scholarly journals Capacity and patient flow planning in post-term pregnancy outpatient clinics: a computer simulation modelling study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Joe Viana ◽  
Tone Breines Simonsen ◽  
Hildegunn E. Faraas ◽  
Nina Schmidt ◽  
Fredrik A. Dahl ◽  
...  
Keyword(s):  
Computer Simulation ◽  
Patient Flow ◽  
Simulation Modelling ◽  
Outpatient Clinics ◽  
Term Pregnancy ◽  
Post Term Pregnancy ◽  
Modelling Study

scholarly journals Capacity and patient flow planning in post-term pregnancy outpatient clinics: a computer simulation modelling study

2019 ◽  
Author(s):  
Joe Viana ◽  
Tone B Simonsen ◽  
Hildegunn E Faraas ◽  
Nina Schmidt ◽  
Fredrik A Dahl ◽  
...  
Keyword(s):  
Simulation Model ◽  
Outpatient Clinic ◽  
Patient Flow ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Base Case ◽  
Term Pregnancy ◽  
Full Factorial Experimental Design ◽  
Arrival Pattern ◽  
Post Term Pregnancy

Abstract Background The demand for a large Norwegian hospital’s post-term pregnancy outpatient clinic has increased substantially over the last 10 years due to changes in the hospital’s catchment area and to clinical guidelines. Planning the clinic is further complicated due to the high did not attend rates as a result of women giving birth. The aim of this study is to determine the maximum number of women specified clinic configurations, combination of specified clinic resources, can feasibly serve within clinic opening times. Methods A hybrid agent based discrete event simulation model of the clinic was used to evaluate alternative configurations to gain insight into clinic planning and to support decision making. Clinic configurations consisted of six factors: X0: Arrivals. X1: Arrival pattern. X2: Order of midwife and doctor consultations. X3: Number of midwives. X4: Number of doctors. X5: Number of cardiotocography (CTGs) machines. A full factorial experimental design of the six factors generated 608 configurations.Results Each configuration was evaluated using the following measures: Y1: Arrivals. Y2: Time last woman checks out. Y3: Women’s length of stay (LoS). Y4: Clinic overrun time. Y5: Midwife waiting time (WT). Y6: Doctor WT. Y7: CTG connection WT. Optimisation was used to maximise X0 with respect to the 32 combinations of X1-X5. Configuration 0a, the base case Y1 = 7 women and Y3 = 102.97 [0.21] mins. Changing the arrival pattern (X1) and the order of the midwife and doctor consultations (X2) configuration 0d, where X3, X4, X5 = 0a, Y1 = 8 woman and Y3 86.06 [0.10] mins.Conclusions The simulation model identified the availability of CTG machines as a bottleneck in the clinic, indicated by the WT for CTG connection effect on LoS. One additional CTG machine improved clinic performance to the same degree as an extra midwife and an extra doctor. The simulation model demonstrated significant reductions to LoS can be achieved without additional resources, by changing the clinic pathway and scheduling of appointments. A more general finding is that a simulation model can be used to identify bottlenecks, and efficient ways of restructuring an outpatient clinic.

scholarly journals Capacity and patient flow planning in post-term pregnancy outpatient clinics: a computer simulation modelling study

2019 ◽  
Author(s):  
Joe Viana ◽  
Tone B Simonsen ◽  
Hildegunn E Faraas ◽  
Nina Schmidt ◽  
Fredrik A Dahl ◽  
...  
Keyword(s):  
Simulation Model ◽  
Outpatient Clinic ◽  
Clinical Guidelines ◽  
Catchment Area ◽  
Patient Flow ◽  
Base Case ◽  
Term Pregnancy ◽  
Clinic Management ◽  
Arrival Pattern ◽  
Post Term Pregnancy

Abstract Background The demand for a large Norwegian hospital’s post-term pregnancy outpatient clinic has increased substantially over the last 10 years due to changes in the hospital’s catchment area and to clinical guidelines. Planning the clinic is further complicated due to the high did not attend rates as a result of women giving birth. The aim of this study was to develop a tool that supports clinic management to better understand and improve capacity and patient flow planning.Methods A hybrid agent based discrete event simulation model of the clinic was used to evaluate alternative configurations to gain insight into clinic planning and to support decision making. Clinic configurations consisted of six factors: X0: Arrivals. X1: Arrival pattern. X2: Order of midwife and doctor consultations. X3: Number of midwives. X4: Number of doctors. X5: Number of cardiotocography (CTGs) machines. A full factorial experimental design of the six factors generated 608 configurations.Results Each configuration was evaluated using the following measures: Y1: Arrivals. Y2: Time last woman checks out. Y3: Women’s length of stay (LoS). Y4: Clinic overrun time. Y5: Midwife waiting time (WT). Y6: Doctor WT. Y7: CTG connection WT. Optimisation was used to maximise X0 with respect to the 32 combinations of X1-X5. Configuration 0a, the base case Y1 = 7 women and Y3 = 102.97 [0.21] mins. Changing the arrival pattern (X1) and the order of the midwife and doctor consultations (X2) configuration 0d, where X3, X4, X5 = 0a, Y1 = 8 woman and Y3 86.06 [0.10] mins.Conclusions From the clinic’s perspective, the changes in catchment area and clinical guidelines led to increased demand. The simulation model demonstrated flexible pathways in the order of midwife/doctor and appointment scheduling increases flow substantially, reducing LoS. Equipment appeared more of a bottleneck than personnel, as one additional CTG machine has the same effect as an extra midwife and an extra doctor, and the WT for CTG connection is a key contributor to LoS. A more general finding is that a simulation model can be used to identify bottlenecks, and efficient ways of restructuring an outpatient clinic.

