents' ability to make a decision. Participants preferred taking an "active" role in decision making. Respondents to the 9-condition survey preferred information before 20 weeks (willingness to pay [WTP] £11.88; CI £5.56 to £19.53) and the 20-condition group after 20 weeks (WTP £15.91; CI £10.64 to £21.63). All respondents disliked receiving information 3 days after birth, with the 20-condition group also being averse to receiving it on day 5 (WTP -£11.20; CI -£18.40 to 5.72). Respondents in both groups preferred to receive their information in an individual discussion. CONCLUSIONS: This study suggests that parents' preferences for receiving NBS information differ from how this information is given in current UK practice.

A structured process for the validation of a decision-analytic model: application to a cost-effectiveness model for risk-stratified national breast screening.

BACKGROUND: Decision-makers require knowledge of the strengths and weaknesses of decision-analytic models used to evaluate healthcare interventions to be able to confidently use the results of such models to inform policy. A number of aspects of model validity have previously been described, but no systematic approach to assessing the validity of a model has been proposed. This study aimed to consolidate the different aspects of model validity into a step-by-step approach to assessing the strengths and weaknesses of a decision-analytic model. METHODS: A pre-defined set of steps were used to conduct the validation process of an exemplar early decision-analytic-model-based cost-effectiveness analysis of a risk-stratified national breast cancer screening programme [UK healthcare perspective; lifetime horizon; costs (£; 2021)]. Internal validation was assessed in terms of descriptive validity, technical validity and face validity. External validation was assessed in terms of operational validation, convergent validity (or corroboration) and predictive validity. RESULTS: The results outline the findings of each step of internal and external validation of the early decision-analytic-model and present the validated model (called 'MANC-RISK-SCREEN'). The positive aspects in terms of meeting internal validation requirements are shown together with the remaining limitations of MANC-RISK-SCREEN. CONCLUSION: Following a transparent and structured validation process, MANC-RISK-SCREEN has been shown to have satisfactory internal and external validity for use in informing resource allocation decision-making. We suggest that MANC-RISK-SCREEN can be used to assess the cost-effectiveness of exemplars of risk-stratified national breast cancer screening programmes (NBSP) from the UK perspective. IMPLICATIONS: A step-by-step process for conducting the validation of a decision-analytic model was developed for future use by health economists. Using this approach may help researchers to fully demonstrate the strengths and limitations of their model to decision-makers.

Understanding the Impact of Different Modes of Information Provision on Preferences for a Newborn Bloodspot Screening Program in the United Kingdom.

Introduction. This study aimed to understand the impact of alternative modes of information provision on the stated preferences of a sample of the public for attributes of newborn bloodspot screening (NBS) in the United Kingdom. Methods. An online discrete choice experiment survey was designed using 4 attributes to describe NBS (effect of treatment on the condition, time to receive results, whether the bloodspot is stored, false-positive rate). Survey respondents were randomized to 1 of 2 survey versions presenting the background training materials using text from a leaflet (leaflet version) or an animation (animation version). Heteroskedastic conditional logistic regression was used to estimate the effect of mode of information provision on error variance. Results. The survey was completed by 1,000 respondents (leaflet = 525; animation = 475). Preferences for the attributes in the DCE were the same in both groups, but the group receiving the animation version had 9% less error variance in their responses. Respondents completing the animation version gave higher ratings compared with the leaflet version in terms of ease of perceived understanding. Subgroup analysis suggested that the animation was particularly effective at reducing error variance for women (20%), people with previous children (16.5%), and people between the ages of 35 and 45 y (11.8%). Limitations. This study used simple DCE with 4 attributes, and the results may vary for more complex choice questions. Conclusion. This study provides evidence that that supplementing the information package offered to parents choosing to take part in NBS with an animation may aid them their decision making. Further research would be needed to test the animation in the health system. Implications. Researchers designing DCE should carefully consider the design of their training materials to improve the quality of data collected. Highlights: Prior to completing a discrete choice experiment about newborn bloodspot screening, respondents were shown information using either a leaflet-based or animated format.Respondents receiving information using an animation version reported that the information was slightly easier to understand and exhibited 9% less error variance in expressing their preferences for a newborn screening program.Using the animation version to present information appeared to have a larger impact in reducing the error variance of responses for specific respondents including women, individuals with children, individuals between the ages of 35 and 45 y, and individuals educated to degree level.

