Testing the Future: How Fake Back Ends Can Drive Real Innovation in Healthcare
Often called a ‘Wizard of Oz’ Experiment, fake back ends help test and refine solutions before investing in full-scale development
We're off to see the wizard,
The Wonderful Wizard of Oz!
We hear he is a whiz of whiz if ever a whiz there was
If ever oh ever a whiz there was
The Wizard of Oz is one because
because, becuase, because, because, becaaaauuuussseee...
Because of the wonderful things he does...- Judy Garland
In healthcare, great ideas abound. The problem isn’t a lack of vision—it’s what happens next. All too often, a team will come up with an exciting concept, pour resources into building it, and launch it only to discover the foundation wasn’t as solid as expected. Assumptions about user needs or workflow compatibility don’t hold up, and the solution fails to gain traction. This isn’t just disappointing; it’s costly. For many organizations , it can be the difference between sustained success and a series of false starts.
But there’s a smarter way to bring ideas to life: testing assumptions with a ‘fake back end.’ This approach, also known as a “Wizard of Oz” experiment, involves simulating technology to validate a concept before fully developing it. In the right context, a fake back end can uncover hidden insights and allow for agile adjustments—saving time, money, and, importantly, the confidence of those affected by the solution.
What is a Fake Back End?
A fake back end is a system where the user experience appears complete and automated, but behind the scenes, it’s powered by human effort rather than sophisticated technology. Imagine the Wizard of Oz, pulling levers and pushing buttons to create an impressive illusion while hiding the actual mechanics. In a similar way, fake back ends create the look and feel of a real product or service, giving users an authentic experience without the need for complex technology at the outset.
The goal of a fake back end is to validate key assumptions. By simulating full functionality, it allows innovators to see how people engage with a solution, measure demand, and uncover potential design flaws—all before investing in a full build.
When and How to Use a Fake Back End
Given the complexity and cost of healthcare technology, a fake back end can be an ideal way to de-risk innovation. However, deciding when and how to implement one effectively requires careful planning. Here’s a step-by-step approach:
1. Identify Key Assumptions
Begin by defining the assumptions that are critical for your concept to succeed. For instance, if you’re developing a patient symptom-checker, does it rely on patients entering specific details? Or, if the solution depends on clinician involvement, are workflows compatible? Defining these assumptions provides a foundation for what you’ll need to validate in your fake back end.
2. Establish Success Metrics
Before you launch, decide what criteria will determine the experiment’s success. Metrics may include patient engagement levels, time saved, or response accuracy. Clear benchmarks allow you to measure progress and validate whether your assumptions hold up as expected.
3. Create a Seamless User Experience
The fake back end experience should feel like the real thing to users. If the experience appears incomplete, feedback might be biased by the interface itself. Aim for a user-centric design so that interactions feel authentic, enabling genuine feedback on the underlying concept rather than superficial issues.
4. Assign a Dedicated Team
The success of a fake back end depends on having a dedicated team behind it. These individuals—whether clinical staff, administrators, or project managers—are responsible for delivering a consistent experience. This team acts as the “wizard behind the curtain,” ensuring each user interaction feels seamless.
5. Iterate and Gather Data Frequently
Collect feedback and data continuously throughout the experiment. Regularly review how the experience aligns with your assumptions and identify any areas where users struggle or lose interest. This approach allows for agile adjustments to refine the experience in real-time.
6. Decide When to Scale or Pivot
After a set period, analyze the experiment’s results. If your assumptions are validated and engagement is high, it may be time to invest in full-scale development. If the fake back end reveals obstacles, consider pivoting or rethinking the concept, saving resources for ideas that are more likely to succeed.
Fake Back End Examples in Healthcare
In healthcare, fake back ends can be helpful for validating ideas and testing workflows. Here are a few examples where they could be applied:
AI Symptom Checkers: Health systems could test AI-driven symptom checkers by first setting up fake back ends where clinical staff review symptoms and send responses that appear automated. This approach would enable teams to measure patient inquiries, typical response times, and whether patients trusted the advice they received, all before fully building an AI system.
Appointment Scheduling Assistants: To de-risk the use of appointment scheduling chatbots, organizations can use fake back ends where human administrators respond to appointment requests that appear to come from an automated assistant. This method would allows team to study user interactions, potential scheduling bottlenecks, and frustrations patients might experience.
Digital Care Plans: Health systems are increasingly looking to personalize care plans. Fake back ends could be conducted by manually curating care plans that appear to come from an automated system.
By doing this for a small number of patients and then gaining direct feedback, teams could rapidly design the right solutions before they are deployed at scale.
Summary
In healthcare, innovation requires more than just a good idea—it demands the assurance that the idea can truly benefit real patients and workflows. Using fake back ends, healthcare organizations can test ideas with minimal risk, allowing for adjustments before diving into full-scale technology.
Much like Dorothy’s journey to the Emerald City, where the Wizard’s magic turned out to be skillfully hidden behind a curtain, fake back ends let teams create the illusion of an advanced system, uncovering critical insights along the way.
With thoughtful planning and a willingness to experiment, fake back ends act as a bridge from concept to reality, ensuring that what’s ultimately delivered aligns with the real needs of patients and providers.
Sometimes, the journey behind the curtain reveals the most valuable lessons of all.
Frequently Asked Questions
1. How do you determine when a fake back end is not enough and it’s time to invest in a fully automated solution?
The transition from a fake back end to a full-scale solution depends on several factors. If the fake back end consistently meets or exceeds success metrics—such as engagement levels, workflow compatibility, and user satisfaction—it may be a sign that the concept is viable and ready for full development. Another indicator is the scalability of the solution. If manual efforts begin to strain resources or slow down the experience, it might be time to consider automation. Ultimately, the decision to invest should be based on validated demand, measurable value, and a clear pathway for improved efficiency or cost-effectiveness.
2. What are some potential risks of using a fake back end in healthcare, and how can they be mitigated?
Fake back ends carry the risk of over-reliance on manual processes, which can lead to inconsistencies in the user experience, especially if the demand outpaces the team’s ability to deliver a seamless experience. To mitigate this, healthcare organizations should clearly define the scope and timeline of the fake back end experiment, ensuring the manual effort remains manageable. Additionally, it’s crucial to communicate with staff and stakeholders about the purpose and limitations of the fake back end to set realistic expectations. Finally, patient privacy must be carefully protected, especially when handling sensitive information manually, so ensuring data handling procedures are compliant is essential.
3. How does a healthcare organization measure the success of a fake back end in ways that will predict real-world effectiveness?
Success in a fake back end experiment can be measured by focusing on key performance indicators that align with real-world goals, such as patient engagement, accuracy of responses, and impact on clinical workflows. By tracking how well users respond to and engage with the fake back end, organizations can assess the likely real-world adoption and satisfaction rates. Regular user feedback, combined with data on the efficiency of the process and clinical impact, will offer insights into how well the solution might perform if automated.
This post is not an endorsement or investing advice. It is personal opinions and does not reflect the views of my past, present or future employers, clients, or colleagues.