Implementation of personalised medicine policies in mental healthcare: results from a stated preference study in the UK

BACKGROUND

Public support for the implementation of personalised medicine policies (PMPs) within routine care is important owing to the high financial costs involved and the potential for redirection of resources from other services.

AIMS

We aimed to determine the attributes of a PMP most likely to elicit public support for implementation. We also aimed to determine whether such support differed between a depression PMP and one for cystic fibrosis.

METHOD

In a discrete-choice experiment, paired vignettes illustrating both the current model of care (CMoC) and a hypothetical PMP for either depression or cystic fibrosis were presented to a representative sample of the UK public (n = 2804). Each vignette integrated varying attributes, including anticipated therapeutic benefit over CMoC, and the annual cost to the taxpayer. Respondents were invited to express their preference for either the PMP or CMoC within each pair.

RESULTS

The financial cost was the most important attribute influencing public support for PMPs. Respondents favoured PMP implementation where it benefited a higher proportion of patients or was anticipated to be more effective than CMoC. A reduction in services for non-eligible patients reduced the likelihood of support for PMPs. Respondents were more willing to fund PMPs for cystic fibrosis than for depression.

CONCLUSIONS

Cost is a significant factor in the public's support for PMPs, but essential caveats, such as protection for services available to PMP-ineligible patients, may also apply. Further research should explore the factors contributing to condition-specific nuances in public support for PMPs.

Does Controlling for Scale Heterogeneity Better Explain Respondents' Preference Segmentation in Discrete Choice Experiments? A Case Study of US Health Insurance Demand

Analyses of preference evidence frequently confuse heterogeneity in the effects of attribute parameters (i.e., taste coefficients) and the scale parameter (i.e., variance). Standard latent class models often produce unreasonable classes with high variance and disordered coefficients because of confounding estimates of effect and scale heterogeneity. In this study, we estimated a scale-adjusted latent class model in which scale classes (heteroskedasticity) were identified using respondents' randomness in choice behavior on the internet panel (e.g., time to completion and time of day). Hence, the model distinctly explained the taste/preference variation among classes associated with individual socioeconomic characters, in which scales are adjusted. Using data from a discrete-choice experiment on US health insurance demand among single employees, the results demonstrated how incorporating behavioral data enhances the interpretation of heterogeneous effects. Once scale heterogeneity was controlled, we found substantial heterogeneity with 4 taste classes. Two of the taste classes were highly premium sensitive (economy class), coming mostly from the low-income group, and the class associated with better educational backgrounds preferred to have a better quality of coverage of health insurance plans. The third class was a highly quality-sensitive class, with a higher SES background and lower self-stated health condition. The last class was identified as stayers, who were not premium or quality sensitive. This case study demonstrates that one size does not fit all in the analysis of preference heterogeneity. The novel use of behavioral data in the latent class analysis is generalizable to a wide range of health preference studies.

Enhancing Public Health Messaging: Discrete-Choice Experiment Evidence on the Design of HIV Testing Messages in China

Introduction. While a growing literature documents the effectiveness of public health messaging on social media, our understanding of the factors that encourage individuals to engage with and share messages is limited. In the context of human immunodeficiency virus (HIV) among men who have sex with men (MSM) in China, rising incidence and low testing rates despite decades of interventions suggest the need for effective, targeted messaging to reach underserved populations. Social media platforms and sex-seeking apps present a promising avenue, as web-based strategies can take advantage of existing trust within dense social networks. Methods. We conducted an online discrete-choice experiment in January 2017 with MSM from across China. Participants were presented with 6 choice tasks, each composed of 2 messages about HIV testing, and were asked in which scenario they were more likely to share the content. Participants were given information about the source of the HIV testing message, the social media sharing platform, and the recipients with whom they would share the message. They were given the option of sharing 1 message or neither. Multinomial and mixed logit models were used to model preferences within 4 subgroups. Results. In total, 885 MSM joined the survey, completing 4387 choice tasks. The most important attribute for 3 of the 4 subgroups was social media sharing platform. Men were more willing to share messages on sex-seeking mobile applications and less willing to share materials on generic (non-MSM) social media platforms. We found that men with more active online presences were less willing to share HIV testing messages on generic social media platforms. Conclusions. Our findings suggest that sex-seeking platforms represent a targeted, efficient method of actively engaging MSM in public health interventions.

