Education and patient preferences for treating type 2 diabetes: a stratified discrete-choice experiment

Residential Address Amplifies Health Disparities and Risk of Infection in Individuals With Diabetic Foot Ulcers

OBJECTIVE

To determine the association between social determinants of health (SDOH) and a diagnosis of diabetic foot ulcer (DFU) infection.

RESEARCH DESIGN AND METHODS

Targeted interrogation of electronic health record data using novel search engines to analyze individuals with a DFU infection during a 5-year period (2013-2017) was performed. We extracted geolocated neighborhood data and SDOH characteristics from the National Neighborhood Data Archive and used univariate and multiple logistic regression to evaluate associations with outcomes in the population with diabetes.

RESULTS

Among 4.3 million people overall and 144,564 individuals with diabetes seen between 2013 and 2017, 8,351 developed DFU, of which cases 2,252 were complicated by a DFU infection. Sex interactions occurred, as men who experienced a DFU infection more frequently identified as having nonmarried status than their female counterparts. For the population with DFU infection, there were higher rates for other SDOH, including higher neighborhood disadvantaged index score, poverty, nonmarriage, and less access to physician/allied health professionals (all P < 0.01). In multiple logistic regression, those individuals who developed DFU infection came from neighborhoods with greater Hispanic and/or foreign-born concentrations (odds ratio 1.11, P = 0.015).

CONCLUSIONS

We found significant differences in neighborhood characteristics driving a higher risk for DFU infection in comparisons with the grouping of individuals with diabetes overall, including increased risk for individuals with Hispanic and/or foreign-born immigration status. These data strongly support the need to incorporate SDOH, particularly ethnic and immigration status, into triage algorithms for DFU risk stratification to prevent severe diabetic foot complications and move beyond biologic-only determinants of health.

Prevalence of Type 2 Diabetes Mellitus in the General Population of Saudi Arabia, 2000-2020: A Systematic Review and Meta-Analysis of Observational Studies

Background

The prevalence of type 2 diabetes mellitus (T2DM) has increased worldwide, including in Saudi Arabia.

Objective

To systematically review the available literature and assess the pooled prevalence of T2DM in Saudi Arabia between 2000 and 2020.

Methods

Observational studies that reported quantitative estimates of the prevalence of T2DM as their main outcome, included the general population of Saudi Arabia, and were published between 2000-2020 and in English were retrieved using three electronic databases (namely, CINAHL, Medline via PubMed, and Web of Science). Retrieved studies were screened, and relevant data were extracted. The Joanna Briggs Institute Critical Appraisal guideline was used to assess the methodological quality of included studies. A random-effects model was used to estimate the prevalence of T2DM.

Results

Twenty-three studies were included in the systematic review, of which 19 were included in the meta-analysis (total pooled population: 258,283). The overall pooled prevalence of T2DM in Saudi Arabia was 16.4% (95% CI: 11.6-17.5). However, there was heterogeneity in the results of the studies [I2 = 99.31%, P < 0.0001] and the summary values varied from 3.18% (95% CI: 1.46-5.95) to 94.34% (95% CI: 89.53-97.38). Although the prevalence of T2DM by age varied across studies, in most studies, it was higher among the older age groups. In addition, the prevalence of diabetes widely varied across the different geographical regions of Saudi Arabia.

Conclusions

This is the first meta-analysis that determined the pooled prevalence of T2DM in Saudi Arabia, and it revealed a high prevalence over the past two decades. However, owing to data collection inconsistencies in the identified studies, neither the modifiable (such as obesity, educational status, emotional support, etc.) nor the non-modifiable (such as gender and age) risk factors of T2DM could be determined, thereby indicating the need for a nationally collective effort in determining these factors.

Patient preferences for the treatment of type 2 diabetes in Australia: a discrete choice experiment

Background

Australia has a high proportion of migrants, with an increasing migration rate from India. Type 2 diabetes is a chronic condition common amongst the Indian population. The decision to initiate and continue medication therapy (conventional or ayurvedic medicine) is complex and is influenced by a wide range of factors.

