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Review of the Cardiff Masters EU Projects with Aneurin Bevan University Health Board
Danny Antebi, Paul Harper, Julie Vile & Janet Williams
Masters students: Elizabeth Allkins, Yiwen Fu
Overview
Background on links between Cardiff University & ABUHB
Brief overview of the two Unscheduled Care Masters Projects
Project feedback to the Health Board
Outcomes and sustainability of the work
Questions
ABUHB – Aneurin Bevan University Health Board
14 hospitals in total, 2 major A&E
Serves an estimated population of over 639,000, approximately 21% of the total population of Wales
Employing over 13,000 staff, two thirds of which are involved in direct patient care
The Modelling Unit
John Frankish – Service Lead/Improvement Coach
Dr Tracey England – Mathematical Modeller
Dr Penny Holborn - Mathematical Modeller
Dr Izabela Komenda – Mathematical Modeller
Dr Julie Vile - Mathematical Modeller
Terry Watkins – Improvement Coach
Mr Hiro Tanaka – Clinical Liaison/Support
Steve Elliott – Financial Support
FunctionsRange from informal advice to analytical support
Variety of mathematical techniques permit best option approach for any project:
Focus - Current ProjectsUnscheduled care:
Modelling demand and capacity for OoH services Improving the accuracy of predictions for RGH ED Aligning staffing profiles to peaks and troughs in demands for RGH ED Improving patient flow Evaluating the effect of individuals presenting in ED under the influence of
alcohol
Mental health: CHMTs skill mix and staffing levels Developing caseload management tool Analysis of CHC packages over a 5 year period
Pathology: The effects of changing the shift patterns in the laboratory at the RGH
Primary care: Evaluating the introduction of a Patient Access system for GPs scheduled care
Scheduled care: Development of a fracture neck of femur database tool
Informatics: Digitalisation of Health Records
Masters Projects
Short-term projects (3 months)
Outputs:
Presentation
Executive summary
20,000 word dissertation!
Unscheduled Care
TOO MUCH DEMAND
PROCESSES ARE TOO SLOW IN HOSPITAL
LACK OF CAPACITY TO TAKE PATIENTS OUT
OF SYSTEM
• Admission avoidance strategies
• Better community model
• Role of WAST
• Consultant at front end
• Alternative pathway for elderly/ frail patients
• Co-locate MIU
• Better computational facilities
•Discharge patients earlier
• Bring in elective patients later
• 24/7 working
• Patient boarding
Modelling patient flow in ED to better understand demand
management strategies.
Elizabeth Allkins
Sponsor Supervisor – Danny Antebi
University Supervisors – Dr Julie Vile and Dr Janet Williams
Aims
Gain insight into the functioning of the Emergency Department in the Royal Gwent Hospital
Explore the effect on the system of actions to redistribute demand, reduce overcrowding and long waiting times
4 hr Breaches & Death Rate
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4 hour breaches
Death rate
DES Simulation modelInput Parameters – easily changed via spreadsheet
Resources
Staff Nurses Doctors Call handler Receptionist
Beds Beds for Majors and wards Rooms for Minors
Xray machine
Validation and Verification processes completed
What-if scenarios
WAST pre-hospital streaming Streaming ambulance patients direct to the MAU
GP trial Streaming GP referrals to a bed in the MAU
Reduction in WAST conveyance rates Reduction of 10% reduced waiting times
Conclusions
Detailed analysis of ED data
Cost saving of CDU Reduction in Majors LOS
Simulation Demonstrated the power of modelling Explored scenarios to improve waiting times Built a solid foundation for future research
Assessing the impact of an ageingpopulation and the effects of
frailty programmes on RGH
Yiwen Fu
Sponsor Supervisor – Danny Antebi
University Supervisors – Dr Julie Vile & Prof. Paul Harper
Aim and backgroundAim
Evaluation: Impact of aging population on RGH Evaluation: Indirect effectiveness of Newport frailty team on ED Simulation models and scenarios: Estimate impact on patient flow in
ED resulting from realisation of operational LoS and attendance targets
Background Pressure from ageing population in ED Newport frailty team: Established at 11th April 2011; Further developed
at 1st Sept 2011 Main patients source: GP and secondary care
Arrival modes
2/3 of patients 65+ arrive by ambulance
2/3 of those under 65 come in a private vehicle
Ambulance 65%
Ambulance19%
The Frailty programme
Joint service provision across ABHB and the 5 local authorities
Set up in April 2011
Provide intermediate care services Keep people happily independent in their own home Services within Community setting Services within the hospital
Aims Reduce bed days Avoid ED and MAU admissions Reduce need for Continuing Health Care Packages
Impact on ED/MAU attendance ratios
The baseline population is increasing and ageing.
