Publications

As the prevalence of multimorbidity grows, provision of effective healthcare is more challenging. Both multimorbidity and complexity in healthcare delivery may be associated with worse outcomes. We studied consecutive, unique emergency non-surgical hospitalisations for patients over 50 years old to three hospitals in Scotland, UK between 2016 and 2024 using linked primary care and hospital records to define multimorbidity (2 + long-term conditions), and timestamped hospital electronic health record (EHR) contacts with nursing and rehabilitation providers to describe intensity of ...

International practice guidelines consider high-sensitivity cardiac troponin (hs-cTn) T and I equivalent irrespective of the clinical indication. This assumption has recently been challenged by clinical and experimental studies suggesting possible differences between cTnT and cTnI, including a diurnal rhythm for cTnT but not cTnI, and a stronger association of hs-cTnT with renal function.

Objective: Medical laboratory data together with prescribing and hospitalisation records are three of the most used electronic health records (EHRs) for data-driven health research. In Scotland, hospitalisation, prescribing and the death register data are available nationally whereas laboratory data is captured, stored and reported from local health board systems with significant heterogeneity.

Predicting risk of future dementia is essential for primary prevention strategies, particularly in the era of novel immunotherapies. However, few studies have developed population-level prediction models using existing routine healthcare data. In this longitudinal retrospective cohort study, we predicted incident dementia using primary and secondary care health records at 5, 10 and 13 years in 144,113 Scottish older adults who were dementia-free prior to 1st April 2009.

The COVID-19 pandemic caused rapid shifts in the workflow of many health services, but evidence of how this affected multidisciplinary care settings is limited. In this data study, we propose a process mining approach that utilises timestamped data from electronic health records to compare care provider patterns across pandemic waves.

Background: Many hospitalised patients require rehabilitation during recovery from acute illness. We use routine data from Electronic Health Records (EHR) to report the quantity and intensity of rehabilitation required to achieve hospital discharge, comparing patients with and without COVID-19.

Synthetic Data has the potential to improve efficiency of data analysis for researchers. However, there is no standard approach to synthetic data governance, access controls or infrastructure requirements, and researchers may face inconsistencies in how they can access or use synthetic data across trusted research environments.

Objectives: To describe the effect of multimorbidity on adverse patient centred outcomes in people attending emergency department.