Capturing the Impact of Constraints on the Cost-Effectiveness of Cell and Gene Therapies: A Systematic Review.

OBJECTIVE: Decision-makers need to resolve constraints on delivering cell and gene therapies to patients as these treatments move into routine care. This study aimed to investigate if, and how, constraints that affect the expected cost and health consequences of cell and gene therapies have been included in published examples of cost-effectiveness analyses (CEAs). METHOD: A systematic review identified CEAs of cell and gene therapies. Studies were identified from previous systematic reviews and by searching Medline and Embase until 21 January 2022. Constraints described qualitatively were categorised by theme and summarised by a narrative synthesis. Constraints evaluated in quantitative scenario analyses were appraised by whether they changed the decision to recommend treatment. RESULTS: Thirty-two CEAs of cell (n = 20) and gene therapies (n = 12) were included. Twenty-one studies described constraints qualitatively (70% cell therapy CEAs; 58% gene therapy CEAs). Qualitative constraints were categorised by four themes: single payment models; long-term affordability; delivery by providers; manufacturing capability. Thirteen studies assessed constraints quantitatively (60% cell therapy CEAs; 8% gene therapy CEAs). Two types of constraint were assessed quantitatively across four jurisdictions (USA, Canada, Singapore, The Netherlands): alternatives to single payment models (n = 9 scenario analyses); improving manufacturing (n = 12 scenario analyses). The impact on decision-making was determined by whether the estimated incremental cost-effectiveness ratios crossed a relevant cost-effectiveness threshold for each jurisdiction (outcome-based payment models: n = 25 threshold comparisons made, 28% decisions changed; improving manufacturing: n = 24 threshold comparisons made, 4% decisions changed). CONCLUSION: The net health impact of constraints is vital evidence to help decision-makers scale up the delivery of cell and gene therapies as patient volume increases and more advanced therapy medicinal products are launched. CEAs will be essential to quantify how constraints affect the cost-effectiveness of care, prioritise constraints to be resolved, and establish the value of strategies to implement cell and gene therapies by accounting for their health opportunity cost.

Estimating the Cost of 3 Risk Prediction Strategies for Potential Use in the United Kingdom National Breast Screening Program.

Background: Economic evaluations have suggested that risk-stratified breast cancer screening may be cost-effective but have used assumptions to estimate the cost of risk prediction. The aim of this study was to identify and quantify the resource use and associated costs required to introduce a breast cancer risk-stratification approach into the English national breast screening program. Methods: A micro-costing study, conducted alongside a cohort-based prospective trial (BC-PREDICT), identified the resource use and cost per individual (£; 2021 price year) of providing a risk-stratification strategy at a woman's first mammography. Costs were calculated for 3 risk-stratification approaches: Tyrer-Cuzick survey, Tyrer-Cuzick with Volpara breast-density measurement, and Tyrer-Cuzick with Volpara breast-density measurement and testing for 142 single nucleotide polymorphisms (SNP). Costs were determined for the intervention as implemented in the trial and in the health service. Results: The cost of providing the risk-stratification strategy was calculated to be £16.45 for the Tyrer-Cuzick survey approach, £21.82 for the Tyrer-Cuzick with Volpara breast-density measurement, and £102.22 for the Tyrer-Cuzick with Volpara breast-density measurement and SNP testing. Limitations: This study did not use formal expert elicitation methods to synthesize estimates. Conclusion: The costs of risk prediction using a survey and breast density measurement were low, but adding SNP testing substantially increases costs. Implementation issues present in the trial may also significantly increase the cost of risk prediction. Implications: This is the first study to robustly estimate the cost of risk-stratification for breast cancer screening. The cost of risk prediction using questionnaires and automated breast density measurement was low, but full economic evaluations including accurate costs are required to provide evidence of the cost-effectiveness of risk-stratified breast cancer screening. Highlights: Economic evaluations have suggested that risk-stratified breast cancer screening may be a cost-effective use of resources in the United Kingdom.Current estimates of the cost of risk stratification are based on pragmatic assumptions.This study provides estimates of the cost of risk stratification using 3 strategies and when these strategies are implemented perfectly and imperfectly in the health system.The cost of risk stratification is relatively low unless single nucleotide polymorphisms are included in the strategy.

