Challenges in healthcare: solutions from improvement science?
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The document discusses challenges faced by the NHS in England, particularly concerning funding, rising demand for healthcare, and the need for reform in healthcare delivery. It emphasizes the importance of improvement science and evidence-based strategies to develop effective solutions, highlighting the role of collaboration, evaluation, and adaptation of interventions in different contexts. Future research directions focus on utilizing informatics, health economics, and big data to enhance healthcare quality and inform policy decisions.
Challenges in healthcare: solutions from improvement science?
- 1. Challenges in healthcare: solutions from improvement science? Dr Jennifer Dixon Chief Executive The Health Foundation
- 3. Funding (NHS in England) 3
- 4. Funding (NHS in England) 4 Period Years Average annual real growth in NHS spending: Entire NHS history 1949−50 to 2010−11 +4.0% Last Labour government 1996−97 to 2009−10 +6.4% Last Conservative government 1978−79 to 1996−97 +3.3% Previous governments 1949−50 to 1978−79 +3.5% Tightest 4 year period 1950–51 to 1954–55 –2.4% Tightest 4 year period in last 50 years 1975−76 to 1979−80 +1.3%
- 5. Reform (NHS in England) Health and Social Care Act 2012 ‘So large you can see it on Google Earth’....(CEO NHS (England))
- 6. Demand 6 – Rising burden of ill health (demography < long term conditions, dying) – Consumer expectations (eg shared decision-making, access to specific treatments) – Population expectations (eg fairness in access, at least minimum standards)
- 7. Value 7 – More than minimum standards – Internationally comparable outcomes – Preventive care, person centred – Population health, building community assets
- 8. Value 8
- 9. Supply side ‘rigidities’ 9 – Growth of hospital care (technology/expectations, degree of specialism, political power of hospitals/professionals) – Poor integration with primary care, community services, and social care – Lower interest in complex and behavioural over simple and scientific – Professional autonomy/low scrutiny – Workforce contracts – Payment mechanisms – Public health...
- 10. 10 – Challenges seeking solutions – Responses
- 11. 11 P Policy ecosystem Provider/care system P P P P P Communities .. and individuals... Improvement efforts
- 12. Policy ecosystem 12 • Incremental change (but ‘punctuated equilibrium’ (Tuohy)) • Historical focus on demand side solutions > tackle provider interests • Devolution to regions or other subnational units and frustration with national control • Payment reform • Control of input prices (pharma) • Market mechanisms: competition and choice • Regulation • Central directives/command • Information policy • Managed care (LTC): risk based accountable care organisations • NICE-like replicas • Defined benefit package • Co-payments/insurance • Social care
- 13. Communities 13 Local government Community groups Voluntary sector Local business
- 14. Provider care system 14 Collaborations and networks - hospital - primary care Competition (some)
- 15. GP practices Community services Social care Other providers Hospital Collaborations and networks Payers Capitation-based £ Risk adjusted Risk and outcome based 15 Lead provider contracting, alliance contracting
- 16. Provider care system 16 Collaborations and networks are developing Quality improvement capacity limited Quality improvement interventions - Differing (and developing) interventions - Differing improvement tools - Differing implementation intensity - Differing context - Differing evaluation methods - Evidence base...(ROI) Spread and scalability is a challenge
- 17. 17 What does the research tell us?
- 18. 18
- 19. Reduction in effectiveness from applying the same fixed-intervention in different contexts Innovation sample Evaluation sample Immediate wide-scale implementation Parry GJ, Carson-Stevens A, Luff DF, McPherson ME, Goldmann DA. Recommendations for Evaluation of Health Care Improvement Initiatives. Academic Pediatrics. 2013.
- 20. Effectiveness may be maintained if we can learn in what contexts the intervention can be amended to work Learn which contexts it can be amended to work in as we move from Innovation to Prototype to Test and Spread Innovation sample Parry GJ, Carson-Stevens A, Luff DF, McPherson ME, Goldmann DA. Recommendations for Evaluation of Health Care Improvement Initiatives. Academic Pediatrics. 2013
- 21. 21 – Challenges seeking solutions – Responses – Evidence and evaluation
- 22. Hierarchy of evidence 22Source: Davies A and Newman S (2011). Evaluating telecare and telehealth interventions. WSDAN briefing paper. Available from: http://www.wsdactionnetwork.org.uk
- 23. Evaluation of service change 23 Arrived Adapting Early InterventionMethods Case study Formative Summative
- 24. Evaluation of service change 24 Method Case study (Early) Formative study (Adapting) Summative study Example intervention Clinical team piloting a change to service delivery: a one stop clinic in urology outpatients Six organisations developing and implementing a model for self management support in chronic care Comparative study of 20 obstetric departments that implement a programme for team-based patient safety training compared with 20 departments not doing the training
- 25. Complex interventions Evaluability tests Early Adapting Arrived
- 26. Evaluability assessment 26 Also known as ‘exploratory evaluation’ Needs to be used more: provides rapid feedback about how the intervention is working helps to develop realistic objectives for the project/programme examines the feasibility of implementation and adaptability informs the design of a full evaluation to gain useful information
- 27. Our best shot? Improvement support Implementation Formative evaluation Real time Allowing course correction Techniques eg PDSA Logic models Statistical process control With internal evaluation
- 28. 28 – Challenges seeking solutions – Responses – Evidence and evaluation – Future research directions
- 29. Future research directions 29 • Informatics to support improved quality of care • Health economics at system level to clinical team level • Big data to direct the focus for new systems of care • Evolution of evaluation techniques
- 30. Personlevelhospitalcost profileoverayear(NHS) (50+yearoldmale,totalannualcost>£35,000) Outpatients DayCase Elective AE Nonelective Time (weeks)
- 31. Big data and linkage (NHS) Census Member file NHS use Inpatient Cost Outpatient Cost A&E Cost GP Community Social care use Nursing home Cost Domicilary care Cost Area level Person level
- 32. Big data and linkage (NHS and social care)
- 33. Big data and risk stratification
- 34. 34 P Policy ecosystem P P P P P .. and individuals... Improvement science Improvement science research can show which are the most promising solutions Research could also demonstrate if they are cost effective Improvement science is about understanding how solutions work, in what context and how to adapt for new settings Provider
- 35. The role of evidence 35 Opinion / ideology Reasoned argument and experience / public Evidence
- 36. Health policy 36 www.health.org.uk Sign-up for our newsletter www.health.org.uk/account/newsletter-registration/ Follow us on Twitter @HealthFDN (http://twitter.com/HealthFDN)
Editor's Notes
- #30: Research into quality improvement needs to broaden out from its established concerns of patient safety, person centred care, professional motivation and studies of industrial improvement methods to consider: how IT and informatics can improve care – not just through telemedicine but bringing everyday IT into play and understanding the human element to get the best out of systems like electronic patient records and electronic prescribing We need to build the evidence for how improving quality adds value by reducing waste and improving efficiency The role that big data could play to help re-design systems to address current and future needs and how to harness the power of the data to design really person-centred, individualised care And we need to really focus on the development of evaluation so that we are using the appropriate methodologies at the right stage of development of an intervention to better understand how the improvement intervention works, when they are ‘promising’ even if not yet delivering and how to adapt to achieve better results.