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:
Modeling ACOs as Macro Integrated Systems of Care
About
In recent healthcare reform trends, financial and a care considerations are resulting in numerous health system mergers, business affiliations and coupling among health care organizations across the care and health continuum. Organizations within this spectrum, such as specialty care, primary care and skilled nursing facilities, are all components that make up the greater macro “ecosystems” of healthcare. The recent healthcare reform trends have lead to a newfound interest in the improvement of care and health maintenance of patients as they move between and across the said “healthcare ecosystems”. Particularly, projects are focusing on improving the boundaries between the organizations of the macro-system to facilitate patient transitioning. This project focuses on modeling these inter-organizational processes at macro-level and configuring the use of these models to improve the overall system. This project will develop and trial a system-wide analytic model of patient, information and personnel flow across all components of accountable care organization and other loosely linked healthcare affiliations.
Results
This research ultimately resulted in the implementation of a basic two-facility, single-direction, single-period, single-decision simulation model, which was validated using synthetic data. We reviewed the literature on Accountable Care Organizations (ACO) and multi-facility flow modeling and interviewed selected healthcare systems to determine their specific needs. Based on the acquired information, a theoretical model of system-level multi-facility flow that expanded previous probabilistic multi-unit model of bed and staff demand was created. This model was then expanded into a stochastic system-wide patient transfer optimization model. A variety of capacity and cost-related objective functions were tested.
Project Team
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Kelly Gallagher
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Meredith Clemmens