The field of medical product development is constantly evolving, with patient-centered approaches gaining importance. Patients’ experiences and perspectives are invaluable in understanding the efficacy and impact of medical interventions. Traditionally, clinical trials and research studies have relied on clinician-reported data and objective measurements. However, in recent years, inclusion of patient-reported outcomes (PROs) has emerged as a valuable resource to inform all stages of the product development life cycle. What is the significance of patient self-reported data in supporting medical product development and how it can positively impact key stages of the development process?

What are Patient Reported Outcomes (PRO)?

A patient-reported outcome (PRO) is data obtained directly from patients and is based on a patient’s perception of a disease and its treatment. PROs are important because they provide a patient perspective on a disease/treatment that might not be captured by a clinical measurement. This information is collected through validated questionnaires or surveys, where patients self-report their experiences; these responses come directly from the patient, without interpretation of the patient’s response by a clinician or anyone else. Traditionally, PROs have been collected using a paper-based questionnaire, but as with most paper forms, many labs have recently migrated to electronic forms, also known as electronic Patient Reported Outcomes (ePRO). PROs offer a unique perspective as they reflect the patients’ feelings, preferences, and day-to-day experiences with a medical condition or treatment. Some examples of PROs include pain levels, physical functioning, mental health, and overall satisfaction with treatment.

How are Patient Reported Outcomes used in the Product Development Life Cycle?

1. Conceptualization (Pre-clinical): 

The product development life cycle starts with conceptualization. In this phase, ideas for new medical products and treatments are brainstormed, evaluated, and selected to move on to the clinical development phase. By engaging patients early in the process, medical developers can gain valuable insights into patient perspectives, preferences, and priorities, ensuring that the product’s concept aligns with actual patient demands. Incorporating patient self-reported data during this phase can be instrumental in identifying unmet patient needs and provide a good foundation for creating a desirable final product that patients will want.

2. Feasibility Assessment: 

During the planning stage, the design is conceptualized. The concept is based on customer needs and technical requirements. The feasibility of the concept is assessed. Product developers evaluate the practicality and viability of their proposed medical product.  There is a prototype analysis, various go-to-market strategies are developed, and an initial testing takes place in order to collect user feedback. The patient’s perspective regarding the product’s design is taken into consideration before moving on to further development steps.

3. Design and Development:

Patient self-reported data plays a pivotal role in the design and development phase. PROs better capture negative, uncomfortable, and impactful symptoms from the patient’s perspective, such as nausea and anxiety. Therefore, they are better at identifying potential risks and side effects, enabling developers to proactively address safety concerns. Incorporating patient perspectives can enhance the usability, functionality, and overall patient experience of the medical product.

4. Validation/Clinical Trials:

Clinical trials are critical in determining a medical product’s safety and efficacy. By utilizing patient self-reported data in these trials, developers can assess patient outcomes and experiences with the product under real-world conditions. PROs measure the subjective elements of patients’ conditions, including health-related quality of life, pain intensity, activity limitations, participation restrictions, satisfaction or adherence to treatment and help to evaluate the burden of disease and treatment from patients’ perspectives. Integrating PROs into clinical trial data not only enhances the data’s comprehensiveness but also validates the product’s efficacy from a patient’s standpoint.

5. Launch and Regulatory Approval: 

Regulatory bodies such as the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are increasingly recognizing the significance of patient self-reported data in evaluating product efficacy and safety. They should still be supported by objective or functional outcomes but by including PROs in clinical trial data submissions, companies can provide regulators with a more comprehensive view of the product’s benefits and potential risks.

6. Post-Market Surveillance:

Once a medical product enters the market, the company must continually monitor its safety and continue to gather patient feedback. Once on the market, it will be sold and used by a more diverse population and therefore may lead to unexpected results.  PRO is one kind of data that researchers can use to track adverse events, product shortcomings, and areas for improvement. Analysis of this feedback can be used for continuous product updates that provide better results for unmet patient needs.

By capturing patients’ experiences and perspectives, patient self-reported data can enrich a clinician’s understanding of the patients’ experience with unique information that could not be gained from biomedical outcomes alone. Integrating PROs into the product development life cycle allows for improved clinical outcomes, accelerated regulatory approvals, and faster product improvements. Companies should embrace patient-centric approaches as they will not only lead to more effective and user-friendly treatments, but also foster stronger patient-company relationships built on trust and empathy.

Through Carenity, a dynamic online community encompassing +500,000 patients and caregivers, EvidentIQ offers direct, compliant, and timely access to real-world patient data. Leveraging our Carenity platforms, we deliver a distinctive range of solutions, including Real-World Evidence, Clinical Trial Optimization, and Scientific Communication and Publications.

Carenity creates a supportive space by uniting individuals facing similar conditions, fostering connections through features like newsfeeds, discussion forums, private messaging, and more. We recognize the significance of technology in combating isolation and enhancing information sharing among members.

We have imagined an innovative model based on collaboration and honesty. On Carenity, patients are invited to express their expectations based on their conditions and on their treatment, so that they can be taken into consideration by those who will be developing the enhanced health solutions for patients.