Quantifying the Impact of Capacity Constraints in Economic Evaluations: An Application in Precision Medicine.

BACKGROUND: Examples of precision medicine are complex interventions featuring both testing and treatment components. Because of this complexity, there are often barriers to the introduction of such interventions. Few economic evaluations attempt to determine the impact of these barriers on the cost-effectiveness of the intervention. This study presents a case study economic evaluation that illustrates how the value of implementation methods may be used to quantify the impact of capacity constraints in a decision-analytic model. METHODS: A baseline decision-analytic model-based economic evaluation of ALK mutation testing was reproduced from a published technology appraisal. Three constraints (commissioning awareness, localization of testing, and pathology laboratory capacity) were identified using qualitative interviews, parameterized, and incorporated into the model. Value of implementation methods were used alongside incremental cost-effectiveness ratios (ICERs) to quantify the impact on the cost-effectiveness and net monetary benefit (NMB) of each capacity constraint and from the 3 constraints combined. RESULTS: Each of the 3 capacity constraints resulted in a loss of NMB ranging from £7773 (0.1% of the total) per year for localized testing to £4,907,893 (77%) for a lack of awareness about commissioning ALK testing. When combined, the constraints resulted in a loss of NMB of £5,289,414 (83%). The localization and limited pathology capacity constraints slightly increased the ICER, but the lack of commissioning awareness constraint did not change the ICER. CONCLUSIONS: Capacity constraints may have a significant impact on the NMB produced by examples of precision medicine. Value of implementation methods can be used to quantify the impact of such constraints by combining the impact of the constraints on the cost-effectiveness of the intervention with the impact on the number of patients receiving the intervention. HIGHLIGHTS: While capacity constraints may prevent the use of precision medicine in clinical practice, economic evaluations rarely account for the impact of such barriers.This study demonstrates how constraints can be identified using qualitative methods and subsequently incorporated into decision-analytic models using quantitative value of implementation methods.In addition, this article demonstrates how value of implementation methods can be used to account for the impact of capacity constraints on the costs and benefits of an intervention as well as the number of patients receiving the intervention.In the case study presented herein, a capacity constraint reducing patient access to an example of precision medicine caused the biggest loss of net monetary benefit.Health economists should consider moving beyond incremental cost-effectiveness ratios to measures of total net monetary benefit to fully capture the impact of implementing precision medicine.

Implementing Interventions with Varying Marginal Cost-Effectiveness: An Application in Precision Medicine.