scholarly journals Patient flow within UK emergency departments: a systematic review of the use of computer simulation modelling methods

BMJ Open ◽  
2017 ◽  
Vol 7 (5) ◽  
pp. e015007 ◽  
Author(s):  
Syed Mohiuddin ◽  
John Busby ◽  
Jelena Savović ◽  
Alison Richards ◽  
Kate Northstone ◽  
...  
Keyword(s):  
Systematic Review ◽  
Computer Simulation ◽  
Emergency Departments ◽  
Patient Flow ◽  
Simulation Modelling ◽  
Modelling Methods

Case report of umbilical vein thrombosis

2019 ◽  
Author(s):  
V.M. Bolotskih, E.R. Semenova
Keyword(s):  
Case Report ◽  
Ultrasound Examination ◽  
Umbilical Vein ◽  
Term Pregnancy ◽  
Vein Thrombosis ◽  
Gestation Age ◽  
Post Term Pregnancy

A case of umbilical vein thrombosis is presented. Thrombotic masses were detected inside umbilical vein during ultrasound examination on the gestation age 40 weeks and 4 days. Such serious complication probably caused by decompensation of chronic placenta insufficiency in post-term pregnancy. In result reduce blood speed and forming thrombus inside umbilical vein

270: Ultrasonic alteration of the estimated date of delivery increases caesarean delivery rates among induced labors for post term pregnancy

2008 ◽  
Vol 199 (6) ◽  
pp. S87
Author(s):  
Rhona Mahony ◽  
Erina Sasaki ◽  
Tilottama Nandy ◽  
Fionnuala MCauliffe ◽  
Colm O'Herlihy ◽  
...  
Keyword(s):  
Caesarean Delivery ◽  
Term Pregnancy ◽  
Post Term Pregnancy

Accuracy of Computer Simulation to Predict Patient Flow during Mass-Casualty Incidents

2008 ◽  
Vol 23 (4) ◽  
pp. 354-360 ◽  
Author(s):  
Jeffrey M. Franc-Law ◽  
Micheal J. Bullard ◽  
F. Della Corte
Keyword(s):  
Emergency Department ◽  
Computer Simulation ◽  
Patient Care ◽  
Patient Flow ◽  
Emergency Department Patient ◽  
Simulation Software ◽  
Simulated Patients ◽  
Disaster Plan ◽  
Data Set ◽  
Patient Database

AbstractIntroduction:Although most hospitals have an emergency department disas- ter plan, most never have been implemented in a true disaster or been tested objectively. Computer simulation may be a useful tool to predict emergency department patient flow during a disaster.Purpose:The aim of this study was to compare the accuracy of a computer simulation in predicting emergency department patient flow during a masscasualty incident with that of a real-time, virtual, live exercise.Methods:History, physical examination findings, and laboratory results for 136 simulated patients were extracted from the disastermed.ca patient database as used as input into a computer simulation designed to represent the emergency department at the University of Alberta Hospital.The computer simulation was developed using a commercially available simulation software platform (2005, SimProcess, CACI Products, San Diego CA). Patient flow parameters were compared to a previous virtual, live exercise using the same data set.Results:Although results between the computer simulation and the live exercise appear similar, they differ statistically with respect to many patient benchmarks. There was a marked difference between the triage codes assigned during the live exercise and those from the patient database; however, this alone did not account for the differences between the patient groups. It is likely that novel approaches to patient care developed by the live exercise group, which are difficult to model by computer software, contributed to differences between the groups. Computer simulation was useful, however, in predicting how small changes to emergency department structure, such as adding staff or patient care areas, can influence patient flow.Conclusions:Computer simulation is helpful in defining the effects of changes to a hospital disaster plan. However, it cannot fully replace participant exercises. Rather, computer simulation and live exercises are complementary, and both may be useful for disaster plan evaluation.

Low 3rd trimester haemoglobin level and the risk of post-term pregnancy

2012 ◽  
Vol 33 (1) ◽  
pp. 46-49 ◽  
Author(s):  
J. Liu ◽  
J. Wang ◽  
R. Ye ◽  
J. Liu ◽  
X. Zheng ◽  
...  
Keyword(s):  
Haemoglobin Level ◽  
Term Pregnancy ◽  
Post Term Pregnancy
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