Decision dashboards for clinicians to make sense of patient-collected data

Description

Many health and wellbeing concerns – ranging from diabetes to post-surgical rehabilitation –  are now supported by technology which encourages patients to log data about themselves.

While this data is of potential use to clinicians, few have the time to process and analyse the data in the time available for a patient consult. The data only becomes useful when trends are analysed and identified, and the data is processed to support decision making. For patient-collected data – which can be complex, unpredictable – this is challenging.

Potential avenues of focus include:

• The development of novel dashboard visualisations
• The use of innovative tangible technologies to expose the data
• Focussing on the communication aspect between patients and clinicians
• Helping participants understand the flow of data and the privacy implications

Other interesting suggestions are welcome.

You will benefit from being part of the Digital Health Lab at the OU (http://www.open.ac.uk/blogs/DHL/). The successful candidate will work in a multi-disciplinary team with colleagues from social psychology, software engineering, and the health sector (including local hospitals).

Skills Required:

Candidates will benefit from having some experience and skill in UX/UI development, programming and having an interest in the domain.

Having experience of undertaking qualitative research and analysis would be ideal. It would be useful if candidates had experience of undertaking Participatory Design activities, and had experience of working in multidisciplinary teams.

Background Reading:

Price, Blaine A.; Kelly, Ryan; Mehta, Vikram; McCormick; Ciaran; Ahmed, Hanad; Pearce, Oliver (2018). Feel My Pain: Design and Evaluation of Painpad, a Tangible Device for Supporting Inpatient Self-Logging of Pain. To be presented at CHI 2018. (Access from http://mcs.open.ac.uk/bp5/papers/2018-CHI/)

Katz, Dmitri; Price, Blaine A.; Holland, Simon; Dalton, Nicholas (2018). Data, Data Everywhere, and Still Too Hard to Link: Insights from User Interactions with Diabetes Apps. To be presented at CHI 2018. (Access from http://mcs.open.ac.uk/bp5/papers/2018-CHI/)

Dowding, Dawn, Rebecca Randell, Peter Gardner, Geraldine Fitzpatrick, Patricia Dykes, Jesus Favela, Susan Hamer et al. "Dashboards for improving patient care: review of the literature." International journal of medical informatics 84, no. 2 (2015): 87-100.

Janne van Kollenburg, Sander Bogers, Heleen Rutjes, Eva Deckers, Joep Frens, and Caroline Hummels. 2018. Exploring the Value of Parent Tracked Baby Data in Interactions with Healthcare Professionals: A Data-Enabled Design Exploration. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Paper 297, 1–12.

Contacts – Dr Daniel Gooch, Professor Blaine Price