Van organische groei naar het ontwerp van acute zorgnetwerken: simulatie als hulpmiddel

Transcription

1 Van organische groei naar het ontwerp van acute zorgnetwerken: simulatie als hulpmiddel Durk Jouke van der Zee (RUG), Hessel Jonker (UMCG Ambulancezorg) 20 april 2015

2 Overview Organizing acute care networks Projects in Northern Netherlands Discussion: benefits of a model based approach

3 Organizing acute care Time to (the right) care determines patient health (tosomeextent). SPEED HEALTH How to organize acute care such that the right care is offered in time?

4 Acute care network Pre hospital Primary care (GP) EMS Self referral Intra hospital Emergency department Diagnostics Treatment Followup Efficiency Balance Timeliness Influences Effectiveness (treatment outcomes)

5 Organizing acute care organic growth Optimize care services along a pathway Bottom up initiatives Use real life testing as a means of estimating performance gains

6 Facilitating a top down approach Use quantitative (simulation) models as a means for decision support on network design Models: Represent acute care networks in a realistic way Serve as an efficient test bed for estimating performance of various alternative set ups of the network (off line) Allow for active stake holder participation (solution engineering). Which adds to solution quality and credibility.

7 I Ambulance network redesign Regions: Friesland, Drenthe Target: 95% A1 calls response time 15 min How to adapt the network: Where to locate ambulance posts? Where, when and how many ambulances (staff) are needed? Relocate ambulance stations? What if.. In order to realize the target? Project duration [Van Werven 2012]

8 Tool: Optima Predict

9 Tool: output statistics Distribution response, transport, time to hospital, etc. Calls per ambulance, station, day, hour, hour of day, etc. distribution response times Statistics scenario results

10 Redesign: Identify weaknesses (where?) Travel time > 12 min < 0 min

11 Identify weaknesses (when?) A1 performance <85% >95% 17 8 Weekend 8 17 Weekdays

12 Linking insights to solutions Problems occur because No staff capacity available (end of shift) Misfit demand and location of supply (stations, #stations, #ambulances) ±100 scenario s simulated Solution Four additional stations Relocate ambulance capacity Additional ambulance capacity > additional staff capacity (21,5 Fte)

13 Solution A1 performance <85% >95% Relocate and extend capacity 24/7 Relocate and extend capacity 24/7 Additional capacity day Relocate capacity Relocate capacity Additional capacity 24/7

14 What if? Closing hospital Dokkum Decision support within 1 day: Response times unchanged Transport times change slightly Causes: Few patients involved Distance effect small Travel time +10 min 10 min Same distribution response times

15 II Optimizing acute stroke care Acute stroke Ischemic stroke: blockage blood vessel Treatment: intravenous thrombolysis (actilyse; dissolve clot) Effectiveness of treatment is strongly time related (window of opportunity < 4.5 hours; every minute counts) Problem & current approach Problem: underutilization (benchmark 30% treatment rate; NL 11% + large variance) A main cause of delays: acute care organization Current approaches: Clinical trial (real life testing); local improvements [Lahr et al. 2013]

16 Modelling the stroke pathway Groningen acute stroke pathway [Lahr et al. 2013; research group: NN neurologists, GPs, EMS ]

17 Optimizing the acute stroke pathway Operational measures Expediting care services Improving diagnostics Publicity campaigns Example: Groningen pathway Current: 22% treatment rate Blood testing (lab vs. POC device): + 3.2% Scoop & run vs Stay and play : + 1.4% Liberal policies in assigning urgent EMS transport: + 0.1%

18 Optimizing acute stroke care networks Network topology Centralize vs. decentralize (NN: treatment rate 22% vs. 14%) Telemedicine Advances in technology: Mobile Stroke Units New treatments: intraarterial treatment (remove clot; Berkhemer et al. 2014)

19 III Ambulance helicopter Serve Dutch Isles Current services stop July 1, 2015 How to proceed? Dutch Isles: OK Beyond. [Porton 2015]

20 Discussion: Network design & models Models may be used instead of real life testing Realistic (valid) models can be built, allowing for precise estimates of network performance Models allow for joint solution engineering starting from a common platform Models allow for efficient testing of a great many solutions

21 What does it take. Tools (may seem expensive, but minor issue) Modeling skills (invest in people) Data collection (integration of databases among care givers) Interdisciplinary approach (health professionals & engineers)

22 References Berkhemer, O.A., Fransen P.S., Beumer D., et al., 2015, A randomized trial of intraarterial treatment for acute ischemic stroke, New England Journal of Medicine, 372(1): Lahr, M.M.H., Luijckx, G.J., Vroomen, P.C.A.J., Zee, D.J. van der, Buskens, E., 2012, Proportion of Patients Treated With Thrombolysis in a Centralized Versus a Decentralized Acute Stroke Care Setting. Stroke, 43(5), Lahr, M.M.H., Luijckx, G.J., Vroomen, P.C.A.J., Zee, D.J. van der, Buskens, E., 2013, The chain of care enabling tpa treatment in acute ischemic stroke: a comprehensive review of organisational models, Journal of Neurology 260(4), Lahr, M.M.H., Zee, D.J. van der, Luijckx, G.J., Vroomen, P.C.A.J., Buskens, E., 2013, A simulation based approach for improving utilization of thrombolysis in acute brain infarction. Medical Care 51(12), Lahr, M.M.H., Zee, D.J. van der, Vroomen, P.C.A.J., Luijckx, G.J., Buskens, E., 2013, Thrombolysis in acute ischemic stroke: A simulation study to improve pre and in hospital delays in community hospitals, PLoS ONE 8(11): e Lahr, M.M.H., Vroomen, P.C.A.J, Luijckx, G.J., Zee, D.J. van der, Vos, R. de, Buskens, E., 2014, Pre hospital factors determining regional variation in thrombolytic therapy in acute ischemic stroke. International Journal of Stroke 9, Werven, R., 2012, Improving the response time performance of A1 priority calls for UMCG Ambulancezorg, Master thesis, University of Groningen. Jansma, T., 2014, Extending the Emergency Medical Services Network for Out of Hospital Cardiac Arrest victims, Master thesis, University of Groningen.