Medicines Breakthrough Collaborative 1
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This document discusses quality improvement approaches to patient safety in medicines optimization. It provides an overview of quality improvement science and outlines several key principles, including using small tests of change and repeated PDSA cycles to drive continuous learning and improvement over time. The document also discusses using a collaborative approach to improvement that engages both staff and patients in the process.
![• ThroughPut Yield (TPY), is defined as the
number of units coming out of a process
divided by the number of units going into
that process over a specified period of
time.[1] Only good units with no rework are
counted as coming out of an individual
process.
• Also related, "first time yield" (FTY) is simply
the number of good units produced divided
by the number of total units going into the
process. First time yield considers only what
went into a process step and what went
out, while FPY adds the consideration of
rework
FIRST PASS YIELD – no rework possible, opportunity missed
• 100 units enter A and 90 leave as good
parts. The FTY for process A is 90/100 =
.9000
• 90 units go into B and 81 leave as good
parts. The FTY for process B is 81/90 = .8889
• 81 units go into C and 73 leave as good
parts. The FTY for C is 73/81 = .90
• 73 units got into D and 64 leave as good
parts. The FTY for D is 64/73 = .87
• 64 units go into E and 58 leave as good
parts 58/64 =.90
• 53 units go into process F 48 leave as good
parts 48/53 =0.9
BUT
• The total first time yield is equal to
FTYofA * FTYofB * FTYofC * FTYofD or
.9000 * .8889 * .90 * .90 = .65
reference - Wikipedia 2/10/14](https://image.slidesharecdn.com/medscollaborative1slideshare-151105134055-lva1-app6891/85/Medicines-Breakthrough-Collaborative-1-11-320.jpg)
Medicines Breakthrough Collaborative 1
- 1. Medicines Breakthrough Collaborative 1 Wednesday 4 November 2015
- 2. A Quality Improvement Approach to Patient Safety in Medicines Optimisation Anna Burhouse Director of Quality West of England AHSN
- 3. WHAT IS QUALITY IMPROVEMENT SCIENCE?
- 4. At present, the evidence is clear that healthcare is not always safe and can lead to poor patient experience and outcomes. At the same time, the economic downturn means an end to year-on-year financial increases. Healthcare services are being challenged to respond to this not through indiscriminate cuts, but by improving efficiency, driving up quality and reducing levels of harm.’ The Health Foundation 2014
- 5. The Triple Aim Population Health Experience of Care Per Capita Cost Don Berwick 2015
- 6. Aims for Improvement • No Needless Deaths • No Needless Pain or Suffering • No Unwanted Waits • No Helplessness • No Waste ……For Anyone • Safety • Effectiveness • Patient-centeredness • Timeliness • Efficiency • Equity
- 7. “The First Law of Improvement” Every system is perfectly designed to achieve exactly the results it gets.
- 9. Building Reliable Systems • Design needs to be woven into working practices, with repeated cycles of adaptation, small steps. • Find what works, adapt or abandon what does not. • When you know what works on a small scale, look to implement more widely. • Ask the people who are on the receiving end of care whether the new methods result in good care. • Open culture, flat hierarchies, challenge is not a threat but a source of new ideas and improvement
- 10. Complexity and Reliability Aim: “90% compliance with Antibiotic Received Within One Hour” (4 step process) Probability of on-time successful completion at each step Steps 90.00% 99.00% 99.90% 99.99% 99.999% 1 90.00% 99.00% 99.90% 99.99% 99.999% 2 81.00% 98.01% 99.80% 99.98% 99.998% 4 65.61% 96.06% 99.60% 99.96% 99.996% 8 43.05% 92.27% 99.20% 99.92% 99.992% 16 18.53% 85.15% 98.41% 99.84% 99.984% 32 3.43% 72.50% 96.85% 99.68% 99.968% 64 0.12% 52.56% 93.80% 99.36% 99.936% 128 0.00% 27.63% 87.98% 98.73% 99.872% If the reliability of each step is 90% then the overall How does the complexity of Diagnosis Correct antibiotic chosen Correct prescription available Antibiotic given within right time scale
- 11. • ThroughPut Yield (TPY), is defined as the number of units coming out of a process divided by the number of units going into that process over a specified period of time.[1] Only good units with no rework are counted as coming out of an individual process. • Also related, "first time yield" (FTY) is simply the number of good units produced divided by the number of total units going into the process. First time yield considers only what went into a process step and what went out, while FPY adds the consideration of rework FIRST PASS YIELD – no rework possible, opportunity missed • 100 units enter A and 90 leave as good parts. The FTY for process A is 90/100 = .9000 • 90 units go into B and 81 leave as good parts. The FTY for process B is 81/90 = .8889 • 81 units go into C and 73 leave as good parts. The FTY for C is 73/81 = .90 • 73 units got into D and 64 leave as good parts. The FTY for D is 64/73 = .87 • 64 units go into E and 58 leave as good parts 58/64 =.90 • 53 units go into process F 48 leave as good parts 48/53 =0.9 BUT • The total first time yield is equal to FTYofA * FTYofB * FTYofC * FTYofD or .9000 * .8889 * .90 * .90 = .65 reference - Wikipedia 2/10/14
