A discrete-choice experiment to elicit preferences of patients with epilepsy for self-management programs

Patient preferences for epilepsy treatment: a systematic review of discrete choice experimental studies

BACKGROUND

This review aimed to 1) identify and assess the quality of discrete choice experiments (DCEs) examining preferences related to epilepsy treatment; 2) summarize the attributes and attribute levels measured in these studies; 3) identify how researchers selected and developed these attributes; and 4) identify which attributes are most important for epilepsy patients.

METHODS

A systematic literature review using PubMed, Web of Science and Scopus databases from database inception to February or April 2022. We included primary discrete-choice experiments eliciting preferences for various attributes of pharmacological and surgical interventions in patients diagnosed with epilepsy or the parents/carers of children with epilepsy. We excluded non- primary studies, studies assessing preferences for nonpharmacological treatment and studies that elicit preferences using methods other than discrete choice experiments. Two authors independently selected studies, extracted data and assessed risk of bias of studies. The quality of the included studies was assessed using two validated checklists. Study characteristics and findings were summarized descriptively.

RESULTS

A total of seven studies were included in the review. The majority of studies explored patients' preferences, and two compared the preferences of patients with physicians. The majority (n = 6) compared two medications, and one compared two surgical options to continuing medication options. The studies examined 44 attributes in total, including side effects (n = 26), efficacy expressed as being seizure free or have fewer seizures (n = 8), costs (n = 3), dosing frequency (n = 3), duration of side effects (n = 2), mortality (n = 1), long-term problems after surgery (n = 1) and surgical options (n = 1). The findings indicate that people with epilepsy have strong preferences for improving seizure control, which was ranked as the top priority in all studies. Patients also have a strong preference for the reduction of adverse effects and may be willing to make trade-offs between improved seizure control and reduction of long-term side effects that may impact their quality of life.

CONCLUSIONS

The use of DCEs in measuring patients' preference for epilepsy treatment is accumulating. However, inadequate reporting of methodological details may reduce decision-makers' confidence in the findings. Suggestions for future research are provided.

Key Drivers and Facilitators of the Choice to Use mHealth Technology in People With Neurological Conditions: Observational Study

Background

There is increasing interest in the potential uses of mobile health (mHealth) technologies, such as wearable biosensors, as supplements for the care of people with neurological conditions. However, adherence is low, especially over long periods. If people are to benefit from these resources, we need a better long-term understanding of what influences patient engagement. Previous research suggests that engagement is moderated by several barriers and facilitators, but their relative importance is unknown.

Objective

To determine preferences and the relative importance of user-generated factors influencing engagement with mHealth technologies for 2 common neurological conditions with a relapsing-remitting course: multiple sclerosis (MS) and epilepsy.

Methods

In a discrete choice experiment, people with a diagnosis of MS (n=141) or epilepsy (n=175) were asked to select their preferred technology from a series of 8 vignettes with 4 characteristics: privacy, clinical support, established benefit, and device accuracy; each of these characteristics was greater or lower in each vignette. These characteristics had previously been emphasized by people with MS and or epilepsy as influencing engagement with technology. Mixed multinomial logistic regression models were used to establish which characteristics were most likely to affect engagement. Subgroup analyses explored the effects of demographic factors (such as age, gender, and education), acceptance of and familiarity with mobile technology, neurological diagnosis (MS or epilepsy), and symptoms that could influence motivation (such as depression).

Results

Analysis of the responses to the discrete choice experiment validated previous qualitative findings that a higher level of privacy, greater clinical support, increased perceived benefit, and better device accuracy are important to people with a neurological condition. Accuracy was perceived as the most important factor, followed by privacy. Clinical support was the least valued of the attributes. People were prepared to trade a modest amount of accuracy to achieve an improvement in privacy, but less likely to make this compromise for other factors. The type of neurological condition (epilepsy or MS) did not influence these preferences, nor did the age, gender, or mental health status of the participants. Those who were less accepting of technology were the most concerned about privacy and those with a lower level of education were prepared to trade accuracy for more clinical support.

Conclusions

For people with neurological conditions such as epilepsy and MS, accuracy (ie, the ability to detect symptoms) is of the greatest interest. However, there are individual differences, and people who are less accepting of technology may need far greater reassurance about data privacy. People with lower levels of education value greater clinician involvement. These patient preferences should be considered when designing mHealth technologies.

Parental preferences for seizure detection devices: a discrete choice experiment

Objective

Previous studies identified essential user preferences for seizure detection devices (SDDs), without addressing their relative strength. We performed a discrete choice experiment (DCE) to quantify attributes' strength, and to identify the determinants of user SDD preferences.

Methods

We designed an online questionnaire targeting parents of children with epilepsy to define the optimal balance between SDD sensitivity and positive predictive value (PPV) while accounting for individual seizure frequency. We selected five DCE attributes from a recent study. Using a Bayesian design, we constructed 11 unique choice tasks and analyzed these using a mixed multinomial logit model.

