How Avi Medical trains their staff in the flow of work with scenario-based, blended, and micro learning

15
10
3
Medical practices
Minutes per week
Learning theories combined

Employees:

108 + medical staff

Industry:

Health

(HR) Tools:

  • Personio (HRIS)
  • Slack (Collaboration)
  • Zavvy (Onboarding, Training)

The Problem: Complex medical training requirements and diverse educational backgrounds

Avi Medical is on a mission to elevate the patient experience and digitizing the health sector. The goal? To provide their patients with the best possible care by combining technology with a human touch.

While the company’s HQ is in Munich, Avi operates 15 medical practices across Germany. And going forward, those will only become more.

Diverse levels of experience

As doctors have diverse backgrounds and different medical specialist training, e.g  previous work experience in hospitals or primary care practices, Avi needs to provide sufficient training in peculiarities of the Germany primary care healthcare system.

Everything the medical staff does has to be meticulously documented. Every clinical picture has to go along with the right set of treatments.

On top of that, they need to be experts in things like

  • How to use Avi’s own internal software
  • Practice operations and daily processes
  • Getting familiar with the company’s vision to democratize best-in-class medical care for a healthier society
  • …and much more

Plus, doctors and nurses need to know all that before working practically. This means that, once they start, every untrained hour is an hour wasted.

Waiting room at Avi medical

So, how to help every doctor and medical assistant become experts regardless of their prior background? 

Highly complex logic and little time

The second challenge Avi faced was that the level of complexity a solution had to live up to was quite high. 

For example, focusing on a detailed documentation and choosing the right combination of services (e.g. blood sampling, initial consultation, sonography, etc.) according to their patients symptoms is quite complex.

But doctors, on the other hand, are busy: Their number 1 priority is (and should be) to take care of patients and provide them with a remarkable treatment experience. So there’s no time to endlessly study the ins and outs of German regulations in the space.

Faced with these challenges, the team at Avi had two main goals:

  1. Get people up-to-speed quickly with in-depth knowledge that aligns all experience levels
  2. Have people continuously train and practice concrete scenarios in a way that can easily be included in daily work
Avi Medical clinic

Solution: Scenario-based microlearning

A solution had to fulfil 3 main criteria:

  • ✨ Enable an appropriate learning experience for everyone regardless of their background
  • 🤯 Reflect the highly complex logic of German medical billing
  • ⏱ Deliver continuous learning programs that fit into the doctors’ busy schedule

To ideally tailor the learning experience to those needs, the solution was structured into 3 phases which are leveraging different learning principles:

1. Phase 1: In-depth theory

Goal: Bridge knowledge gaps fast and establish a baseline
Delivery: Blended learning - online component
Content focus: Theory

Next to getting across preboarding-related topics, this step gives new medical staff members a first overview into core topics and establishes a basic knowledge foundation.

Learners go through this step in their own time and according to their previous experience. This way, those without prior knowledge can get up to speed - and the others don’t have to sit through lengthy sessions on things they already know.

Phase 2: Immersive live training 

Goal: Consolidate knowledge and answer questions
Delivery: Blended learning - live component
Content focus: Interactive, social

Phase two is all about deepening the knowledge. This is also a great opportunity to ask open questions and discuss edge cases. Since newbies now already know the basics, they are able to join the conversations instead of zoning out.

Phase 3: Continuous learning journeys

Goal: Expand knowledge in the flow of work
Delivery: Microlearning
Content focus: Scenario-based, interactive
Avi Onboarding Journeys

Main requirement for this step was to find a way that reflects highly complex relationships and logic.

And by integrating Typeform’s quiz builder into Zavvy’s workflows, they found it.

In a nutshell, Avi created a microlearning program that is engaging and easy to implement into daily work life. Doctors regularly receive small, practical lessons that combine theory with practical tasks.  

  • Frequency: Every 2 weeks, doctors receive 5 micro lessons that take less than 5 minutes each to complete.
  • Learning Style: The scenario-based lessons take learners through interactive cases in which they have to solve work problems such as selecting the combination of medical codes for a certain treatment.
  • Logic: Based on their answers, learners get immediate feedback. This is even true if they end up with the right result although choosing the wrong approach.
Logic tree in one of Avi's interactive case studies
  • Feedback: Learners can give feedback on every lesson and ask questions when things are unclear directly on Zavvy.
  • Mobile: Doctors can easily complete the courses on their phone in between patients.

The results: An improved medical learning experience and reduced error rates

Within weeks, doctors have integrated the microlearning program into their work routine. And the training program paid off quickly.

“It makes me proud to see what we achieved - especially since the outcome is so visible and the feedback is so positive".

Key results

  • ❤️ Great feedback from learners who are enjoying the experience
  • 📈 High participation rates as doctors have integrated the microlearning cases into their weekly routines
  • 📉 Reduced error rates
  • 📊An overall more efficient way to attain knowledge
  • 🔄 Thanks to the insights section, the team at Avi can also identify unclarities right away and approach the participants directly.

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