Biomedical subjects

Mark W Isken

Publications and source records attributed to Mark W Isken.

4 recordsLinked to original sources

PubMed2005

Collection and preparation of sensor network data to support modeling and analysis of outpatient clinics.

Simulation studies of outpatient clinics often involve significant data collection challenges. We describe an approach for data collection using sensor networks which facilitates the collection of a large volume of very detailed patient flow data through healthcare clinics. Such data requires extensive preprocessing before it is ready for analysis. We present a general data preparation framework for sensor network generated data with particular emphasis on the creation and analysis of patient path strings. Several examples of the analysis of sensor network data are also presented. Our approach has been used in two large outpatient clinics in the United States.

Ambulatory Care Facilities↗

PubMed2005

Hillmaker: an open source occupancy analysis tool.

Managerial decision making problems in the healthcare industry often involve considerations of customer occupancy by time of day and day of week. We describe an occupancy analysis tool called Hillmaker which has been used in numerous healthcare operations studies. It is being released as a free and open source software project.

Computer Communication Networks↗

PubMed2002

Simulation analysis of pneumatic tube systems.

Pneumatic tube systems play an important material handling role in many hospitals. These systems are costly and complex to design and operate, yet little exists in the way of analytical methodologies for them. We present a decision support framework based on defining relevant system performance metrics, traffic analysis reporting, as well as discrete event simulation modeling. We have used this approach to analyze numerous pneumatic tubes systems in the United States and present a representative case study from a large tertiary care hospital. Our general approach can be generalized to other computer controlled hospital operational systems such as elevators, track vehicles, automatic guided vehicles, workflow enabled processes, and laboratory automation systems.

Computer Simulation↗

PubMed2002

Data mining to support simulation modeling of patient flow in hospitals.

Spiraling health care costs in the United States are driving institutions to continually address the challenge of optimizing the use of scarce resources. One of the first steps towards optimizing resources is to utilize capacity effectively. For hospital capacity planning problems such as allocation of inpatient beds, computer simulation is often the method of choice. One of the more difficult aspects of using simulation models for such studies is the creation of a manageable set of patient types to include in the model. The objective of this paper is to demonstrate the potential of using data mining techniques, specifically clustering techniques such as K-means, to help guide the development of patient type definitions for purposes of building computer simulation or analytical models of patient flow in hospitals. Using data from a hospital in the Midwest this study brings forth several important issues that researchers need to address when applying clustering techniques in general and specifically to hospital data.

Algorithms↗