Patient and physician preferences for ulcerative colitis treatments in the United States

Purpose: This study aimed to elicit patient and physician preferences for ulcerative colitis (UC) treatments in the United States (US).

Patients and methods: The following UC treatment attributes included in the discrete-choice experiment (DCE) were identified during qualitative interviews with both patients and physicians: time to symptom improvement, chance of long-term symptom control, risks of serious infection and malignancy, mode and frequency of administration, and need for steroids. The DCE survey instruments were developed and administered to patients and physicians. A random-parameters logit model was used to estimate preference weights and conditional relative importance for these attributes.

Results: A total of 200 patients with moderate to severe UC (status determined using self-reported medication history) and 200 gastroenterologists completed the survey. Patients’ average age was 42 years; most (59%) were female. Patients considered symptom control 2.5 times as important as time to symptom improvement and 5-year risk of malignancy almost as important as long-term symptom control (relative importance, 0.79 vs 0.96 for long-term symptom control); they preferred oral to subcutaneous or intravenous administration (relative importance, 0.47 vs 0.11 and 0.18, respectively). For physicians, symptom control was the most important attribute and was five times as important as the risk of malignancy.

Conclusion: Both patients and physicians considered long-term symptom control the most important attribute relative to others; however, risk of malignancy was of almost-equal importance to patients but not physicians. Differences between patients’ and physicians’ preferences highlight the need for improved communication about the relevant benefits and risks of different UC treatments to improve therapeutic decision-making.

Comparing the Noncomparable: The Need for Equivalence Measures That Make Sense in Health-Economic Evaluations

BACKGROUND

The popularity of quality-adjusted life years (QALYs) has been resistant to concerns about validity and reliability. Utility-theoretic outcome equivalents are widely used in other areas of applied economics. Equivalence values can be derived for time, money, risk, and other metrics. These equivalence measures preserve all available information about individual preferences and are valid measures of individual welfare changes.

OBJECTIVE

The objective of this study was to derive alternative generalized equivalence measures from first principles and illustrate their application in an empirical comparative-effectiveness example.

METHODS

We specify a general-equilibrium model incorporating neoclassical utility functions, health production function, severity-duration preferences, and labor-market tradeoff function. The empirical implementation takes advantage of discrete-choice experiment methods that are widely accepted in other areas of applied economics and increasingly in health economics. We illustrate the practical significance of restrictive QALY assumptions using comparative-effectiveness results based on both QALYs and estimates of welfare-theoretic time-equivalent values for anti-tumor necrosis factor and prolonged corticosteroid treatments for Crohn's disease in three distinct preference classes.

RESULTS

The QALY difference between the two treatments is 0.2 months, while time-equivalent values range between 0.5 and 1.3 months for aggregate and class-specific differences. Thus, the QALY-based analysis understates welfare-theoretic values by 60%-85%.

CONCLUSION

These results suggest that using disease-specific equivalence values offer a meaningful alternative to QALYs to compare global outcomes across treatments. The equivalence values approach is consistent with principles of welfare economics and offers several features not represented in QALYs, including accounting for preference nonlinearities in disease severity and duration, inclusion of preference-relevant nonclinical healthcare factors, representing preferences of clinically-relevant patient subpopulations, and including utility losses related to risk aversion.

Patient Preferences in Regulatory Benefit-Risk Assessments: A US Perspective

Demands for greater transparency in US regulatory assessments of benefits and risks, together with growing interest in engaging patients in Food and Drug Administration regulatory decision making, have resulted in several recent regulatory developments. Although Food and Drug Administration's Center for Drug Evaluation and Research (CDER) and Center for Devices and Radiological Health (CDRH) have established patient-engagement initiatives, CDRH has proposed guidelines for considering quantitative data on patients' benefit-risk perspectives, while CDER has focused on a more qualitative approach. We summarize two significant studies that were developed in collaboration and consultation with CDER and CDRH. CDER encouraged a patient advocacy group to propose draft guidance on engaging patient and caregiver stakeholders in regulatory decision making for Duchenne muscular dystrophy. CDRH sponsored a discrete-choice experiment case study to quantify obese respondents' perspectives on "meaningful benefits." CDRH and CDER issued draft guidance in May and June 2015, respectively, on including patient-preference data in regulatory submissions. Both organizations face challenges. CDER is working on integrating qualitative data into existing evidence-based review processes and is exploring options for therapeutic areas not included on a priority list. CDRH has adopted an approach that requires patient-preference data to satisfy standards of valid scientific evidence. Although that strategy could facilitate integrating patient perspectives directly with clinical data on benefits and harms, generating such data requires building capacity.

Physician preferences for bone metastasis drug therapy in Canada

BACKGROUND

Currently in Canada, several bone-targeted agents (btas) with varying characteristics are available for the prevention of skeletal-related events (sres) in patients with bone metastasis secondary to solid tumours. In the present study, we evaluated the preferences of physicians in Canada for the various attributes of the available btas.

METHODS

Physicians treating patients with bone metastasis from solid tumours were invited to complete an online discrete-choice experiment. Respondents were asked to choose between pairs of hypothetical medications for virtual patients. Each hypothetical medication was described based on predefined key attributes: time until first sre, time until worsening of pain, medication-related annual risk of osteonecrosis of the jaw (onj), medication-related annual risk of renal impairment, and mode of administration. A random-parameters logit model was used to analyze the choices between hypothetical medications and thus infer physician preferences for medication attributes.

RESULTS

Responses from the 200 physicians who completed the discrete-choice experiment suggested that months until first sre, risk of renal impairment, and months until worsening of pain were considered the most important attributes affecting choice of bta. The annual risk of onj was considered the least important attribute.

CONCLUSIONS

When making treatment decisions about the choice of bta for patients with bone metastasis from solid tumours, delaying sres and worsening of pain, and reducing the risk of renal impairment are primary considerations for physicians in Canada.

Accounting for Attribute-Level Non-Attendance in a Health Choice Experiment: Does it Matter?

An extensive literature has established that it is common for respondents to ignore attributes of the alternatives within choice experiments. In most of the studies on attribute non-attendance, it is assumed that respondents consciously (or unconsciously) ignore one or more attributes of the alternatives, regardless of their levels. In this paper, we present a new line of enquiry and approach for modelling non-attendance in the context of investigating preferences for health service innovations. This approach recognises that non-attendance may not just be associated with attributes but may also apply to the attribute's levels. Our results show that respondents process each level of an attribute differently: while attending to the attribute, they ignore a subset of the attribute's levels. In such cases, the usual approach of assuming that respondents either attend to the attribute or not, irrespective of its levels, is erroneous and could lead to misguided policy recommendations. Our results indicate that allowing for attribute-level non-attendance leads to substantial improvements in the model fit and has an impact on estimated marginal willingness to pay and choice predictions.

How does cost matter in health-care discrete-choice experiments?

Willingness-to-pay (WTP) estimates derived from discrete-choice experiments (DCEs) generally assume that the marginal utility of income is constant. This assumption is consistent with theoretical expectations when costs are a small fraction of total income. We analyze the results of five DCEs that allow direct tests of this assumption. Tests indicate that marginal utility often violates theoretical expectations. We suggest that this result is an artifact of a cognitive heuristic that recodes cost levels from a numerical scale to qualitative categories. Instead of evaluating nominal costs in the context of a budget constraint, subjects may recode costs into categories such as 'low', 'medium', and 'high' and choose as if the differences between categories were equal. This simplifies the choice task, but undermines the validity of WTP estimates as welfare measures. Recoding may be a common heuristic in health-care applications when insurance coverage distorts subjects' perception of the nominal costs presented in the DCE instrument. Recoding may also distort estimates of marginal rates of substitution for other attributes with numeric levels. Incorporating 'cheap talk' or graphic representation of attribute levels may encourage subjects to be more attentive to absolute attribute levels.