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BRINGING AN EVIDENCE BASE TO DECISION- MAKING COMPLEX ENVIRONMENTS. - PDF document

12/18/2019 North West London Research Symposium Prof Becky Malby BRINGING AN EVIDENCE BASE TO DECISION- MAKING COMPLEX ENVIRONMENTS. 1 CHALLENGING PREVAILING ASSUMPTIONS 2 1 12/18/2019 What you see determines what you do 3 Many


  1. 12/18/2019 North West London Research Symposium Prof Becky Malby BRINGING AN EVIDENCE BASE TO DECISION- MAKING COMPLEX ENVIRONMENTS. 1 CHALLENGING PREVAILING ASSUMPTIONS 2 1

  2. 12/18/2019 What you see determines what you do 3 Many practices hold numerous hypotheses that shape their current work • Demand is rising • We are just meeting it but can’t carry on – we don ’ t turn people away We don ’ t have enough capacity and we need • more staff/ money • Frequent attenders all have more than one chronic disease • Secondary care shifts the burden onto us • Social care is failing 4 2

  3. 12/18/2019 The big picture of demand vs. capacity is optimistic While typically 15% - 20% of appointment requests can’t be meet at reception in a practice • This is far less than the 40% of GP appointments that are seen as inappropriate – unnecessary, • avoidable or potentially moveable within the practice Unmet Inappropriate is far less than demand* appointments Reception contacts GP appointments Academies 15% 40% 85% Yes 60% appropriate combined* No Inapprop.  Appointment booked No appt  Appropriate appt possible * Over 10,000 contacts / appointments ** Not including missed calls 5 5 GP views: There is significant variation on what constitutes a GP appointment Across practices…. Variation between practices from ‘ 80% of our appts are inappropriate’ to ‘less than 50% of our apps are appropriate’ Within practices…. Variation between GPS from 40% of my appts are appropriate to 90% are 6 6 3

  4. 12/18/2019 Super Attenders go to GP Surgeries because they have what sort of problems? 7 Nurse Attender Identifier Age Gender GP appts GP #1 % GP #2 % QOF registers QOFs appts category 1 64 yrs Female 46 5 Super attender 30% 20% 1 CHD, 2 49 yrs Female 39 2 Super attender 62% 15% 1 obesity, 3 51 yrs Female 35 6 Super attender 86% 14% 3 cancer,mental_health,obesity, 4 97 yrs Female 35 1 Super attender 54% 46% 1 atfib, 5 52 yrs Male 34 4 Super attender 38% 26% 1 depression, 6 23 yrs Male 33 4 Super attender 67% 12% 1 learning_disability, 7 47 yrs Female 33 0 Super attender 70% 15% 0 8 64 yrs Female 33 4 Super attender 33% 27% 2 CVD,hypertension, 9 72 yrs Female 32 7 Super attender 56% 16% 1 stroke_tia, 10 37 yrs Female 30 9 Super attender 27% 23% 1 asthma, 11 62 yrs Male 29 5 Super attender 28% 28% 3 asthma,CVD,hypertension, 12 63 yrs Female 28 2 Super attender 46% 29% 1 diabetes, 13 48wks Male 26 3 Super attender 38% 23% 0 14 61 yrs Male 26 1 Super attender 23% 23% 3 asthma,cancer,depression, 15 46 yrs Female 26 0 Super attender 73% 27% 2 depression,mental_health, 16 56 yrs Female 26 2 Super attender 54% 19% 0 17 96 yrs Female 26 2 Super attender 65% 27% 2 CKD,dementia, 18 48 yrs Male 24 2 biweekly 46% 17% 1 depression, 8 8 4

  5. 12/18/2019 Frequent attender review (top 100) Life situation: Over half are known to be in a struggling or chaotic life style 9 9 People who attend frequently are a product of the General Practice’s behaviour not the population’s health 10 5

  6. 12/18/2019 TAKING AN EVIDENCE BASED APPROACH 11 A&E is Overburdened (Breaches ) Because A Demand is rising – more people are coming to A&E B Primary Care is Failing C There are no beds in the hospital so there is backlog D A&E is doing more tests and interventions so the workload is changing E We don ’ t have enough clinicians in A&E 12 6

