Parallel Session 2.3.3 What's Your Problem? Lessons on How to Solve National and Local Challenges
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Parallel Session 2.3.3 What's Your Problem? Lessons on How to Solve National and Local Challenges

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  • Does this low PICU usage reflect a high standard of acute care? Or are children being cared for outside PICU ie in adult or neonatal ICU, or do we do a higher level of HDU Care? Not clearCan we improve or is this as good as it gets?
  • All of these drivers And many more (the original driver diagram rolls to 5 A4 pages) have a part to play. However you cannot ask a whole team to adopt all changes at once. So prioritiseSegment into pilot populations and then spread once reliable.
  • PEWS is a tool but it isn’t thw whole answerChildren are physiologically robust – physiological changes seen lateAlso need “Gut instinct”, experience, training,
  • PEWS of 0 but scores for staff concern and concern re airway
  • Particularly note the parental concerns
  • Multiple parallel projects – hundreds of PDSAs – and still many more to goA team allocated to each major workstream – multidisciplinary or at minimum 1 nurse and 1 doctor
  • Ask anyone on the ward – “who is the sickest patient?” or “which patient are you most concerned about today?” and you should get the same answer.
  • All started coming togethe in Aug/sept 2011Redesigned PEWS form – what was the challenge within the ward – find out the problem and put together a solution design together!
  • I don’t think so
  • Trend down but not meeting run chart rules
  • Is this significant?Is it all down to patient safety work – also significant work going on in palliative care processes (quality and patient centred rather than safety). Is it because it was a quiet winter with fewer sick patients?
  • May 2011 – 11 respondents
  • Need to know what you are aiming for and set appropriate measures .Move with what your data tells you.This is work that never finishes – the more you look the more you find.Your unit needs to be ready for that – need to understand that data isn’t bad and as long as you are taking measures to improve is what matters. All other units will have similar data – they just don’t know that because they aren’t looking.

Parallel Session 2.3.3 What's Your Problem? Lessons on How to Solve National and Local Challenges Parallel Session 2.3.3 What's Your Problem? Lessons on How to Solve National and Local Challenges Presentation Transcript

  • IMPROVING OUTCOMES FORSICK CHILDRENNHS Tayside
  • Sick Children – Our Journey in Tayside• 7000 acutely unwell children referred annually – ~30% admitted• ICU admissions ~ 7 per 1000 admissions – Tayside accounts for 10% of all inpatient paediatric admissions per annum in Scotland, only 5% of PICU admissions• How many patients deteriorate in our care?• How many ICU admissions/deaths are preventable?• Can we improve?
  • Team ‘buy in’ - What is your Project 1?• What really drives the team nuts – what is the biggest waste, safety, inefficiency issue that annoys all staff• Start there• Consult all staff re the process and empower all staff to test changes• Don’t dismiss ideas until you have tried them• Credit the team with team success
  • Tayside “Project 1”• 5/12 old boy• Presented at 10 am to SSAA• Unwell for 3-4 hours with pyrexia and runny nose, still feeding and babbling and smiling• Known to unit – complicated neonatal course• Thought to be well but not discharged due to parental concern – first febrile illness since discharge• Sudden collapse in unit and died with meningococcal sepsis by 6pm
  • Case review• Non recognition of the sick child• Then late recognition and failure to act promptly• Failure to escalate• Once escalated senior multidisciplinary team involved in simultaneous resuscitation• Team invested in this patient as well known to unit• huge division in team ensued with a blame culture• How do we turn this around and restore faith in each other and our team? We do our best to ensure we provide the appropriate and timely care to all our patients.
