Martin Bardsley: integration and innovation in health

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Martin Bardsley: integration and innovation in health

  1. 1. © Nuffield Trust09 May 2014 Integration and innovation – meeting the challenges of evaluation in the new system Martin Bardsley Nuffield Trust
  2. 2. © Nuffield Trust Predictive risk modelling Resource allocation Descriptive studies Evaluations Integrated care pilots nuffield trust Nuffield Trust Research team – data linkage projects Risk sharing for CCGs nuffield trust Combined predictive model nuffield trust Person based resource allocation nuffield trust Social care at end of life nuffield trust Cancer and social care nuffield trust Predicting social care costs nuffield trust Virtual Wards nuffield trust WSD nuffield trust Marie Curie Nursing Service nuffield trust
  3. 3. © Nuffield Trust Aims Background Exploiting routine information 2 case studies of retrospective evaluations a. Marie Curie Nursing service b. Partnerships for Older People
  4. 4. © Nuffield Trust 10 year trend in emergency admissions (46 million admits) 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 2001/02Q1 2001/02Q3 2002/03Q1 2002/03Q3 2003/04Q1 2003/04Q3 2004/05Q1 2004/05Q3 2005/06Q1 2005/06Q3 2006/07Q1 2006/07Q3 2007/08Q1 2007/08Q3 2008/09Q1 2008/09Q3 2009/10Q1 2009/10Q3 2010/11Q1 2010/11Q3 Numberofemergencyadmissions (millions) No ACS diagnosis ACS primary diagnosis ACS secondary diagnosis +35% (40%) +34%
  5. 5. © Nuffield Trust By ambulatory care sensitive conditions…
  6. 6. © Nuffield Trust Interventions to reduce avoidable admissions Primary Care ED Depts Hospital Transition Practice features Assess/obs wards Structured Discharge Transition care management Medication review GPs in A&E Medication Review Rehabilitation Case management Senior Clinician Review Specialist Clinics Self management and education Telemedicine Coordination end of life (EOL) care Hospital at home Virtual Wards see Purdy et al (2012) Interventions to Reduce Unplanned Hospital Admission: A series of systematic reviews. Bristol University Final Report)
  7. 7. © Nuffield Trust Why the current interest in integrated care? • Rising levels of chronic disease • Ageing population • Increasing levels of hospital admissions and readmissions, especially among the elderly and vulnerable, and children • Economic hard times, and unsustainable health and social care economies • And too often we still do not get it right in terms of care co- ordination, care planning, communication with families • Interest in prevent solutions that reduce the need for hospital admissions
  8. 8. © Nuffield Trust Integration Sara Shaw, Rebecca Rosen and Benedict Rumbold What is integrated care? An overview of integrated care in the NHS. Research report. Nuffield Trust June 2011
  9. 9. © Nuffield Trust What information do we have on whether these are working?…… © Nuffield Trust
  10. 10. © Nuffield Trust Data are everywhere… GP Local Authority Commissioner A&E OP IP Pharmacy Community Health Services Up there Housing Council Tax Council Social Services Social care provider Ambulance ControlNHS Direct Commissioning data ...
  11. 11. © Nuffield Trust Exploiting person level data Linking data a. over time to look at what happens to people – not just events b. across care providers to build broader picture Person level Capture services provided ->costs; quality Descriptions of health -> outcomes
  12. 12. © Nuffield Trust Linkage not new The Oxford Record Linkage Study: A Review of the Method with some Preliminary Results by E D Acheson DM MRCP and J G Evans MB MRCP (Nuffield Department of Clinical Medicine, Oxford University) Proc R Soc Med. 1964 April; 57(4): 269–274.
  13. 13. © Nuffield Trust Tomb raiders?