  7. 12/18/2019 The evidence? A&E breaches are related to • increasing acuity/ complexity, • increased length of stay, • staffing and facilities out of pace with the changes in need in A&E, • increase in case management within A&E, not as the dominant narrative suggests, as a result of increased numbers and poor primary care Wyatt, S. (2019) Waiting Times and Attendance Durations at English Accident and Emergency Departments. The Strategy Unit 13 POWER OF NETWORKS 14 7

  8. 12/18/2019 15 Do Better Do Better Do Well Do Well Do Better Do Better Things Things Mechanistic Mechanistic Participative Participative Relational Relational Control Control Improvement Improvement Coproduction Coproduction adapted from Anderson-Wallace, Blantern and Boydell,2000-2007 16 8

  9. 12/18/2019 17 18 9

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  11. 12/18/2019 2 years of 2.5 recorded 6 months 6 months 6 months 6 months 6 months later admitted to Mental Health Hospital 21 And the GP said… “ If all the teams this individual encountered in the past 2 years actually worked together (not just lip service to integration) e.g. sat in the same place, discussed cases together, she would have found herself in the right place having the right care for her much sooner ” 22 11

  12. 12/18/2019 Managing Complex Needs Mildly & Mildly & • Practice & Moderately Moderately Community Complex level 1 Complex level 1 High Complexity High Complexity • PCN level 2 level 2 High Complexity High Complexity (including (including • ICS specialist care) specialist care) level 3 level 3 23 Networks “Networks have become the predominant organizational form of every domain of human activity” Castells (2011) “Networks are cooperative structures where an interconnected group of individuals, coalesce around a shared purpose and where members contribute as peers on the basis of reciprocity and exchange (in turn based on trust, respect, and mutuality).” Malby & Anderson-Wallace (2016) Useful For • Generating creative and innovative solutions • Rapid learning and development • Amplifying the effectiveness of individual members 24 12

  13. 12/18/2019 Networks Work When: • There is clear shared purpose and identity • They are creative and innovative • They meet member needs • They are supported by adapted leadership • They have strong relationships and ties • They generate helpful outputs 25 CLEAR PURPOSE 26 13

  14. 12/18/2019 PCN Range of Purposes/ Intent (Actual Intent) Network Approach: Working at Scale a) Learning and innovation b) Delivering complex care/ integrated care (for some as part of the ICS) together c) Support communities to help themselves – increasing community assets d) Get upstream into prevention by collaborating with schools/ nurseries/ families e) Act as an integrator – connecting and enabling partners 27 PCN Range of Purposes/ Intent (Actual Intent) Transactional Approach: Economies of Scale a) Alleviate GP pressures (new staff), improve workload and therefore improve workforce job satisfaction b) To get the income (practices won’t survive without the NCDES) and scalable investment c) Deliver extended hours d) Sort out failing / struggling practices 28 14

  15. 12/18/2019 Typology of Networks Delivery/ Delivery/ • Collaboration and Coordination Development Development • Boundary Spanner • Hub and Spoke Networks Networks Learning & Learning & • Shared and New Knowledge Support Support • Distributed Leadership Networks Networks • Passion and Commitment Agency/ Agency/ • Amplification and Advocacy Advocacy Advocacy • Dynamic Leadership • Democratic engagement Networks Networks 29 Delivery Networks Learning Networks Agency Networks 30 15

  16. 12/18/2019 Learning Networks 31 Communities of Practice “Communities of practice are groups of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly.” Wenger-Trayner 2015 Critically therefore CoP member instigates / joins a CoP because: • They care about the domain (of practice) • They have shared competence and practice • They want to learn together how to develop their practice (at a detailed competence level). https://beckymalby.wordpress.com/2017/12/05/facilit ating-communities-of-practice/ 32 16

  17. 12/18/2019 LSBU Primary Care Quality Academy • Advocate for improvement and innovation in Primary Care • Provide local solutions and programmes where there is a gap • Coach and supervise local newly developed teams in these skills and approaches. • Facilitate strategic development in these areas. • Host pan-London communities of practice • Catalyse the development of data scientists, data literacy for improvement and innovation in professionals and citizens. 33 Networks Fail Because Of: • Fails to reach common understanding across members of purpose and direction • Over-management cementing relationships and structures that need to be dynamic and evolving & Institutionalisation • Over expectation of network member’s willingness or ability to collaborate which damages creativity of the parts • Predicating some members over others, • Constraining network member’s independence, • Not recognising when leadership needs to change / rotate • Lack of impact in terms of network member’s purpose. 34 17

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