We have recently introduced several application enhancements, including the production of new standard variable sets to simplify data selection; changes to selecting study populations to give greater control around data analysis; and an updated and more intuitive application form. Together, these improvements make our application process more straightforward.
Expanding our standard variable set collection
To make data selection simpler, we are exploring which variables are the most useful within the most-popular datasets we host. (A variable is a category of information, such as medicine name, prescription date, etc.)
Following our recent efforts, we have added several new standard variable sets – to sit alongside Laboratory Testing and Prescriptions – within our Metadata Catalogue, such as all GP datasets, National Records of Scotland Death Code, and the Scottish Index of Multiple Deprivation. The following are particularly valuable for a range of projects:
Lothian Observability: People residing outwith Lothian may be treated by specialist services within NHS Lothian hospitals and facilities. As DataLoch only hosts Lothian data, this variable set allows researchers to easily determine when people lived in the Lothian region. Researchers will therefore be able to ascertain whether gaps in data coverage across secondary care records are due to location changes rather than any other reason.
Demographics: Details about the statistical characteristics of people resident or using health care services in the Lothian region. Data are curated from both primary and secondary care systems and we have addressed major contradictions between source datasets.
Observations: A collection of lifestyle information, risk scores and measurements that can impact health. We process data from several sources to improve the reliability and relevance of data for projects.
When selecting our standard variable sets, researchers now only need to provide a single justification; the selection of any additional variables still has to be individually justified.
Researchers unfamiliar with the data will particularly benefit, as they will be less likely to overlook key variables when making their selections.
Simplifying the selection of study populations for projects
After a pilot earlier in 2025, we are now changing the way data extracts are constructed to give researchers greater control over their analytical efforts and to streamline the data delivery process. The most important benefit identified so far is that researchers can access wider study populations for their analysis allowing for better fine-tuning, reporting and validation of data, which enables research insights to be produced with greater confidence. There are also practical improvements, such as fewer communications around data-extract requirements, and for researchers and DataLoch staff to consider fewer parameters when defining and preparing data extracts.
Minor updates to the DataLoch Application Form
In October 2025, we introduced an updated version of our application form. Following informal feedback from applicants, we have made a number of minor improvements, including a single section seeking project team details and streamlining questions around the arrangements for data access. This form is now in use for all new applications and is available through the application portal or by contacting dataloch@ed.ac.uk.
Next steps
Our efforts to improve the application experience will continue into 2026. We plan to develop and introduce further standard variable sets, focussing initially on Lothian extracts of Scottish Morbidity Records hospital records.
We will also conduct an in-depth review of our application documentation to further improve the experience for applicants. If you are interested in being part of this review process, then get in touch:
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