Results

One hundred parents responded to the online questionnaire link; 49 completed all tasks, whereas 28 completed the questions, but not the DCE. Most parents preferred a relatively high sensitivity (80%–90%) over a high PPV (>50%). The preferred sensitivity‐to‐PPV ratio correlated with seizure frequency (r = −.32), with a preference for relative high sensitivity and low PPV among those with relative low seizure frequency (p = .04). All DCE attributes significantly impacted parental choices. Parents expressed preferences for consulting a neurologist before device use, personally training the device's algorithm, interaction with their child via audio and video, alarms for all seizure types, and an interface detailing measurements during an alarm. Preferences varied between subgroups (learning disability or not, SDD experience, relative low vs. high seizure frequency based on the population median).

Significance

Various attributes impact parental SDD preferences and may explain why preferences vary among users. Tailored approaches may help to meet the contrasting needs among SDD users.

Patient preferences pertaining to treatment options for drug-resistant focal epilepsy

OBJECTIVE

To determine patient acceptability of benefit-risk trade-offs in selecting treatment options for drug-resistant mesial temporal lobe epilepsy, including open brain surgery, laser ablation (laser interstitial thermal therapy [LITT]), and continued medications.

METHODS

A discrete-choice experiment survey was developed, consisting of 20 versions that were randomly assigned to respondents. Each version had 8 sets of constructed treatment alternatives, representing open brain surgery, LITT, or continued medical management. For each set, respondents indicated the treatment alternative they would choose first. Treatment alternatives were characterized by varying levels of chance of seizure freedom for at least 2 years (20-70%), risk of 30-day mortality (0-10%), and risk of neurological deficits (0-40%). Respondents' choices were analyzed using random-parameters logit models to quantify acceptable benefit-risk trade-offs. Preference heterogeneity was evaluated using latent-class analysis.

RESULTS

The survey was administered to 2 cohorts of adult patients with drug-resistant epilepsy: a Duke cohort identified using diagnostic codes (n = 106) and a web-recruited panel with a self-reported physician diagnosis of drug-resistant epilepsy (n = 300). Based on mean preference weights, respondents who indicated a willingness to consider surgical intervention would accept a reduction in chance of seizure freedom from 70% to a minimum-acceptable benefit (MAB) of 23% if they could undergo LITT rather than open brain surgery. For a reduction in 30-day mortality from 1% to 0%, MAB was 52%. For a reduction in risk of long-term deficits from 10% to 0%, MAB was 39%. Latent-class analysis revealed additional choice patterns identifying respondent groups that more strongly favored continuing medications or undergoing surgery.

CONCLUSION

Patients who are receptive to surgery would accept significantly lower treatment effectiveness to undergo a minimally invasive procedure relative to open brain surgery. They also were willing to accept lower treatment benefit to reduce risks of mortality or neurological deficits.

Barriers and facilitators to implementation of epilepsy self-management programs: a systematic review using qualitative evidence synthesis methods

BACKGROUND

Epilepsy affects nearly 50 million people worldwide. Self-management is critical for individuals with epilepsy in order to maintain optimal physical, cognitive, and emotional health. Implementing and adopting a self-management program requires considering many factors at the person, program, and systems levels. We conducted a systematic review of qualitative and mixed-methods studies to identify facilitators and barriers that impact implementation and adoption of self-management programs for adults with epilepsy.

METHODS

We used established systematic review methodologies for qualitative and mixed-methods studies. We included studies addressing facilitators (i.e., factors that aided) or barriers (i.e., factors that impeded) to implementation and adoption of self-management interventions for adults with epilepsy. We conducted a narrative thematic synthesis to identify facilitators and barriers.

RESULTS

The literature search identified 2700 citations; 13 studies met eligibility criteria. Our synthesis identified five themes that categorize facilitators and barriers to successful implementation epilepsy self-management: (1) relevance, intervention content that facilitates acquisition of self-management skills; (2) personalization, intervention components that account for the individual's social, physical, and environmental characteristics; (3) intervention components, components and dosing of the intervention; (4) technology considerations, considerations that account for individual's use, familiarity with, and ownership of technology; and (5) clinician interventionist, role and preparation of the individual who leads intervention. We identified facilitators in 11 of the 13 studies and barriers in 11 of the 13 studies and classified these by social-ecological level (i.e., patient/caregiver, program, site/system).

CONCLUSION

Identification of facilitators and barriers at multiple levels provides insight into disease-specific factors that influence implementation and adoption of self-management programs for individuals with epilepsy. Our findings indicate that involving individuals with epilepsy and their caregivers in intervention development, and then tailoring intervention content during the intervention, can help ensure the content is relevant to intervention participants. Our findings also indicate the role of the clinician (i.e., the individual who provides self-management education) is important to intervention implementation, and key issues with clinicians were identified as barriers and opportunities for improvement. Overall, our findings have practical value for those seeking to implement and adopt self-management interventions for epilepsy and other chronic illnesses.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number is CRD42018098604.

