Predicting first admission and readmission in heart failure patients

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Technical Summary

Our objectives are to identify the main predictors of emergency (re)hospitalisation in patients with heart failure and their relative importance. In this observational study with a retrospective cohort design, we will first identify in the linked CPRD-HES-ONS database each patient's first NHS contact for HF (either practice consultation or hospital admission) and take this as the diagnosis date and start of follow-up. All patients in the database up to March 2014 will be considered, taking into account patient and practice data quality flags, database follow-up, eligibility and coverage periods. Predictors will include demographics, comorbidities, frailty, physiology and medications. After descriptive analysis and an assessment of missing data, statistical methods will include survival analysis in a competing risks framework and multiple logistic regression, with forced entry of predictors where possible. We will explore the need for adjustment for clustering within practices.


Alex Bottle - Chief Investigator - Imperial College London
Azeem Majeed - Collaborator - Imperial College London
Martin Cowie - Collaborator - King's College London (KCL)
Paul Aylin - Collaborator - Imperial College London


HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation