Closing the Loop by Operationalizing Systems Engineering and Design (CLOSED)
Motivation:
Specific Aims :
Aim 1:​Use systems engineering and patient engagement to design, develop, and refine a highly reliable “closed loop” system for diagnostic tests and referrals that ensures diagnostic orders and follow-up occur reliably within clinically- and patient-important time-frames.
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Aim 2: Use systems engineering and patient engagement to design, develop, and refine a highly reliable “closed loop” system for symptoms that ensures clinicians receive and act on feedback about evolving symptoms and physical findings of concern to patients or clinicians.
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Aim 3: Design for generalizability across health systems more broadly so that the processes created in Aims 1 and 2 are effective in (1) a practice in an underserved community, (2) a large tele-medicine system, and (3) a representative range of simulated other health system settings and populations.
Partners:
Sunday, June 2, 2019
Sunday, June 2, 2019
Approach:
Sunday, June 2, 2019
Results to Date:
Research >> EAGER >> Differential Equations Epidemic Model
Differential Equations Epidemic Model
About
The aim of this project is to develop an adaptable framework to model the epidemiological growth of the prescription and illicit opioid co-epidemics over different regional topologies in addition to gaining insights on different growth mechanisms.
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The project uses systems dynamics methods in order to capture the complex systems associated with the prescription and illicit opioid epidemics. Traditional epidemiological modeling techniques are applied in formulating representative differential equations to model transitions between the general public, general opioid exposure, and aberrant use behaviors. This formulation is used to explore the trajectories of prescription opioid misuse, heroin use, and opioid related overdose over different regional areas. Continuing research aims to explore the pipeline by which individuals initiate opioid use, transition between pharmaceutical and illicit products, and recovery from addictive behaviors. The model framework will be used to provide insights into macroscopic effects of policy interventions.
Results
Published in the 2018 Winter Simulation Conference Proceedings
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