Article Text

Download PDFPDF

Effects and costs of implementing predictive risk stratification in primary care: a randomised stepped wedge trial
  1. Helen Snooks1,
  2. Kerry Bailey-Jones2,
  3. Deborah Burge-Jones2,
  4. Jeremy Dale3,
  5. Jan Davies4,
  6. Bridie Angela Evans1,
  7. Angela Farr5,
  8. Deborah Fitzsimmons5,
  9. Martin Heaven1,
  10. Helen Howson6,
  11. Hayley Hutchings1,
  12. Gareth John7,
  13. Mark Kingston1,
  14. Leo Lewis8,
  15. Ceri Phillips5,
  16. Alison Porter1,
  17. Bernadette Sewell5,
  18. Daniel Warm9,
  19. Alan Watkins1,
  20. Shirley Whitman4,
  21. Victoria Williams1,
  22. Ian Russell1
  1. 1 Medical School, Swansea University, Swansea, UK
  2. 2 Abertawe Bro Morgannwg University Health Board, Neath Port Talbot, UK
  3. 3 Warwick Medical School, University of Warwick, Coventry, UK
  4. 4 Independent service user, Cardiff, UK
  5. 5 Swansea Centre for Health Economics, Swansea University, Swansea, UK
  6. 6 Bevan Commission, Swansea, UK
  7. 7 NHS Wales Informatics Service, Cardiff, UK
  8. 8 International Foundation for Integrated Care, Oxford, UK
  9. 9 Hywel Dda University Health Board, Carmarthen, UK
  1. Correspondence to Professor Helen Snooks, Medical School, Swansea University, Swansea SA28PP, UK; h.a.snooks{at}


Aim We evaluated the introduction of a predictive risk stratification model (PRISM) into primary care. Contemporaneously National Health Service (NHS) Wales introduced Quality and Outcomes Framework payments to general practices to focus care on those at highest risk of emergency admission to hospital. The aim of this study was to evaluate the costs and effects of introducing PRISM into primary care.

Methods Randomised stepped wedge trial with 32 general practices in one Welsh health board. The intervention comprised: PRISM software; practice-based training; clinical support through two ‘general practitioner (GP) champions’ and technical support. The primary outcome was emergency hospital admissions.

Results Across 230 099 participants, PRISM implementation increased use of health services: emergency hospital admission rates by 1 % when untransformed (while change in log-transformed rate ΔL=0.011, 95% CI 0.010 to 0.013); emergency department (ED) attendance rates by untransformed 3 % (while ΔL=0.030, 95% CI 0.028 to 0.032); outpatient visit rates by untransformed 5 % (while ΔL=0.055, 95% CI 0.051 to 0.058); the proportion of days with recorded GP activity by untransformed 1 % (while ΔL=0.011, 95% CI 0.007 to 0.014) and time in hospital by untransformed 3 % (while ΔL=0.029, 95% CI 0.026 to 0.031). Thus NHS costs per participant increased by £76 (95% CI £46 to £106).

Conclusions Introduction of PRISM resulted in a statistically significant increase in emergency hospital admissions and use of other NHS services without evidence of benefits to patients or the NHS.

  • cluster trials
  • emergency department
  • health services research
  • primary care
  • cost-effectiveness

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:

View Full Text

Statistics from


  • Funding This study was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research Programme (Grant Number: 09/1801/1054).

  • Competing interests HS is a member of the National Institute of Health Research (NIHR) Health Technology Assessment(HTA) editorial board and a scientific advisor to the NIHR Health Services and Delivery Research (HS&DR) Programme.

  • Patient consent Obtained for questionnaire respondents.

  • Ethics approval We obtained ethical approval for the study from the Multicentre Research Ethics (MREC) Committee for Wales (reference 10/MRE09/25), and SAIL use approval from their Information Governance Review Panel.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Quantitative data are stored in the Secure Anonymised Information Linkage (SAIL) databank at the Health Information Research Unit (HIRU) of Swansea University. Requests to use datasets within SAIL are welcome but must comply with HIRU’s information governance policy.

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Linked Articles