Abstract
IntroductionThis study implemented MendelScan, a primary care rare disease case-finding tool, into a UK National Health Service population. Rare disease diagnosis is challenging due to disease complexity and low physician awareness. The 2021 UK Rare Diseases Framework highlights as a key priority the need for faster diagnosis to improve clinical outcomes.Methods and resultsA UK primary care locality with 68,705 patients was examined. MendelScan encodes diagnostic/screening criteria for multiple rare diseases, mapping clinical terms to appropriate SNOMED CT codes (UK primary care standardised clinical terminology) to create digital algorithms. These algorithms were applied to a pseudo-anonymised structured data extract of the electronic health records (EHR) in this locality to "flag" at-risk patients who may require further evaluation. All flagged patients then underwent internal clinical review (a doctor reviewing each EHR flagged by the algorithm, removing all cases with a clear diagnosis/diagnoses that explains the clinical features that led to the patient being flagged); for those that passed this review, a report was returned to their GP. 55 of 76 disease criteria flagged at least one patient. 227 (0.33%) of the total 68,705 of EHR were flagged; 18 EHR were already diagnosed with the disease (the highlighted EHR had a diagnostic code for the same RD it was screened for, e.g. Behcet’s disease algorithm identifying an EHR with a SNOMED CT code Behcet's disease). 75/227 (33%) EHR passed our internal review. Thirty-six reports were returned to the GP. Feedback was available for 28/36 of the reports sent. GP categorised nine reports as "Reasonable possible diagnosis" (advance for investigation), six reports as "diagnosis has already been excluded", ten reports as "patient has a clear alternative aetiology", and three reports as "Other" (patient left study locality, unable to re-identify accurately). All the 9 cases considered as "reasonable possible diagnosis" had further evaluation.ConclusionsThis pilot demonstrates that implementing such a tool is feasible at a population level. The case-finding tool identified credible cases which were subsequently referred for further investigation. Future work includes performance-based validation studies of diagnostic algorithms and the scalability of the tool.
Highlights
This study implemented MendelScan, a primary care rare disease case-finding tool, into a UK National Health Service population
Mendelian has developed a digital case-finding tool, “MendelScan”, that can analyse structured clinical vocabulary, such as SNOMED CT codes [17] from primary care electronic health records (EHR) and highlight patterns of data that correspond to an increased likelihood of the patient being affected by certain Rare diseases (RD)
The report included the unique patient identifier, to enable re-identification and matching to the Results Delivering MendelScan into a primary care locality involved a process starting with setting up the agreements through to receiving feedback from the reports sent to GPs
Summary
This study implemented MendelScan, a primary care rare disease case-finding tool, into a UK National Health Service population. Rare disease diagnosis is challenging due to disease complexity and low physician awareness. The 2021 UK Rare Diseases Framework highlights as a key priority the need for faster diagnosis to improve clinical outcomes. Rare diseases (RD) are individually rare but collectively common [1], with an estimated 6000–8000 RD they affect 3.5–5.9% of the population or 263–446 million persons globally [2]. Buendia et al Orphanet Journal of Rare Diseases (2022) 17:54 definition of a rare disease, with most legislative frameworks using point prevalence. In the UK and the European Union (EU), a rare disorder is defined as affecting fewer than 1 in 2000 persons [4, 5]. Of all RD, 149 diseases (4.2%) have a prevalence in the range of 1–5 per 10,000, these account for 77.3–80.7% of the total population of patients affected. RD are a significant burden to healthcare systems and society, in the US the annual economic burden of 379 RD, with a combined incidence of 15.5 million, was estimated to be $966 billion in 2019 [6]
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