Physician and patient willingness to pay for electronic cardiovascular disease management

Physician preferences for treatment of low-density lipoprotein cholesterol among patients with atherosclerotic cardiovascular disease (ASCVD)-A discrete choice experiment

Objective

Approximately 80 % of patients with atherosclerotic cardiovascular disease (ASCVD) do not achieve the guideline-based target for low-density lipoprotein (LDL-C) levels in current clinical practice, particularly the 95 % of ASCVD patients receiving oral statin monotherapy. The objective was to determine physician prescribing preferences for LDL-C lowering therapies beyond statins for patients with ASCVD.

Methods

A discrete choice experiment (DCE) survey was administered to cardiologists and primary care physicians in the United States, presenting a series of treatment choices systematically varied across 8 treatment attributes: % LDL-C reduction, myalgias, other side effects, route and frequency of administration, time to prior authorization, patient monthly out-of-pocket cost (mOOP), and adherence. Data were analyzed using logistic regression to estimate preference weights for each attribute.

Results

A total of 200 cardiologists and 50 primary care physicians (PCPs) completed the survey. Both exhibited similar prescribing preferences, highly valuing efficacy in reducing LDL-C levels and minimization of patients OOP cost. Each additional 10 % reduction in LDL-C was associated with a 69 % relative increase in physician preference. By contrast, a 10 % relative decrease in preference was observed for each $10 additional monthly mOOP. Compared to PCPs, cardiologists tended to place more emphasis on LDL-C reduction, being more willing to accept higher mOOP or side effects. Although oral therapies were preferred, injectable therapies, like the PCSK9 siRNA-like drug, administered less frequently that allowed for greater LDL-C reduction were seen as having considerable utility, especially among patients with a history of medication nonadherence.

Conclusion

These results document considerable preference similarities among cardiologist and PCP prescribers of LDL-C lowering therapies for ASCVD. Broad availability of several therapies with varying administration frequencies and product profiles are likely of great value to prescribing physicians aiming to achieve target LDL-C concentrations. Considering all aspects of treatment, most participants preferred a PCSK9 siRNA-like drug.

Stakeholders' preferences for the design and delivery of virtual care services: A systematic review of discrete choice experiments

This systematic review aimed to synthesise evidence from discrete choice experiments (DCEs) eliciting preferences for virtual models of care, as well as to assess the quality of those DCEs and compare the relative preferences for different stakeholder groups. Articles were included if published between January 2010 and December 2022. Data were synthesised narratively, and attributes were assessed for frequency, significance, and relative importance using a semi-quantitative approach. Overall, 21 studies were included encompassing a wide range of virtual care modalities, with the most common setting being virtual consultations for outpatient management of chronic conditions. A total of 135 attributes were identified and thematically classified into six categories: service delivery, service quality, technical aspects, monetary aspects, health provider characteristics and health consumer characteristics. Attributes related to service delivery were most frequently reported but less highly ranked. Service costs were consistently significant across all studies where they appeared, indicating their importance to the respondents. All studies examining health providers' preferences reported either system performance or professional endorsement attributes to be the most important. Substantial heterogeneity in attribute selection and preference outcomes were observed across studies reporting on health consumers' preferences, suggesting that the consideration of local context is important in the design and delivery of person-centred virtual care services. In general, the experimental design and analysis methods of included studies were clearly reported and justified. An improvement was observed in the quality of DCE design and analysis in recent years, particularly in the attribute development process. Given the continued growth in the use of DCEs within healthcare settings, further research is needed to develop a standardised approach for quantitatively synthesising DCE findings. There is also a need for further research on preferences for virtual care in post-pandemic contexts, where emerging evidence suggests that preferences may differ to those observed in pre-pandemic times.

Preferences of older adults for healthcare models designed to improve care coordination: evidence from Western Switzerland

Implementing innovations in care delivery in Switzerland is challenging due to the fragmented nature of the system and the specificities of the political process (i.e., direct democracy, decentralized decision-making). In this context, it is particularly important to account for population preferences when designing policies. We designed a discrete choice experiment to study population preferences for coordination-improving care models. Specifically, we assessed the relative importance of model characteristics (i.e., insurance premium, presence of care coordinator, access to specialists, use of EMR, cost-sharing for chronic patients, incentives for informal care), and predicted uptake under different policy scenarios. We accounted for heterogeneity in preferences for the status quo option using an error component logit model. Respondents attached the highest importance to the price attribute (i.e. insurance premium) (0.31, CI: 0.27- 0.36) and to the presence of a care coordinator (0.27, CI: 0.23 - 0.31). Policy scenarios showed for instance that gatekeeping would be preferred to free access to specialists if the model includes a GP or an interprofessional team as a care coordinator. Although attachment to the status quo is high in the studied population, there are potential ways to improve acceptance of alternative care models by implementation of positively valued innovations.

Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis

Background

Despite the great potential of eHealth, substantial costs are involved in its implementation, and it is essential to know whether these costs can be justified by its benefits. Such needs have led to an increased interest in measuring the benefits of eHealth, especially using the willingness to pay (WTP) metric as an accurate proxy for consumers’ perceived benefits of eHealth. This offered us an opportunity to systematically review and synthesize evidence from the literature to better understand WTP for eHealth and its influencing factors.

Objective

This study aimed to provide a systematic review of WTP for eHealth and its influencing factors.

Methods

This study was performed and reported as per the Cochrane Collaboration and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, CINAHL Plus, Cochrane Library, EconLit, and PsycINFO databases were searched from their inception to April 19, 2022. We conducted random-effects meta-analyses to calculate WTP values for eHealth (at 2021 US dollar rates) and meta-regression analyses to examine the factors affecting WTP.

Results

A total of 30 articles representing 35 studies were included in the review. We found that WTP for eHealth varied across studies; when expressed as a 1-time payment, it ranged from US $0.88 to US $191.84, and when expressed as a monthly payment, it ranged from US $5.25 to US $45.64. Meta-regression analyses showed that WTP for eHealth was negatively associated with the percentages of women (β=−.76; P<.001) and positively associated with the percentages of college-educated respondents (β=.63; P<.001) and a country’s gross domestic product per capita (multiples of US $1000; β=.03; P<.001). Compared with eHealth provided through websites, people reported a lower WTP for eHealth provided through asynchronous communication (β=−1.43; P<.001) and a higher WTP for eHealth provided through medical devices (β=.66; P<.001), health apps (β=.25; P=.01), and synchronous communication (β=.58; P<.001). As for the methods used to measure WTP, single-bounded dichotomous choice (β=2.13; P<.001), double-bounded dichotomous choice (β=2.20; P<.001), and payment scale (β=1.11; P<.001) were shown to obtain higher WTP values than the open-ended format. Compared with ex ante evaluations, ex post evaluations were shown to obtain lower WTP values (β=−.37; P<.001).

Conclusions

WTP for eHealth varied significantly depending on the study population, modality used to provide eHealth, and methods used to measure it. WTP for eHealth was lower among certain population segments, suggesting that these segments may be at a disadvantage in terms of accessing and benefiting from eHealth. We also identified the modalities of eHealth that were highly valued by consumers and offered suggestions for the design of eHealth interventions. In addition, we found that different methods of measuring WTP led to significantly different WTP estimates, highlighting the need to undertake further methodological explorations of approaches to elicit WTP values.

Systematic review and validity assessment of methods used in discrete choice experiments of primary healthcare professionals

INTRODUCTION

Discrete choice experiments (DCEs) have been used to measure patient and healthcare professionals preferences in a range of settings internationally. Using DCEs in primary care is valuable for determining how to improve rational shared decision making. The purpose of this systematic review is to assess the validity of the methods used for DCEs assessing the decision making of healthcare professionals in primary care.

MAIN BODY

A systematic search was conducted to identify articles with original data from a discrete choice experiment where the population was primary healthcare professionals. All publication dates from database inception to 29th February 2020 were included. A data extraction and validity assessment template based on guidelines was used. After screening, 34 studies met the eligibility criteria and were included in the systematic review. The sample sizes of the DCEs ranged from 10 to 3727. The published DCEs often provided insufficient detail about the process of determining the attributes and levels. The majority of the studies did not involve primary care healthcare professionals outside of the research team in attribute identification and selection. Less than 80% of the DCEs were piloted and few papers investigated internal or external validity.

CONCLUSIONS

For findings to translate into improvements in rational shared decision making in primary care DCEs need to be internally and externally valid and the findings need to be able to be communicated to stakeholders in a way that is understandable and relevant.

Patient and physician preferences for multiple sclerosis treatments in Germany: A discrete-choice experiment study

Objective

To assess heterogeneity in patient and physician preferences for multiple sclerosis treatment features and outcomes via a discrete-choice experiment.

Method

Patients with self-reported multiple sclerosis and treating physicians participated in an online discrete-choice experiment. Patients, each considering a better or worse reference condition, and physicians, each considering two patient profiles, chose between hypothetical treatment profiles defined by seven attributes with varying levels: years until disability progression, number of relapses in the decade, mode of administration, dosing frequency, and risks of mild, moderate, and severe side effects. Latent class analysis was used to measure respondent preferences and identify potential subgroups with distinct preferences.

Results

Distinct treatment preferences emerged among subgroups of patients (n = 301) and physicians (n = 308). Patients in class 1 (43% of sample) were most concerned about side effects; chief concerns of class 2 patients (57%) were delaying disability progression and avoiding severe side-effect risks. The most important attributes for physicians (by class) were delaying disability (class 1, 45%), avoiding severe side-effect risks and (class 2, 33%), and avoiding all side-effect risks (class 3, 22%).

