QResearch Logo
Menu

Validation of QPrediction scores in QResearch and CPRD

Status

Ongoing

Title

Validation of QPrediction scores in QResearch and CPRD (QResearch ref SPCR 93)

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

The QResearch database and the Clinical Practice Research Datalink (CPRD) databases are two large general practice databases which are used for research. The CPRD was set up in 1988 and is of similar nature and size to QResearch although it is derived from practices using a different clinical computer system and covers a different population.

A series of risk prediction models have been developed using the QResearch database to predict a wide range of important clinical outcomes for patients. The algorithms were originally developed using a 2/3rd sample of practices contributing to the QResearch database and validated on the remaining third. None have been validated on the CPRD.

The objectives of this study are to compare the QResearch and CPRD databases for the following a range of measures over time:

Demographic ​characteristics: age/sex/ethnicity/deprivation
Recording rates of data for clinical values such as smoking status, body mass index, blood pressure and laboratory data
Incidence, prevalence, mortality and survival of a range of chronic diseases
To examine the linked ONS deaths, HES and Cancer Registry data on both databases and evaluate its usefulness e.g. what % of total cases of a serious outcome (such as heart disease, cancer, renal failure, thrombosis, diabetes) can be identified using the GP record alone and what % using only the ONS linked death record, HES data and the Cancer Registry data
To validate the performance of a series of risk prediction scores which have been developed on the QResearch database

Chief Investigator

Professor Julia Hippisley-Cox

Lead Applicant Organisation Name

Sponsor

Oxford

Location of research

Oxford

Date on which research approved

01-Feb-2019

Project reference ID

Q71

Generic ethics approval reference

18/EM/0400

Are all data accessed are in anonymised form?

Yes

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

Risk factors and outcomes for multiple clinical conditions on GP, HES, cancer registry and mortality data

Funding Source

National School for Primary Care Research

Public Benefit Statement

Research Team

Professor Julia Hippisley-Cox, Professor Carol Coupland, Dr Peter Brindle

Department of Health Disclaimer

The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR School for Primary Care Research, NIHR, NHS or the Department of Health.​

Publications

Access Type

Trusted Research Environment (TRE)

Share this