Objective

To determine preferences for conventional vs. ayurvedic medicines in Indian migrants with diabetes, and to identify the factors that may influence their preferences.

Methods

A discrete choice experiment was conducted with participants in Australia who were migrants from India with type 2 diabetes (n=141). Each respondent evaluated eight choice tasks consisting of eight attributes describing medicines and outcomes of medication taking; and were asked to choose 'conventional', or 'ayurvedic' medicine. A mixed multinomial logit model was used to estimate preferences.

Results

Overall, respondents' preference to initiate a medicine was negative for both conventional (β=-2.33164, p<0.001) and ayurvedic medicines (β=-3.12181, p<0.001); however, significant heterogenicity was noted in participants' preferences (SD: 2.33122, p<0.001). Six significant attributes were identified to influence preferences. In decreasing rank order: occurrence of hypoglycaemic events (relative importance, RI=24.33%), weight change (RI=20.00%), effectiveness of medicine (RI=17.91%), instructions to take with food (RI=17.05%), side effects (RI=13.20%) and formulation (RI=7.49%). Respondents preferred to initiate a medicine despite potential side effects.

Conclusions

There was a greater preference for conventional medicine, though neither were preferred. Medicine attributes and medication-taking outcomes influenced people's preferences for an antidiabetic medicine. It is important to identify individual preferences during healthcare consultations to ensure optimal medication-taking.

Patients' Preferences for Sodium-Glucose Cotransporter 2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists

PURPOSE

To determine patients' preferences for sodium-glucose cotransporter 2 inhibitors (SGLT-2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs).

PATIENTS AND METHODS

A cross-sectional, web-based discrete choice experiment was conducted among US adults with type 2 diabetes mellitus (T2DM) in May 2021. Six attributes-the route and frequency of administration, the chance of reaching target HbA1c in six months, the percentage reduction in the risk of major adverse cardiovascular events (MACE), the chance of gastrointestinal side effects, the chance of genital infection, and out-of-pocket cost per month-were identified from literature review and consultation with patients and clinicians. A Bayesian efficient design was used to generate choice sets. Each choice set contained two hypothetical SGLT-2i and GLP-1 RA alternatives described by the attributes and an opt-out alternative. A total of 176 patients were asked to select the most preferred option from each choice set. Mixed logit (ML) and latent class (LC) models were developed. The conditional relative importance of each attribute was determined.

RESULTS

The ML model showed the out-of-pocket cost had the highest conditional relative importance, followed by the chance of reaching the target HbA1c. The best LC model revealed two patient classes. All attributes were significantly important to the patients in both classes, except the chance of genital infection in class 2. Compared to the patients in class 2, the patients in class 1 were older (approximately 65 vs 56 years) and had a higher number of comorbidities (approximately three vs two).

CONCLUSION

T2DM patients placed different preference weights or importance across SGLT-2i and GLP-1 RA attributes. Preference heterogeneity was found among patients with different ages and numbers of comorbidities.

Preferences for Patients with Type 2 Diabetes Mellitus for Medications in Shandong Province, China: A Discrete Choice Experiment

PURPOSE

To evaluate preferences for medications among patients with type 2 diabetes mellitus (T2DM) from urban community health stations or rural village clinics in Shandong province, China.

METHODS

We use a discrete choice experiment (DCE) to measure the medication preferences. Each patient completed six DCE choice sets. The attributes for the DCE questionnaire include mode of administration, out-of-pocket medication cost per month, fasting blood glucose control effect and frequency of hypoglycemia events. The conditional logit model (Clogit) and mixed logit model (MXL) were used to evaluate choice data.

