Extending closed-loop control to the management of chronic disease.

Vanderbilt University Medical Center, Nashville, TN 37203, USA.
Transactions of the American Clinical and Climatological Association 01/2010; 122:93-102.
Source: PubMed


A closed-loop control process assures that a system performs within control limits by direct feedback of the system's output to change the system's inputs. We developed methods for the closed-loop control of system-based practice, using ventilator management as a model or test bed. The control system has three components: 1) an explicit end-to-end plan; 2) a record of what is done as it is done; and 3) an instant display of the status of each patient against the plan for that patient. The status display provides process control by showing the clinical team where corrections are needed while the team still has the time needed to act prospectively. We are extending these methods to the management of chronic disease. Their extension requires engagement of the patient as a member of the team, a coordinated plan across the care continuum, informatics algorithms to stratify individual patients according to co-morbidities and their current level of control, and a means of detecting the presence or absence of a reaction to each action taken by the team.

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    • "A centralized transactional messaging engine called the Generic Interface Engine (GIE) manages communication and information exchange between systems. This early adoption and integration of electronic clinical information systems have had significant impact in the domains of clinical care, patient safety, provider accountability, and improved documentation [16] [17] [18] [19]. The end result of our early launch and continuously evolving clinical systems is an information-rich environment covering 2 million patients, with longitudinal records spanning more than a decade. "
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    ABSTRACT: The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure.
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