Abstract
BackgroundRising demand for health care has prompted interest in new technologies to support a shift of care from hospital to community and primary care, which may require clinicians to undertake new working practices. A predictive risk stratification tool (Prism) was developed for use in primary care to estimate patients’ risk of an emergency hospital admission. As part of an evaluation of Prism, we aimed to understand what might be needed to bring Prism into effective use by exploring clinicians and practice managers’ attitudes and expectations about using it. We were informed by Normalisation Process Theory (NPT) which examines the work needed to bring an innovation into use.MethodsWe conducted 4 focus groups and 10 interviews with a total of 43 primary care doctors and colleagues from 32 general practices. All were recorded and transcribed. Analysis focussed in particular on the construct of ‘coherence’ within NPT, which examines how people understand an innovation and its purpose.ResultsRespondents were in agreement that Prism was a technological formalisation of existing practice, and that it would function as a support to clinical judgment, rather than replacing it. There was broad consensus about the role it might have in delivering new models of care based on active management, but there were doubts about the scope for making a difference to some patients and about whether Prism could identify at-risk patients not already known to the clinical team. Respondents did not expect using the tool to be onerous, but were concerned about the work which might follow in delivering care. Any potential value would not be of the tool in isolation, but would depend on the availability of support services.ConclusionsPolicy imperatives and the pressure of rising demand meant respondents were open to trying out Prism, despite underlying uncertainty about what difference it could make.Trial registrationControlled Clinical Trials no. ISRCTN55538212.
Highlights
Rising demand for health care has prompted interest in new technologies to support a shift of care from hospital to community and primary care, which may require clinicians to undertake new working practices
Rising demand for health care, from people living with long term conditions, is prompting service providers and policy makers to turn to new technologies in order to improve efficiency and effectiveness
In combination with a software platform, the models provide clinical risk prediction tools [3], whose two functions in supporting health care are case finding for improved clinical management, and resource allocation through budgeting or service planning [4]
Summary
Rising demand for health care has prompted interest in new technologies to support a shift of care from hospital to community and primary care, which may require clinicians to undertake new working practices. A predictive risk stratification tool (Prism) was developed for use in primary care to estimate patients’ risk of an emergency hospital admission. Clinical risk prediction models use demographic information, diagnoses, and service use data to stratify a population’s risk of having or developing a specified disease, or experiencing an outcome such as emergency admission to hospital [1, 2]. In combination with a software platform, the models provide clinical risk prediction tools [3], whose two functions in supporting health care are case finding for improved clinical management, and resource allocation through budgeting or service planning [4]. The funding commitment is considerable: £160 million per year in England alone [6]
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