In the field of Health Technology Assessment (HTA), understanding the preferences of patients, healthcare professionals, and other stakeholders is crucial for making informed decisions. One valuable tool for capturing these preferences is the Discrete Choice Experiment (DCE). This article aims to explore what a DCE is, its value in HTA, the main steps involved in implementing a DCE, and best practices when building a DCE. By following these steps, researchers can effectively elicit and analyze preferences, leading to better-informed decision-making processes.

What is a DCE?

A Discrete Choice Experiment (DCE) is a quantitative research method used to assess and measure preferences. It presents participants with a set of hypothetical choices between different health interventions or treatment options, each with different attributes, and asks them to state their preferred option. By analyzing these choices, researchers can determine which attributes are most important to patients and stakeholders and how they weigh the trade-offs between different attributes.

What is the value of DCE?

Patient Preference Studies (PPS) like DCE can be implemented in each step of the medical development process life cycle in various ways. For example, DCE provides valuable insights into patient needs during the discovery phase and can also help with trial design during the clinical development phase. Preferences can also be used to evaluate the value of healthcare interventions and during the HTA phase, stakeholders can use these insights to allocate resources more efficiently and effectively to develop treatments with preferred attributes.

Main steps to implementing a DCE:

Step 1. Define the research question: Clearly articulate the research objectives and the specific preferences to be measured. Identify the target population and relevant attributes that influence decision-making.

Step 2. Design the choice sets-choose the attributes and identify levels: Develop choice sets that represent the alternatives. Define the attributes and their levels based on a thorough literature review, expert input, and stakeholder engagement. Ensure that the combinations of attribute levels are realistic and representative of the decision context. Consider the appropriate number of choices to balance the respondent burden and statistical efficiency.

Step 3. Pilot testing: Before conducting the main study, it is essential to pilot test the DCE design. This helps identify any issues with the questionnaire, refine the attribute descriptions, and ensure that the choice sets are understandable and realistic to respondents.

Step 4. Sampling and data collection: Determine the appropriate sample size and sampling strategy based on the research question and target population. Consider the mode of data collection, such as online surveys, face-to-face interviews, or telephone interviews, based on the target population and available resources. Use the appropriate data collection method to minimize biases and maximize response rates.

Step 5. Data analysis and interpretation: Employ appropriate statistical techniques to analyze the data and estimate preference models. There are three main types of models to choose from. The first is a model to estimate preference weights conditional importance of attributes. The second model identifies groups with similar treatment preferences. The last one is an estimation of willingness to pay. After running the various models, interpret the results in the context of the research question. Provide clear and concise summaries of the findings, including the relative importance of attributes.

Best practices when building a preference study using DCE

• It is important to involve stakeholders, such as patients, caregivers, and healthcare professionals, in the design process to ensure that the research question and the attributes of interest are relevant and meaningful. This can be achieved through focus groups, interviews, or surveys.
• The experimental design should be simple, the number of attributes and levels should be kept to a minimum to avoid overwhelming the participants. Generally, the number of attributes to evaluate is between 5 and 8. The main categories of treatment attributes are: Benefits, Risk, and Treatment Modalities.

• The questions should be written in a way that reduces biases.  For example, there should be neutrality in phrasing the questions and each attribute should show up an equal number of times in the DCE.
• Clear instructions and guidance should be provided to the participants to ensure that they understand the purpose of the study and how to complete the DCE. It is important to explain the concept of trade-offs and the hypothetical nature of the choices.

Discrete Choice Experiments (DCEs) are valuable tools in the field of Health Technology Assessment (HTA) for eliciting and measuring preferences. By following the main steps outlined above and adhering to best practices, researchers can effectively design and implement preference studies using DCEs. The insights gained from DCEs contribute to evidence-based decision making, helping policymakers allocate resources and make informed choices that align with the preferences of patients, healthcare professionals, and other stakeholders.

EvidentIQ can provide support when conducting DCE studies. From the experimental design stage to implementation and reporting, EvidentIQ can customize a solution that can help you effectively execute your patient preference study. They offer best-in-class Real World Evidence (RWE) methodologies, such as DCE, for patient studies in multiple diseases and geographical areas thanks to their direct access to a global patient platform. Patient studies can focus on treatment preference, quality of life, value of health, disease/treatment burden, unmet needs, etc. EvidentIQ can help generate unique Real World Data (RWD) to significantly help life sciences customers support the value story of their product for HTA submission, pricing and reimbursement as well as their scientific communication within the clinical community.

