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 >> Surgical Site Infection Reduction >> SSI Signal Characterization
SSI Signal Characterization
Aim
To evaluate the performance of standard and alternative SPC detection rules for SSI surveillance.
Partners & Research Team
From the Healthcare Systems Engineering Institute:
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Postdoctoral Fellow: Iulian Ilies, PhD
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Undergraduate Students: Nathan Holler, Nicole Nehls
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Project Manager: Margo Jacobsen
Methods
Statistical process control (SPC) methods were originally developed for quality control in manufacturing, however SPC is increasingly being used in healthcare applications. Despite these different contexts (assembly line vs. patient safety), the SPC approaches used are largely the same. This project explores what characteristics investigates how well standard SPC methods detect clinically-relevant (vs. statistically-significant) signals.
Results
Institute for Healthcare Improvement National Forum 2017 Conference Poster (Available in December after the conference).