Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Family Preservation Services under Managed Care: Current Practices and Future Directions

Family preservation service agencies in the State of Kansas have undergone major changes since the implementation of a managed care model of service delivery in 1996. This qualitative study examines the successes and barriers experienced by agency directors in utilization of a managed care system. Outcome/ performance measures utilized by the State of Kansas are reviewed, and contributing factors to the successes and limitations of the program are discussed. Included in these reviews is an analysis and presentation of literature and research which has been used as support for the current program structure. Recommendations for further evolution of practice are proposed.

International comparison of wait times and quality of care: A pilot study

During the healthcare reform debate in the United States in 2009/2010, many health policy experts expressed a concern that expanding coverage would increase waiting times for patients to obtain care. Many complained that delays in obtaining care in turn would compromise the quality of healthcare in the United States. Using data from The Commonwealth Fund 2010 International Health Policy Survey in Eleven Countries, this study explored the relationship between wait times and quality of care, employing a wait time scale and several quality of care indicators present in the dataset. The impact of wait times on quality was assessed. Increased wait time was expected to reduce quality of care. However, this study found that wait times correlated with better health outcomes for some measures, and had no association with others. Since this is a pilot study and statistical significance was not achieved for any of the correlations, further research is needed to confirm and deepen the findings. However, if future studies confirm this finding, an emphasis on reducing wait times at the expense of other health system level performance variables may be inappropriate. ^