Biggin Fran, White Laura M, Ashcroft Quinta, Howcroft Timothy, Chandrabalan Vishnu Vardhan, Emsley Hedley, Knight Jo
Lancaster University Faculty of Health and Medicine, Lancaster, UK.
Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK.
BMJ Neurol Open. 2025 Sep 23;7(2):e001202. doi: 10.1136/bmjno-2025-001202. eCollection 2025.
The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is a standardised framework for organising healthcare data. This study uses data in the OMOP CDM format to analyse information on neurology patients.
Routinely collected data harmonised to OMOP at a large referral hospital in England were used. A study cohort was defined as patients who attended at least one neurology outpatient appointment between 01 April 2022 and 31 March 2023 (n=23 862). Data collected at all visits to the hospital made by this cohort between 01 April 2021 and 31 March 2024 were extracted. The cohort was then divided into four subcohorts according to appointment types attended: outpatient appointment(s) only (n=15 2); outpatient appointment(s) and inpatient stay(s) (n=2750); outpatient appointment(s) and emergency department attendance(s) (n=1658); outpatient appointment(s), inpatient stay(s) and emergency department attendance(s) (n=4199).
We found there to be more data available for patients who had at least one inpatient stay or emergency department attendance than for those with only outpatient appointments. Notably, an average of 0 out of 100 patients in the outpatient only subcohort had a record of a condition, compared with 100 out of 100 patients in the subcohort with outpatient appointments, emergency attendances and inpatient stays.
Neurology outpatients have far less data recorded than inpatients or patients attending emergency departments. This disparity arises from the lack of outpatient diagnostic coding and impairs the advancement of research in this area. Using the OMOP CDM structure makes it easy to highlight these differences.
观察性医学结局合作组织(OMOP)通用数据模型(CDM)是用于组织医疗保健数据的标准化框架。本研究使用OMOP CDM格式的数据来分析神经病学患者的信息。
使用在英格兰一家大型转诊医院按照OMOP进行统一的常规收集数据。研究队列定义为在2022年4月1日至2023年3月31日期间至少参加过一次神经病学门诊预约的患者(n = 23862)。提取该队列在2021年4月1日至2024年3月31日期间在医院的所有就诊时收集的数据。然后根据所参加的预约类型将该队列分为四个亚组:仅门诊预约(n = 152);门诊预约和住院(n = 2750);门诊预约和急诊科就诊(n = 1658);门诊预约、住院和急诊科就诊(n = 4199)。
我们发现,与仅进行门诊预约的患者相比,至少有一次住院或急诊科就诊的患者可获得的数据更多。值得注意的是,仅门诊亚组中平均每100名患者中有0名有病情记录,而在有门诊预约、急诊科就诊和住院的亚组中,每100名患者中有100名有病情记录。
神经病学门诊患者记录的数据远少于住院患者或急诊科就诊患者。这种差异源于门诊诊断编码的缺乏,并且不利于该领域研究的进展。使用OMOP CDM结构便于突出这些差异。