CASE STUDY
HELIOS

UX Designer
Not tech-savvy patients
Alleviating the load on staff
Data not sent to the USA
Get in touch

How to help thousands of patients with smartphones admitted into our clinics every day?

Product Management
Helios Clinics

The briefing

The Smart.Helios team showed me what they had learned from a professional researcher: that virtually all patients entering a hospital or clinic, brought a smartphone with them (which was not really a surprise).
And that virtually all patients start by asking the staff virtually the same questions.
My task was to explore ways of helping the patients with answers, and the staff by alleviating the load on them.

Challenge

Majority of patients are not tech-savvy
NLP (natural language processing) à la IBM's Watson et al. meant sending data to the USA
Data protection laws in eHealth are extremely strict

Analysis

The "decision tree" covering the most frequently asked questions & their answers wasn't very large, at least in the 1st phase
The UI needed to be really simple

Solution

Focus on smartphone usage
A simple 'clickbot' which any one could use

Role

UX Designer
Researcher
Interviews
Focus Groups
Usability Tests

Tools

Paper & Pen
Sketch
Flinto

Deliverables

Customer Flows
Wireframes
Layouts
Prototypes

The short answer

A web-based "clickbot", because all patients and their relatives have a smartphone
Simple questions providing simple answers
Hi-fidelity mobile prototype validated with patients in a clinic
Creation of decision tree covering most question & answer scenarios

The approach

Screens showing the screens "in action". The provided research was distilled into obvious, very obvious, and even more obvious questions. Those things that every patient aks when admitted into hospital, i.e. today this would have been a chatbot.

Screens showing the most frequently asked questions & answers

Simple question - do you have an account or not?

Help in adding a password for the account

Animated GIF demonstrating the fluid interaction of the website

The nitty gritty

After many sketches, and thousands of post-it notes on walls, I knew where each question and answer within the "descision tree" would lead to, and what exactly would appear on which page.
That knowledge needed to be made available to all.
And that is best communicated by visualizing the user flow.
This is a small section of the digitalized flow that I made.
A user flow like this shows how patients are welcomed by the website application, how they "move" through it, what they see, how they respond, and sets up a blueprint for the application.

A user flow shows how patients "move" through the application

Our proof of concept was a clickable prototype for testing purposes, which I took to a clinic in Berlin, and tested with in-house patients, and some of their relatives.
The next stage would normally be fine concept... exploring those lovely little UI details that help make an application special, and nitty-gritty discussions with developers (front-end, back-end, DevOps etc.).
Unfortunately, the setup at Smart.Helios at the time was incomplete, and there were no engineers... we decided to wait with any further work until the team was on board.
I prepared everything for a hand-over to the product manager, and moved on.

First responses were positive, allowing visitors to easily get to what was interesting for them. However, that initial positive response turned quickly sour, as visitors were presented with all of their potentially interesting activities on a very long page (which was the cause of the original high bounce rate!).

This led to to, what is in essence, a simple solution: Applying the filters for the visitors, and presenting a dynamic list showing the "Top Pick" from each of the filters.
This entire list would be permanently adapted to show the current "Top Pick" from each filter, and the filters would be adapted to seasonal fluctuations, as measured by the analysts.
This is how I came up with an automated curated list.

Cookies