Predictive Risk Stratification Models: PRISMATIC2

• Research type

  Research Study

• Full title

  Predictive Risk Stratification Models: Assessment Of Implementation Consequences (PRISMATIC2)

• IRAS ID

  316826

• Contact name

  Helen A Snooks

• Contact email

  h.a.snooks@swansea.ac.uk

• Sponsor organisation

  Swansea University

• Duration of Study in the UK

  2 years, 11 months, 31 days

• Research summary

  Numbers of emergency admissions have risen over the past decade. They can be associated with adverse outcomes, including functional decline and hospital acquired infections. Software that produces scores for patients’ risk of emergency hospital admission has been introduced in GP practices, supported by National Health Service (NHS) policy. It was hoped that this would reduce admissions as GPs arrange community support to those at risk of hospitalisation. Our PRISMATIC evaluation in South Wales found that emergency admissions to hospital, emergency department (ED) attendances and days spent in hospital increased following implementation of risk prediction software in GP practices. It is unclear if this occurred elsewhere, or why.

  We aim to:
  1. Assess the effects and costs of introducing emergency admission predictive risk stratification tools across England
  2. Investigate how GPs change their practice in relation to managing risk when the software is introduced
  3. Understand patients’ views on communication of risk scores by GPs.

  We will analyse data on emergency admissions, ED attendances and days spent in hospital between 2010 and 2021, and link in the dates when predictive risk stratification was introduced in each area.
  We will investigate GP decision-making in detail at a small number (n=16) of practices, in eight contrasting former CCG areas. We will interview GPs and other primary care staff (n=48) to explore whether they changed their decision making when the risk prediction software became available. We will also conduct two focus groups with patients (n=~16) and patient interviews (n=16) to explore their experiences and discuss how hearing about their own risk may affect their views and health behaviours, including self-care.

  PRISMATIC2 will give policymakers a better understanding of the effects of predictive risk software on costs, processes and outcomes of care across a range of settings

• REC name

  London - Harrow Research Ethics Committee

• REC reference

  23/LO/0036

• Date of REC Opinion

  8 Feb 2023

• REC opinion

  Further Information Favourable Opinion