What is Precision Medicine? It's an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person. Precision Medicine combines patient data with innovation and diverse partnerships to more precisely predict and diagnose diseases, target therapies, and personalize health and wellness plans. One of the patient data values this project focuses on is a patient's biomarker results (Genetics & Molecular Testing).
The Target Audience are Oncologists looking to put their patient on a more targeted treatment or clinical trial based on their biomarkers, disease progression, and line of therapy.
On average, it takes at least 2 - 6 weeks for results to be faxed or PDFs automatically sent to G2. Physicians call the waiting period a “Black box” because they don’t know exactly when to expect results. Ideally, they prefer results back before the patient’s 2nd visit, if not they may put them on a standard treatment but not a targeted one. In addition, physicians need to do manual data entry into the EHR for any biomarker insights that can be useful for system alerts. How might we make it easier for physicians to auto-ingest discrete results into the EHR so that they can make more informed treatment decisions?
To gain a better understanding of the Physician’s workflow, we interviewed 5 physicians with varied specialties and practice sizes. Each session was 45 minutes to 1 hour long asking open-ended questions about ordering tests and treatment decision workflow.
An overall takeaway from our insights are understanding that our users need quick turnaround times, especially when results can affect the treatment decision for their patient. Our current EHR has manual data entry for biomarker data, Physicians don’t have enough time, and depending on the size of the practice may not have scribes to do this for them. Lastly, data needs to be searchable and integrated throughout the entire system in order for it to assist Physicians with future treatment decisions.
The define stage focuses on understanding the users and their tasks in all stages of ordering molecular test results. There may be many pain points but mapping out their journey helped us prioritize the top issues on where the team should focus first. It also helped us gain education and empathy about the ordering process.
Creating the workflow was in collaboration with a previous design team that also did Discovery on only the process of ordering tests. We were able to take their research and expand on it further to cover the entire Molecular Results workflow.
The Lead Designer and I created a very comprehensive user journey that includes quotes to describe the insights for each stage. Most of the user pain points are related to ordering the tests, receiving results, documentation, and using the data for future considerations (ex. clinical trial eligibility). My favorite part of user journeys is identifying the opportunities to help solve those problems.
The design team explored ways to integrate and consider biomarker data intuitively in ways that can inform therapy decision-making and clinical trials consideration. The challenge was mapping out all entry points and capabilities within our current EHR.
In this Happy Path example, the user is in their EHR called G2. Once results are received, there are multiple ways they can access them based on our current system. No matter where the user discovers the lab results, they should have the ability to “add” the discrete data into Problems List where the information is integrated into a treatment decision tool called CVP.
One of the solutions to explore was a Test Orders Queue. This is where the user can track the status of an order and once delivered, review the results, and help eliminate the “Black Box” of uncertainty. Another challenge was how physicians review the results before adding them into the system.
1.0 Molecular Results Modal --> 2.0 CVP
0.0 Orders Tab --> 0.1 Orders Queue
Although our team was only in the Discovery phase, we used our Design Systems to create the visual design to prototype for concept testing.
Goal & Opportunities
Alleviate uncertainties and unnecessary efforts related to ordering status and result updates.
Explored Solutions
Effectively provide order status tracking with timely progress updates on orders.
Goal and Opportunities
Improve results interpretation and chart population.
Explored Solutions
Present all relevant and actionable information in an intuitive summary, while requiring little to no documentation from the physician’s end.
Goal and Opportunities
Physicians expect timely and accurate data across the EHR/EMR.
Explored Solutions
Enhance the existing experience by auto-populating data where relevant for cross-product reference.
Goal and Opportunities
Auto populates biomarker data and view biomarker-assisted therapy recommendations.
Explored Solutions
Make it easy for clinicians to learn about emerging therapies and clinical trials and suggest ways to identify patients that may benefit quickly.
Learnings and insights were directly applied to our concepts to ensure the right solutions within the product are released. This also greatly helped us detect potential costly issues well in advance. We spoke with 4 new physicians at different practices outside of our initial interviews to learn even more about ordering molecular tests. Our goal was to validate the solutions and to assist with prioritizing for business requirements.
Workflow Insights
Overall, the new concepts presented in the prototype were well received and felt intuitive. It helped solve their two main problems, alleviates stress related to not knowing when results may be available, and eliminate manual data entry.
Entry Points
Given that clinicians and practice workflows varied greatly, there doesn’t seem to be a conclusive One-size-fits-all data entry point.
Decision Making
Surface emerging therapies (including targeted inhibitors). Display treatments for rare mutations
that NGS results may have uncovered. Thinking of a change in treatment (should a patient not be tolerating current therapy). Consider therapy choices for if a patient progresses (1st line, 2nd line, 3rd line, etc).
The below persona is a fictional character based on insights from interviews and usability testing with 9 Oncologists. We felt confident there was enough data to create a new "flavor" of the General Oncologist persona. These types of Physicians are usually Primary Investigators for clinical trials and their focus is finding/watching patients for clinical trial eligibility through the molecular testing data or disease progression.
The Lead Designer and I were very humbled to be a part of this exploration bringing Precision Medicine to the forefront of Ontada. Unfortunately, other business priorities and limited engineering resources led us to move on to other projects, but a year later it was picked back up by other designers to continue the work while using our research and guidance!
One of the most frustrating realizations in healthcare design is that there are many pain points that can not be solved with technology. There are lots of processes like insurance approvals on patients having access to biomarker testing that is out of our control.