Using discrete choice experiments to develop and deliver patient-centered psychological interventions: a systematic review

Developing and/or tailoring psychological interventions to align with patient preferences is a critical component of patient-centered care and has the potential to improve patient engagement and treatment outcomes. Discrete choice experiments (DCEs) are a quantitative method of assessing patient preferences that offer numerous strengths (i.e., ability to account for trade-offs), but are not routinely incorporated into health psychology coursework, likely leaving many unaware of the potential benefits of this methodology. To highlight the potential applications of DCEs within health psychology, this systematic review synthesises previous efforts to utilise DCEs to inform the design of patient-centered psychological care, defined as interventions targeting psychological (e.g., depression, anxiety) or behavioural health (e.g., pain management, adherence) concerns. Literature searches were conducted in March 2017 and November 2019 for articles reporting on DCEs using the terms 'discrete choice', 'conjoint', or 'stated preference'. Thirty-nine articles met all inclusion criteria and used DCEs to understand patient preferences regarding psychosocial clinical services (n = 12), lifestyle behaviour change interventions (n = 11), HIV prevention and/or intervention services (n = 10), disease self-management programmes (n = 4), or other interventions (n = 2). Clinical implications as well as limitations and directions for future research are discussed.

Digital and technological opportunities in epilepsy: Toward a digital ecosystem for enhanced epilepsy management

This commentary details the implications of a growing body of literature supporting several categories of supportive digital tools for the self-management of epilepsy. Although many prior review articles have focused on specific forms of digital epilepsy solutions, we propose the concept of an integrated self-management digital ecosystem. This would include categories of tools including self-management education programs, electronic diaries for self-monitoring, and automated wearables for seizure detection. Within these categories, individual interventions have been studied and made available to patients for years, but the evolution of a digital ecosystem promises the potential to integrate these tools in a manner that can meaningfully benefit patients' health. This commentary presents a discussion of the possible concerns that are preventing more widespread adoption of these digital health resources. Barriers are identified at multiple positions of the healthcare system, including the individual, the organizational, the community, and the policy levels.

Understanding patients' preferences for osteoporosis treatment: the impact of patients' characteristics on subgroups and latent classes

This study revealed patterns in osteoporosis patients' treatment preferences, which cannot be related to socio-demographic or clinical characteristics, implicating unknown underlying reasons. Therefore, to improve quality of care and treatment, patients should have an active role in treatment choice, irrespective of their characteristics.

INTRODUCTION

Patient centeredness is important to improve the quality of care. Accounting for patient preferences is a key element of patient centeredness, and understanding preferences are important for successful and adherent treatment. This study was designed to identify different preferences profiles and to investigate how patient characteristics influence treatment preferences of patients for anti-osteoporosis drugs.

METHODS

Data from a discrete choice experiment among 188 osteoporotic patients were used. The hypothetical treatment options were characterized by three attributes: treatment efficacy, side effects, and mode/frequency of administration. A mixed logit model was used to measure heterogeneity across the sample. Subgroup analyses were conducted to identify potential effect of patient characteristics. Latent class modeling (LCM) was applied. Associations between patients' characteristics and the identified latent classes were explored with chi-square.

RESULTS

All treatment options were important for patients' decision regarding osteoporotic treatment. Significant heterogeneity was observed for most attributes. Subgroup analyses revealed that patients with a previous fracture valued efficacy most, and patients with a fear of needles or aged > 65 years preferred oral tablets. Elderly patients disliked intravenous medication. Three latent classes were identified, in which 6-month subcutaneous injection was preferred in two classes (86%), while oral tablets were preferred in the third class (14%). No statistically significant associations between the profiles regarding socio-demographic or clinical characteristics could be found.

CONCLUSIONS

This study revealed patterns in patients' preferences for osteoporosis treatment, which cannot be related to specific socio-demographic or clinical characteristics. Therefore, patients should be involved in clinical decision-making to reveal their preferences.

Characteristics of Future Models of Integrated Outpatient Care

Replacement of fee-for-service with capitation arrangements, forces physicians and institutions to minimize health care costs, while maintaining high-quality care. In this report we described how patients and their families (or caregivers) can work with members of the medical care team to achieve these twin goals of maintaining-and perhaps improving-high-quality care and minimizing costs. We described how increased self-management enables patients and their families/caregivers to provide electronic patient-reported outcomes (i.e., symptoms, events) (ePROs), as frequently as the patient or the medical care team consider appropriate. These capabilities also allow ongoing assessments of physiological measurements/phenomena (mHealth). Remote surveillance of these communications allows longer intervals between (fewer) patient visits to the medical-care team, when this is appropriate, or earlier interventions, when it is appropriate. Systems are now available that alert medical care providers to situations when interventions might be needed.

Caring electronically for young outpatients who have epilepsy

PURPOSE

The purpose of this study was to review electronic tools that might improve the delivery of epilepsy care, reduce medical care costs, and empower families to improve self-management capability.

METHOD

We reviewed the epilepsy-specific literature about self-management, electronic patient-reported or provider-reported outcomes, on-going remote surveillance, and alerting/warning systems.

CONCLUSIONS

The improved care delivery system that we envision includes self-management, electronic patient (or provider)-reported outcomes, on-going remote surveillance, and alerting/warning systems. This system and variants have the potential to reduce seizure burden through improved management, keep children out of the emergency department and hospital, and even reduce the number of outpatient visits.