Providing the best care for patients who suffer from one of the rare life-limiting conditions that are collectively known as neuromuscular disease (impaired functioning of the muscles), requires efficient planning of specialised health services. To meet the health needs of patients it is important to know how many people in the UK currently have neuromuscular conditions, and whether this is spread evenly across different regions. Surprisingly, the most recent estimates are 10 years old, and did not provide any regional information. Due to advances in treatment, people with conditions such as Duchenne muscular dystrophy, are now living longer. So older estimates may underestimate the total number of current people in the UK with a neuromuscular condition. Additionally, it is important to also estimate how many people we expect to have these conditions in the future.
In the UK, a patientÂ’s health and healthcare is recorded electronically both at their local general practice and for any subsequent hospital care they may have. These large databases offer a vital resource to conduct real-world research studies, especially for rare conditions, which require a large population to detect enough people with the disease. Our proposal is to use these databases to estimate how many patients in the UK are living with a neuromuscular condition, both currently (prevalence) and those newly diagnosed between 2000-18 (incidence). Additionally, we will provide a detailed description of their health and their contacts with the health service, making comparisons with the general population.
The project will utilise large routine national datasets to address the scarcity of up-to-date and accurate information on the epidemiology of neuromuscular disease (NMD) in the UK. It will use both the GOLD and Aurum primary care datasets, to classify patients with these rare conditions using Read codes and provide updated and detailed information on how many people in the UK are living with NMD. Additionally, we will utilise practices in England which have been linked to hospital admissions and mortality data, to further describe the health and healthcare of these patients.
We will estimate the incidence and prevalence of NMD in the UK between 2000-18 by exploiting the longitudinal and historical medical information recorded on the primary care record. Population denominators will be estimated from the registration data of all general practices in the UK contributing data during the study period. A description of regional and social-economic patterns will be provided. We will then describe the health characteristics and healthcare utilisation of patients with NMD, encompassing consultations, referrals and co-morbidities (identified from the primary care record), hospital admissions and mortality (extracted from linked data, England only). Finally, we will create an age-sex-practice matched population sample of patients without NMD in 2015 to compare annual indicators of health and healthcare usage. This will compare recent utilisation in the previous year, and subsequent outcomes (hospitalisations, mortality) up to end of 2018. We will use Poisson regression models to make comparisons between patients with and without NMD across different measures of healthcare utilisation, and Cox regression for mortality.
Measures of healthcare utilisation (Primary care consultations, emergency admissions for ambulatory care sensitive conditions) and All-Cause Mortality
Iain Carey - Chief Investigator - St George's, University of London
Iain Carey - Corresponding Applicant - St George's, University of London
Derek Cook - Collaborator - St George's, University of London
Niranjanan Nirmalananthan - Collaborator - St George's, University of London
Stephen DeWilde - Collaborator - St George's, University of London
Tess Harris - Collaborator - St George's, University of London
2011 Rural-Urban Classification at LSOA level;HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Carstairs Index for 2011 Census (Excluding Northern Ireland)