Dr Matt Willis

Matt Willis is a researcher studying automation and computerisation in the NHS system with Prof. Meyer. Matt’s research interests include sociotechnical systems in healthcare settings and patient oriented infrastructures.

Email: matthew.willis@oii.ox.ac.uk
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Dr. Matt Willis earned his PhD in Information Science & Technology from Syracuse University. He has been a researcher in academic, government, and private institutional settings including Sandia National Laboratories, the U.S. Department of Veterans Affairs, and several university affiliated research centres where he was a contributor to multiple grants from the National Science Foundation (NSF), National Institutes of Health (NIH), Defence Advanced Research Projects Agency (DARPA), and Intelligence Advanced Research Projects Activity (IARPA).

Matt joined the Oxford Internet Institute to work on a project sponsored by The Health Foundation entitled “The Future of Healthcare: Computerisation, Automation, and General Practice Services.” The project seeks to understand the impact of automation in the NHS and how automation can support the provision of healthcare within the NHS.

Matt’s intellectual foundation is formed by the research areas of Computer Supported Cooperative Work, Human-Computer Interaction, Sociotechnical Systems, Health Communication, and Social Shaping of Technology. Matt’s research focuses on patient assemblages: the patterns, processes, and practices of patients use of technologies in supporting their health and well-being. As a researcher, Matt values interdisciplinary collaboration and multi-methodological quantitative and qualitative approaches to both data collection and analysis.

Research interests

sociotechnical systems in healthcare, computer supported cooperative work, digital assemblages, human-computer interaction, digital research methods

Positions held at the OII

  • Researcher, June 2016 –

Latest blog posts

Current projects

Past projects

  • The Future of Healthcare: Computerisation and Automation, and General Practice Services

    Participants: Professor Eric T. Meyer, Dr Michael A. Osborne, Dr Angela Coulter, Dr Carl Benedikt Frey, Dr Matt Willis

    The Future of Healthcare: Computerisation, Automation, and General Practice Services project is a collaboration between the Oxford Internet Institute, the Oxford Department of Engineering Science, and the Oxford Martin School, at the University of Oxford.

Chapters

Conference papers

Journal articles

  • Link, G.J.P., Lumbard, K., Conboy, K., Feldman, M., Feller, J., George, J., Germonprez, M., Goggins, S., Jeske, D., Kiely, G., Schuster, K. and Willis, M. (2017) "Contemporary issues of open data in information systems research: Considerations and recommendations", Communications of the Association for Information Systems. 41 (1) 587-610.
  • Mickelson, R.S., Willis, M. and Holden, R.J. (2015) "Medication-related cognitive artifacts used by older adults with heart failure", Health Policy and Technology. 4 (4) 387-398.
  • Weiss, D., White, J., Stohr, R. and Willis, M. (2015) "Influencing healthcare policy: implications of legislators information source preferences for public relations practitioners and public information o fficers", Online Journal of Communication and Media Technologies. 5 (1) 114-135.
  • Possemato, K., Bishop, T.M., Willis, M.A. and Lantinga, L.J. (2013) "Healthcare Utilization and Symptom Variation Among Veterans Using Behavioral Telehealth Center Services", The Journal of Behavioral Health Services & Research. 40 (4) 416-426.
  • White, J., Willis, M. and Stohr, R. (2013) "Legislators reliance on mass media as information sources: Implications for symmetrical communication between public information o cers, public relations practitioners and policymakers", PRism. 9 (1).
  • Yu, B., Willis, M., Sun, P. and Wang, J. (2013) "Crowdsourcing Participatory Evaluation of Medical Pictograms Using Amazon Mechanical Turk", Journal of Medical Internet Research. 15 (6) e108.

Reports

  • Qualitative Data Analysis

    This course is designed to provide students with the knowledge and skills to carry out qualitative data analysis of a variety of kinds of data (e.g. text, photos, videos) collected from both online and offline settings.