Anyone remember (probably not with fondness) those quirky little Tamagotchi pets?

We have been exploring the feasibility of using a similar approach in Tamagotchi Cases.

Why do this? They are so annoying

Consider how many professions have an expectation of providing on-call services. Just because you are not at work does not mean you are not available. Now we are not being misty-eyed about the vocation of Marcus Welby MD who always seemed to be available to his patients. If you don’t get some rest and time off, you will burn out.

But not all learners in the professions have the same degree of resilience. Should we not be introducing them to some of the expectations that their professional clients will have? This could be done within a relatively safe environment, where a missed page or call will not have disastrous consequences.

Now in medical education, some would argue that residents get plenty of practice at being on-call. While this is true, there is a difference between the protected on-call  environment of residency (with its wise implementation of the 28-hour rule etc), and the subtle difference in expectations in some professional communities.

These communities might be geographic (e.g. a small rural town) but they can also be functional (e.g. being one of two pediatric surgeons in a small city or group of towns). And if you are one of those two surgeons, what do you do when your colleague needs assistance? This can get quite complex. Some professionals adapt well to these demands, showing strong resilience. But not all… and we don’t do anything to assess, or let them self-assess their tolerance for this level of availability.

Automatic Alerts

We have adapted some of the scenarios within OLab3 so that they act in a manner somewhat similar to the Tamagotchi pet. When they are in need, they call for help. If you ignore them too long, they deteriorate and get into trouble, sending an escalating series of messages. Provide good advice and a prompt response: then they will remain much more well-behaved.

We modified our Pop-up Message function in OLab3 to provide this service. This gave our scenario authors the ability to easily modify the range of “on-call” times within which the students could be alerted. We connected this to the standard cron service available on a Linux server, which simplified the timer and scheduling services.

We attempted to use Twitter for our ‘paging service’. Initially, this seemed quite promising and easy to use. However, we did find it frustrating that the Twitter API was constantly changing, which created a lot of extra development work. A more stable messaging interface is needed for this to be a practical approach.

Continuity in Family Medicine training

For our own particular purposes, we explored this approach in order to try and address some of the challenges of family medicine residency training. One of the four primary principles of CFPC is continuity of care. But what do we mean by that? Are we really expecting our future family docs to be like Marcus Welby? How do you find an appropriate life-work balance?

If others are also interested in exploring this approach to testing and simulating being on-call, please contact us.