  14. 14. © Nuffield Trust Information flows
  15. 15. Accident and emergency 350,000 records Outpatients 1,680,000 records Inpatients 360,000 records Social care 240,000 records Community matrons 20,000 records GPs 60 practices 48.5 million records Relative size of data sets collected For one primary are trust (PCT) area (WSD project) March 2011
  16. 16. © Nuffield Trust Health and social care timeline – an individual’s history
  17. 17. © Nuffield Trust Data linkage Social & secondary care interface
  18. 18. © Nuffield Trust Final year costs: by age 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 <55 55-64 65-74 75-84 85-94 >=95 Estimatedaveragecostsper decedent,£ Age band Female All costs Hospital costs Social care costs
  19. 19. One person hospital cost profile over a year 50+ year old male, total annual cost > £35,000 Outpatients DayCase Elective AE Nonelective Time (weeks)
  20. 20. © Nuffield Trust Used of linked person level data Audit and Quality Improvement Patient safety (e.g. monitoring drug side effects or surgical mortality rates) Public Health programmes (immunisation; monitoring cancer rates) Evaluate Services (are they effective and cost effective?) Planning services (e.g. ICU bed availability; pandemic flu plans; manage changing patterns of demand) Manage Performance (e.g. readmission targets; health outcomes indicators) Resource allocation Research
  21. 21. Why rely on using existing data for research? Advantage Disadvantage • Descriptors of events and health status • Constrained by the data that are collected – and quality/consistency of coding • Volume of cases versus costs of data collection • Handling sensitive personal information (+/- consent) • Comprehensive coverage • Coverage of the data – unknown unknowns • Enables retrospective studies/ not time sensitive • Volume of data – complex processing
  22. 22. © Nuffield Trust Example (1) Impact of Marie Curie Nursing Service on place of death & hospital use at the end of life http://www.nuffieldtrust.org.uk/publications/marie-curie- nursing Chitnis, X. , Georghiou, T., Steventon, A. & Bardsley, M. J. (2013). Effect of a home-based end-of-life nursing service on hospital use at the end of life and place of death: a study using administrative data and matched controls. BMJ Supportive & Palliative Care, 1–9. doi:10.1136/bmjspcare-2012-000424 © Nuffield Trust
  23. 23. © Nuffield Trust Methods • 29,538 people who received MCNS care from January 2009 to November 2011 • Sophisticated matching techniques used to select 29,538 individually matched controls from those who died in England from January 2009 – November 2011 • Matched on demographic, clinical and prior hospital use variables • People started receiving MCNS care on average eight days before death
  24. 24. © Nuffield Trust Evaluation: The Marie Curie Nursing Service Intervention: • Nursing care support to people at end of life, in their homes Nuffield commissioned to evaluate impact: • Are recipients more likely to die at home? • Reduction in emergency hospital admissions at end of life? Methods: • Retrospective matched control study – use of already existing administrative data
  25. 25. © 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 this group as study control group 30,000 individuals - died Jan 2009 to Nov 2011 & received Marie Curie nursing service before death
  26. 26. © Nuffield Trust Final datasets available for analysis Nuffield trust ONS deaths Hospital inpatient, outpatient, AEMC data - desensitised N = 30,000 • person details • dates of service • type of service Identifiers: Names, DOB, Addresses, etc • dates & place of death for all people in England, • associated hospital (HES) records Identifiers: Nuffield Trust specific HESID
  27. 27. © 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
  28. 28. © Nuffield Trust Results - Proportion of people dying at home • 77% of MCNS patients died at home but only 35% of controls • Impact of MCNS care on home deaths greater for those with no history of cancer then for those with cancer Figure 2 – Place of death for Marie Curie Nursing Service patients & matched controls
  29. 29. © Nuffield Trust Emergency admissions for cases where nursing started 3-7 days before death
  30. 30. © Nuffield Trust Emergency admissions for cases where nursing started 8-14 days before death
  31. 31. © Nuffield Trust Impact of MCNS care on hospital costs Table 1 – Post index date hospital costs for Marie Curie cases and matched controls Mean (sd) hospital costs per person Activity Type Marie Curie cases Matched controls Difference Emergency admissions £463 (£1,758) £1,293 (£2,531) £830 Elective admissions £106 (£961) £350 (£1,736) £244 Outpatient attendances £33 (£212) £76 (£340) £43 A&E attendances £9 (£34) £31 (£60) £22 All hospital activity £610 (£2,172) £1,750 (£3,377) £1,140 • Significantly greater reduction in costs among those with no recent history of cancer • Also cost reduction much greater for those who started receiving MCNS care earlier (£2,200 for those >2 weeks before death)
  32. 32. © Nuffield Trust Summary • Evaluation of large-scale, existing palliative care service using well-matched controls • Caveats – not all costs considered; unobserved differences about MCNS users • Those who received home-based palliative care: • Much more likely to die at home • Lower use of hospital care (particularly unplanned) • Lower hospital costs • Impact of MCNS care greater for those without cancer – surprising finding, although literature limited
  33. 33. Example (2) Evaluation of community based interventions impact on hospital admissions Retrospective evaluation using matched controls Adam Steventon, Martin Bardsley, John Billings, Theo Georghiou and Geraint Lewis An evaluation of the impact of community-based interventions on hospital use. A case study of eight Partnership for Older People Projects (POPP) . Nuffield Trust March 2011 © Nuffield Trust
  34. 34. © Nuffield Trust The Partnership for Older People Projects (POPPs) “We recommend expanding the Partnerships for Older People Projects (POPPs) approach to prevention across all local authorities and PCTs.” •£60m investment by the Department of Health with aim to: “shift resources and culture away from institutional and hospital- based crisis care” •146 interventions piloted in 29 sites. •National evaluation of whole programme found £1.20 saving in bed days per £1 spent.
