Clinical effectiveness of an emergency admission predictive risk model in primary care

Problem

New approaches are needed to safely reduce emergency admissions to hospital by targeting interventions effectively in primary care. A predictive risk stratification tool (PRISM) identifies each registered patient’s risk of an emergency admission in the following year, allowing practitioners to identify and manage according to risk. We evaluated the introduction of PRISM in primary care in one area of the UK, assessing its impact on emergency admissions and other service use.

Approach

We conducted a randomised stepped wedge trial with participant-level anonymised linked outcomes, and economic and qualitative components. PRISM was implemented in 11 Welsh primary care practice clusters (total 32 practices) over a year from March 2013. We analysed routine linked data outcomes for 18 months, and consulted staff at each practice before and after implementation. At the same time as the study, but independent of it, an incentive payment (QOF) was introduced to encourage primary care practitioners to identify high risk patients and manage their care.

Findings

We included outcomes for 230,099 registered patients, assigned to ranked risk groups. Overall, the rate of emergency admissions was higher in the intervention phase than in the control phase: adjusted difference in number of emergency admissions per participant per year at risk ΔL = 0.011 (95% CI 0.010, 0.013). Patients in the intervention phase spent more days in hospital per year: adjusted ΔL = 0.029 (95% CI 0.026, 0.031). Both effects were consistent across risk groups.Primary care activity increased in the intervention phase overall ΔL = 0.011 (95% CI 0.007, 0.014); except for the two highest risk groups which showed a decrease in the number of days with recorded activity.PRISM implementation cost £0.12 per patient per year; costs of healthcare use per patient were higher in the intervention phase (Δ = £76, 95% CI £46, £106).Qualitative data showed low use by GPs and practice staff, who cited workload challenges, and concern over a lack of support services to help meet identified need. All staff reported using PRISM to generate lists of patients to target for prioritised care to meet QOF targets.

Consequences

Introduction of a predictive risk model in primary care was associated with increased emergency episodes across the general practice population and at each risk level, in contrast to the intended purpose of the model. Further work is needed to assess the most appropriate use of emergency admission risk tools, including assessment of the impact of targeting of services at different levels of risk, rather than the current policy focus on those at highest risk.