Case Study: Reducing Waiting Time
One of the few determinants of demand that healthcare managers can control is waiting time. Ample evidence indicates that long waits discourage patients and drive up costs. Acton (1975) estimated that the elasticity of demand with respect to waiting time was â 0.96 in clinics (where waits tended to be long) and â 0.25 in physiciansâ offices (where waits tended to be shorter). This finding suggests that reducing waits by 10 percent could increase volume by 3 to 10 percent. In an environment in which many providers would like to add patients, reducing waits represents a strat-egy worth considering.Christie Clinic in Champaign, Illinois, uses a simple management technique called a huddle to increase efficiency. Each day the staff, including physicians, meets briefly to identify problems and review potential solutions. In less than a year after starting the huddles, waits for appointments decreased by 28 percent, volume rose by 10 percent with no increase in head count (meaning that costs went down), and patient satisfaction rose by 9 percent (Toussaint and Berry 2013). More volume may not be the only benefit of reducing waiting time. Long waits for patients often mean long waits and wasted time for staff as well. Another hospital experienced unacceptable wait times for intravenous pumps in the emergency department. Initially diagnosed as an inadequate number of pumps, the problem turned out to be a poorly defined process for making pumps available. In fact, the hos-pital had more pumps than it needed. It was able to reduce waits for pumps while decreasing its inventory by 20 percent, saving $300,000 in the process. The new process also sharply reduced the amount of time nurses spent looking for pumps, increasing their time with patients (Toussaint and Berry 2013).Both of these examples took place in organizations that were using Lean approaches to performance improvement. Lean emphasizes eliminating steps in production that do not add value for customers and can lead to major gains. The major alternative to Lean is Six Sigma, which can also result in significant improvements. Six Sigma is a structured approach that stresses defining the organizationâs problem from the perspective of internal and external customers, measuring key aspects of performance, analyzing the data, and implementing an improvement plan (McLaughlin and Olson 2012). Organizations that are not using Lean or Six Sigma to become more efficient will find it increasingly hard to compete with organizations that are.
Discussion questions:
⢠Actonâs estimates suggest that demand is more sensitive to waiting time than to out-of-pocket price. Why might that be the case?
⢠For the sake of argument, assume that the entire 10 percent increase in volume at Christie Clinic is due to the 28 percent reduction in waits for appointments. What elasticity of demand with respect to appointment waits do the data for the Christie Clinic imply?
⢠Why would waits for patients result in waits for staff?
Case Study: Reducing Waiting Time
One of the few determinants of demand that healthcare managers can control is waiting time. Ample evidence indicates that long waits discourage patients and drive up costs. Acton (1975) estimated that the elasticity of demand with respect to waiting time was â 0.96 in clinics (where waits tended to be long) and â 0.25 in physiciansâ offices (where waits tended to be shorter). This finding suggests that reducing waits by 10 percent could increase volume by 3 to 10 percent. In an environment in which many providers would like to add patients, reducing waits represents a strat-egy worth considering.Christie Clinic in Champaign, Illinois, uses a simple management technique called a huddle to increase efficiency. Each day the staff, including physicians, meets briefly to identify problems and review potential solutions. In less than a year after starting the huddles, waits for appointments decreased by 28 percent, volume rose by 10 percent with no increase in head count (meaning that costs went down), and patient satisfaction rose by 9 percent (Toussaint and Berry 2013). More volume may not be the only benefit of reducing waiting time. Long waits for patients often mean long waits and wasted time for staff as well. Another hospital experienced unacceptable wait times for intravenous pumps in the emergency department. Initially diagnosed as an inadequate number of pumps, the problem turned out to be a poorly defined process for making pumps available. In fact, the hos-pital had more pumps than it needed. It was able to reduce waits for pumps while decreasing its inventory by 20 percent, saving $300,000 in the process. The new process also sharply reduced the amount of time nurses spent looking for pumps, increasing their time with patients (Toussaint and Berry 2013).Both of these examples took place in organizations that were using Lean approaches to performance improvement. Lean emphasizes eliminating steps in production that do not add value for customers and can lead to major gains. The major alternative to Lean is Six Sigma, which can also result in significant improvements. Six Sigma is a structured approach that stresses defining the organizationâs problem from the perspective of internal and external customers, measuring key aspects of performance, analyzing the data, and implementing an improvement plan (McLaughlin and Olson 2012). Organizations that are not using Lean or Six Sigma to become more efficient will find it increasingly hard to compete with organizations that are.
Discussion questions:
⢠Actonâs estimates suggest that demand is more sensitive to waiting time than to out-of-pocket price. Why might that be the case?
⢠For the sake of argument, assume that the entire 10 percent increase in volume at Christie Clinic is due to the 28 percent reduction in waits for appointments. What elasticity of demand with respect to appointment waits do the data for the Christie Clinic imply?
⢠Why would waits for patients result in waits for staff?