Sources: 

https://www.youtube.com/watch?v=IPIkIXWOJ5g
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8546533/#:~:text=A%20discrete%20choice%20experiment%20

https://yhec.co.uk/glossary/discrete-choice-experiment-dce/

https://bmjopen.bmj.com/content/11/3/e045803

https://systematicreviewsjournal.biomedcentral.com/articles/10.1186/s13643-021-01647-z

Patient recruitment has often focused on traditional media methods like TV, newspaper, and radio, which often lead to a low recruitment conversion rate. Digital patient recruitment can target specific communities that are both more likely to be interested in and eligible to participate in the clinical trial which, in turn, can save money and keep the clinical trial on schedule.

What is patient recruitment?

Patient recruitment is the process of identifying, screening, and enlisting eligible patients that are willing to participate in a clinical trial.

There are different methods of patient recruitment. Traditional advertising media channels include TV, radio, or brochures. However, the use of these methods often results in a majority of interested patients being ineligible to participate due to specific exclusion criteria. Investigators can use existing patient databases to identify possible candidates but only patients who are searching for clinical trials would be registered in these. That leaves a large untapped market. Patients can also be recruited directly by their physician or an advocacy group. This recruitment method generally has a higher conversion rate: the number of potential participants informed about the trial vs. number of patients finally recruited to participate. Patients are more likely to be persuaded by a personal connection than a mass marketing advertisement. Both the physician and advocacy group earn the patient’s trust and act as a liaison informing them of the benefits of the trial and calming any hesitations. Digital marketing is also becoming more prevalent. This includes advertising online using keyword targeting. 1 in 3 adults have researched online for medical information. Specific ads are pushed to people who use particular keywords when discussing their conditions on social media or while searching for treatments using search engines. Digital tools can help target wider audiences who already are engaged and interested in a particular illness. These methods typically offer more of a return on investment of advertising funds.

Challenges of patient recruitment

Bringing new treatments to market as quickly as possible is the goal of every clinical trial team. Patient recruitment is a critical part of the trial schedule and budget. If a trial has trouble with patient recruitment, it can extend the length of the trial timeline and incur additional costs. Also, if the trial fails to get enough participants, and the pre-established sample size is not achieved, it could cause the sponsor to abandon the results. Ultimately, efficient patient recruitment can reduce costs and can ensure the trial completion.

One of the main challenges to patient recruitment is that the number of available patients who meet the trial inclusion criteria is often fewer than expected. Since conversion rates are usually low, around 10%, the size of the initial patient pool will affect the total number of participants. The next challenge is identifying and targeting the groups that meet eligibility requirements. Most people are not familiar with what a clinical trial is or how to participate in one. Therefore, in addition to the challenge of finding eligible patients, it is necessary to also educate and convince them to participate. Finally, patient retention is another challenge to completing clinical trials. Patients volunteer to participate in clinical trials and can choose at any time to quit. Prolonged interest in the trial is a vital characteristic that one should look for during the recruitment phase.

How to conduct proper patient recruitment

After the proper approvals have been processed for the trial, and the research team assembled, then it is time to start patient recruitment.