Conclusion

Patients and physicians have diverse preferences for multiple sclerosis treatments, reflecting heterogeneity in the disease course and available therapies and the need for shared decision making.

How to Implement Adherence-Promoting Programs in Clinical Practice? A Discrete Choice Experiment on Physicians' Preferences

INTRODUCTION

The aim of this study was to examine physicians' preferences regarding adherence-promoting programs (APPs), and to investigate which APP characteristics influence the willingness of physicians to implement these in daily practice.

MATERIALS AND METHODS

A discrete choice experiment was conducted among general practitioners, cardiologists, neurologists and ophthalmologists in Germany. The design considered five attributes with two or three attribute levels each: validation status of the APP; possibility for physicians to receive a certificate; type of intervention; time commitment per patient and quarter of the year to carry out the APP; reimbursement for APP participation, per included patient and quarter of the year.A multinomial logit model was run to estimate physicians' utility for each attribute and to evaluate the influence of different levels on the probability of choosing a specific APP. The relative importance of the attributes was compared between different pre-defined subgroups.

RESULTS

In total, 222 physicians were included in the analysis. The most important characteristics of APPs were time commitment to carry out the program (34.8% importance), reimbursement (33.3%), and validation status of the program (23.7%). The remaining attributes (type of intervention: 3.6%; possibility to receive a certificate: 4.7%) were proven to be less important for a physician's decision to participate in an APP. Physicians on average preferred APP alternatives characterized by little time commitment (β=1.456, p<0.001), high reimbursement for work (β=1.392, p<0.001), "positive validation status" (β=0.990, p<0.001), the "possibility to get a certificate" (β=0.197, p<0.001), and the provision of "tools for both physicians and patients" (β=0.150, p<0.001).

CONCLUSION

For the majority of the physicians participating in this survey, the willingness to implement an APP is determined by the associated time commitment and reimbursement. Considering physicians' preferences regarding different APP features in the promoting process of these programs may enhance physicians' participation and engagement.

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.

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.

Application of discrete choice experiments to enhance stakeholder engagement as a strategy for advancing implementation: a systematic review

Background

One of the key strategies to successful implementation of effective health-related interventions is targeting improvements in stakeholder engagement. The discrete choice experiment (DCE) is a stated preference technique for eliciting individual preferences over hypothetical alternative scenarios that is increasingly being used in health-related applications. DCEs are a dynamic approach to systematically measure health preferences which can be applied in enhancing stakeholder engagement. However, a knowledge gap exists in characterizing the extent to which DCEs are used in implementation science.

Methods

We conducted a systematic literature search (up to December 2016) of the English literature to identify and describe the use of DCEs in engaging stakeholders as an implementation strategy. We searched the following electronic databases: MEDLINE, Econlit, PsychINFO, and the CINAHL using mesh terms. Studies were categorized according to application type, stakeholder(s), healthcare setting, and implementation outcome.

Results

Seventy-five publications were selected for analysis in this systematic review. Studies were categorized by application type: (1) characterizing demand for therapies and treatment technologies (n = 32), (2) comparing implementation strategies (n = 22), (3) incentivizing workforce participation (n = 11), and (4) prioritizing interventions (n = 10). Stakeholders included providers (n = 27), patients (n = 25), caregivers (n = 5), and administrators (n = 2). The remaining studies (n = 16) engaged multiple stakeholders (i.e., combination of patients, caregivers, providers, and/or administrators). The following implementation outcomes were discussed: acceptability (n = 75), appropriateness (n = 34), adoption (n = 19), feasibility (n = 16), and fidelity (n = 3).

Conclusions

The number of DCE studies engaging stakeholders as an implementation strategy has been increasing over the past decade. As DCEs are more widely used as a healthcare assessment tool, there is a wide range of applications for them in stakeholder engagement. The DCE approach could serve as a tool for engaging stakeholders in implementation science.

Electronic supplementary material

The online version of this article (10.1186/s13012-017-0675-8) contains supplementary material, which is available to authorized users.

Do patients and health care providers have discordant preferences about which aspects of treatments matter most? Evidence from a systematic review of discrete choice experiments

OBJECTIVES

To review studies eliciting patient and healthcare provider preferences for healthcare interventions using discrete choice experiments (DCEs) to (1) review the methodology to evaluate similarities, differences, rigour of designs and whether comparisons are made at the aggregate level or account for individual heterogeneity; and (2) quantify the extent to which they demonstrate concordance of patient and healthcare provider preferences.

METHODS

A systematic review searching Medline, EMBASE, Econlit, PsycINFO and Web of Science for DCEs using patient and healthcare providers.