  35. 35. © Nuffield Trust From the 146 interventions offered under POPP, we selected eight for an in-depth study of hospital use Support workers for community matrons Intermediate care service with generic workers Integrated health and social care teams Out-of-hours and daytime response service + 4 different short term assessment and signposting services
  36. 36. © Nuffield Trust Our preferred option for this evaluation: link participants to HES through a trusted third party Collate files and add NHS numbers Derive HES ID Collate patient lists Patient identifiers (e.g. NHS number) Trial information (e.g. start and end date) Non-patient identifiable keys (e.g. HES ID, pseudonymised NHS number) Participating sites Information Centre Nuffield Trust
  37. 37. © Nuffield Trust Prevalence of health diagnoses categories in intervention and control groups 0% 10% 20% 30% 40% 50% 60% Control Intervention
  38. 38. © Nuffield Trust Overcoming regression to the mean using a control group 0.0 0.1 0.2 0.3 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Numberofemergencyhospitaladmissions perheadpermonth Month Intervention Start of intervention
  39. 39. © Nuffield Trust Overcoming regression to the mean using a control group 0.0 0.1 0.2 0.3 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Numberofemergencyhospitaladmissions perheadpermonth Month Intervention Start of intervention
  40. 40. © Nuffield Trust Overcoming regression to the mean using a control group 0.0 0.1 0.2 0.3 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Numberofemergencyhospitaladmissions perheadpermonth Month Intervention Start of intervention
  41. 41. © Nuffield Trust Overcoming regression to the mean using a control group 0.0 0.1 0.2 0.3 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 11 12 Numberofemergencyhospitaladmissions perheadpermonth Month Control Intervention Start of intervention
  42. 42. © Nuffield Trust Impact of eight different interventions on hospital use
  43. 43. © Nuffield Trust Conclusions • Able to undertake a retrospective evaluation of changes in hospital use for eight projects, over 5,000 subjects • Study took less than three months once permissions obtained • Findings suggest that none of these projects were delivering the anticipated reduction in hospital use • The approach has limitations e.g. there is always the risk of unmeasured confounders; end points limited by the data available. • The ability to track individual histories using existing data sets has great strengths and wider application
  44. 44. © Nuffield Trust Findings from other studies study © Nuffield Trust
  45. 45. © Nuffield Trust And for three virtual wards…
  46. 46. © Nuffield Trust And 11 integrated care pilots (all pilots combined n=11,296) • Elective admissions & outpatient attendances reduced more quickly for intervention patients than matched controls. • However, emergency admissions appeared to have increased more quickly. Difference in difference analysis (individual patient level) Absolute difference (per head) Relative difference p-value Emergency admissions 0.02 +2 % 0.03 A&E attendance -0.01 -1% 0.26 Elective admissions -0.04 -4% 0.003 Outpatient attendance -0.20 -20% <0.001 * * Difference also detected at practice level
  47. 47. © Nuffield Trust nine observations 1. Recognise that planning and implementing large scale service changes take time 2. Define the service intervention clearly including what it is meant to achieve and how, and manage implementation well 3. Be explicit about how the desired outcomes are supposed to arise and use interim markers of success 4. Consider generalisability and context: they are important 5. If you want to demonstrate statistically significant change, size and time matter 6. Hospital use and costs are not the only impact measures 7. Pay attention to the process of implementation as well as outcome 8. Carefully consider the best models for evaluation 9. Work with what you have: organisation and structural change may not achieve desired outcomes
  48. 48. © Nuffield Trust Summary • Emergency admissions and urgent care seen as critical drives of need for new services • Many different initiatives aimed at integrating across primary/secondary care divide – often with explicit aims to reduce emergency admissions • Huge potential in exploiting linked data sets for retrospective evaluation of new models of care • Evaluation of many integrated care initiatives suggest reducing emergency admission is very difficult – though they may have other benefits • Some evidence that a well established programme for end of life care does reduce need for hospital care
  49. 49. © Nuffield Trust09 May 2014 www.nuffieldtrust.org.uk Sign-up for our newsletter www.nuffieldtrust.org.uk/newsletter Follow us on Twitter: Twitter.com/NuffieldTrust © Nuffield Trust Ian.blunt@nuffieldtrust.org.uk Adam.steventon@nuffieldtrust.org.uk

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