Derivation and validation of the QAdmissions algorithm to predict the risk of emergency admissions

What is the aim of the study and why is it important?

QAdmissions is a risk prediction algorithm which calculates an individual’s risk of emergency admission taking account of their individual risk factors such as age, sex, ethnicity, clinical values and diagnoses. Ischaemic stroke is identified according to clinical codes recorded on the primary care record or the linked mortality or hospital record. The research describing the derivation and validation of the algorithm has been published in the BMJ Open.

QAdmissions is used to quantify an individual’s risk of emergency admission in order to prioritise and inform decisions regarding interventions to lower risk. It is used by GP practices to deliver the Designated Enhanced Service specification required by NHS England. It is updated regularly to ensure the algorithms remain calibrated to the current population since the incidence of disease and the prevalence of risk factors changes over time. The updates also enable the algorithm to take account of improvements to data quality (for example increases in the completeness of recording of risk factors such as ethnicity or laboratory values) and also allows adaptations to any changes which might be required to improve the predictive power of the tool or the population to which is applied.

Chief Investigator

Julia Hippisley-Cox



Location of research


Date on which research approved


Project reference ID


Generic ethics approval reference


Are all data accessed are in anonymised form?


Brief summary of the dataset to be released (including any sensitive data)

Risk factors for unplanned hospital admissions, frailty and mortality linked to these outcomes recorded on GP, hospital or mortality records

Implications and Impact

The QAdmissions tool risk stratifies patients to identify those most likely to have an unplanned admission so that care packages can be put in place. The intention of the “Designated Enhanced Service” which NHS England is running, and which QAdmissions supports, is that this will result in fewer unplanned emergency admissions with improvement of care for patients and monetary savings. QAdmissions is recommended by the 2016 NICE guideline on multi-morbidity [NH56], which refers to it as the most commonly used tool across the NHS, and by NHS England’s designated enhanced service.

Funding Source

No external funding

Research Team

Professor Julia Hippisley-Cox, Professor Carol Coupland


  • Predicting risk of emergency admission to hospital using primary care data: derivation and validation of QAdmissions
    Authors: Hippisley-Cox J, Coupland CA.
    Ref: BMJ Open 2013;3:e003482 doi:10.1136/bmjopen-2013-003482.
  • Development and validation of QMortality ris​k prediction algorithm to estimate short term risk of ​death and assess frailty: cohort study
    Authors: Hippisley-Cox J, Coupland C
    Ref: BMJ 2017;358:j4208

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