Insights from the 2006 Disease Management Colloquium

This roundtable discussion emanates from the presentations given and issues raised at the 2006 Disease Management Colloquium, which was held May 10–12, 2006 in Philadelphia, Pennsylvania

Up from Crisis: Overhauling Healthcare Information, Payment, and Delivery in Extraordinary Times. Dialogue with Featured Speakers from the 6th Annual Connected Health Symposium

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78098/1/tmj.2009.9948.pd

Autoregulation modelling of cerebral haemodynamics

The Circle of Willis (CoW) is a ring-like structure of blood vessels found at the base of the brain. Its main function is to distribute a constant flow oxygen-rich arterial blood to the cerebral mass, despite changes in afferent pressures or flows. This objective is achieved by a local mechanism known as autoregulation, whereby the resistance in small vessels branching from the CoW changes by vasodilation or vasoconstriction of the smooth muscle cells surrounding the vessel. A one-dimensional (1D) model of the CoW is developed to simulate a series of possible clinical scenarios such as occlusions in afferent arteries, absent or string-like circulus vessels, or arterial infarctions. A series of studies investigates various features of autoregulatory behaviour. Firstly, a simple model is created to verify solution methods; secondly, the model is validated against a three-dimensional (3D) Computational Fluid Dynamics (CFD) model; and lastly, the decentralised nature of cerebral autoregulation is investigated. Finally, an advanced, metabolic model of autoregulation is created, incorporating the successful aspects of the early model, as well as more physiologically accurate dynamics. The advanced model captures cerebral haemodynamic autoregulation by using a Proportional-Integral-Derivative (PID) controller to modify efferent artery resistances and partial pressures of oxygen to maintain optimal efferent flow rates and oxygen supply to the cerebral mass for a given circle geometry and afferent blood pressure. This advanced model is physiologically relevant, matching the accepted physiological responses of blood flow as a function of arterial pressure, tissue oxygen partial pressure as a function of blood flow, as well as limited transient clinical data. Results match accepted physiological response and exhibit excellent correlation with the limited clinical data available. In addition, a set of boundary conditions and geometry is presented for which the autoregulated system cannot provide the necessary efferent flow rates and perfusion, representing a condition with increased risk of stroke and highlighting the importance of modelling the haemodynamics of the Circle of Willis. The system model created is computationally simple so it can be used to identify at-risk cerebral arterial geometries and conditions prior to surgery or other clinical procedures. In addition, the solution for the CoW arterial system is obtained in a far shorter time period using this time-varying resistance model than with higher dimensional CFD methods, and requires significantly less computational effort while retaining a high level of accuracy

Design and Implementation of Analytical Mathematics for SIFT-MS Medical Applications

Selected Ion Flow Tube-Mass spectrometry (SIFT-MS) is an analytical measurement technology for the real-time quantification of volatile organic compounds in gaseous samples. This technology has current and potential applications in a wide variety of industries, although the focus of this research is in medical science. In this field, SIFT-MS has potential as a diagnostic device, capable of determining the presence of a particular disease or condition. In addition, SIFT-MS can be used to monitor the progression of a disease state, or predict deviations from expected behaviour. Lastly, SIFT-MS can be used for the identification of biomarkers of a particular disease state. All these possibilities are available non-invasively and in real-time, by analysing breath samples. SIFT-MS produces an extensive amount of data, requiring specific mathematical methods to identify biomarker masses that differ significantly between populations or time-points. Two classification methods are presented for the analysis of SIFT-MS mass scan data. The first method is a cross-sectional classification model, intended to differentiate between the diseased and non-diseased state. This model was validated in a simple test case. The second method is a longitudinal classification model, intended to identify key biomarkers that change over time, or in response to treatment. Both of these classification models were validated in 2 clinical trials, investigating renal function in humans and rats. The first clinical trial monitored changes in breath ammonia, TMA and acetone concentrations over the course of dialysis treatment. Correlations with the current gold standard plasma creatinine, and blood urea nitrogen were reported. Finally, biomarkers of renal function were identified that change predictably over the course of treatment. The second trial induced acute renal failure in rats, and monitored the change in renal function observed during recovery. For comparison and validation of the result, a 2-compartment model was developed for estimating renal function via a bolus injection of a radio-labelled inulin tracer, and was compared with the current gold standard plasma creatinine measurement, modified using the Cockcroft-Gault equation for rats. These two methods were compared with SIFT-MS monitoring of breath analytes, to examine the potential for non-invasive biomarkers of kidney function. Results show good promise for the non-invasive, real-time monitoring of breath analytes for diagnosis and monitoring of kidney function, and, potentially, other disease states

The Future of Home Health Care:A Strategic Framework for Optimizing Value

The Future of Home Health project sought to support transformation of home health and home-based care to meet the needs of patients in the evolving U.S. health care system. Interviews with key thought leaders and stakeholders resulted in key themes about the future of home health care. By synthesizing this qualitative research, a literature review, case studies, and the themes from a 2014 Institute of Medicine and National Research Council workshop on “The Future of Home Health Care,” the authors articulate a vision for home-based care and recommend a bold framework for the Medicare-certified home health agency of the future. The authors also identify challenges and recommendations for achievement of this framework