Significant reductions in number of 65+ attending MAU (1st contact): 1,995 (2011/2012) -> 1,884 (2012/2013). Number of patients under 65 remained relatively stable over same period. Early days – some natural variability in system, numbers increased in year frailty
team was initiated. Need to re-evaluate in the future!
Lack of evidence to support a reduction in ED attendances: Numbers and ratios fell for ALL patients except those aged 65-74 between the
‘during’ and ‘after’ period. Possibly some evidence of a small impact - between 2012-2013 the ratios of
patients aged 75+ fell at a more dramatic rate than those under 65. Need to re-evaluate in the future!
Marginal (but not significant) reductions in the assessed-in rate
Results of simulation
Scenarios results are compared with baseline results Relative large impacts on Major unit
Scenario 1 Reduction on service time (65+ only) Reduction rate is linearly related to performances Gradually improve all performances
Scenario 2 Reduction on attendances (65+ only) Reduction rate is curvedly related to performances Mainly improve queuing size and queuing time
ConclusionsSmall cohort of population but uses a non-equivalently large proportion of resources
Impact of Newport frailty team – need to evaluate in future
Better care management would benefit hospital and patients Introduce a frailty consultant to ED?
Further research Impact of Newport frailty team on MAU/quality of life Apply same techniques to other Local Authorities Need IT software to capture the relevant data More detailed simulation model
Feedback to Heath Board
Aneurin Bevan Continuous Improvement and
Cardiff University Event
Developing Mathematical Models in Healthcare
Wednesday 11 September 2013
Malpas Court, Whittle Drive,
Malpas, Newport, NP20 6NS
Programme
From 13:00
Registration and Coffee
13:30Opening, Welcome and Introduction
Prof. Paul Harper – Head of Operational Research, Cardiff University and Dr Danny Antebi – Director, ABCi
13:40How can the ABCi Modelling Unit support you?Dr Julie Vile – Mathematical Modeller, ABCi
Session 1
13:50
Presentation 1 – Elizabeth Allkins“Admission avoidance strategies to redirect high demands for A&E services in ABHB”
14:15Presentation 2 – Yiwen Fu“The impact of an ageing population on unscheduled care services in ABHB”
14:40Presentation 3 – Hannah Williams“Compliance with national guidelines for stroke in radiology”
15:05 Coffee
Session 2
15:35Outcomes of Kayne Putman’s 2012 Dermatology MSc Dissertation Prof. Alex Anstey – Director, R&D
15:40Presentation 4 – Harriet Jones“Patient flow through hospital-based therapies for psoriasis at ABHB”
16:05
Presentation 5 – Bradley Hardy“Development of a model to simulate sample-flow through the Biochemistry Laboratory in ABHB”
16:30Summing up & CloseDr Paul Buss, Interim Medical Director - ABHB
Outcomes and sustainability
Extract from email to students from Dr Julie Vile:
“The buzz you created at the event was something rarely seen at the NHS and I've hardly been able to get any work done this morning, due to the large number of people coming in the office praising your work which has really helped to raise the profile of the Modelling Unit within our health board.”
Outcomes and sustainability
Quote from Dr Danny Antebi
Director of ABCi (Aneurin Bevan Continuous Improvement):
“ Having seen some of the projects the mathematicians have been working on, senior managers in Aneurin Bevan University Health Board are becoming more and more convinced of the value of this approach. In my view we can’t manage increasingly complex systems, be they in health or otherwise, without modelling as an integral part of our design and analysis.”
Outcomes and sustainability
Modelling patient flow in ED to better understand demand management strategies – Elizabeth Allkins
Built a solid foundation for future research and the model is to be used to explore future scenarios
Assessing the impact of an ageing population and the effects of frailty programmes on RGH – Yiwen Fu
Recommended that a frailty team be placed within ED and a pilot is now underway
Questions?
www.cf.ac.uk/maths/research/researchgroups/ opresearch/healthcare
http://www.wales.nhs.uk/sitesplus/866/page/69767
Follow us on twitter @abciab
Email: Julie.Vile@wales.nhs.uk
Compliance with National Guidelines for stroke in radiology – Hannah Williams
The model identified a significant increase in compliance with revised guidelines and proposed changes to the initial plan for extended working hours
Modelling the provision of phototherapy services for dermatology clinics – Harriet Jones
The tool is to be further explored and recommendations on the location of future psoriasis centres are to be considered in South Wales Plan
Simulating the automated clinical biochemistry track system at RGH – Bradley Hardy
Identified reductions in cost and staff workload by removing/replacing analysers which are being considered for implementation
Other Masters Projects
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