Livli is a long-term to-do app connecting this hospital with its senior patients. The overall goal is making bad habits better and good habits great.

In 2012 I applied for and was given the opportunity to join the Swedish Foundation of Industrial Design (SVID) as an Interaction Designer.

I was paired up with Madeleine Canderudh and together we moved down to southern Sweden where we were asked to help a hospital explore what digital could mean for them.

«The task: Explore what digital technologies can do for a hospital working with senior citizens.»

This is Livli

The concept is an app that unifies their patients behaviour of setting goals and reviewing them, and the hospitals desire to reach out with more of their knowledge.

  • Livli hand

Behind the scenes

Given how loosely defined this task was, our main challenge was understanding the hospital and their agenda.

Livli qulturum

A good continous conversation with the hospital

During the course of the project we had continous conversations with the Executive of Learning and Innovation. He was great at helping us understand the overall goals of the hospital and the work they are doing with seniors. He also connected us with both staff and seniors.

“In the best of worlds we get rid of all of our patients. We do not want people to be in need of our help.”

Learning about the staff

When talking to the staff we wanted to learn about what their work life looks like. That includes, for example, what they do, how they work and—in my opinion the most interesting part—what concerns they have.

Learning about the seniors

The same goes for our time spent with the seniors themselves. So again we talked a lot with them to understand what their life looks like, what their ambitions and goals are and what they feel the hospital gives them.

Learnings and the opportunity we saw

We learned that the seniors set goals for themselves each month and that the hospital wants more ways to reach out with their knowledge.

Livli review 2


Towards the end of the project we had learned that the hospital staff wants more ways to reach out with their knowledge, as soon as possible. That is key to preventive healthcare. We had also learned that the seniors the hospital work with are a part of a monthly meet up where they discuss health and risks at home. At these meet up’s they define goals that they then review the following month.


To support their current behaviour of setting goals, a kind of to-do app could be valuable. To cater the hospitals desire to reach out, we figured they could inject their knowledge into the review and define steps of this iterative life planning the seniors are doing each month.

From the left: Home screen with the to-do list. Feedback screen where the hospital can inject knowledge and feedback. Definition screen where the user adds new to-do's based off of the just completed one.
  • Livli screens 3

A video of the concept

I put together this video for them to use when pitching the concept for funding. This was sent to the Swedish Association of Local Authorities and Regions (SKL) that later went on to fund the development of this concept.


The concept is idealistic in the sense that it rapidly turns into a scenario that can be hard to maintain as the number of users grows. Since users manually add goals, they can come in any shape, and these are ideally manually reviewed by the hospital in order for them to inject their feedback and knowledge. So I suspect that this could rapidly scale into something unmanageable. Even in the best of cases the nurses could feedback and review goals for their own select few patients—but not for vast numbers.

Imagining a next step

The next challenge to tackle here is balancing the level of automation versus the level of human interaction. Automating too compromises the hospitals ambition to reach out, but keeping it too manual requires additional staffing to manually “parse” all goals defined.

I would like to explore keeping the manual input, but parsing it in an attempt to map it to a predefined goal that the hospital can manage automatically. As new inputs get added, their database of predefined goals grow. And as the system learns more, the need for manual parsing by the staff reduces.