Infections of the bone (osteomyelitis) and joints (such as septic arthritis) can affect people of all ages. Infections can reach a bone or joint by travelling through the bloodstream or spreading from nearby tissue. Infections can also begin in the bone itself if an injury exposes the bone to the air. Bacteria are typically the cause of these infections. Treatment of bacterial infections of the bone and joints often involves both antibiotic treatment and surgical procedures. However, the dose and type of antibiotic needed depends on the type of bacteria causing the infection. Rapid treatment with the right type and dose of antibiotic is often needed to eliminate the infection and prevent chronic infection or further complications such as death of the bone tissue, which would then need to be surgically removed.
We aim to characterise and estimate the size of the population of people in the UK who have received a diagnosis of bone or joint infection and estimate the cost of these diseases to the National Health Service (NHS). For people who have the information recorded, we will also characterise the number of patients whose infections were caused by different classes of bacteria, called Gram-negative and Gram-positive, and the cost of their care.
We aim to estimate the prevalence and incidence of bone infection (osteomyelitis) and joint infection (such as septic arthritis) in a UK population based on CPRD and to characterise their epidemiology in terms of healthcare resource use. Our special interest is in the type of pathogen responsible for the infection where recorded, with the aim of informing future treatments.
Acceptable patients eligible for linkage to HES data and having an ICD-10 code indicative of osteomyelitis or direct infection of a joint will be selected. NHS resource use (primary care consultations, prescriptions, outpatient appointments and inpatient admissions) and associated costs will be characterised. Prior comorbidities will be determined in Aurum using prodcode and medcode classifications.
Period prevalence will be calculated for 2019, based on patients registered at 31st December 2018. We will also calculate the incidence of osteomyelitis and joint infections in 2019. Frequency of healthcare use, as primary-care contacts, inpatient episodes, outpatient attendances, prescriptions issued in primary care, and frequency and type of surgical procedures (via OPCS codes) will be calculated for 2019. Clinical manifestations will be determined in HES from ICD-10 and OPCS codes. Linked HES admitted patient care data will aid the selection of cases and enable analysis of inpatient resource use; HES outpatient data and will enable analysis of outpatient resource use. HES A&E data will enable analysis of resource use.
Prevalence and incidence of osteomyelitis and joint infections; NHS resource use associated with osteomyelitis and joint infections; NHS resource use associated with Gram-negative and Gram positive osteomyelitis and joint infections.
Cerys Jenkins - Chief Investigator - Pharmatelligence Limited t/a Human Data Sciences
Elgan Mathias - Corresponding Applicant - Pharmatelligence Limited t/a Human Data Sciences
Andrew Cooper - Collaborator - Shionogi BV
Ellen Hubbuck - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Harry Fisher - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Sara Lopes - Collaborator - Shionogi BV
Stefano Verardi - Collaborator - Shionogi BV
Stephen Marcella - Collaborator - Shionogi Inc
Ellen Hubbuck - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient