Melanoma Clinical Trials -old

Melanoma Clinical Trials

Capstone Project

The process of matching patients with melanoma to suitable clinical trials is currently inefficient, time-consuming, and inaccessible for oncologists. The main website for searching clinical trials, Clinicaltrials.gov, only serves as a reporting tool and does not prioritize the best interests of patients. The lack of trial discoverability directly contributes to the challenges faced by oncologists in identifying appropriate trials.

To address this issue, we collaborated with Dr. Bryan Carroll to undertake a redesign of Clinicaltrials.gov. The redesign incorporates several key features, including enhanced search functionality, easily understandable trial details, and the ability to apply directly to trials. These improvements aim to provide oncologists with better-curated trial recommendations, ultimately saving them valuable time that would otherwise be spent navigating through a large number of trials.

MY ROLE

UX Researcher, UX Designer

DURATION

January 2023 - May 2023

CLIENT

Dr. Bryan Carroll, University Hospitals of Cleveland

TEAM

Anna Rippert, Saloni Gandhi, Namita Rao, Sruti Srinidhi, Wenqing Yin

View Solution

"Your solution doesn't reinvent the wheel but instead, creates a bridge between patients and clinical trials ... you can literally change thousands of people's lives with this."

- Surgeon at University Hospitals

Context

Melanoma, the deadliest skin cancer, has a rising diagnosis rate. Clinical trials offer advanced treatments for aggressive melanoma, relying on human volunteers. Second opinions are crucial for patients who haven't responded to other treatments. Yet, barriers limit access to these clinical trial opportunities for those with aggressive melanoma.

The patient's journey begins with a dermatologist diagnosing melanoma through skin tests and excision. An oncologist then provides treatment using various therapies. If the cancer is advanced, the case is presented to the Tumor Board for evaluation. If internal trials are unavailable, the melanoma medical oncologist identifies suitable external clinical trials by collaborating with specialists and searching clinicaltrials.gov. Once a trial is found, the oncologist engages in eligibility discussions with trial coordinators. Our solution is tailored specifically for oncologists, as they are the primary users responsible for finding trials.

Research

Interviews

To gain insight into the handling of complex melanoma cases, we conducted 9 structured interviews using a directed storytelling approach. In collaboration with our client, we developed personas/mock patients to guide the storytelling process.

Domain Research

In order to grasp the nuances and terminology related to melanoma and clinical trials, we conducted thorough domain research. This involved studying multiple academic papers and documenting common vocabulary. This endeavor facilitated effective communication with oncologists, surgeons, and dermatologists during our interview sessions, as we established a shared understanding.

Competitive Analysis

To delve deeper into the challenges that oncologists face, we explored the existing resources and solutions currently available. By doing so, we aimed to identify the problems that are not actively being addressed in the field.

Insights

Based on our research, we have uncovered the following insights through affinity diagramming:

External clinical trials are inaccessible to oncologists.

Oncologists rely on their personal connections to find trials.

Determining whether a patient is eligible for a clinical trial is time-consuming.

The only resources to access external clinical trials are through word of mouth or on clinicaltrials.gov

Relying on their internal network does not always offer the best care for the patient’s needs.

It can take multiple months to get in contact with a trial coordinator and enrolling a patient into a clinical trial.

The Challenge:

How might we increase the visibility of different approaches to oncologists so they can determine the right clinical trials and medical centers for melanoma patients faster?

Ideation

Utilizing the "crazy 8's" technique, we generated a comprehensive set of 40 diverse ideas encompassing both physical and digital solutions. These ideas were subsequently clustered together during collaborative brainstorming sessions.

Through this process, we identified 12 promising concepts, with each team member contributing by highlighting their concerns or recognizing areas where significant value could be generated.

In the final phase, we presented these 12 ideas to the client and engaged in an iterative process. Together with the client, we carefully evaluated the feasibility, user-centeredness, and value proposition of each idea. As a result, we narrowed down our selection to a refined set of 4 final ideas.

Idea 1

Facilitating referrals for clinical trials

Idea 2

Portal for standard application

Idea 3

Optimising search and filter

Idea 4

Online tumor board

Low-Fidelity Prototyping

To gather feedback on the feasibility of each idea and address any concerns, we conducted speed-dating sessions with six oncologists, presenting them with each storyboard. Taking their feedback into account, we iterated on the storyboards to address their concerns and refine our concepts. Ultimately, we selected the storyboard that demonstrated the highest potential value for oncologists, ensuring its alignment with their needs and preferences.

Mid-Fidelity Prototype

After validating our low-fidelity concept, our team collaborated to create a comprehensive user workflow with greater detail. During the mid-fidelity process, I took on a leadership role , overseeing all mid-fidelity deliverables. Each team member was tasked with designing an interface for each of the workflows (Search, Recommended Trials, Trials Details, and Application). Through parallel prototyping, we were able to explore diverse visualizations of interactions and information. Presented below is the flow I personally designed, accompanied by insights into my design decisions:

Search for a clinical trial for a specific patient

Accessible on clinicaltrials.gov to avoid users switching back and forth between platforms

Patient data drawn from Electronic Medical Records to save time inputting information like past medical history

Ability to always go back to a regular search

Testing

In order to gather feedback on the user workflow and interactions, we conducted testing of the mid-fidelity prototype with six oncologists. Our objective was to employ think-aloud protocols to capture their reactions, questions, concerns, and overall impact. The testing process yielded the following findings:

Discrete searching options help narrow down and eliminate unfit clinical trials
Categorizing each trial's details improves scannability and saves time
Not all Electronic Medical Records are the same for each hospital which may make it hard to extract them from the search

solution

Solution

View interactive Figma prototype here!

Break down of the values generated for each core interface:

Search for a clinical trial for a specific patient

The new Advanced Search tab allows oncologists to search for clinical trials for specific patients. This provides them with search results that are more curated for their patient's conditions compared to their current search function.

The Advanced Search is organized into categories that grow in specificity, allowing oncologists to better navigate and easily answer the search questions.

View clinical trial in detail

The current trial details page is very text-heavy, containing many long lists of text, and has been noted to be difficult to navigate by all oncologists interviewed. By organizing the text into categories, oncologies can easily scan the information they are searching for. A horizontal menu has been created to allow oncologists to easily jump to specific sections without having to scroll to find a section.

The Eligibility Criteria section has turned into an interactive checklist to assist oncologists in efficiently determining whether their patient is eligible for a clinical trial. The Eligibility criteria have been split into "Priority" and "Preferred" to further help oncologists digest information easier.

Oncologists often compare clinical trials to see which one would best suit their patient, which involves a lot of back and forth. A new Compare Panel has been added to help improve the efficiency of this process.

Min

Recommend clinical trials best suited for patient

Through the machine learning algorithm our team developed, oncologists can now see how much of a match a clinical trial is given the information they provided in the search. This allows oncologists to clearly see which clinical trials may be a match at first glance, saving time determining this manually.

The additional columns "Criteria Match" and "Criteria Non-Match" lets oncologists be able to see why or why not a clinical trial is a match. During testing, oncologists noted that this feature would save them time and effort in discovering this information themselves.

Ability to apply to clinical trials directly

Currently, you cannot apply directly to clinical trials on clinical trials.gov. To mitigate the month's oncologists spend getting in contact with the trial coordinator, oncologists can now apply directly on the website.

Multiple clinical trials can be applied at the same time with a single application, further saving time from oncologists doing it manually. The application is pre-generated using information from the oncologist's account.

Lastly, oncologists can submit their Match Percentage score to showcase to the trial coordinator that the patient will be a good fit for their trials, further saving weeks doing this manually over email and phone calls.

Next Steps

Pitch solution to clinicaltrials.gov

The clinicaltrials.gov modernization team is dedicated to redesigning clinicaltrials.gov to be more usable. Our client will take over our designs and pitch the solution for them to implement into clinicaltrials.gov.

Scale across all cancers beyond melanoma

The solution has been made specifically for melanoma but is applicable and has the opportunity to be designed for all diseases beyond melanoma.

Fully build out the ML algorithm

The current ML algorithm is a proof of concept and only uses a few user inputs. Building it fully out will further filter down the clinical trials and provide oncologists with the best recommendations.

Website Re-design

Amazon Brand Registry

MY ROLE​

Interviews

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Domain Research

Competitive Analysis​

MY ROLE

Competitive Analysis