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:
Online Training Materials
HSyE's mission includes fostering broader awareness and training in healthcare systems engineering, ranging from online lectures and exercises through more formal programs. Please feel free to browse below or contact us if we can provide other assistance or customized training.
A 16-part series covering healthcare applications of a range of common systems engineering methods, including process improvement, human factors, reliability, modeling, optimization and design. Can be viewed separately, with accompanying quizzes, or towards a certificate of completion of 12 core + elective topics.
![online training modules HSyE website image[1].png](https://static.wixstatic.com/media/bef7d2_7eb3fcecde7f4daab5bd20b66175be02~mv2.png/v1/fill/w_258,h_129,al_c,q_85,usm_0.66_1.00_0.01,enc_avif,quality_auto/online%20training%20modules%20HSyE%20website%20image%5B1%5D.png)
Online interactive modules based on four classic training exercises about natural and special cause variation, statistical control charts, variation reduction, process tampering, and designed experiments (Deming's red bead experiment, Nelson's funnel exercise, dice process variation exercise, Box's catapult experiment).