Sources:

https://www.americanpharmaceuticalreview.com/Featured-Articles/594397-The-Lifecycle-from-Drug-Development-Through-Approval-Processes/#:~:text=The%20average%20lifecycle%20of%20drug,about%2010%20to%2012%20years.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1629006/

https://www.americanpharmaceuticalreview.com/Featured-Articles/594397-The-Lifecycle-from-Drug-Development-Through-Approval-Processes/#:~:text=The%20average%20lifecycle%20of%20drug,about%2010%20to%2012%20years.

https://learn.marsdd.com/article/product-development-lifecycle-new-drug-development/

https://toolbox.eupati.eu/resources/patient-reported-outcomes-pros-assessment/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219423/

https://www.bsigroup.com/en-US/medical-devices/Our-services/product-lifecycle/

https://ep.bmj.com/content/105/3/185

https://toolbox.eupati.eu/resources/patient-reported-outcomes-pros-assessment/

https://jpro.springeropen.com/articles/10.1186/s41687-020-00219-4

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

An evidence generation strategy is an advanced plan for generating evidence necessary for all the steps of the product life cycle. Traditionally, research follows consecutive steps which is more of a reactive process. Using an evidence generation strategy allows for proactive planning and execution of a holistic strategy.

What is evidence generation and what is it used for?

Evidence generation is multifaceted and includes various study designs and data sources. Typically, each department involved in the process (e.g., clinical development, medical affairs, and health economics and outcomes research (HEOR)) works in a siloed structure and independent from one another to come up with evidence to support their specific research topics.

Integrated evidence-generation plan (IEP) is a strategy used where the upfront research plan is developed specifically to find evidence to address the concerns of each stakeholder group (payers, clinicians, patients). Beyond simply proving if a therapy is effective and safe, pharmaceutical companies need to prove that the new treatment is addressing market gaps that the current products do not meet.

Each of these stakeholders have different needs and questions regarding new treatments. Payers, those who pay for the development of the treatment, want to ensure the final product has a value to the healthcare system and will prove to be profitable when launched. Clinicians look for evidence-based research to show how the new treatment is different from existing options. Patients need to know how the new treatment will meet their needs and solve their problems.

An IEP will pinpoint these motivations from each group and strategically set up testing to address each one. Considered in the planning are all functions, geographies, and the entirety of the life cycle to meet the needs of the various stakeholders. Demonstrating the economic, clinical and patient burden of a disease is a key need early in the development process and sets the stage to inform stakeholders regarding the potential value of a product.

Why it is important to have a plan early?

Early evidence-generation planning is key to allowing time to connect all the dots between functions and requirements. It is of vital importance when demonstrating value for the new treatment and it must be demonstrated throughout the lifecycle of the product (early development, clinical research, launch, and post approval) to understand the implications of how the product will address needs at each step along the way.

Impactful data points for each function team (medical, clinical, commercial) can be identified and a roadmap created to ensure the evidence-generation plan includes steps to achieve these data results which will add to the products overall value proposition. A cross-functional and early approach ensures the funding and required expertise is available at all stages.

What are the main steps where you could need evidence?

The ultimate goal of the treatment is to hit the market and provide a solution for the patient, add value to the healthcare community in the form of a differentiated treatment, while being profitable for the developer. Therefore, during the development of the product, it is beneficial to incorporate these factors into each stage of the product lifecycle.

In the early stages of development, there is a need to understand the current state of care for the target patient population. This includes conducting market research, literature reviews and developing a Health Economics and Outcomes Research (HEOR) strategy, identifying possible clinical trial designs, among other tasks that could benefit from evidence-generation. At this point in the product life cycle, the payer stakeholder is interested in the economic burden of disease in order to justify resources required to develop and adopt a new treatment.

During the clinical research and development stage is when patient trials and market access strategies start to be executed. Evidence generation collected from Randomized Clinical Trials (RCT) and patient reported outcomes (PRO) can be paired with Real World Evidence for proof of treatment effectiveness and differentiation of current on-the-market products. Clinicians will be most interested in the data that comes from this stage.

To launch a new product, a medical affairs team may use the evidence to inform their market access strategy and develop communications that target patient needs identified early on in the IEP. The launch stage is where the end prescriber and patient will be convinced of the value of the new treatment based on evidence leveraged through the marketing campaign.

The integrated evidence-generation plan utilizes the research results of all functions: market research, health economics and outcomes research, clinical trials, market access, patient-reported outcomes, literature reviews, etc, and combines them with the strategic objectives and ultimate value proposition. Be proactive with your go-to-market strategy, and plan in advance to address the needs of each stakeholder group. Along with a software suite for clinical trials, EvidentIQ offers the ability to run prospective and direct-to-patient studies with patient-reported outcomes through its Carenity Patient Platform. Carenity part of the EvidentIQ Group is a key partner to consider to support your data generation plan.

Take a look at our RWE offer.

Sources

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5047978/

https://www.openhealthgroup.com/news/17-01-2022/key-elements-of-a-real-world-evidence-generation-plan
https://marimacinsight.com/evidence-generation-strategy/
https://www.futuremedicine.com/doi/10.2217/cer-2017-0073
https://www.evidera.com/wp-content/uploads/2017/05/Strategic-Evidence-Generation-Planning-Product-Positioning.pdf
https://www.mckinsey.com/industries/life-sciences/our-insights/integrated-evidence-generation-a-paradigm-shift-in-biopharma

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.