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VP172 Clinical Effectiveness Of A Predictive Risk Model In Primary Care
- Helen Snooks, Alison Porter, Mark Kingston, Alan Watkins, Hayley Hutchings, Shirley Whitman, Jan Davies, Bridie Evans, Kerry Bailey-Jones, Deborah Burge-Jones, Jeremy Dale, Deborah Fitzsimmons, Martin Heaven, Helen Howson, Gareth John, Leo Lewis, Ceri Philips, Bernadette Sewell, Victoria Williams, Ian Russell
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 33 / Issue S1 / 2017
- Published online by Cambridge University Press:
- 12 January 2018, p. 229
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INTRODUCTION:
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 those at higher risk. We evaluated the introduction of PRISM in primary care in one area of the United Kingdom, assessing its impact on emergency admissions and other service use.
METHODS:We conducted a randomized stepped wedge trial with cluster-defined control and intervention phases, and participant-level anonymized linked outcomes. PRISM was implemented in eleven primary care practice clusters (total thirty-two practices) over a year from March 2013. We analyzed routine linked data outcomes for 18 months.
RESULTS: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, delta = .011 (95 percent Confidence Interval, CI .010, .013). Patients in the intervention phase spent more days in hospital per year: adjusted delta = .029 (95 percent CI .026, .031). Both effects were consistent across risk groups.
Primary care activity increased in the intervention phase overall delta = .011 (95 percent CI .007, .014), except for the two highest risk groups which showed a decrease in the number of days with recorded activity.
CONCLUSIONS: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. Future evaluation work could assess the impact of targeting of different services to patients across different levels of risk, rather than the current policy focus on those at highest risk.
VP132 Cost Effectiveness Of A Predictive Risk Model In Primary Care
- Helen Snooks, Alison Porter, Mark Kingston, Bridie Evans, Deborah Burge-Jones, Jan Davies, Hayley Hutchings, Alan Watkins, Shirley Whitman, Bernadette Sewell, Kerry Bailey-Jones, Jeremy Dale, Deborah Fitzsimmons, Jane Harrison, Martin Heaven, Gareth John, Leo Lewis, Ceri Philips, Victoria Williams, Daniel Warm, Ian Russell
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 33 / Issue S1 / 2017
- Published online by Cambridge University Press:
- 12 January 2018, pp. 209-210
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INTRODUCTION:
Emergency admissions to hospital are a major financial burden on health services. In one area of the United Kingdom (UK), we evaluated a predictive risk stratification tool (PRISM) designed to support primary care practitioners to identify and manage patients at high risk of admission. We assessed the costs of implementing PRISM and its impact on health services costs. 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.
METHODS:We conducted a randomized stepped wedge trial in thirty-two practices, with cluster-defined control and intervention phases, and participant-level anonymized linked outcomes. We analysed routine linked data on patient outcomes for 18 months (February 2013 – September 2014). We assigned standard unit costs in pound sterling to the resources utilized by each patient. Cost differences between the two study phases were used in conjunction with differences in the primary outcome (emergency admissions) to undertake a cost-effectiveness analysis.
RESULTS:We included outcomes for 230,099 registered patients. We estimated a PRISM implementation cost of GBP0.12 per patient per year.
Costs of emergency department attendances, outpatient visits, emergency and elective admissions to hospital, and general practice activity were higher per patient per year in the intervention phase than control phase (adjusted δ = GBP76, 95 percent Confidence Interval, CI GBP46, GBP106), an effect that was consistent and generally increased with risk level.
CONCLUSIONS:Despite low reported use of PRISM, it was associated with increased healthcare expenditure. This effect was unexpected and in the opposite direction to that intended. We cannot disentangle the effects of introducing the PRISM tool from those of imposing the QOF targets; however, since across the UK predictive risk stratification tools for emergency admissions have been introduced alongside incentives to focus on patients at risk, we believe that our findings are generalizable.
OP75 Implementing Risk Stratification In Primary Care: A Qualitative Study
- Alison Porter, Helen Snooks, Mark Kingston, Jan Davies, Hayley Hutchings, Shirley Whitman, Alan Watkins, Bridie Evans, Kerry Bailey-Jones, Deborah Burge-Jones, Jeremy Dale, Deborah Fitzsimmons, Jane Harrison, Helen Howson, Martin Heaven, Gareth John, Leo Lewis, Ceri Philips, Bernadette Sewell, Daniel Warm, Victoria Williams, Ian Russell
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 33 / Issue S1 / 2017
- Published online by Cambridge University Press:
- 12 January 2018, pp. 34-35
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INTRODUCTION:
A predictive risk stratification tool (PRISM) to estimate a patient's risk of an emergency hospital admission in the following year was trialled in general practice in an area of the United Kingdom. PRISM's introduction coincided with a new incentive payment (‘QOF’) in the regional contract for family doctors to identify and manage the care of people at high risk of emergency hospital admission.
METHODS:Alongside the trial, we carried out a complementary qualitative study of processes of change associated with PRISM's implementation. We aimed to describe how PRISM was understood, communicated, adopted, and used by practitioners, managers, local commissioners and policy makers. We gathered data through focus groups, interviews and questionnaires at three time points (baseline, mid-trial and end-trial). We analyzed data thematically, informed by Normalisation Process Theory (1).
RESULTS:All groups showed high awareness of PRISM, but raised concerns about whether it could identify patients not yet known, and about whether there were sufficient community-based services to respond to care needs identified. All practices reported using PRISM to fulfil their QOF targets, but after the QOF reporting period ended, only two practices continued to use it. Family doctors said PRISM changed their awareness of patients and focused them on targeting the highest-risk patients, though they were uncertain about the potential for positive impact on this group.
CONCLUSIONS:Though external factors supported its uptake in the short term, with a focus on the highest risk patients, PRISM did not become a sustained part of normal practice for primary care practitioners.