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Using Simulation To Understand Orthopaedic Flow Through Triage Ekwutosi Chigbo Ezeh Supervised by Dr Navid Izady 16/10/13 University of Southampton University.

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Presentation on theme: "Using Simulation To Understand Orthopaedic Flow Through Triage Ekwutosi Chigbo Ezeh Supervised by Dr Navid Izady 16/10/13 University of Southampton University."— Presentation transcript:

1 Using Simulation To Understand Orthopaedic Flow Through Triage Ekwutosi Chigbo Ezeh Supervised by Dr Navid Izady 16/10/13 University of Southampton University Hospital Southampton - Solent NHS – ISTC (CARE UK) Southampton City Clinical Commissioning Group

2 Background When patients require orthopaedic assessment they are referred by their GP to an Integrated Medical Assessment and Treatment (IMAT) service for triage to determine the appropriate referral pathway For orthopaedics, these routes include physiotherapy, podiatry, rehabilitation programmes, pain management services, and community re-ablement services, as well as orthopaedic surgery (three tier system) Evidence that some patients are routed incorrectly, leading to wastage and poor patient experience Aims: to identify how patients are referred, then triaged then routed; quantify where patients are initially routed incorrectly and subsequently rerouted; use simulation to test alternative pathway designs

3 Providers modelled In 2012-13 the Southampton Musculoskeletal service (including IMATs, physiotherapy, rheumatology and pain management) served 16,000 patients and provided 38,000 outpatient appointments Southampton City CCG (Tier 1) NHS Solent (Moorgreen Hospital) – community-based outpatient clinics, physio and reablement (Tier 2) Independent Sector Treatment Centre at the Royal South Hants hospital (Tiers 2 & 3) University Hospital Southampton (Tiers 2 & 3) Many others – highly complex patient flow through different sectors with a multiplicity of providers and over 400 pathways, which were modelled as a series of clinics

4 Patient flow between providers

5 Challenges Limited data available for modelling the whole system (lack of referral numbers; medical conditions recorded; referral destination; no entrance data for cohort) Significant differences in data across providers No universal identifiers linking data Appointment scheduling procedures required to model waiting times, but were not available

6 Moorgreen Hospital Simul8 Model 160 pathways in total!

7 Outpatient Clinics

8 Solent : Accepted & Cancelled Referrals

9 Top 95% of pathways in Solent NHS CLINIC No. of Appts% of Total Cumulative % MGH MSK Physio691329.78% ADC MSK Physio656728.29%58.07% MGH MSK SPINAL19338.33%66.40% MGH CAS18137.81%74.21% MGH MSK HAND9243.98%78.19% MGH MSK LOWER LIMB9143.94%82.13% ADC MSK SHOULDER6502.80%84.93% ADC MSK SPINAL6492.80%87.72% ADC MSK FEET6482.79%90.51% ADC MSK LOWER LIMB5042.17%92.69% MGH MSK FEET3591.55%94.23% MGH MSK SHOULDER1860.80%95.03%

10 Number of consecutive appointments per pathway

11 Conclusions Many limitations of model due to data challenges Enhancement of current data available needed to effectively model this We found less inefficiency in the system than was perhaps initially perceived by our client: the majority of patients are correctly triaged at Tier 1, while 94% of patients referred to Tier 2 attend only the first clinic they are referred to Despite the data limitations, the modelling process highlighted many key issues for the providers to think about

12 OR - clinical perspective Dr Cathy Price UHS FT

13 NHS perspective Are pathways of care Timely? - treatment delivered within an acceptable waiting period (need to understand rate of deterioration whilst waiting) Effective? - no bounce around, minimal follow ups Efficient? - minimal number of follow ups

14 Commissioning Landscape Multiple Providers within small geography Confusing entry criteria One large teaching hospital Multiple Signposting Tier 2 services for GPs Collaboration difficult across providers Commissioned time points for providers to meet to review cases (virtual clinics) Patient experience confusing Clinical effectiveness unclear

15 Modelling /OR – comments Brought some clarity on efficiency (minimal follow ups) in Signposting service – pretty efficient Clinical Effectiveness hard to ascertain within timescale (no follow ups per provider – needed to be accurately agreed ) Model built that allowed for varying scenarios Concerning number of differing outcomes for patients (400+ pathways ) No easy way to ID patient through whole system i.e. more confident modelling would require this


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