RESULTS

A total of 887 patients with T2DM completed the survey. The mean age of participants was 64 years, 36.42% experienced complications, and the mean duration of diabetes was about 8 years. Overall, patients' ideal medication would not have hypoglycemia events, provide normal fasting glucose levels, have oral medication three times a day and lower monthly medication cost. Patients prioritized the frequency of hypoglycemia events (β=15.055, P < 0.01) and were willing to spend CNY 393.10 per month to avoid hypoglycemia events. For patients with higher educational levels and with longer diagnosis time, the effect of fasting blood glucose was more relevant than all other outcomes.

CONCLUSION

This study provides information on T2DM patients' preference for medications. Our results suggest that clinical doctors should present patients with a variety of pharmaceutical characteristics and include their preference into medication decision, which will improve patient adherence and health outcomes.

Improving Uptake of Non-Communicable Disease Screening in Sri Lanka: Eliciting Peoples' Preferences using a Discrete Choice Experiment

A national programme to universally screen the population between 35 - 65 years for non-communicable diseases was established at 'Healthy Lifestyle Centres (HLCs)' in 2011 in Sri Lanka. Despite several efforts by policy makers, the uptake of screening remained below 10% of the target population and with disparities in uptake across districts and among men and women. Considering service beneficiaries as a vital stakeholder, a discrete choice experiment was carried out to estimate people's preference for a NCD screening service delivery model in rural, urban and estate sectors in a district in Sri Lanka. The choice design and the general survey questionnaire was developed through focus group discussions, literature reviews and stakeholder consultations. Data was collected by stratified random sampling, with 187 participants from the urban sector, 253 from the rural sector and 152 from the estate/plantation sector. Peoples' preference was assessed as utility estimates derived using multinomial logistic regression. Reliability was assessed within test among all study participants and with test-retest among 40 participants showed 80% precision. Urban and rural sectors gave the highest priority to workplace screening over screening at HLCs. The estates attributed the highest priority for cost free screening. If cost free screening is offered with having to spend 1-2 hours at the most preferred opening times for each sector with warm and friendly staff, the uptake of screening can predicted to be increased by 65, 29 and 21 times respectively in urban, rural and estate sectors relative to having to attend HLCs from 8am - 4 pm, spending more than 2 hours and Rs. 1000 with unfriendly staff. Thus, peoples' preferences on service delivery aspects seemed to have differed from government priorities. Preferences when ill and apparently healthy differed, as they preferred to spend less time and money when healthy than when ill.

Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities

PURPOSE

To determine the association of social factors with Covid-19 mortality and identify high-risk clusters.

METHODS

Data on Covid-19 deaths across 3,108 contiguous U.S. counties from the Johns Hopkins University and social determinants of health (SDoH) data from the County Health Ranking and the Bureau of Labor Statistics were fitted to Bayesian semi-parametric spatiotemporal Negative Binomial models, and 95% credible intervals (CrI) of incidence rate ratios (IRR) were used to assess the associations. Exceedance probabilities were used for detecting clusters.

RESULTS

As of October 31, 2020, the median mortality rate was 40.05 per 100, 000. The monthly urban mortality rates increased with unemployment (IRRadjusted:1.41, 95% CrI: 1.24, 1.60), percent Black population (IRRadjusted:1.05, 95% CrI: 1.04, 1.07), and residential segregation (IRRadjusted:1.03, 95% CrI: 1.02, 1.04). The rural monthly mortality rates increased with percent female population (IRRadjusted: 1.17, 95% CrI: 1.11, 1.24) and percent Black population (IRRadjusted:1.07 95% CrI:1.06, 1.08). Higher college education rates were associated with decreased mortality rates in rural and urban counties. The dynamics of exceedance probabilities detected the shifts of high-risk clusters from the Northeast to Southern and Midwestern counties.

CONCLUSIONS

Spatiotemporal analyses enabled the inclusion of unobserved latent risk factors and aid in scientifically grounded decision-making at a granular level.

Line of therapy and patient preferences regarding lung cancer treatment: a discrete-choice experiment

OBJECTIVE

A growing literature on patient preferences informs decisions in research, regulatory science, and value assessment, but few studies have explored how preferences vary across patients with differing treatment experience. We sought to quantify patient preferences for the benefits and risks of lung cancer treatment and test how preferences differed by line of therapy (LOT).