- 13. Old Methodology • Design and them implementation. • Audit, followed by change, followed by audit • Audit time consuming, complex and difficult • Audit of paperwork rather than whether care is better. • Extremely slow process, taking design cycles into years rather than days
- 14. Changing our approach No action taken here Reject defectives Better Quality Worse Old Way (Quality Assurance) Requirement, Specification or Threshold Action taken on all occurrences Better Quality Worse Source: Robert Lloyd, Ph.D New Way (Quality Improvement
- 15. The Three Faces of Performance Measurement Aspect Improvement Accountability Research Aim Improvement of care (efficiency & effectiveness) Comparison, choice, reassurance, motivation for change New knowledge (efficacy) Methods: • Test Observability Test observable No test, evaluate current performance Test blinded or controlled • Bias Accept consistent bias Measure and adjust to reduce bias Design to eliminate bias • Sample Size “Just enough” data, small sequential samples Obtain 100% of available, relevant data “Just in case” data • Flexibility of Hypothesis Flexible hypotheses, changes as learning takes place No hypothesis Fixed hypothesis (null hypothesis) • Testing Strategy Sequential tests No tests One large test • Determining if a change is an improvement Analytic Statistics (statistical process control) Run & Control charts No change focus (maybe compute a percent change or rank order the results) Enumerative Statistics (t-test, F-test, chi square, p-values) • Confidentiality of the data Data used only by those involved with improvement Data available for public consumption and review Research subjects’ identities protected
- 16. Knowledge Base for Continual Improvement Knowledge for Improvement ▪ Systems ▪ Variation ▪ Psychology ▪ Improvement techniques Continual Improvement Subject and Discipline Knowledge + Adapted from Don Berwick 2015
- 17. • Appreciation of a system • Understanding of Variation • Theory of knowledge • Psychology (adapted from Langley et al) The Science of Improvement
- 18. THE MODEL FOR IMPROVEMENT: PLAN, DO, STUDY, ACT
- 19. When you combine the 3 questions with the… PDSA cycle, you get… Source: The Improvement Guide p. 10 …the Model for Improvement. A Model for Learning and Change
- 20. Bayes’ Simple Rule Thanks to Bob Lloyd for this slide “By updating our initial belief about something with objective new information, we get a new and improved belief.” Rev. Thomas Bayes (1701-1761)
- 21. Changes that Result in Improvement Hunches Theories Ideas A P DS A P DSDATA Learning over Time Repeated Uses of the Cycle
- 22. Develop approaches to improve glycemic control Proactive glycemic control an integral part of system A P S D A P S D Cycle 1: Develop system to track Hbalc levels for diabetic population Cycle 2: Establish protocol for HbAlc routine measurements Cycle 3: Collaborative planning or control levels Cycle 4: Set target levels for HbAlc levels Cycle 5: Implement protocol with all staff Learning over Time Improving Management of Population – Diabetic Blood Sugar Levels
- 23. Self Care Support Delivery System Design Decision Support Clinical Information Systems Using Multiple “Ramps” over time: Chronic Disease Care
- 24. A Collaborative Approach • Do you know how good you are? • Do you know where you stand relative to the best? • Do you know where the variation exists? • Do you know the rate of improvement over time?
- 25. The Breakthrough Series National AHSN MO patient safety collaborative
- 26. People support what they help to create: microsystems
- 29. “The most important single change in the NHS… would be for it to become, more than ever before, a system devoted to continual learning and improvement of patient care, top to bottom and end to end…” Don Berwick
- 30. Diabetes Digital Coach Elizabeth Dymond Deputy Director of Enterprise West of England AHSN
- 31. AHSN’s Mission • Building a culture of collaboration and partnerships • Speeding up adoption of innovation into practice • Creating wealth through co-development testing and early evaluation and spread of new products and services Driving Innovation by making the NHS a Lead Customer
- 32. Challenge led approach AHSN Challenges R4H
- 33. National scene “We want to see patients and carers involved in decisions about their care, receiving appropriate structured education to support self-management, having more control and managing their own health, care and treatment.” Act for Diabetes 2014 NHS England Provide staff and patients with access to high-quality tools for structuring and recording care-planning and shared decision-making. Kings Fund 2014 The NHS Five Year Forward View committed to developing a National Diabetes Prevention Programme. A delivery group from NHS England, Public Health England and Diabetes UK is currently leading the design of the programme.
