Data Connect Publications
Below are selected publications featuring research supported by our routine data and end-to-end services.
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| Mason S, Stone T, Jacques R, Lewis J, Simpson R, Kuczawski M, Franklin M. Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System. Med Decis Making. 2022 Nov;42(8):999-1009.. |
| CUREd Database. ±¬ÁÏTV.. Accessed 3/5/2024. |
| Lewis J, Weich S, O'Keeffe C, et al. Use of urgent, emergency and acute care by mental health service users: A record-level cohort study. PLoS One. 2023 Feb 13;18(2):e0281667.. |
| Hotham R, O'Keeffe C, Stone T, Mason S and Burton C. Heterogeneity of reasons for attendance in frequent attenders of emergency departments and its relationship to future attendance. Emergency Medicine Journal. 2022;39(1): 10-15. doi: |
| Burton C, Stone T, Oliver P, et al. Frequent attendance at the emergency department shows typical features of complex systems: analysis of multicentre linked data. Emergency Medicine Journal. Published Online First: 26 May 2021. |
| Dr Jen Lewis, Prof Suzanne Mason; ±¬ÁÏTV. Understanding demand for emergency care using regional routine data from emergency department and acute hospital admissions.. |
| Health Data Research (HDR) UK. Remote health monitoring smartphone app reduces emergency hospital admissions from care homes by 25%. News story.. Accessed 3/5/2024. |
| Health Data Research (HDR) UK. The Healthcall app. An animation.. Accessed 3/5/2024. |
| Lewis, J., Simpson, R. M., Stone, T., Ennis, N., Jay, N., Croft, S., . . . Mason, S. M. (2025). Clinical advisors at NHS 111 improve accuracy for paediatric patients and their advice is more reliably followed: a retrospective observational cohort study. Archives of Disease in Childhood. doi: |
| Marshall, C., Kumar, A., Saraiva, S., West, R. M., Mason, S. M., Burton, C. D., . . . Guthrie, E. (2025). Trimodal age distribution of frequent attendance at the emergency department: a descriptive analysis of national, English, secondary care data using a retrospective cohort. BMJ Open, 15(10). doi: |
| England, T., Brailsford, S., Burton, C., Martin, G., Mason, S. M., Maynou, L., . . . Conroy, S. (2025). A new approach to getting simulation models used in healthcare: an example from emergency care. Journal of the Operational Research Society, 76(12), 2579-2590. doi: |
| McDermott, M., Kimenai, D. M., Anand, A., Huang, Z., Houston, A., Williams, S., . . . Mills, N. L. (2024). Adoption of high-sensitivity cardiac troponin for risk stratification of patients with suspected myocardial infarction: a multicentre cohort study. The Lancet Regional Health - Europe, 43. doi: |
| Garner, A., Preston, N., Caiado, C. C. S., Stubington, E., Hanratty, B., Limb, J., . . . Knight, J. (2024). Understanding health service utilisation patterns for care home residents during the COVID-19 pandemic using routinely collected healthcare data. BMC Geriatrics, 24. doi: |
| Montana, L., Magallanes, J., Juarez, M., van Gemeren, L., Wood,S., Mason, S., . . . Villa-Uriol, M. -C. (2025). EventBox: A novel visual encoding for interactive analysis of temporal and multivariate attributes in event sequences. IEEE Transactions on Visualization and Computer Graphics. doi: |
| Montana, L., Magallanes, J., Juarez, M., van Gemeren, L., Wood, S., Mason, S., . . . Villa-Uriol, M. -C. (2025). EventBox: a Novel Visual Encoding for Interactive Analysis of Temporal and Multivariate Attributes in Event Sequences. IEEE Transactions on Visualization and Computer Graphics, 1-11. doi: |