METHODS

Preferences were elicited using a discrete choice experiment (DCE) following rigorous patient and stakeholder engagement. The DCE spanned five attributes (each with three levels): progression-free survival (PFS), short-term side effects, long-term side effects, risk of developing late-onset side effects, and mode of administration (MOA) - each defined across 3 relevant levels. A D-efficient design was used to generate 3 survey blocks of 9 paired-profile choice tasks each and respondents were asked which profile they preferred and then if they preferred to have no treatment (opt-out). A mixed logit model, controlling for opt-out, was used to estimate preferences. Preferences and trade-offs between PFS and other attributes were compared across two groups: those receiving ≤1 LOT and those receiving ≥2 LOT.

RESULTS

Of the 466 participants, 42% received ≤1 LOT and 58% received ≥2 LOT. Stated preferences differed between the groups overall (p<.001) and specifically for 18 months of PFS (p<.001), moderate short-term side effects (p<.001), no long-term side effects (p=.03), and 30% chance of late-onset side effects (p=.02). Those receiving differing amounts of LOT were willing to trade different amounts of PFS to change from moderate to mild short-term side effects (p<.001), moderate to no (p<.001) and mild to no (p<.001) long-term side effects. There were also differing amounts of tradeoff acceptable between the groups for a 10% decrease in risk of late-onset side effects (p=.016), a decrease in MOA from infusion every 3 weeks to pills taken daily at any time (p=.005) and from pills taken daily without food to pills taken daily at any time (p<.001).

CONCLUSION

We demonstrate differences in preferences based on experience with LOT, suggesting that patient treatment experience may have an impact on their preferences. As patient preference data become an important component of treatment decision making, preference differences should be considered when recommending therapies at different stages in the treatment journey. Understanding patient preferences regarding treatment decisions is essential to informing shared decision-making and ensuring treatment plans are consistent with patients' goals.

The Association of Social Determinants of Health With COVID-19 Mortality in Rural and Urban Counties

Purpose

To identify the county‐level effects of social determinants of health (SDoH) on COVID‐19 (corona virus disease 2019) mortality rates by rural–urban residence and estimate county‐level exceedance probabilities for detecting clusters.

Methods

The county‐level data on COVID‐19 death counts as of October 23, 2020, were obtained from the Johns Hopkins University. SDoH data were collected from the County Health Ranking and Roadmaps, the US Department of Agriculture, and the Bureau of Labor Statistics. Semiparametric negative binomial regressions with expected counts based on standardized mortality rates as offset variables were fitted using integrated Laplace approximation. Bayesian significance was assessed by 95% credible intervals (CrI) of risk ratios (RR). County‐level mortality hotspots were identified by exceedance probabilities.

Findings

The COVID‐19 mortality rates per 100,000 were 65.43 for the urban and 50.78 for the rural counties. Percent of Blacks, HIV, and diabetes rates were significantly associated with higher mortality in rural and urban counties, whereas the unemployment rate (adjusted RR = 1.479, CrI = 1.171, 1.867) and residential segregation (adjusted RR = 1.034, CrI = 1.019, 1.050) were associated with increased mortality in urban counties. Counties with a higher percentage of college or associate degrees had lower COVID‐19 mortality rates.

Conclusions

SDoH plays an important role in explaining differential COVID‐19 mortality rates and should be considered for resource allocations and policy decisions on operational needs for businesses and schools at county levels.

Do people have differing motivations for participating in a stated-preference study? Results from a latent-class analysis

BACKGROUND

Researchers and policy makers have long suspected that people have differing, and potentially nefarious, motivations for participating in stated-preference studies such as discrete-choice experiments (DCE). While anecdotes and theories exist on why people participate in surveys, there is a paucity of evidence exploring variation in preferences for participating in stated-preference studies.

