CS Colloquium 2/27/2012 "Continuous Process Improvement in Healthcare Delivery: A Systems Approach"

Continuous Process Improvement in Healthcare Delivery: A Systems Approach

Continuous Process Improvement in Healthcare Delivery: A Systems Approach

Dr. Shengyong Wang, Assistant Professor, Industrial and Systems Engineering, Department of Mechanical Engineering, University of Akron

Hospitals are facing tremendous challenges to make the healthcare delivery systems safe, effective, patient-centered, timely, efficient, and equitable. While medical practice relies of qualitative and quantitative factors, the management and operation of hospitals is a science that relies on rigorous analysis to make decisions that would sustain the continuous improvements while concurrently enhancing the patients’ experience. With the delivery of the best care to patients at the lowest operating costs being the ultimate goal of hospital operations, industrial and systems engineering tools can be used in a variety ways to achieve these objectives. The strategic use of these tools, such as statistical quality control, supply chain management, modeling and simulation, failure-mode effects analysis, lean methodology, and human factors, can be readily used to measure, characterize, and optimize performance in a healthcare system. In this research seminar, the application of industrial and systems engineering techniques to model and optimize healthcare delivery systems at various levels will be discussed through four research endeavors.

  1. Deploying ‘lean’ in hospital design
    The schematic design of a hospital has generally been an artistic endeavor which lacks the data and support to justify the placement of key locations. Focusing on creating the best design for patient care as well as staff workflow, ‘Lean’ was applied into the schematic design of a proposed Greenfield hospital. It is the first hospital in the nation that was completely designed and constructed based on ‘lean’ principles. The detailed design process, such as the blocking and stacking of floors, inter-department and inner-department design, will be presented.
  2. Hospital bed capacity planning
    Hospital bed capacity planning has been one of the major challenges for healthcare decision makers. To better understand patient flow, patient pathways were constructed by analyzing data and identifying the patients’ critical path based on their length-of-stay and flow volume. The complex nature of inpatient flow within a hospital was captured in a simulation model, which was then used to study the impact on the hospital capacity with a predicted increase in demand over a finite planning horizon. The results of the simulation were then combined with the analysis of patient pathways to identify the nursing units that would need additional capacity in the future.
  3. Hospital pharmacy staffing model
    There is a national shortage of pharmacists in the nation. Although there are quite a few nursing staffing models mentioned in the literature, to the best of the author’s knowledge, there is no hospital pharmacy staffing model available in the literature or in practice. A pharmacy staffing model incorporating the various workload factors of the pharmacist with an accurate forecasting of pharmacy orders at individual inpatient units has been developed and implemented at a community hospital.
  4. Scheduling low-acuity patient in the emergency department
    Traditionally, Emergency Department (ED) does not operate based on appointments. While most low-acuity patients experience prolonged waiting time before being seen by a physician, mainly due to bed availability, they have some flexibility on their arrival time to the ED. Aiming at creating a balanced system and improving the patients’ experience at the ED, a Bayesian model combining historical trends and real-time information was established to schedule low-acuity patients’ arrivals.

Short Bio:
Shengyong Wang is an Assistant Professor in the Department of Mechanical Engineering at the University of Akron (UA). Prior to joining the faculty of UA, he worked as a Research Assistant Professor in the Department of Systems Science & Industrial Engineering at the State University of New York at Binghamton for three years. He received his Ph.D. in Industrial Engineering from Purdue University in 2006, his M.S. from Singapore-MIT Alliance in 2001, and his B.S. from Beijing University of Aeronautics and Astronautics in 2000. His research focuses on the modeling, decision making, control, and resource allocation of complex systems in a variety of domains, including manufacturing systems, aerospace systems, and healthcare delivery systems. His research has been funded by Summa Health System, Akron General Medical Center, Virtua Health, Lake Health, and Parma Community General Hospital. His publication record includes over 40 archival journal and conference papers. He is a senior member of IIE and ASQ, and a member of IEEE, ASEM, and INFORMS. And he holds a Six Sigma Black Belt certification from ASQ.

POSTED: Tuesday, February 21, 2012 03:33 PM
Updated: Thursday, March 30, 2023 12:22 AM
Computer Science