Rowan Anna, Bates Chris, Hulme William, Evans David, Davy Simon, A Kennedy Nicholas, Galloway James, E Mansfield Kathryn, Bechman Katie, Matthewman Julian, Yates Mark, Brown Jeremy, Schultze Anna, Norton Sam, J Walker Alex, E Morton Caroline, Bhaskaran Krishnan, T Rentsch Christopher, Williamson Elizabeth, Croker Richard, Bacon Seb, Hickman George, Ward Tom, Green Amelia, Fisher Louis, J Curtis Helen, Tazare John, M Eggo Rosalind, Inglesby Peter, Cockburn Jonathan, I McDonald Helen, Mathur Rohini, Ys Wong Angel, Forbes Harriet, Parry John, Hester Frank, Harper Sam, J Douglas Ian, Smeeth Liam, A Tomlinson Laurie, W Lees Charlie, Evans Stephen, Smith Catherine, M Langan Sinéad, Mehkar Amir, MacKenna Brian, Goldacre Ben
The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.
TPP, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
Wellcome Open Res. 2021 Dec 22;6:360. doi: 10.12688/wellcomeopenres.17360.1. eCollection 2021.
At the outset of the COVID-19 pandemic, there was no routine comprehensive hospital medicines data from the UK available to researchers. These records can be important for many analyses including the effect of certain medicines on the risk of severe COVID-19 outcomes. With the approval of NHS England, we set out to obtain data on one specific group of medicines, "high-cost drugs" (HCD) which are typically specialist medicines for the management of long-term conditions, prescribed by hospitals to patients. Additionally, we aimed to make these data available to all approved researchers in OpenSAFELY-TPP. This report is intended to support all studies carried out in OpenSAFELY-TPP, and those elsewhere, working with this dataset or similar data. Working with the North East Commissioning Support Unit and NHS Digital, we arranged for collation of a single national HCD dataset to help inform responses to the COVID-19 pandemic. The dataset was developed from payment submissions from hospitals to commissioners. In the financial year (FY) 2018/19 there were 2.8 million submissions for 1.1 million unique patient IDs recorded in the HCD. The average number of submissions per patient over the year was 2.6. In FY 2019/20 there were 4.0 million submissions for 1.3 million unique patient IDs. The average number of submissions per patient over the year was 3.1. Of the 21 variables in the dataset, three are now available for analysis in OpenSafely-TPP: Financial year and month of drug being dispensed; drug name; and a description of the drug dispensed. We have described the process for sourcing a national HCD dataset, making these data available for COVID-19-related analysis through OpenSAFELY-TPP and provided information on the variables included in the dataset, data coverage and an initial descriptive analysis.
在新冠疫情初期，英国没有可供研究人员使用的常规综合医院药品数据。这些记录对于许多分析都很重要，包括某些药物对严重新冠疫情结果风险的影响。在英格兰国民医疗服务体系（NHS）的批准下，我们着手获取一组特定药物的数据，即“高成本药物”（HCD），这些药物通常是用于治疗长期病症的专科药物，由医院开给患者。此外，我们旨在使这些数据可供OpenSAFELY - TPP中所有获批的研究人员使用。本报告旨在支持在OpenSAFELY - TPP以及其他地方使用该数据集或类似数据进行的所有研究。我们与东北委托支持单位和NHS数字部门合作，安排整理了一个单一的全国性HCD数据集，以帮助为应对新冠疫情提供信息。该数据集是根据医院向委托方提交的付款记录编制而成。在2018/19财政年度，HCD中有280万份提交记录，涉及110万个唯一患者ID。该年度每位患者的平均提交记录数为2.6份。在2019/20财政年度，有400万份提交记录，涉及130万个唯一患者ID。该年度每位患者的平均提交记录数为3.1份。数据集中的21个变量中，现在有三个可在OpenSafely - TPP中进行分析：配药的财政年度和月份；药物名称；以及所配药物的描述。我们描述了获取全国性HCD数据集的过程，通过OpenSAFELY - TPP使这些数据可用于与新冠疫情相关的分析，并提供了有关数据集中包含的变量、数据覆盖范围和初步描述性分析的信息。
