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Berry Jaeker, Jillian Alexandra

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Berry Jaeker

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Jillian Alexandra

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Berry Jaeker, Jillian Alexandra

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    Increased Speed Equals Increased Wait: The Impact of a Reduction in Emergency Department Ultrasound Order Processing Time
    (2014-01-27) Berry Jaeker, Jillian Alexandra; Tucker, Anita Lynn; Lee, Michael H.
    We exploit an exogenous process change at two emergency departments (EDs) within a health system to test the theory that increasing capacity in a discretionary work setting increases wait times due to additional services being provided to customers as a consequence of reduced marginal costs for a task. We find that an increase in physician’s capacity for ordering ultrasounds (U/S) resulted in an 11.5 percentage point increase in the probability of an U/S being ordered, confirming that resource availability induces demand. Furthermore, we find that the additional U/S demand increased the time to return other radiological tests due to the higher demand placed on radiologists from the additional U/S. Consequently, the average length of stay (LOS) for patients with an abdominal complaint increased by nearly 30 minutes, and the waiting time to enter the ED increased by 26 minutes. We do not find any indications of improved performance on clinical metrics, with no statistical change in the number of admissions to the hospital or readmissions to the ED within 72 hours. Our study highlights an important lesson for process improvement in interdependent service settings: increasing process capacity at one step in the process can increase demand at that step, as well as for a subsequent shared service, and both can result in an overall negative impact on performance.
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    Hurry Up and Wait: Differential Impacts of Congestion, Bottleneck Pressure, and Predictability on Patient Length of Stay
    (2012-12-06) Berry Jaeker, Jillian Alexandra; Tucker, Anita Lynn
    High work load, from high inventory levels, impacts unit processing times, but prior operations management studies have found conflicting results regarding direction. Thus, it is difficult to predict inventory’s effects on productivity a priori, inhibiting effective capacity management in high load systems. We categorize load into in-process inventory (congestion) and incoming inventory, decomposing the latter into its levels of bottleneck (BN) pressure and predictability, and quantify the magnitudes and directions of change on processing times. Using data from 283 hospitals, we find (1) high congestion increases a patient’s hospital stay up to 28%, indicating inefficiencies from overloaded resources; (2) a patient stays up to 11.7% longer if there is a high load of incoming low BN pressure patients, consistent with the slowdown associated with “social loafing”; (3) a patient’s stay is up to 10.2% shorter when there is a high incoming load of predictable patients, consistent with workload smoothing.