Purpose. A range of barriers may constrain the effective implementation of strategies to deliver precision medicine. If the marginal costs and consequences of precision medicine vary at different levels of implementation, then such variation will have an impact on relative cost-effectiveness. This study aimed to illustrate the importance and quantify the impact of varying marginal costs and benefits on the value of implementation for a case study in precision medicine. Methods. An existing method to calculate the value of implementation was adapted to allow marginal costs and consequences of introducing precision medicine into practice to vary across differing levels of implementation. This illustrative analysis used a case study based on a published decision-analytic model-based cost-effectiveness analysis of a 70-gene recurrence score (MammaPrint) for breast cancer. The impact of allowing for varying costs and benefits for the value of the precision medicine and of implementation strategies was illustrated graphically and numerically in both static and dynamic forms. Results. The increasing returns to scale exhibited by introducing this specific example of precision medicine mean that a minimum level of implementation (51%) is required for using the 70-gene recurrence score to be cost-effective at a defined threshold of €20,000 per quality-adjusted life year. The observed variation in net monetary benefit implies that the value of implementation strategies was dependent on the initial and ending levels of implementation in addition to the magnitude of the increase in patients receiving the 70-gene recurrence score. In dynamic models, incremental losses caused by low implementation accrue over time unless implementation is improved. Conclusions. Poor implementation of approaches to deliver precision medicine, identified to be cost-effective using decision-analytic model-based cost-effectiveness analysis, can have a significant economic impact on health systems. Developing and evaluating the economic impact of strategies to improve the implementation of precision medicine will potentially realize the more cost-effective use of health care budgets.

Prostate cancer survivors' preferences on the delivery of diet and lifestyle advice: a pilot best-worst discrete choice experiment.

BACKGROUND: Lifestyle factors, including diet and physical activity, are associated with prostate cancer progression and mortality. However, it is unclear how men would like lifestyle information to be delivered following primary treatment. This study aimed to identify men's preferences for receiving lifestyle information. METHODS: We conducted a cross-sectional pilot best-worst discrete choice experiment which was nested within a feasibility randomised controlled trial. Our aim was to explore men's preferences of receiving diet and physical activity advice following surgery for localised prostate cancer. Thirty-eight men with a mean age of 65 years completed best-worst scenarios based on four attributes: (1) how information is provided; (2) where information is provided; (3) who provides information; and (4) the indirect cost of receiving information. Data was analysed using conditional logistic regression. Men's willingness to pay (WTP) for aspects of the service was calculated using an out-of-pocket cost attribute. RESULTS: The combined best-worst analysis suggested that men preferred information through one-to-one discussion ß = 1.07, CI = 0.88 to 1.26) and not by email (ß = - 1.02, CI = - 1.23 to - 0.80). They preferred information provided by specialist nurses followed by dietitians (ß = 0.76, CI = 0.63 to 0.90 and - 0.16, CI = - 0.27 to - 0.05 respectively) then general nurses (ß = - 0.60, CI = - 0.73 to - 0.48). Three groups were identified based on their preferences. The largest group preferred information through individual face-to-face or group discussions (ß = 1.35, CI = 1.05 to 1.63 and 0.70, CI = 0.38 to 1.03 respectively). The second group wanted information via one-to-one discussions or telephone calls (ß = 1.89, CI = 1.41 to 2.37 and 1.03, CI = 0.58 to 1.48 respectively), and did not want information at community centres (ß = - 0.50, CI = - 0.88 to - 0.13). The final group preferred individual face-to-face discussions (ß = 0.45, CI = 0.03 to 0.88) but had a lower WTP value (£17). CONCLUSIONS: Men mostly valued personalised methods of receiving diet and physical activity information over impersonal methods. The out-of-pocket value of receiving lifestyle information was important to some men. These findings could help inform future interventions using tailored dietary and physical activity advice given to men by clinicians following treatment for prostate cancer, such as mode of delivery, context, and person delivering the intervention. Future studies should consider using discrete choice experiments to examine information delivery to cancer survivor populations.

