Article

Business process reengineering at the hospitals: A case study at Singapore hospital

ABSTRACT K KE EY YW WO OR RD DS S B Bu us si in ne es ss s p pr ro oc ce es ss s r re ee en ng gi in ne ee er ri in ng g, , H He ea al lt th hc ca ar re e. . A AB BS ST TR RA AC CT T As health care costs increase, there is a need for healthcare service providers to look for ways to contain costs and to achieve a higher efficiency at their operating facilities without sacrificing quality. This paper studies a case in employing business process reengineering techniques on one aspect of a health care service – surgical work. The system is simulated focusing on the processes that contribute to the effective functioning of an operating theatre. I IN NT TR RO OD DU UC CT TI IO ON N Business process reengineering (BPR) has become increasingly important in recent years. Customers now have the choice of different product and service providers, to provide them with the same core product or service that they want. Over the last fifteen years, companies have been forced to reengineering their business processes to stay competitive because customers are demanding better products and services. Improving and redesigning business processes is paramount for businesses to stay competitive. With the escalating health care costs, healthcare service providers in Singapore are also continuously seeking ways to stay competitive and provide quality service to the customers. Little research has been done on the employment of BPR in healthcare systems. Healthcare industry has traditionally emphasized on breakthroughs in operating procedures and technology in the bid to stay competitive. Healthcare service providers are beginning to understand that BPR initiatives could be a better solution to achieving competitive advantage.

9 Bookmarks
 · 
411 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Discrete-event process simulation, originally the benefactor of the manufacturing sector of the economy, has expanded aggressively into the service sector of the economy, much to the benefit and gratitude of its new cadre of industrial engineers and management strategists. The study documented in this paper originated within a large health-care insurance provider seeking optimal strategies relative to target inventories of pending inquiries concerning insurance policy coverage and concomitant staffing levels of policy analysts. Since several clients of this insurance provider were large companies within the automotive industry, the provider dedicated significant staffing segments to the service of these accounts (hence to the employees of those automotive companies who thereby held insurance coverage). The simulation study worked within this constraint to provide management valuable strategic recommendations. Most specifically, the insurance provider wished to develop a model capable of predicting service levels (average time required to answer specific questions submitted on behalf of two major clients and average inventory level of these questions pending) as a function of number of full-time-equivalent analysts assigned to each of those clients.
    11/2013;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Discrete-event process simulation, originally the benefactor of the manufacturing sector of the economy, has expanded aggressively into the service sector of the economy, much to the benefit and gratitude of its new cadre of industrial engineers and management strategists. The study documented in this paper originated within a large health-care insurance provider seeking optimal strategies relative to target inventories of pending inquiries concerning insurance policy coverage and concomitant staffing levels of policy analysts. Since several clients of this insurance provider were large companies within the automotive industry, the provider dedicated significant staffing segments to the service of these accounts (hence to the employees of those automotive companies who thereby held insurance coverage). The simulation study worked within this constraint to provide management valuable strategic recommendations. Most specifically, the insurance provider wished to develop a model capable of predicting service levels (average time required to answer specific questions submitted on behalf of two major clients and average inventory level of these questions pending) as a function of number of full-time equivalent analysts assigned to each of those clients.
    Proceedings of the 20th European Conference on Modelling and Simulation, Bonn, Germany; 05/2006
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The health care industry in the United States, and in many other countries as well, is undergoing unremitting pressures to improve standards of patient care and service, reduce costs, and increase efficiency. These pressures stem from higher expectations by health-care consumers, increased demands stemming from changing demographics (particularly the “graying” of populations), and more rigorous auditing of expenditures by both private insurers and government. In response, health-care industry practitioners, managers, and administrators are increasingly availing themselves of the analytical techniques, including simulation, provided by the discipline of industrial engineering. In this paper, we document a simulation study undertaken to improve patient service at a dental clinic. The simulation analysis validated innovative ways to improve patient throughput and decrease patient waiting times with zero incremental cost.
    Proceedings of the 21st European Conference on Modelling and Simulation, Prague, Czech Republic; 06/2007

Full-text (2 Sources)

View
648 Downloads
Available from
May 27, 2014