1. The first step to patient recruitment is to select the eligibility requirements for participation and to establish a target audience. Once an ‘ideal’ candidate has been identified, research into that persona type will help the recruiter understand how best to market to them. This research should include:-motivation to participate: What will it take to convince the patient to volunteer their time and energy to participate? Are they motivated by money? In the search for a cure? Will the trial help their condition? What is the value proposition you are offering the candidate? Clearly articulate the relevance of the study and emphasize the possible benefits in your marketing materials.-condition area:  What condition do they have? The type of condition may affect a patient’s willingness to participate in trials. According to a study, patients with chronic conditions are less likely to participate in trials for new drugs because it can take a long time to find the correct treatment for these conditions. You should tailor the outreach approaches to match the type of condition.-best marketing media: What marketing channel will they most interact with? What age is the ideal candidate for your study? What media type do they want to interact with? Does this person want a brochure, video, blog, pdf to download? The marketing strategy you develop should match these aspects of your candidate.
2. Create a simple process for participation. The intake paperwork should be user-friendly, easy to understand, and accessible. Electronic enrollment is one way to simplify this process and gain more interaction with possible participants. Digital tools include online screening questionnaires, scheduling services, and trial information materials. It should be easy for a participant to contact someone involved in the trial and ask questions; this can also be done online.
3. Next, set goals, milestones, and track the conversion rate– how many people see and interact with your marketing vs how many enroll. This will help determine the number of people that need to see your ad before you get enough for your trial- help determine the type of advertising. You may do this through a pilot study and/or through analysis of past trial recruitment statistics.Once you have one persona for each of your ideal candidates, then you may choose to run a pilot study. A pilot study is a scaled down version of the clinical trial requiring fewer participants which tests the trial’s feasibility. If the pilot study fails to recruit enough patients, then it is likely the trial will also fail, and resources would be wasted. The pilot study will also help the researchers identify potential barriers to patient recruitment. Adjustments to the recruitment strategy can be implemented to avoid the same pitfalls during the patient recruitment. This may include changing screening criteria, adding more test sites, or modifying the marketing mix.   If you choose not to do a pilot study, you may analyze data from your past enrollment performance to help you determine a feasible enrollment estimate. This will allow you to adequately manage the finances and staff resources of the study. Pay attention to the number of patients recruited, how long it took to get the first enrollment, and what percentage of the enrollment goal was achieved. Use this past data to identify what form of marketing worked best for the audience.
4. Create a marketing strategy. Identify the marketing mix for your message (place-where will you advertise, product-how will you position your trial, price-what is it that you will give the volunteers, promotion- how will you tell your audience about the trial, process-what is the process to be involved, people-who is involved to get your trial participants). Make sure the information is clearly written and easy to understand, pay attention to not use complex medical jargon. Patients need to feel comfortable with the trial and understand the process. The marketing elements should have a clear call to action. Offering them a roadmap of what is expected of them and how the results will be used.
5. Start recruiting and stay organized. Execute your carefully planned recruitment. Track all your results and capture, in detail, the contact information from interested patients, even those that may not be eligible because perhaps they will be interested in a future study. Remember to ensure patient privacy and that your data collection/retention is following all privacy laws.

Best practices

Tailor communication strategy. Communication is key to building trust, establishing expectations, explaining processes, and keeping the patients informed. The communication plan starts the first interaction the patient has with the trial. The marketing materials should anticipate and answer the patients’ questions. Do the images and terminology reflect the target population? Take into consideration cultural and language differences of your participants. This will make them feel more at ease and comfortable with the process of the trial.

Follow up with patients. Incorporate digital elements like text messages, automated emails or personalized scheduling reminders. These tools can be used to remind patients to take the next steps. Is there constant contact with the trial participant to keep them involved in the trial? Incorporate a range of outreach methods to reach patients and provide them with the necessary information and useful content to keep their interest.

Answer every question the patient has regarding the trial. Keep the physician or advocacy group involved and address any doubts, concerns and to convey the benefits of the study. Use social media platforms to keep connected with the audience and inform them of the results via mixed media like infographics and video.

Show appreciation for the trial participants. Many are receiving financial compensation but that is not always enough to get a participant to “buy into” the study and continue to give their time. How can this trial benefit them- does it help give them a better understanding of their condition? The trial will also move research forward and can help other patients like them in the future.

Keep it interesting. Recruitment and retention are largely affected by the enthusiasm of the lead investigator. If they are showing interest and providing proper follow up because they believe in the success of the study, the participants will too.

Include digital tools. Online aspects are used for patient recruitment, retention, and for the trial itself. Digital patient recruitment can target more precisely a larger audience. Follow up messages via email, social media, or text messages are a great way to encourage patients to take the next step and keep them interested. Tracking enrollment numbers and keeping an updated database can help keep investigators organized. The clinical trial itself can be performed ‘decentralized,’ where the patients are all virtual. Digital clinical trials can widen the eligibility pool. If the trial is available remotely, then there are more people that can participate as location is no longer a limitation. In-person aspects of the trial should be coordinated in conjunction with local health sites. Direct-to-patient lab services are also available and can be explored when necessary.

