Health technology assessment (HTA) bodies like the National Institute for Health and Care Excellence (NICE) make recommendations about the use of healthcare technologies in the health care system based on treatment effectiveness and/or costs over the patients lifetime. In chronic conditions like chronic obstructive pulmonary disease (COPD) this is typically done using health economic models which combine data from various sources including routinely collected healthcare records. In COPD, information is required on disease severity and progression, risk of COPD exacerbations, death, health-related quality of life, and the use of healthcare services.
In this exploratory study we will explore the variation in disease severity (or lung function) in patients with COPD, the risk of COPD exacerbations (i.e. acute worsening of symptoms) by disease severity, and healthcare visits (e.g. to the GP) and medication use by both disease severity and exacerbations.
Health technology assessment (HTA) bodies (e.g. the National Institute for Health and Care Excellence (NICE) in England) make recommendations about the use of healthcare technologies in the health care system based on their clinical and cost-effectiveness. This is often done using health economic decision models, which are populated with data from various sources including observational databases. In chronic obstructive pulmonary disease (COPD) information is required on disease severity and progression, risks of COPD exacerbations, death, health-related quality of life, and healthcare resource utilisation.
We aim to use CPRD data to estimate some of these key parameters, namely the distribution of COPD patients by disease severity, rates of COPD exacerbations by disease severity, and healthcare utilisation and costs by both disease severity and history of exacerbations.
We will estimate these parameters using CPRD (GOLD) data that will be mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. The common data model ensures that otherwise disparate datasets have the same structure and clinical coding languages (e.g. SNOMED for clinical terms and RxNorm for drugs). This increases the interoperability of data such that code developed on any one data set can be applied to others in the same format. This is important for HTA, because it allows parameters (e.g. healthcare costs) to be easily translated to different populations and settings.
Lung function
Rate of COPD exacerbations
Healthcare resource utilisation (including health and social care contacts, outpatient appointments, diagnostic and monitoring tests, A&E attendances, hospital admissions, and medications where possible)
Daniel Prieto-Alhambra - Chief Investigator - University of Oxford
Edward Burn - Corresponding Applicant - University of Oxford
Seamus Kent - Collaborator - National Institute for Health and Clinical Excellence - NICE
Victoria Y Strauss - Collaborator - University of Oxford