An open source software project for obstetrical procedure scheduling and occupancy analysis.

Increases in the rate of births via cesarean section and induced labor have led to challenging scheduling and capacity planning problems for hospital inpatient obstetrical units. We present occupancy and patient scheduling models to help address these challenges. These patient flow models can be used to explore the relationship between procedure scheduling practices and the resulting occupancy on inpatient obstetrical units such as labor and delivery and postpartum. The models capture numerous important characteristics of inpatient obstetrical patient flow such as time of day and day of week dependent arrivals and length of stay, multiple patient types and clinical interventions, and multiple patient care units with inter-unit patient transfers. We have used these models in several projects at different hospitals involving design of procedure scheduling templates and analysis of inpatient obstetrical capacity. In the development of these models, we made heavy use of open source software tools and have released the entire project as a free and open source model and software toolkit.

Short term hospital occupancy prediction.

Inpatient census, or occupancy, is a primary driver of resource use in hospitals. Fluctuations in occupancy complicate decisions related to staffing, bed management, ambulance diversions, and may ultimately impact both quality of patient care and nursing job satisfaction. We describe our approach in building a computerized model to provide short-term occupancy predictions for an entire hospital by nursing unit and shift. Our model is a comprehensive system built using real hospital data and utilizes statistical predictions at the individual patient level. We discuss the results of piloting an early version of the model at a mid-size community hospital. The primary focus of the paper is on the development and methodology of a second generation of the predictive occupancy model. The results and accuracy of this new model is compared to a variety of other predictive methods based on tests using 2 years of actual hospital data.

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.