Accounting for Capacity Constraints in Economic Evaluations of Precision 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. METHODS: A meta-review was conducted of published systematic reviews of economic evaluations of precision medicine (test-treat interventions) and individual studies included in these reviews. Due to the volume of studies identified, a sample of papers published from 2007 to 2015 was collated. A narrative analysis identified whether potential capacity constraints were discussed qualitatively in the studies and, if relevant, which quantitative methods were used to account for capacity constraints. RESULTS: A total of 45 systematic reviews of economic evaluations of precision medicine were identified, from which 222 studies focusing on test-treat interventions, published between 2007 and 2015, were extracted. Of these studies, 33 (15%) qualitatively discussed the potential impact of capacity constraints, including budget constraints; quality of tests and the testing process; ease of use of tests in clinical practice; and decision uncertainty. Quantitative methods (nine studies) to account for capacity constraints included static methods such as capturing inefficiencies in trials or models and sensitivity analysis around model parameters; and dynamic methods, which allow the impact of capacity constraints on cost effectiveness to change over time. CONCLUSIONS: Understanding the cost effectiveness of precision medicine is necessary, but not sufficient, evidence for its successful implementation. There are currently few examples of evaluations that have quantified the impact of capacity constraints, which suggests an area of focus for future research.

The role of information provision in economic evaluations of non-invasive prenatal testing: a systematic review.

BACKGROUND: Technological progress has led to changes in the antenatal screening programmes, most significantly the introduction of non-invasive prenatal testing (NIPT). The availability of a new type of testing changes the type of information that the parent(s) require before, during and after screening to mitigate anxiety about the testing process and results. OBJECTIVES: To identify the extent to which economic evaluations of NIPT have accounted for the need to provide information alongside testing and the associated costs and health outcomes of information provision. METHODS: A systematic review of economic evaluations of NIPTs (up to February 2018) was conducted. Medline, Embase, CINAHL and PsychINFO were searched using an electronic search strategy combining a published economic search filter (from NHS economic evaluations database) with terms related to NIPT and screening-related technologies. Data were extracted using the Consolidated Health Economic Evaluation Reporting Standards framework and the results were summarised as part of a narrative synthesis. RESULTS: A total of 12 economic evaluations were identified. The majority of evaluations (n = 10; 83.3%) involved cost effectiveness analysis. Only four studies (33.3%) included the cost of providing information about NIPT in their economic evaluation. Two studies considered the impact of test results on parents' quality of life by allowing utility decrements for different outcomes. Some studies suggested that the challenges of valuing information prohibited their inclusion in an economic evaluation. CONCLUSION: Economic evaluations of NIPTs need to account for the costs and outcomes associated with information provision, otherwise estimates of cost effectiveness may prove inaccurate.

Accounting for Scale Heterogeneity in Healthcare-Related Discrete Choice Experiments when Comparing Stated Preferences: A Systematic Review.

BACKGROUND: Scale heterogeneity, or differences in the error variance of choices, may account for a significant amount of the observed variation in the results of discrete choice experiments (DCEs) when comparing preferences between different groups of respondents. OBJECTIVE: The aim of this study was to identify if, and how, scale heterogeneity has been addressed in healthcare DCEs that compare the preferences of different groups. METHODS: A systematic review identified all healthcare DCEs published between 1990 and February 2016. The full-text of each DCE was then screened to identify studies that compared preferences using data generated from multiple groups. Data were extracted and tabulated on year of publication, samples compared, tests for scale heterogeneity, and analytical methods to account for scale heterogeneity. Narrative analysis was used to describe if, and how, scale heterogeneity was accounted for when preferences were compared. RESULTS: A total of 626 healthcare DCEs were identified. Of these 199 (32%) aimed to compare the preferences of different groups specified at the design stage, while 79 (13%) compared the preferences of groups identified at the analysis stage. Of the 278 included papers, 49 (18%) discussed potential scale issues, 18 (7%) used a formal method of analysis to account for scale between groups, and 2 (1%) accounted for scale differences between preference groups at the analysis stage. Scale heterogeneity was present in 65% (n = 13) of studies that tested for it. Analytical methods to test for scale heterogeneity included coefficient plots (n = 5, 2%), heteroscedastic conditional logit models (n = 6, 2%), Swait and Louviere tests (n = 4, 1%), generalised multinomial logit models (n = 5, 2%), and scale-adjusted latent class analysis (n = 2, 1%). CONCLUSIONS: Scale heterogeneity is a prevalent issue in healthcare DCEs. Despite this, few published DCEs have discussed such issues, and fewer still have used formal methods to identify and account for the impact of scale heterogeneity. The use of formal methods to test for scale heterogeneity should be used, otherwise the results of DCEs potentially risk producing biased and potentially misleading conclusions regarding preferences for aspects of healthcare.

