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Development of an innovative SQL-based approach to identify potential patients with neurotransmitter disorders
Background
The neurotransmitter disorders (NTDs) signs and symptoms range from early-onset severe neurological manifestations, often accompanied with developmental delay, to later-onset moderate movement disorders [1]. Timely diagnosis remains challenging.
Methods
To develop the SQL algorithm we analysed pseudonymised patient records from the Hospital Episode Statistics (HES) database, which covers all National Health Service inpatient admissions in England, between April 2010 and May 2020. Data extracted included diagnoses, clinical procedures, clinical specialty, and tariff codes. Records with NTD diagnoses (International Statistical Classification of Diseases and Related Health Problems 10th Revision codes E708-E709) were extracted. Clinical codes were ordered by frequency and, using expert clinical input, scored between one and five based on the degree of association with NTDs. To help characterise potentially undiagnosed patients, those records with a total score ≥ 53 were flagged as potential NTDs, and the five most common codes were then used as further selection criteria.
Results
A total of 55 million patients were admitted to English hospitals in the 10-year study period; 1,972 records had a weighted score of ≥ 53. The most common code recorded in these records was pediatric neurology, followed by epilepsy, dystonia, cerebral palsy, and hypotonia. A total of 1,469 patients, which formed the case review population, had a score ≥ 53, attended pediatric neurology, were diagnosed with epilepsy, and had a diagnosis of dystonia, cerebral palsy, or hypotonia.
Conclusions
An innovative SQL coding approach using de-identified hospital records profiled potential patients with NTDs for further testing. This derived from the hospital patient administration system (PAS) has implications for shortening the time to definitive diagnosis and enabling earlier intervention. Our methodology may be applied to other rare diseases or under diagnosed conditions.
Authors
E Fox, V Mehta, R Madhu3, E Wassmer, R Arora, T Cox, D Heaton, J Granerod & M Rance
Journal
International Journal of Rare Diseases & Disorders
Therapeutic Area
Rare disease
Center of Excellence
Real-world Evidence & Data Analytics
Year
2022
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