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• W4226040349 abstract "Using computer software in general practice to predict patient risk of emergency hospital admission has been widely advocated, despite limited evidence about effects. In a trial evaluating the introduction of a Predictive Risk Stratification Model (PRISM), statistically significant increases in emergency hospital admissions and use of other NHS services were reported without evidence of benefits to patients or the NHS.To explore GPs' and practice managers' experiences of incorporating PRISM into routine practice.Semi-structured interviews were carried out with GPs and practice managers in 18 practices in rural, urban, and suburban areas of south Wales.Interviews (30-90 min) were conducted at 3-6 months after gaining PRISM access, and ∼18 months later. Data were analysed thematically using Normalisation Process Theory.Responders (n = 22) reported that the decision to use PRISM was based mainly on fulfilling Quality and Outcomes Framework incentives. Most applied it to <0.5% practice patients over a few weeks. Using PRISM entailed undertaking technical tasks, sharing information in practice meetings, and making small-scale changes to patient care. Use was inhibited by the model not being integrated with practice systems. Most participants doubted any large-scale impact, but did cite examples of the impact on individual patient care and reported increased awareness of patients at high risk of emergency admission to hospital.Qualitative results suggest mixed views of predictive risk stratification in general practice and raised awareness of highest-risk patients potentially affecting rates of unplanned hospital attendance and admissions. To inform future policy, decision makers need more information about implementation and effects of emergency admission risk stratification tools in primary and community settings." @default.
• W4226040349 created "2022-05-05" @default.
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• W4226040349 date "2021-08-26" @default.
• W4226040349 modified "2023-10-02" @default.
• W4226040349 title "Implementing emergency admission risk prediction in general practice: a qualitative study" @default.
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• W4226040349 doi "https://doi.org/10.3399/bjgp.2021.0146" @default.
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