What are colorectal cancer survivors' preferences for dietary advice? A best-worst discrete choice experiment.

PURPOSE: Studies on healthy lifestyle interventions in survivors of colorectal cancer have been disappointing, demonstrating only modest changes. This study aims to quantify people's preferences for different aspects of dietary intervention. METHOD: A best-worst discrete choice experiment was designed and incorporated into a questionnaire including participants' characteristics and a self-assessment of lifestyle. RESULTS: The response rate was 68% and 179 questionnaires were analysed. When analysing aggregate preferences, the modes of information provision selected as the most preferred were "face-to-face" (willingness to pay (WTP) £63.97, p ≤ 0.001) and "telephone" (WTP £62.36, p < 0.001) discussions whereas group discussions were preferred least (WTP -£118.96, p ≤ 0.001). Scenarios that included hospitals were most preferred (WTP £17.94, p = 0.031), and the favoured provider was bowel cancer nurses (WTP £75.11, p ≤ 0.001). When investigating preference heterogeneity, three sub-groups were identified: Firstly, "technophiles" preferring email (WTP £239.60, p ≤ 0.001) were male, were younger and had fewer risk factors. Secondly, a "one-to-one" group had strong preference for interventions over the telephone or at their local doctors and were older (WTP £642.13, p ≤ 0.001). Finally, a "person-centred" group preferred face-to-face individual or group sessions (WTP £358.79, p < 0.001) and had a high risk lifestyle. CONCLUSION: For survivors of colorectal cancer, there is not one approach that suits all when it comes to providing dietary advice. IMPLICATIONS FOR CANCER SURVIVORS: This is important information to consider when planning healthy lifestyle interventions which include dietary advice for survivors of colorectal cancer. Aligning services to individuals' preferences has the potential to improve patient experience and outcomes by increasing uptake of healthy lifestyle advice services and promoting a more tailored approach to dietary modifications, acknowledging sub-groups of people within the total population of colorectal cancer survivors.

The Role of Information Provision in Economic Evaluations of Newborn Bloodspot Screening: A Systematic Review.

BACKGROUND: The extent to which economic evaluations have included the healthcare resource and outcome-related implications of information provision in national newborn bloodspot screening programmes (NBSPs) is not currently known. OBJECTIVES: To identify if, and how, information provision has been incorporated into published economic evaluations of NBSPs. METHODS: A systematic review of economic evaluations of NBSPs (up to November 2014) was conducted. Three electronic databases were searched (Ovid: Medline, Embase, CINAHL) using an electronic search strategy combining a published economic search filter with terms related to national NBSPs and screening-related technologies. These electronic searches were supplemented by searching the NHS Economic Evaluations Database (NHS EED) and hand-searching identified study reference lists. The results were tabulated and summarised as part of a narrative synthesis. RESULTS: A total of 27 economic evaluations [screening-related technologies (n = 11) and NBSPs (n = 16)] were identified. The majority of economic evaluations did not quantify the impact of information provision in terms of healthcare costs or outcomes. Five studies did include an estimate of the time cost associated with information provision. Four studies included a value to reflect the disutility associated with parental anxiety caused by false-positive results, which was used as a proxy for the impact of imperfect information. CONCLUSION: A limited evidence base currently quantifies the impact of information provision on the healthcare costs and impact on the users of NBSPs; the parents of newborns. We suggest that economic evaluations of expanded NBSPs need to take account of information provision otherwise the impact on healthcare costs and the outcomes for newborns and their parents may be underestimated.