METHODS

We used a DCE to estimate preferences for participating in preference research among an online survey panel sample. Preferences for the characteristics of a study to be conducted at a local hospital were assessed across five attributes (validity, relevance, bias, burden, time and payment) and described across three levels using a starring system. A D-efficient experimental design was used to construct three blocks of 12 choice tasks with two profiles each. Respondents were also asked about factors that motivated their choices. Mixed logistic regression was used to analyze the aggregate sample and latent class analysis identified segments of respondents.

RESULTS

629 respondents completed the experiment. In aggregate "study validity" was most important. Latent class results identified two segments based on underlying motivations: a quality-focused segment (76%) who focused most on validity, relevance, and bias and a convenience-focused segment (24%) who focused most on reimbursement and time. Quality-focused respondents spent more time completing the survey (p < 0.001) and were more likely to identify data quality (p < 0.01) and societal well-being (p < 0.01) as motivations to participate.

CONCLUSIONS

This information can be used to better understand variability in motivations to participate in stated-preference surveys and the impact of motivations on response quality.

Preferences of people with type 2 diabetes for telemedical lifestyle programmes in Germany: protocol of a discrete choice experiment

INTRODUCTION

Telemedical lifestyle programmes for people with type 2 diabetes mellitus (T2DM) provide an opportunity to develop a healthier lifestyle and consequently to improve health outcomes. When implementing new programmes into standard care, considering patients' preferences may increase the success of the participants. This study aims to examine the preferences of people with T2DM with respect to telemedical lifestyle programmes, to analyse whether these preferences predict programme success and to explore the changes that may occur during a telemedical lifestyle intervention.

METHODS AND ANALYSIS

We outline the protocol of the development and assessment of a discrete choice experiment (DCE) to examine patient preferences in a telemedical lifestyle programme with regard to the functions of the online portal, communication, responsibilities, group activities and time requirements. To develop the design of the DCE, we conducted pilot work involving healthcare experts and in particular people with T2DM using cognitive pretesting. The final DCE is being implemented within a randomised controlled trial for investigating whether participation in a telemedical lifestyle intervention programme sustainably improves the HbA1c values in 850 members of a large German statutory health insurance with T2DM. Preferences are being assessed before and after participants complete the programme. The DCE data will be analysed using regression and latent class analyses.

ETHICS AND DISSEMINATION

The DCE study has been approved by the ethics committee of the medical faculty of the Heinrich Heine University Duesseldorf, registration number 2018-242-ProspDEuA, registered on 6 December 2018. The TeLIPro trial is registered at the US National Library of Medicine, registration number NCT03675919, registered on 15 September 2018. We aim to disseminate our results in peer-reviewed journals, at national and international conferences and among interested patient groups and the public.

Understanding Reasons for Treatment Discontinuation, Attitudes and Education Needs Among People Who Discontinue Type 2 Diabetes Treatment: Results from an Online Patient Survey in the USA and UK

INTRODUCTION

Type 2 diabetes mellitus (T2DM) requires long-term treatment to achieve and maintain glycaemic control; however, up to 50% of people with T2DM discontinue treatment by 1 year. It is therefore important to understand the patient perspective of therapeutic adherence and persistence.

METHODS

An online questionnaire was presented to people with T2DM in the USA and UK on PatientLive^®, a platform of Carenity, an online patient community. Those who discontinued at least one T2DM treatment within the last 6 months answered open-ended questions aimed to assess the reasons for discontinuation, how discontinuation could have been prevented, and what would have improved the experience with the discontinued treatment. Thematic qualitative analysis was performed on respondents' answers to these questions.

