Slipped capital femoral epiphysis (SCFE) is one of the most common hip diseases of adolescence that can cause marked disability, yet there is little robust evidence to guide treatment. Fundamental aspects of the disease, such as frequency, are unknown and consequently the desire of clinicians to undertake robust intervention studies is somewhat prohibited by a lack of fundamental knowledge. The study is an anonymized nationwide comprehensive cohort study with nested consented within the mechanism of the British Orthopaedic Surgery Surveillance (BOSS) Study. All relevant hospitals treating SCFE in England, Scotland, and Wales will contribute anonymized case details. Potential missing cases will be cross-checked against two independent external sources of data (the national administrative data and independent trainee data). Patients will be invited to enrich the data collected by supplementing anonymized case data with patient-reported outcome measures. In line with recommendations of the IDEAL Collaboration, the study will primarily seek to determine incidence, describe case mix and variations in surgical interventions, and explore the relationships between baseline factors (patients and types of interventions) and two-year outcomes.Aims
Methods
There is widespread variation in the management of rare orthopaedic disease, in a large part owing to uncertainty. No individual surgeon or hospital is typically equipped to amass sufficient numbers of cases to draw robust conclusions from the information available to them. The programme of research will establish the British Orthopaedic Surgery Surveillance (BOSS) Study; a nationwide reporting structure for rare disease in orthopaedic surgery. The BOSS Study is a series of nationwide observational cohort studies of pre-specified orthopaedic disease. All relevant hospitals treating the disease are invited to contribute anonymised case details. Data will be collected digitally through REDCap, with an additional bespoke software solution used to regularly confirm case ascertainment, prompt follow-up reminders and identify potential missing cases from external sources of information (i.e. national administrative data). With their consent, patients will be invited to enrich the data collected by supplementing anonymised case data with patient reported outcomes. The study will primarily seek to calculate the incidence of the rare diseases under investigation, with 95% confidence intervals. Descriptive statistics will be used to describe the case mix, treatment variations and outcomes. Inferential statistical analysis may be used to analyze associations between presentation factors and outcomes. Types of analyses will be contingent on the disease under investigation.Introduction
Methods