INCLUSION CRITERIA

peer-reviewed; complete empiric text in English from 1995 to 31July 2015; discussing a healthcare-related topic; DCE methodology; comparing patients and healthcare providers.

DESIGN

Systematic review.

RESULTS

We identified 38 papers exploring 16 interventions in 26 diseases/indications. Methods to analyse results, determine concordance between patient and physician values, and explore heterogeneity varied considerably between studies. The majority of studies we reviewed found more evidence of mixed concordance and discordance (n=28) or discordance of patient and healthcare provider preferences (n=12) than of concordant preferences (n=4). A synthesis of concordance suggested that healthcare providers rank structure and outcome attributes more highly than patients, while patients rank process attributes more highly than healthcare providers.

CONCLUSIONS

Discordant patient and healthcare provider preferences for different attributes of healthcare interventions are common. Concordance varies according to whether attributes are processes, structures or outcomes, and therefore determining preference concordance should consider all aspects jointly and not a binary outcome. DCE studies provide excellent opportunities to assess value concordance between patients and providers, but assessment of concordance was limited by a lack of consistency in the approaches used and consideration of heterogeneity of preferences. Future DCEs assessing concordance should fully report the framing of the questions and investigate the heterogeneity of preferences within groups and how these compare.

COPD-treating nurses' preferences for inhaler attributes - a discrete choice experiment

OBJECTIVE

To assess nurses' preferences for various attributes of chronic obstructive pulmonary disease (COPD) inhalation devices in order to obtain information about the relative importance of the different attributes and their assigned levels.

METHODS

Data from a web-based questionnaire among Danish nurses who treat patients with COPD (accomplished in the spring/summer of 2015) was used. A total of 222 nurses completed the questionnaire which was based on discrete choice experiment (DCE) methodology. The probability of choosing an alternative from a number of choices in a discrete choice game was estimated by means of the conditional logit model.

RESULTS

The two most important attributes according to the COPD-treating nurses were "Indicator when empty" and "Inspiratory flow rate". In addition, the nurses considered the attribute "Obvious that dose is given" important. The three least-valued attributes were frequency of doses, whether the inhaler requires fine motor skills and whether it requires hand strength.

CONCLUSION

Inhalation devices can be classified into five categories, where the soft mist inhaler (SMI) includes the three most important attributes among its characteristics.

LIMITATIONS

The study sample size does not allow for subgroup analysis, which would have been valuable. The questionnaire design gives an indication of nurses' preferences and it is assumed that these are similar to real life choices, but the current study cannot conclude on the nurses' actual choices.

Patients' and physicians' preferences for type 2 diabetes mellitus treatments in Spain and Portugal: a discrete choice experiment

OBJECTIVE

To assess Spanish and Portuguese patients' and physicians' preferences regarding type 2 diabetes mellitus (T2DM) treatments and the monthly willingness to pay (WTP) to gain benefits or avoid side effects.

METHODS

An observational, multicenter, exploratory study focused on routine clinical practice in Spain and Portugal. Physicians were recruited from multiple hospitals and outpatient clinics, while patients were recruited from eleven centers operating in the public health care system in different autonomous communities in Spain and Portugal. Preferences were measured via a discrete choice experiment by rating multiple T2DM medication attributes. Data were analyzed using the conditional logit model.

RESULTS

Three-hundred and thirty (n=330) patients (49.7% female; mean age 62.4 [SD: 10.3] years, mean T2DM duration 13.9 [8.2] years, mean body mass index 32.5 [6.8] kg/m(2), 41.8% received oral + injected medication, 40.3% received oral, and 17.6% injected treatments) and 221 physicians from Spain and Portugal (62% female; mean age 41.9 [SD: 10.5] years, 33.5% endocrinologists, 66.5% primary-care doctors) participated. Patients valued avoiding a gain in bodyweight of 3 kg/6 months (WTP: €68.14 [95% confidence interval: 54.55-85.08]) the most, followed by avoiding one hypoglycemic event/month (WTP: €54.80 [23.29-82.26]). Physicians valued avoiding one hypoglycemia/week (WTP: €287.18 [95% confidence interval: 160.31-1,387.21]) the most, followed by avoiding a 3 kg/6 months gain in bodyweight and decreasing cardiovascular risk (WTP: €166.87 [88.63-843.09] and €154.30 [98.13-434.19], respectively). Physicians and patients were willing to pay €125.92 (73.30-622.75) and €24.28 (18.41-30.31), respectively, to avoid a 1% increase in glycated hemoglobin, and €143.30 (73.39-543.62) and €42.74 (23.89-61.77) to avoid nausea.

CONCLUSION

Both patients and physicians in Spain and Portugal are willing to pay for the health benefits associated with improved diabetes treatment, the most important being to avoid hypoglycemia and gaining weight. Decreased cardiovascular risk and weight reduction became the third most valued attributes for physicians and patients, respectively.