Am J Perinatol 2021; 38(04): 370-376
DOI: 10.1055/s-0039-1697590
Original Article

A Simple Approach to Adjust for Case-Mix When Comparing Institutional Cesarean Birth Rates

James Jeffry Howbert
1   Obstetrical Care Outcomes Assessment Program, Foundation for Health Care Quality, Seattle, Washington
Ellen Kauffman
1   Obstetrical Care Outcomes Assessment Program, Foundation for Health Care Quality, Seattle, Washington
Kristin Sitcov
1   Obstetrical Care Outcomes Assessment Program, Foundation for Health Care Quality, Seattle, Washington
Vivienne Souter
1   Obstetrical Care Outcomes Assessment Program, Foundation for Health Care Quality, Seattle, Washington
› Author Affiliations
Funding The Foundation for the Health Care Quality is a 501(c)(3) nonprofit organization supported by the membership dues from the participants in its programs. There was no other funding for this study.


Objective This study aimed to develop a validated model to predict intrapartum cesarean in nulliparous women and to use it to adjust for case-mix when comparing institutional laboring cesarean birth (CB) rates.

Study Design This multicenter retrospective study used chart-abstracted data on nulliparous, singleton, term births over a 7-year period. Prelabor cesareans were excluded. Logistic regression was used to predict the probability of CB for individual pregnancies. Thirty-five potential predictive variables were evaluated including maternal demographics, prepregnancy health, pregnancy characteristics, and newborn weight and gender. Models were trained on 21,017 births during 2011 to 2015 (training cohort), and accuracy assessed by prediction on 15,045 births during 2016 to 2017 (test cohort).

Results Six variables delivered predictive success equivalent to the full set of 35 variables: maternal weight, height, and age, gestation at birth, medically-indicated induction, and birth weight. Internal validation within the training cohort gave a receiver operator curve with area under the curve (ROC-AUC) of 0.722. External validation using the test cohort gave ROC-AUC of 0.722 (0.713–0.731 confidence interval). When comparing observed and predicted CB rates at 16 institutions in the test cohort, five had significantly lower than predicted rates and three had significantly higher than predicted rates.

Conclusion Six routine clinical variables used to adjust for case-mix can identify outliers when comparing institutional CB rates.

Publication History

Received: 05 February 2019

Accepted: 12 August 2019

Article published online:
04 November 2019

© 2019. Thieme. All rights reserved.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

  • References

  • 1 Kozhimannil KB, Arcaya MC, Subramanian SV. Maternal clinical diagnoses and hospital variation in the risk of cesarean delivery: analyses of a National US Hospital Discharge Database. PLoS Med 2014; 11 (10) e1001745
  • 2 Pasko DN, McGee P, Grobman WA. et al; Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units (MFMU) Network. Variation in the nulliparous, term, singleton, vertex cesarean delivery rate. Obstet Gynecol 2018; 131 (06) 1039-1048
  • 3 Cáceres IA, Arcaya M, Declercq E. et al. Hospital differences in cesarean deliveries in Massachusetts (US) 2004-2006: the case against case-mix artifact. PLoS One 2013; 8 (03) e57817
  • 4 Keeler EB, Park RE, Bell RM, Gifford DS, Keesey J. Adjusting cesarean delivery rates for case mix. Health Serv Res 1997; 32 (04) 511-528
  • 5 Souza JP, Betran AP, Dumont A. et al. A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study. BJOG 2016; 123 (03) 427-436
  • 6 Gibson K, Bailit JL. Cesarean delivery as a marker for obstetric quality. Clin Obstet Gynecol 2015; 58 (02) 211-216
  • 7 American College of Obstetricians and Gynecologists; Society for Maternal-Fetal Medicine. Obstetric care consensus no. 1: safe prevention of the primary cesarean delivery. Obstet Gynecol 2014; 123 (03) 693-711
  • 8 Main EK, Moore D, Farrell B. et al. Is there a useful cesarean birth measure? Assessment of the nulliparous term singleton vertex cesarean birth rate as a tool for obstetric quality improvement. Am J Obstet Gynecol 2006; 194 (06) 1644-1651
  • 9 Kauffman E, Souter VL, Katon JG, Sitcov K. Cervical dilation on admission in term spontaneous labor and maternal and newborn outcomes. Obstet Gynecol 2016; 127 (03) 481-488
  • 10 MATLAB and Statistics Toolbox Release. Natick, MA: The MathWorks, Inc.; 2015. a
  • 11 Hosmer DW, Lemeshow S. Applied Logistic Regression. New York, NY: John Wiley; 1989
  • 12 Value-based payments in obstetrics and gynecology. ACOG Committee Opinion No. 744. American College of Obstetricians and Gynecologists. Obstet Gynecol 2018; 132: e53-e59
  • 13 Fantini MP, Stivanello E, Frammartino B. et al. Risk adjustment for inter-hospital comparison of primary cesarean section rates: need, validity and parsimony. BMC Health Serv Res 2006; 6: 100
  • 14 Smith GC, Dellens M, White IR, Pell JP. Combined logistic and Bayesian modeling of cesarean section risk. Am J Obstet Gynecol 2004; 191 (06) 2029-2034
  • 15 Dimick JB, Osborne NH, Hall BL, Ko CY, Birkmeyer JD. Risk adjustment for comparing hospital quality with surgery: how many variables are needed?. J Am Coll Surg 2010; 210 (04) 503-508
  • 16 Walker KF, Bugg GJ, Macpherson M. et al; 35/39 Trial Group. Randomized trial of labor induction in women 35 years of age or older. N Engl J Med 2016; 374 (09) 813-822
  • 17 Grobman WA, Rice MM, Reddy UM. et al; Eunice Kennedy Shriver National Institute of Child Health and Human Development Maternal–Fetal Medicine Units Network. Labor induction versus expectant management in low-risk nulliparous women. N Engl J Med 2018; 379 (06) 513-523
  • 18 Bailit JL, Love TE. The role of race in cesarean delivery rate case mix adjustment. Am J Obstet Gynecol 2008; 198 (01) 69.e1-69.e5
  • 19 Bailit JL, Schulkin J, Dawson NV. Risk-adjusted cesarean rates: what risk factors for cesarean delivery are important to practicing obstetricians?. J Reprod Med 2007; 52 (03) 194-198
  • 20 Kleinrouweler CE, Cheong-See FM, Collins GS. et al. Prognostic models in obstetrics: available, but far from applicable. Am J Obstet Gynecol 2016; 214 (01) 79-90
  • 21 Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med 2015; 162 (01) 55-63