Data-Driven Design

Designers usually get to know their users in order to design for them. This can be done for example by interviews, observations and context mapping. In all of these design methods, designers are trying to understand the user in their context and by their means. However, with data-driven design, the data that all users create together will become the basis for the designer.

Data-Driven Health Care. Image retrieved from MIT.

The amount of information in the world is growing with a rate of 60% each year (Donhorst, & Anfara (2010). But that does not mean that this information is directly available for the decision makers. An example of these are the translators of the IKNL (2018). This organisation is analysing most of the cancer patients in the Netherlands that are visiting a doctor in a hospital and provide data to hospitals and communicate via their website. Via these websites, patients are able to see for example what the quality of life is after a specific kind of treatment. When this data is made available for the patients, it leads to better share decision making, because they are better informed (Raghupathi, Raghupathi, 2014).

Although probabilities derived from large batches of data are often more reliable than human reasoning, patients will always tend to trust the human more. Therefore, in data-driven design in the Healthcare application, the balance should be found between data and a doctor as a middleman. Moreover, an average doctor has a short amount of time with their patient and they also need to use this time to process data. In order to collect more data, the most important design challenge is to find a way to collect more without interfering with the doctor-patient time. Additionally, Grossglauser & Saner state that the use of data will also contribute to detect health issues quicker and will automate processes where medical staff is needed less. (Grossglauser & Saner, 2014).

References and Interesting Links:

  • Donhost, M. J., & Anfara, V. A. (2010). Data-Driven Decision Making. Middle School Journal, 42(2), 56–63.
  • Grossglauser, M., & Saner, H. (2014). Data-driven healthcare: from patterns to actions. European journal of preventive cardiology, 21(2_suppl), 14-17.
  • IKNL. (2018). IKNL – Integraal Kankercentrum Nederland.
  • Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2(1), 3.

Topic Contributors: Laura Heikamp and Milou Mertens