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Xavier Chitnis & Michael Cooke: Marie Curie service impact
 

Xavier Chitnis & Michael Cooke: Marie Curie service impact

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    Xavier Chitnis & Michael Cooke: Marie Curie service impact Xavier Chitnis & Michael Cooke: Marie Curie service impact Presentation Transcript

    • © Nuffield Trust The impact of the Marie Curie Nursing Service on place of death and hospital use at the end of life Xavier Chitnis, Michael Cooke Predictive Risk Conference 8th July 2013
    • © Nuffield Trust Background: End of Life Care at home • Spending time with loved ones, pain control, and being cared from in their preferred place are among the top priorities for people at the end of life (Engelberg et al. 2005) • Surveys of the general public and dying people suggest the majority would prefer to die at home (Gomes et al. 2013) • 51% of deaths in hospital in England in 2011, with only 22% of deaths at home • The 2011 VOICES survey asked bereaved relatives whether the person who died had enough choice about where they died: Hospital 29% yes, care home 53%, hospice 70%, home 88%.
    • © Nuffield Trust Evaluation: The Marie Curie Nursing Service (MCNS) • Service model: home-based end-of-life nursing care delivered my registered nurses and healthcare assistants, most often 9 hour shifts of overnight care. 30,000 patients per year across UK. • Longstanding belief: MCNS enables more people to die at home and reduces the amount of time they spend in hospital • Evidence gaps: • How many MCNS patients die at home? Service data has gaps. • How much time do MCNS patients spend in hospital? • What is a fair comparison? We know ≠ ‘general’ dying population • Aim: To evaluate the impact of Marie Curie Nursing Service care on place of death, hospital use and costs at the end of life
    • © Nuffield Trust Matched control studies – broad aim >1M individuals - died Jan 2009 to Nov 2011, did not receive service (everyone else) 30,000 individuals - died Jan 2009 to Nov 2011 & received Marie Curie nursing service before death
    • © Nuffield Trust Matched control studies – broad aim >1M individuals - died Jan 2009 to Nov 2011, did not receive service (everyone else) Aim to find 30,000 individuals who match almost exactly on a broad range of characteristics Use these people as study control group 30,000 individuals - died Jan 2009 to Nov 2011 & received Marie Curie nursing service before death
    • © Nuffield Trust Final datasets available for analysis Nuffield trust Identifiers: HESID on all ONS deaths Hospital inpatient, outpatient, AEMC data - desensitised Use all this info to carry out matched control analysis
    • © Nuffield Trust Measure Mean (sd) Age (years) 75.2 (12.1) Female 47.60% History of cancer 76.90% Number of different cancers (in preceding three years) 1.6 (1.3) Number of chronic conditions 1.5 (1.5) Median number of days from first MCNS visit to death 8 Characteristics of Marie Curie Cohort (n=31,107)
    • © Nuffield Trust Stages in matching process • Construct longitudinal histories for agreed time periods and estimate costs • Match on selected variables eg time to death; age; gender; deprivation health conditions/diagnoses; cancer type and history, prior hospital use (IP, OP and A&E) • Select cases with the best match • Compare hospital activity and costs
    • © Nuffield Trust Period of interest 23rd May 2010 9th March 2010 Date of death Time (days) First Marie Curie Nursing Service visit 9th May 2010 Index date 23rd February 2010 Marie Curie case Matched control 14 days Figure 1 - Process for calculating the index date
    • © Nuffield Trust Control group – how well matched? 0% 5% 10% 15% 20% 25% 30% 35% 40% 19-44 45-54 55-64 65-74 75-84 85+ %ofeachgroup Age band Age 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % White % Black % Asian % Other Ethnicity Ethnicity 0% 2% 4% 6% 8% 10% 12% 14% 1 2 3 4 5 6 7 8 9 10 Decile of deprivation Deprivation 0% 5% 10% 15% 20% 25% 30% 35% 40% 19-44 45-54 55-64 65-74 75-84 85+ %ofeachgroup Age band Age 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % White % Black % Asian % Other Ethnicity Ethnicity 0% 2% 4% 6% 8% 10% 12% 14% 1 2 3 4 5 6 7 8 9 10 Decile of deprivation Deprivation Marie Curie Controls