Recruiting enough patients that qualify for clinical trials is always a challenge. Traditional marketing methods often fail to recruit enough trial participants. Now, with the use of digital tools, it is possible to more efficiently and cost effectively target patients willing and able to participate in trials. EvidentIQ offers a suite of applications within a single integrated cloud platform for clinical data management, clinical operations, and patient centricity. These digital tools not only help for recruitment but also with patient tracking, communication, retention, and can provide statistics for when planning your next clinical trial.

Take a look at our complete offer here.

How to leverage data linkage to get better outcomes?

EvidentIQ, a leading clinical data science group, announced its partnership with Feel Therapeutics, a digital therapeutics US-based company. The alliance between these two visionaries of tech has resulted in the building of unique end-to-end solutions to link data and digitize clinical trials through a seamless patient journey supported by direct access to patients, best-in-class technologies and in-house data science expertise.

• What is Real-World Evidence and the different sources of Real-World Data?
• How to collect real-time physiological data 24/7 to monitor emotions, physical activity, and sleep quality: the example of Feel Therapeutics Data Monitoring and Digital Endpoint Discovery Platform
• How to efficiently collect self-reported outcomes?
• How to combine these two innovative data sources?

On May 12th our data linkage webinar took place. We showed you how innovative Real-World-Evidence generation can help to efficiently combine digital biomarkers and self-reported outcomes.

Access the replay! We will walk you through the new data linkage thanks to this partnership, combining best-in-class technologies and expertise of EvidentIQ and Feel Therapeutics.

Access the replay


Download the presentation

Contact us for more information: pro@carenity.com

April 5^th, 2022, Hamburg (GERMANY). Today, Carenity, part of the EvidentIQ Group, announced its partnership with Feel Therapeutics, a US-based digital biomarkers and therapeutics company. The alliance has produced a series of unique end-to-end solutions to seamlessly capture continuous digital biomarker data and digitize clinical trials throughout the patient journey. The solutions are supported by direct access to 500,000 patients, patented technology for continuous health monitoring, and in-house data science expertise to support real world evidence (RWE) generation and clinical research capabilities for life science industry customers.

 

Data linkage shows the importance of integrating data sets for better health outcomes

 

The data linkage approach combines rich, self-reported patient data collected through EvidentIQ’s Carenity platform with continuous, physiological data captured by Feel’s data monitoring device, and translates them into digital biomarkers. The combined datasets offer a complete patient picture and generate new evidence, bringing RWE to the next level. Throughout the process, EvidentIQ and Feel Therapeutics employ patient recruitment & onboarding, data monitoring and linkage capabilities, and data science expertise. They will also apply study design services such as protocol writing, questionnaire development (ePROs, ediaries), as well as IRB/EC submission and advisory board.

 

DCT has become the new gold standard to optimize clinical trials

 

Catalyzed by the COVID-19 pandemic and supported by recent changes to the regulatory framework, DCT (Decentralized Clinical Trials) adoption has risen steadily in recent years, with an expected growth of 28% in 2022 and a total of more than 1,300 clinical trials including a virtual component expected to commence this year. EvidentIQ and Feel Therapeutics offer an innovative hybrid or fully virtual clinical trial experience that include patient insight-driven DCT strategy definition, study design, patient recruitment, trial management software suite, study monitoring and biostatistics. The joint offering leverages Carenity’s patient platform to design a patient centric DCT and accelerate patient recruitment, with state-of-the art electronic data capture (EDC) and eClinical solutions (eConsent, eCOA…) employed throughout the trial. Decentralization is further enabled by Feel’s data monitoring device, which captures digital biomarkers and passively monitors patients, as well as its data science expertise and the use of its proprietary biomarker discovery and real world data platform.

 

With this best-in-class data linkage and DCT offering, EvidentIQ and Feel Therapeutics become a strategic partner for the life sciences industry to run innovative, patient-centric studies and generate powerful, high quality data from clinical trials.

 

About Feel Therapeutics

 

Feel Therapeutics (FKA Sentio Solutions) is a San Francisco based company which develops digital biomarkers and therapeutics to reinvent the way we diagnose, manage, and care for mental health by using continuous, objective and passive data collection. The company is backed by top VC firms and has kicked-off deployments with large Health & Life insurers in the USA and Germany.

 

Contact us for more information.

 

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