System simulation modelling of TBI care added value for health care decision making?
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1 System simulation modelling of TBI care added value for health care decision making? 1 st Turku Traumatic Brain Injury Symposium Peter Ylén VTT Technical Research Centre of Finland
2 Purpose A dynamic simulation model for evaluating long-term socioeconomic effects of different choices in traumatic brain injury treatment Starting from prevention of the incident to decades after the rehabilitation Includes many different interest groups, such as, patient, accute phase hospital, society, rehabilitation unit, patient s relatives, emergency room, etc What-if scenarios and sensitivity analysis
3 Contents System dynamics model Structure: Feedback loops in the model Simulation Results Scenarios Base (no changes to current policies) New diagnostic tools (improves the accuracy of diagnoses) Advertisement Campaign (increases the willingness of patients to get to a doctor after a head injury) TBI Prevention (e.g. lower speed limits) All policy improvements Sensitivity tests Conclusions
4 Manageable complexity Models for decision making Simulation Mathematical formulation Fit models to data Systems thinking Shared and formalized mental models Mental models Expert opinion Unanalyzed written case reports Exactness and detail of representation
5 What is system dynamics Identifying complex cause and effect relationships Tool to help communicate mental models Understanding the long- and short-term consequences of actions Foreseeing unintended consequences Finding leverage seeing where actions and change can lead to significant and enduring improvements Simulating policies under different assumptions and uncertainties
6 Health care services - the model dependencies
7 Patient flow
8 TBI care System model of treatment chain Incidence ER Hospital Life with TBI Rehabilitation
9 ER and hospital Incorrect diagnoses Discharge Secondary injuries More difficult readmissions Resource inadequacy More incorrect diagnoses Patients less willing to wait if they have only mild symptoms Worst case scenario Readmissions spiral out of control, consume resources Expensive and ineffective
10 Long term problems More prone to new TBI Rehabilitation increases quality of life and reduces long term costs Less stress on health care system
11 The Main Feedback Loops
12 Resource Inadequacy at ER Leads to Secondary Injuries and Readmissions Lack of resources causes hurry and inaccurate diagnoses If the injury is not diagnosed early enough it has tendency to generate severe secondary injuries Red Loop
13 Long Queueing Times Decreases Willingness to Go to ER in Time Long queuing time has tendency to decrease the willingness to get to a doctor Sometimes this leads to secondary injuries Green Loop
14 Discharging Based on Inaccurate Diagnoses tends to lead Readmissions Blue Loop
15 Resource Inadequacy in Hospital Leads to Readmissions and sec. injuries Lack of resources in hospital leads to inaccurate diagnoses and sometimes to secondary injuries Violet Loop
16 Patients after TBI tend to get more Injuries In long term the patients are more prone to injuries and other long term problems (e.g. depression and alcoholism) Yellow Loop
17 Detailed view to the Model The detailed model is rather complex due to myriads of interdependencies between parts of the system
18 About the model The model consists of several feedback loops most of which are positive (reinforcing) The system tends to be unstable The most important negative (balancing) feedback loops are those that adjust the capacities of TBI treatment and rehabilitation
19 Simulation Results
20 Example Scenario Simulations Base No changes to current policies New diagnostic tools are adopted Improves the accuracy of diagnoses Prevention policies (e.g. lower speed limits) are adopted Decreased incidence rate Advertisement campaign to increase awareness of TBIs Increases the willingness of patients to get to a doctor after a head injury All policy improvements together (mentioned above)
21 Resource Spending (~money)
22 TBI Deaths per Year
23 Costs on Society
24 About the Results Based on the preliminary simulations it seems that preventing TBIs is clearly the best policy to reduce costs on society and to improve the quality of life of the population This is rather expected - nevertheless Some of the results show so called worse-before-betterbehaviour (see advertisement campaign for example) See also the minor improvement of the results due to new and improved diagnosis tools This needs more elaboration!!
25 Sensitivity to uncertainties
26 Some Sensitivity Tests Several uncertain parameters were varied Left column: No diagnosis tools in use Right column: Diagnosis tools in use
27 About sensitivity tests Diagnosis tools improve the accuracy of the diagnoses Especially when the accuracy of the diagnoses is otherwise poor (in a hurry and by inexperienced doctors) Diagnosis tools make the system significantly more robust under uncertainty
28 Conclusions
29 Conclusions Preliminary simulations of the socio-economic model are possible Validation needs to be completed Parameter values need to be set according to all the data collected
1st Turku Traumatic Brain Injury Symposium Turku, Finland, January 2014
The TBIcare decision support tool aid for the clinician Jyrki Lötjönen & Jussi Mattila, VTT Technical Research Centre of Finland Validation of the decision support tool Ari Katila University of Turku 1st
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