It is well known that blood clots are a risk after surgery, particularly hip and knee replacement. A number of studies have used hospital data to estimate the risk of developing a blood clot soon after joint replacement surgery. However, blood clots can develop after a patient has been discharged from hospital and may be treated by their GP. This study will therefore use data from GP practices and death certificates, as well as hospital data, to provide comprehensive estimates of blood clot risk in the six months after knee, hip or shoulder replacement. How this risk has changed since 2007 will be explored, including the impact of changes in NHS guidance.
Blood clot risk will not be the same for every patient, even if they undergo the same surgery. The study will also investigate how blood clot risk varies depending on a patient’s characteristics (such as age, gender, blood pressure etc.). Establishing which patients face a similar risk based on their personal characteristics - as well as their date of surgery and the region they live in – means that high-risk patient groups can be discerned so as to better inform future guidelines for care. Furthermore, variations across regions can be investigated by comparing patient groups with the same characteristics, ensuring that any differences are not a result of patient mix. Insight into geographical variations, or the lack thereof, are crucial to monitoring healthcare equity.
Venous Thromboembolism (VTE), a term including both deep vein thrombosis and pulmonary embolism, can be a serious complication after joint replacement surgery. UK studies to measure the risk of VTE after joint replacement surgery have thus far looked exclusively at hospital data. However, using hospital data alone may substantially underestimate post-surgical VTE risk [1,5]. This retrospective cohort study will therefore use three data sources combined to better estimate the VTE risk after joint replacement surgery: hospital data (Hospital Episode Statistics), primary care data (Clinical Practice Research Datalink) and death certificate information (Office of National Statistics).
This study has two main aims. The first is to provide comprehensive, joint-specific estimates of VTE risk in the six months after primary knee, hip and shoulder replacement surgery, and to explore changes in risk over time. Logistic regression will be used to investigate temporal variations in VTE risk from October 2007 to February 2020, including potential seasonal patterns and step changes in risk due to National Institute of Health and Care Excellence (NICE) guideline updates (e.g. NG89, released in March 2018, covering the assessment and management of VTE risk in hospitals).
The second aim of this study is to better understand patient specific VTE risk in the six months after primary knee, hip or shoulder replacement surgery. VTE risk will be related to patient covariates, region and date of surgery using a random forest model (RFM) in order to allow for complex, interactive and nonlinear relationships. The relationship between risk and patient attributes will be explored, as will regional and temporal variations in risk when holding patient attributes constant. We will also use the similarity matrix resulting from the RFM to cluster patients into groups of relatively homogenous risk, which could provide important information for future NICE guideline updates.
Venous Thromboembolism (deep vein thrombosis; pulmonary embolism) recorded in primary care, secondary care or on death certificate in the 6 months after joint replacement surgery.
John Powell - Chief Investigator - University of Oxford
Nadja Leith - Corresponding Applicant - University of Oxford
Clare Bankhead - Collaborator - University of Oxford
Cynthia Wright Drakesmith - Collaborator - University of Oxford
Jonathan Rees - Collaborator - University of Oxford
Sarah Brown - Collaborator - University of Oxford
Subhashisa Swain - Collaborator - University of Oxford
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation