Laboratory data availability in the Born in Bradford cohort (Data note)

BiB studies have collected a wide range of biological samples from participants, from pregnancy and birth through follow-up studies, resulting in a rich collection of biomarker data. However, a comprehensive inventory of this data does not exist. Therefore, I propose developing a data note that compiles this information to support researchers interested in using our data. This paper would describe the sample collection and processing methods, provide a detailed description of the available samples and their sample sizes, stratified by participant type. We will expand this further by adding clinical test results from samples recorded in linked primary and secondary care records. This would require extracting relevant information from the linked routine health records.

AIM: Summarise the available laboratory tests for the Born in Bradford participants OBJECTIVES: Describe the methods used to extract and link multiple sources of laboratory data into an accessible data asset.
Describe the data asset over time in terms of missing/incomplete data and data coverage by age, gender, ethnicity, and Index of Multiple Deprivation (IMD).
Identify the most common laboratory tests in each clinical setting (A&E, inpatient, outpatient, and primary care).
RATIONAL: The Born in Bradford cohort has generated a substantial volume of biological and health data through sample collections at key life stages (REF ??). While this has resulted in a valuable pool of biomarker information, a centralised and structured inventory of this data is currently lacking. Developing such an asset will support researchers in identifying and accessing relevant laboratory test data for future studies.

In addition to BiB’s collected samples, linked routine health records contain clinical test results from blood and other laboratory investigations. However, these are often stored across fragmented systems and care settings. By extracting and linking these data, we can produce a detailed and inclusive dataset that reflects real-world clinical practice.