RESULTS

Oral antidiabetics were the most commonly discontinued treatments (93/161), followed by insulin (40/161) and glucagon-like peptide 1 receptor agonists (13/161). Main reasons for treatment discontinuation overall were side effects (57/161), mostly gastrointestinal side effects and weight gain. The second most reported reason was drug efficacy issues (42/161). Key factors stated to prevent discontinuation were an improved care pathway (45/161) and more efficacious treatments with fewer side effects (41/161). In the USA, treatment cost played an important role in discontinuation (14/89) and discontinuation prevention (12/89). More information about T2DM and associated treatments (56/161), help with T2DM management (24/161), and increased and informative patient-physician interaction (12/161) would have been helpful for many respondents in both countries, while some patients noted that no additional information would have been useful to improve their understanding and experience with their T2DM treatment (64/161).

CONCLUSIONS

These results emphasise the need for focused medical education and improved communication to enhance patient experience and prevent treatment discontinuation. Understanding of attributes preferred by people with T2DM can help improve therapeutic adherence and outcomes with current medications, and guide development of future therapies.

Analysis of Patient Preferences in Lung Cancer - Estimating Acceptable Tradeoffs Between Treatment Benefit and Side Effects

OBJECTIVE

Increased treatment options and longer survival for lung cancer have generated increased interest in patient preferences. Previous studies of patient preferences in lung cancer have not fully explored preference heterogeneity. We demonstrate a method to explore preference heterogeneity in the willingness of patients with lung cancer and caregivers to trade progression-free survival (PFS) with side effects.

PATIENTS AND METHODS

Patients and caregivers attending a national lung cancer meeting completed a discrete-choice experiment (DCE) designed through a collaboration with patients. Participants answered 13 choice tasks described across PFS, short-term side effects, and four long-term side effects. Side effects were coded as a one-level change in severity (none-mild, mild-moderate, or moderate-severe). A mixed logit model in willingness-to-pay space estimated preference heterogeneity in acceptable tradeoffs (time equivalents) between PFS and side effects. The study was reported following quality indicators from the United States Food and Drug Administration's patient preference guidance.

RESULTS

A total of 87 patients and 24 caregivers participated in the DCE. Participants would trade 3.7 month PFS (95% CI (CI): 3.3-4.1) for less severe functional long-term treatment side effects, 2.3 months for less severe physical long-term effects (CI: 1.9-2.8) and cognitive long-term effects (CI: 1.8-2.8), 0.9 months (CI: 0.4-1.4) for less severe emotional long-term effects, and 1.8 months (CI: 1.4-2.3) for less severe short-term side effects. Most participants (90%) would accept treatment with more severe functional long-term effects for 8.4 additional month PFS.

CONCLUSION

Participants would trade PFS for changes in short-term side effects and long-term side effects, although preference heterogeneity existed. Lung cancer treatments that offer less PFS but also less severe side effects might be acceptable to some patients.

Opportunities and challenges for the inclusion of patient preferences in the medical product life cycle: a systematic review

BACKGROUND

The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators. This review aimed to understand the potential roles, reasons for using PP and the expectations, concerns and requirements associated with PP in industry processes, regulatory benefit-risk assessment (BRA) and marketing authorization (MA), and HTA and reimbursement decision-making.

METHODS

A systematic review of peer-reviewed and grey literature published between January 2011 and March 2018 was performed. Consulted databases were EconLit, Embase, Guidelines International Network, PsycINFO and PubMed. A two-step strategy was used to select literature. Literature was analyzed using NVivo (QSR international).

RESULTS

From 1015 initially identified documents, 72 were included. Most were written from an academic perspective (61%) and focused on PP in BRA/MA and/or HTA/reimbursement (73%). Using PP to improve understanding of patients' valuations of treatment outcomes, patients' benefit-risk trade-offs and preference heterogeneity were roles identified in all three decision-making contexts. Reasons for using PP relate to the unique insights and position of patients and the positive effect of including PP on the quality of the decision-making process. Concerns shared across decision-making contexts included methodological questions concerning the validity, reliability and cognitive burden of preference methods. In order to use PP, general, operational and quality requirements were identified, including recognition of the importance of PP and ensuring patient understanding in PP studies.

