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Simulation model of the relationship between cesarean section rates and labor duration.

Publication ,  Journal Article
Hicklin, KT; Ivy, JS; Wilson, JR; Cobb Payton, F; Viswanathan, M; Myers, ER
Published in: Health Care Manag Sci
December 2019

Cesarean delivery is the most common major abdominal surgery in many parts of the world, and it accounts for nearly one-third of births in the United States. For a patient who requires a C-section, allowing prolonged labor is not recommended because of the increased risk of infection. However, for a patient who is capable of a successful vaginal delivery, performing an unnecessary C-section can have a substantial adverse impact on the patient's future health. We develop two stochastic simulation models of the delivery process for women in labor; and our objectives are (i) to represent the natural progression of labor and thereby gain insights concerning the duration of labor as it depends on the dilation state for induced, augmented, and spontaneous labors; and (ii) to evaluate the Friedman curve and other labor-progression rules, including their impact on the C-section rate and on the rates of maternal and fetal complications. To use a shifted lognormal distribution for modeling the duration of labor in each dilation state and for each type of labor, we formulate a percentile-matching procedure that requires three estimated quantiles of each distribution as reported in the literature. Based on results generated by both simulation models, we concluded that for singleton births by nulliparous women with no prior complications, labor duration longer than two hours (i.e., the time limit for labor arrest based on the Friedman curve) should be allowed in each dilation state; furthermore, the allowed labor duration should be a function of dilation state.

Duke Scholars

Published In

Health Care Manag Sci

DOI

EISSN

1572-9389

Publication Date

December 2019

Volume

22

Issue

4

Start / End Page

635 / 657

Location

Netherlands

Related Subject Headings

  • United States
  • Time Factors
  • Stochastic Processes
  • Pregnancy
  • Labor, Obstetric
  • Humans
  • Health Policy & Services
  • Female
  • Decision Trees
  • Computer Simulation
 

Citation

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ICMJE
MLA
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Hicklin, K. T., Ivy, J. S., Wilson, J. R., Cobb Payton, F., Viswanathan, M., & Myers, E. R. (2019). Simulation model of the relationship between cesarean section rates and labor duration. Health Care Manag Sci, 22(4), 635–657. https://doi.org/10.1007/s10729-018-9449-3
Hicklin, Karen T., Julie S. Ivy, James R. Wilson, Fay Cobb Payton, Meera Viswanathan, and Evan R. Myers. “Simulation model of the relationship between cesarean section rates and labor duration.Health Care Manag Sci 22, no. 4 (December 2019): 635–57. https://doi.org/10.1007/s10729-018-9449-3.
Hicklin KT, Ivy JS, Wilson JR, Cobb Payton F, Viswanathan M, Myers ER. Simulation model of the relationship between cesarean section rates and labor duration. Health Care Manag Sci. 2019 Dec;22(4):635–57.
Hicklin, Karen T., et al. “Simulation model of the relationship between cesarean section rates and labor duration.Health Care Manag Sci, vol. 22, no. 4, Dec. 2019, pp. 635–57. Pubmed, doi:10.1007/s10729-018-9449-3.
Hicklin KT, Ivy JS, Wilson JR, Cobb Payton F, Viswanathan M, Myers ER. Simulation model of the relationship between cesarean section rates and labor duration. Health Care Manag Sci. 2019 Dec;22(4):635–657.
Journal cover image

Published In

Health Care Manag Sci

DOI

EISSN

1572-9389

Publication Date

December 2019

Volume

22

Issue

4

Start / End Page

635 / 657

Location

Netherlands

Related Subject Headings

  • United States
  • Time Factors
  • Stochastic Processes
  • Pregnancy
  • Labor, Obstetric
  • Humans
  • Health Policy & Services
  • Female
  • Decision Trees
  • Computer Simulation