Optimizing appointment template and number of staff of an OB/GYN clinic--micro and macro simulation analyses.

BACKGROUND: The Department of Obstetrics and Gynecology (OB/GYN) at the University of Arkansas for Medical Sciences (UAMS) tested various, new system-restructuring ideas such as varying number of different types of nurses to reduce patient wait times for its outpatient clinic, often with little or no effect on waiting time. Witnessing little progress despite these time-intensive interventions, we sought an alternative way to intervene the clinic without affecting the normal clinic operations. AIM: The aim is to identify the optimal (1) time duration between appointments and (2) number of nurses to reduce wait time of patients in the clinic. METHODS: We developed a discrete-event computer simulation model for the OB/GYN clinic. By using the patient tracker (PT) data, appropriate probability distributions of service times of staff were fitted to model different variability in staff service times. These distributions were used to fine-tune the simulation model. We then validated the model by comparing the simulated wait times with the actual wait times calculated from the PT data. The validated model was then used to carry out "what-if" analyses. RESULTS: The best scenario yielded 16 min between morning appointments, 19 min between afternoon appointments, and addition of one medical assistant. Besides removing all peak wait times and bottlenecks around noon and late in the afternoon, the best scenario yielded 39.84 % (p<.001), 30.31 % (p<.001), and 15.12 % (p<.001) improvement in patients' average wait times for providers in the exam rooms, average total wait time at various locations and average total spent time in the clinic, respectively. This is achieved without any compromise in the utilization of the staff and in serving all patients by 5 pm. CONCLUSIONS: A discrete-event simulation model is developed, validated, and used to carry out "what-if" scenarios to identify the optimal time between appointments and number of nurses. Using the model, we achieved a significant improvement in wait time of patients in the clinic, which the clinic management initially had difficulty achieving through manual interventions. The model provides a tool for the clinic management to test new ideas to improve the performance of other UAMS OB/GYN clinics.

Effects of regional brain injury on the newborn autonomic nervous system.

OBJECTIVE: Cerebral mapping of central autonomic nervous system (ANS)(1) function in mature animals and humans lateralizes sympathetic and parasympathetic influence predominantly to the right and left cerebral hemispheres, respectively. Spectral analysis of heart rate variability (HRV)(2) is an established measure of ANS function. We examined whether such lateralization is present in the term newborn. METHODS: We retrospectively reviewed records of infants >36 weeks of gestation diagnosed with hypoxic ischemic encephalopathy (HIE).(3) We included infants with neonatal EEG and regional injury on brain MRI, which was scored using a schema. We extracted ECG signals from the EEG recording, but excluded periods of electrographic seizure activity to eliminate possible seizure influence on HRV. HRV was evaluated by spectral analysis in the high frequency (HF(4); 0.3-1 Hz) and low frequency (LF(5); 0.05-0.25 Hz) ranges, and the LF/HF ratio was examined to assess sympatho-vagal balance. The relation between the injured brain regions and HRV was studied using multiple linear regression models. RESULTS: We studied 40 neonates with HIE. Injury to the right cerebral cortex (p=0.009) and right cerebellum (p=0.041) predicted a decreased LF/HF ratio. Injury to the left cerebral cortex (p=0.035) and left cerebellum (p=0.041) was associated with an increased LF/HF ratio. The association between brain injury location and the individual LF or HF spectral powers of brain injury did not reach significance. CONCLUSIONS: Our data suggest that a functional lateralization for cerebral autonomic influence is established by term gestation.