  • Improvement Aim – ambitious or naïveOutcome Primary Drivers Secondary Drivers (change concepts) Early recognition (PEWS, watcher criteria) Appropriate escalation (PEWS escalation flow chart) Appropriate, Appropriately trained staff (life support courses, senior review, up timely and skilling, regular updates) reliable Testing theory in real time real place (emergency simulation) recognition and management of Guidelines for common emergencies updated and immediately sick children accessible (review dates and website updating)Zero preventable Functioning appropriate equipment (bedspace checks, resus trolley) readmissions, Appropriate medicines ( in date, algorithms, remove unused) crash calls, HDU/ PICU Timely ( teaching re timelines, process change) admissions. SBAR – handover, escalation In-ward deaths Effective Safety Briefing Multidisciplinary rounding by June 2013 communication Daily goals Effective discharge planning Effective readmission planning /CYADM, anticipatory care plans Multiagency Infrastructure Empower all staff to voice concerns and culture to Safety walkrounds promote Learning from adverse events (case note reviews, IR1, PTT) safety Sharing all data with whole team +/- patients and carers Capability and capacity
  • Can we predict who will deteriorate? Can we prevent it? % acute admissions to HDU Tayside Childrens Hospital Nov 2011 - April 2012 35 30 25 20 % 15 10 5 0 0 1 2 3 4 5 6 7 PEWS score80% of acute admissions to HDU have a PEWS <3 Why admit to HDU?
  • What causes concern & doesn’t score in PEWS?
  • WatchersGut Feelings....... “Researchers explain that intuition represents one of the ways our brains store, process and retrieve information........ The researchers .... concluded that intuition - a feeling that something is right or wrong - is the brain drawing on past experiences and current external cues to make a decision; a process so rapid that the reaction is subconscious.” British Journal of Psychology (April 2008)
  • How do we know a change is an improvement?• Outcome measures – Crash call rate, HDU & ICU admission rates, In ward mortality rate – Prediction of Watchers• Process Measures – PEWS, SBAR, MDR, DG, safety brief, equipment checks, guideline checks, simulations, time to first dose of antibiotics, adherence to specific guidelines• Balancing measures – HDU admission rate, staff feedback (simulation), time invested in measuring v delivering service
  • How to move towards Safety Culture of recognising deteriorating children?
  • Safety Brief – shared mental model MULTIDISCIPLINARY SAFETY BRIEFING WARD 29 DATE: TIME: PLANNED EMPTY BEDS ANTICIPATED / ADMISSION (bays/SR) DISCHARGES SWARD ISSUES PROBLEM DETAILS (including bed number) YES NOPATIENTS WITH SIMILAR NAMESHIGH PEWS / WATCHERSPATIENTS WITH INDIVIDUALISED PROTOCOLS (eg CYPADM)
  • Results: process measures Reaching >98% compliance with process measures summer 2011
  • Ap r 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200Ma -09 yJu -09 n-0 Ju 9Au l-09 gSe -09 p-0 Oc 9 tNo -09 v-0De 9 c-Ja 09 nFe -10 b-1Ma 0 r Ap -10 r-1Ma 0 yJu -10 n-1 Ju 0Au l-10 gSe -10 p-1 Oc 0 tNo -10 v-1De 0 c-Ja 10 nFe -11 b-1Ma 1 r Ap -11 r-1Ma 1 y HDU Admission RateJu -11 n-1 Ward 29, Ninewells Hospital Ju 1Au l-11 g HDU Admission RateSe -11 p-1 Oc 1 t Ward 29, Ninewells HospitalNo -11 v-1De 1 c-Ja 11 nFe -12 b-1Ma 2 r Ap -12 r-1Ma 2 yJu -12 n-1 Ju 2Au l-12 gSe -12 p- Oc 12 tNo -12 v-1De 2 c-1 2 Balancing measure: HDU admission rate
  • Ap r 0 5 10 15 20Ma -09 y-0Ju 9 n-0 Ju 9 lAu -09 g-0Se 9 p- Oc 09 tNo -09 vDe -09 c-0Ja 9 nFe -10 b-Ma 10 r Ap -10 r-1Ma 0 yJu -10 n-1 Ju 0 lAu -10 g-1Se 0 p- Oc 10 tNo -10 v-1De 0 c-Ja 10 nFe -11 b-Ma 11 r Ap -11 r-1Ma 1 y AdmissionJu -11 Ward 29, 29, Ninewells Hospital n-1 Ju 1 lAu -11 g-1Se 1 PICUICU Admission Rate Rate p- Oc 11 tNo -11 Ward Ninewells Hospital v-1De 1 c-Ja 11 nFe -12 b-Ma 12 r Ap -12 r-1Ma 2 yJu -12 n-1 Ju 2 lAu -12 g-1Se 2 p- Oc 12 tNo -12 v-1De 2 c-1 2 Outcome measure – PICU admission rate
  • Ja n-1 0 10 20Fe 0 b- 10Ma r-1 0 Ap r-1Ma 0 y-1Ju 0 n-1 0 Ju l-1Au 0 g-1Se 0 p-1 0 Oc t -1No 0 v-1De 0 c-1 0Ja n-1Fe 1 b- 11Ma r-1 1 Ap r-1Ma 1 y-1Ju 1 n-1 1 Ju l-1Au 1 g-1Se 1 p-1 Ninewells 1 Oc t -1 Crash Call RateNo 1 Ward 29,HDU, SSAA Ninewells Hospital v-1De 1 c-1 1Ja n-1 Ward 29, Crash Call Rate HospitalFe 2 b- 12Ma r-1 2 Ap r-1Ma 2 y-1Ju 2 n-1 2 Ju l-1Au 2 Outcome measure: Crash Calls g-1Se 2 p-1 2 Oc t -1No 2 v-1De 2 c-1 2
  • Ap r- 0 10Ma 09 y-0Ju 9 n-0 Ju 9 l-Au 09 g-0Se 9 p-0 Oc 9 t-No 09 v-0De 9 c-0Ja 9 n-Fe 10 b- 1Ma 0 r-1 Ap 0 r-Ma 10 y-1Ju 0 n-1 Ju 0 l-Au 10 gSe -10 p-1 Oc 0 t-No 10 v-1De 0 c-1Ja 0 n-Fe 11 b-Ma 11 r- Ap 11 r-Ma 11 In Ward Mortality Rate y-1Ju 1 Ward 29, Ninewells Hospital n-1 Ju 1 l-Au 11 g-1 In-Ward Mortality RateSe 1 p-1 Oc 1 t- Ward 29, Ninewells HospitalNo 11 v-1De 1 c-1Ja 1 n-Fe 12 b-Ma 12 r- Ap 12 r-Ma 12 y-1Ju 2 n-1 Ju 2 l-Au 12 g-1Se 2 p-1 Oc 2 Outcome measure: In-Ward Mortality t-No 12 vD e -1 2 c-1 2
  • Outcome measure: combined outcomePotential for national Serious Harm Index? Ward 29 Ninewells Hospital total significant events rate (total mortality + crash calls + ICU admissions)40353025201510 5 0 Apr-10 Aug-10 Apr-11 Aug-11 Apr-12 Feb-10 Sep-10 Jun-10 Oct-10 Nov-10 Dec-10 Feb-11 Sep-11 Jun-11 Oct-11 Nov-11 Dec-11 Feb-12 Jan-10 Mar-10 May-10 Jul-10 Jan-11 Mar-11 May-11 Jul-11 Jan-12 Mar-12 May-12 Simulation New PEWS charts and reliability started for multiple process measures across whole unit
  • Who is the sickest patient on the ward? • 16 different responses May • Little overlap • No agreement with attending 2011 Consultant • Agreement May • Theory: Early recognition and shared mental model increases number of reviews, decreases 2012 time to treatment and prevents deterioration
  • Tayside “Project 1” outcomes• Tayside team believe in themselves as individuals and as a team• We know we are providing high quality care (and have the data to show it)• We may be improving outcomes for children but it is early days• We know we have improved staff morale (and have data to prove it!)• We now we have a team who “knows how to improve”• We are now on project 40+
  • Learning / Challenges – developing a Safety Culture• Data is everything: – Baseline – And accurate, appropriate measurement• Person dependence & improvement fatigue• Capability and capacity• Culture – transparency about “bad data”• Running before we could walk – especially simulation• “spread control”• What do we not know? Should we be worried about it?