Predictive risk stratification model: a randomised stepped-wedge trial in primary care (PRISMATIC)
Authors: Snooks Helen , Bailey-Jones Kerry , Burge-Jones Deborah , Dale Jeremy , Davies Jan , Evans Bridie , Farr Angela , Fitzsimmons Deborah , Harrison Jane , Heaven Martin , Howson Helen , Hutchings Hayley , John Gareth , Kingston Mark , Lewis Leo , Phillips Ceri , Porter Alison , Sewell Bernadette , Warm Daniel , Watkins Alan , Whitman Shirley , Williams Victoria , Russell Ian T 
Published: January 2018

Background

With a higher proportion of older people in the UK population, new approaches are needed to reduce emergency hospital admissions, thereby shifting care delivery out of hospital when possible and safe.

Study aim

To evaluate the introduction of predictive risk stratification in primary care.

Objectives

To (1) measure the effects on service usage, particularly emergency admissions to hospital; (2) assess the effects of the Predictive RIsk Stratification Model (PRISM) on quality of life and satisfaction; (3) assess the technical performance of PRISM; (4) estimate the costs of PRISM implementation and its effects; and (5) describe the processes of change associated with PRISM.

Design

Randomised stepped-wedge trial with economic and qualitative components.

Setting

Abertawe Bro Morgannwg University Health Board, south Wales.

Participants

Patients registered with 32 participating general practices.

Intervention

PRISM software, which stratifies patients into four (emergency admission) risk groups; practice-based training; and clinical support.

Main outcome measures

Primary outcome – emergency hospital admissions. Secondary outcomes – emergency department (ED) and outpatient attendances, general practitioner (GP) activity, time in hospital, quality of life, satisfaction and costs.

Data sources

Routine anonymised linked health service use data, self-completed questionnaires and staff focus groups and interviews.

Results

Across 230,099 participants, PRISM implementation led to increased emergency admissions to hospital [ΔL = 0.011, 95% confidence interval (CI) 0.010 to 0.013], ED attendances (ΔL = 0.030, 95% CI 0.028 to 0.032), GP event-days (ΔL = 0.011, 95% CI 0.007 to 0.014), outpatient visits (ΔL = 0.055, 95% CI 0.051 to 0.058) and time spent in hospital (ΔL = 0.029, 95% CI 0.026 to 0.031). Quality-of-life scores related to mental health were similar between phases (Δ = –0.720, 95% CI –1.469 to 0.030); physical health scores improved in the intervention phase (Δ = 1.465, 95% CI 0.774 to 2.157); and satisfaction levels were lower (Δ = –0.074, 95% CI – 0.133 to –0.015). PRISM implementation cost £0.12 per patient per year and costs of health-care use per patient were higher in the intervention phase (Δ = £76, 95% CI £46 to £106). There was no evidence of any significant difference in deaths between phases (9.58 per 1000 patients per year in the control phase and 9.25 per 1000 patients per year in the intervention phase). PRISM showed good general technical performance, comparable with existing risk prediction tools (c-statistic of 0.749). Qualitative data showed low use by GPs and practice staff, although they all reported using PRISM to generate lists of patients to target for prioritised care to meet Quality and Outcomes Framework (QOF) targets.

Limitations

In Wales during the study period, QOF targets were introduced into general practice to encourage targeting care to those at highest risk of emergency admission to hospital. Within this dynamic context, we therefore evaluated the combined effects of PRISM and this contemporaneous policy initiative.

Conclusions

Introduction of PRISM increased emergency episodes, hospitalisation and costs across, and within, risk levels without clear evidence of benefits to patients.

Future research

(1) Evaluation of targeting of different services to different levels of risk; (2) investigation of effects on vulnerable populations and health inequalities; (3) secondary analysis of the Predictive Risk Stratification: A Trial in Chronic Conditions Management data set by health condition type; and (4) acceptability of predictive risk stratification to patients and practitioners.

Trial and study registration

Current Controlled Trials ISRCTN55538212 and PROSPERO CRD42015016874.

Funding

The National Institute for Health Research Health Services Delivery and Research programme.