CONCLUSIONS

Despite the array of opportunities and added value of using PP throughout the different steps of the MPLC identified in this review, their inclusion in decision-making is hampered by methodological challenges and lack of specific guidance on how to tackle these challenges when undertaking PP studies. To support the development of such guidance, more best practice PP studies and PP studies investigating the methodological issues identified in this review are critically needed.

Willingness to pay for flexibility at the workplace for people with diabetes and chronic disease: a discrete choice experiment in a population of workers in Denmark

Background

The number of people of working age suffering from chronic disease is increasing. Chronic diseases such as diabetes can cause negative work-related consequences in the form of early retirement or absenteeism. Providing flexible workplace accommodations may enable the person with diabetes to retain their position in the labor market. However, the successfulness of such accommodations depends largely on the perceptions of those not suffering from diabetes. The purpose of this study was to examine preferences of a population of workers in Denmark for flexibility at the workplace, for people with diabetes and for people with chronic disease in general, measured as their willingness to pay (WTP).

Methods

Respondents were drawn from online panels and randomized to answer an online survey regarding flexibility at the workplace for people with diabetes or chronic disease in general. One thousand one hundred and three respondents were included in the analysis. Based on discrete choice experiments included in the survey, we analyzed WTP for five flexibility attributes: part-time, customizing job description, additional break with pay and time off for medical visits with and without pay. We further examined perceptions of the employer’s responsibility to ensure workplace flexibility for five different specific chronic diseases including diabetes. Finally, we analyzed differences in WTP for flexibility across subgroups.

Results

Respondents’ WTP was significantly higher for chronic disease in general compared to diabetes for the possibility of part-time (81€/month vs. 47€/month, p < 0.001) and customizing job description (58€/month vs. 41€/month, p = 0.018) attributes, as well as for the overall average (49€/month vs. 36€/month, p = 0.008). Ensuring workplace flexibility for patients with a specific chronic disease other than diabetes (cancer, heart disease, arthritis and COPD) was to a higher degree considered a responsibility of the employer. Average WTP for flexibility varied across subgroups, consistently yielding a larger amount for chronic disease in general.

Conclusions

The population examined in this study are willing to pay less for flexibility at the workplace for people with diabetes compared to people with chronic disease in general. This finding was evident in terms of specific flexibility attributes and on average across subgroups.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6919-6) contains supplementary material, which is available to authorized users.

The Potential Role of Individual-Level Benefit-Risk Assessment in Treatment Decision Making: A DIA Study Endpoints Community Workstream

Benefit-risk assessment is the cornerstone of decision making in medical care, playing a critical role in bringing treatments to market by informing decisions regarding drug development, licensing and reimbursement, and informing treatment decisions made by health care professionals and patients in clinical practice. In regulatory approval decision making, benefit and risk attributes are identified and defined based on available, aggregated clinical data from registration trials. In the context of major developments in recent years for involvement of patients as partners in all phases of drug development and in health care improvement, decision makers increasingly recognize the importance of informing treatment decisions by patient needs, values, experiences, and preferences. Using this as a basis, a DIA workstream was convened to explore the potential of individual-level benefit-risk assessment as a supplement to traditional group-level benefit-risk assessment for evaluating treatment. Various approaches as to how this information could be collected, including via patient-reported outcome measures, open-ended questioning, and stated-preference methods are presented. The utility of this information for various stakeholders is discussed.

Factors and situations influencing the value of patient preference studies along the medical product lifecycle: a literature review

Industry, regulators, health technology assessment (HTA) bodies, and payers are exploring the use of patient preferences in their decision-making processes. In general, experience in conducting and assessing patient preference studies is limited. Here, we performed a systematic literature search and review to identify factors and situations influencing the value of patient preference studies, as well as applications throughout the medical product lifecyle. Factors and situations identified in 113 publications related to the organization, design, and conduct of studies, and to communication and use of results. Although current use of patient preferences is limited, we identified possible applications in discovery, clinical development, marketing authorization, HTA, and postmarketing phases.