    • © Nuffield Trust 0% 10% 20% 30% 40% 50% Comorbidities 0% 5% 10% 15% 20% 25% 30% 35% Cancer diagnoses Control group – how well matched? Diagnostic history 0% 10% 20% 30% 40% 50% Comorbidities 0% 5% 10% 15% 20% 25% 30% 35% Cancer diagnoses Marie Curie Controls
    • © Nuffield Trust Place of death for Marie Curie patients and matched controls
    • © Nuffield Trust Mean (sd) activity per person Activity type Marie Curie Matched controls Crude difference IRR P value Emergency admissions 0.15 (0.48) 0.44 (0.73) -0.29 0.34 <.0001 Elective admissions 0.06 (0.78) 0.14 (1.16) -0.08 0.47 <.0001 Outpatient attendances 0.25 (1.65) 0.52 (2.01) -0.27 0.46 <.0001 A&E attendances 0.10 (0.38) 0.34 (0.63) -0.24 0.28 <.0001 Emergency bed-days 1.32 (5.59) 3.60 (8.97) -2.28 0.37 <.0001 Elective bed-days 0.25 (2.38) 0.45 (3.35) -0.2 0.58 <.0001 Hospital activity for Marie Curie patients and matched controls
    • © Nuffield Trust Number of emergency admissions per 1,000 people by day over the last three months of life
    • © Nuffield Trust Number of emergency admissions per 1,000 people by day over the last three months of life (continued)
    • © Nuffield Trust Post-index date average hospital costs for Marie Curie patients and matched controls
    • © Nuffield Trust Proportion of deaths at home for Marie Curie patients and matched controls, by history of cancer
    • © Nuffield Trust Difference in adjusted hospital costs per person between Marie Curie patients and controls, by history of cancer
    • © Nuffield Trust Conclusions • Evaluation of large-scale, existing end-of-life care service using well-matched controls • Those who received home-based nursing care: • Much more likely to die at home • Lower use of hospital care • Lower hospital costs • Impact of MCNS care greater for those without cancer – surprising finding, although literature limited • Results confirm previous work on benefits of home-based support but added significance from numbers studied and the breadth of service provision
    • © Nuffield Trust Conclusions (continued) • Caveats: • Other costs – reduction in hospital costs considered against other costs (including MCNS care), and possible increased used of other services (e.g. GPs, community services & social care) • Unobserved confounders – although groups well-matched, there may have been unobserved factors not recorded in routine data influencing suitability for home-based end-of-life care, e.g. personal preferences, availability of family/carer support etc.
    • © Nuffield Trust Impact for Marie Curie Understanding our patients • Much richer understanding of demographic profile, clinical characteristics and outcomes for MCNS patients • Outcomes for patients with and without cancer of great interest Commissioning • Can demonstrate, for the first time, that service reduces hospital costs and increases the number of home deaths • Breakdowns by service type enable us to build much more robust business cases for the potential impact of new services
    • © Nuffield Trust Impact for Marie Curie ‘The report clearly shows that specialist nurses support patient choice, reduce unwanted hospital admission and also appear to realise significant savings. Nurses see too many instances of patients at the end of their life having to come into hospital, often at night and against their best wishes. This obviously causes distress to individuals and families. The NHS needs to sustain investment in this specialist, out of hours care, so that wherever and whenever a person dies, they can be given excellent pain-relief, dignity and care.’ Dr Peter Carter, RCN Chief Executive and General Secretary
    • © Nuffield Trust www.nuffieldtrust.org.uk Sign-up for our newsletter www.nuffieldtrust.org.uk/newsletter Follow us on Twitter: Twitter.com/NuffieldTrust © Nuffield Trust