- 34. Challenge Process • Members work together • Define an unmet need Challenge Definition • Challenge is published • Companies respond Challenge Launch • Best solutions picked • Lead Customers • Projects up to £50K Review •Evaluation •Learning shared •Next steps Go - live Soft Start Innovation
- 38. Clinical Commissioning Groups Bath and North East Somerset Bristol Gloucestershire North Somerset South Gloucestershire Swindon Wiltshire
- 39. • “By working with the AHSNH we would be able to access technologies and providers that otherwise we would not be aware of but neither would we have the internal resource to procure.” (South Gloucestershire CCG) • “Together we are leading on redesigning the clinical pathway for our patients with Diabetes and are consequently very interested in this project.” (BANES CCG) • “I was interested to read about the diabetes mobile and web based work in the West of England AHSN newsletter. We would be keen to be involved in testing and evaluation of products if you are looking for this.” (North Somerset CCG)
- 40. Opportunities for company applicants Your innovative product will be used & evaluated in a real world setting. You will submit a quotation rather than a tender as we are looking to evaluate a number of innovative solutions with the costs of each one less than £50,000 You will receive a report on the evaluation which will also be shared with West of England AHSN members who commission and provide healthcare services across our region with a population of 2.4 million people. You have the opportunity to develop your products in line with commissioner and provider requirements. Increased potential for sales in West of England healthcare providers. Increased potential for national sales as the 15 AHSNs across England share case studies. Registration on national portals to receive alerts on further relevant public sector procurement opportunities.
- 41. What if ……healthcare records were shared between the person with diabetes and other people and services that the person wishes to share that record with? Viewing, inputting and editing rights are controlled by the person with diabetes and records are available in real time. What if….. services were set up so that healthcare professionals and patients can email, text and phone each other? What if ……services were truly joined up to be person-centric and personalized to account for many people with diabetes having another long term condition?
- 42. What if ….we can enable every citizen to self-care in their own way to the benefit of their health, both physical & mental?
- 44. Diabetes 139 per cent more likely to be admitted to hospital with angina 94 per cent more likely to be admitted to hospital with myocardial infarction 126 per cent more likely to be admitted to hospital with heart failure 63 per cent more likely to be admitted to hospital with a stroke 400 per cent more likely to be admitted to hospital for a major amputation and 817 per cent more likely to be admitted with a minor amputation 272 per cent more likely to be admitted to hospital for renal replacement therapy (ESKD) http://www.hscic.gov.uk/nda
- 45. mHealth • ….also known as mobile health, covers medical and public health practice supported by mobile devices • Mobile phones • Patient monitoring devices • Apps • Wearables • Health information • Medication reminders
- 46. Self-Management 99% of diabetes care falls to self-management. Shared decision making: clinicians and patients working together to – clarify treatment, management or self- management support goals, – share information about options and preferred outcomes to reach mutual agreement on the best course of action
- 47. Key Dates 2015 • 23rd June – Launch • 22nd July – Deadline for submissions - 27 • 27th July – Prepare shortlist - 19 • 31st July – Review panel - 8 • 15th Sept – Interviews - 5 • 4th Nov – Test Bed submission
- 49. Thank you
- 50. Next steps • Discussions starting on how this programme links with MO work • Test Bed decision end Dec 2015 • Start Diabetes Digital Coach tools projects • Thank you
- 51. Transfer of Care – Supporting Patients Martin Littleton, Implementation Manager Avon Local Pharmaceutical Committee Supporting Community Pharmacy across Avon
- 52. Supporting Community Pharmacy across Avon Why is it needed?
- 53. Supporting Community Pharmacy across Avon Hospital Discharge Project • At point of discharge from hospital patients are signed up to the service • Patient information securely transferred to the chosen pharmacy • Pharmacy accesses data on PharmOutcomes – Includes an attached TTA letter • Pharmacy contacts the patients – Medication review – Review of new medicines where appropriate – Ensure the patient is clear about their condition and how to administer their medicines
- 54. Supporting Community Pharmacy across Avon Proof of concept • The technology of PharmOutcomes would work for this service • Pharmacies would contact patients • Patients would be receptive to the service • Demonstrated outcomes (small scale)
- 55. Supporting Community Pharmacy across Avon Patients are benefiting
- 56. Supporting Community Pharmacy across Avon Outcomes Are Better • Mid July patient discharged and not seen in pharmacy • Patient re-admitted. Discharge in September and pharmacy followed up • Patient not been discharged through service since Patient not intervened with • Patient went in with one medication and came out with nine • Pharmacist spent time explaining and introduced a compliance aid • Patient now happy Multiple medication • GP didn’t want to get involved • Pharmacy contacted hospital and investigated • Diagnosis correct, pharmacist intervened and patient now happy to take medication Pharmacist intervention with hospital
- 57. Supporting Community Pharmacy across Avon What next? • Pharmacy contractor engagement and training • Is the payment via an MUR or NMS sustainable? – Good outcomes achieved without these • Is there the possibility of a commissioned service…what would this look like?