Development and validation of software tool for using original Robson ten group classification system for analysing caesarean section rates:  a step towards minimizing errors from a large volume centre in a resource country

Gayathri Sreekumar; Sasirekha Rengaraj; Uma Vijayasundaram; Aman Kumar; Saiful Islam Tapadar; Prasad Indrajit Satyendra; Srujan Sarathi Samal

doi:10.18203/2320-1770.ijrcog20241437

Authors

Gayathri Sreekumar Department of Obstetrics and Gynaecology, JIPMER, Puducherry, India
Sasirekha Rengaraj Department of Obstetrics and Gynaecology, JIPMER, Puducherry, India https://orcid.org/0000-0002-6440-2039
Uma Vijayasundaram Department of Computer Science, Pondicherry University, Puducherry, India
Aman Kumar Department of Computer Science, Pondicherry University, Puducherry, India
Saiful Islam Tapadar Department of Computer Science, Pondicherry University, Puducherry, India
Prasad Indrajit Satyendra Department of Computer Science, Pondicherry University, Puducherry, India
Srujan Sarathi Samal Department of Computer Science, Pondicherry University, Puducherry, India

DOI:

https://doi.org/10.18203/2320-1770.ijrcog20241437

Keywords:

RTGCS, Robson classification, CS, Caesarean audit, Application, App

Abstract

Background: To develop and validate a software tool for classifying caesarean sections (CS) using original Robson ten group (RTG) system of classification and to compare it with manual entry period using excel sheet.

Methods: The study was conducted in a tertiary care centre to include the data of all women delivered between July 1^st 2023 and September 30^th 2023. Two months retrospective data was collected for developing the App and it was validated by comparing its accuracy with that of three health care workers. The App was developed to enable classification using a logic-driven if-else condition structure. It was tested in real time for a month period.

Result: A total of 227 deliveries were collected for development of App and it was found to have maximum agreement with that of the gold standard with Kappa score 1, whereas the maximum accuracy of the health workers was 0.933 Kappa score with respect to gold standard. The App was tested in real time and compared with the data entered manually. The misclassification and missing data were nil which used to be 15-20% in groups 2, 10 and 9 when the data were entered manually.

Conclusions: This App was found to be helpful in saving time and minimize human errors in large institutions. It provided accurate data on RTG classification and it ensured all the details for classifying CS are entered. It helps to audit CS systematically.

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References

Harrison MS, Garces AL, Goudar SS, Saleem S, Moore JL, Esamai F, et al. Cesarean birth in the Global Network for Women's and Children's Health Research: trends in utilization, risk factors, and subgroups with high cesarean birth rates. Reprod Health. 2020;17(3):165.

Betran AP, Torloni MR, Zhang JJ, Gülmezoglu AM, WHO Working Group on Caesarean Section. WHO Statement on Caesarean Section Rates. BJOG. 2016;123(5):667-70.

Betrán AP, Ye J, Moller AB, Zhang J, Gülmezoglu AM, Torloni MR. The Increasing Trend in Caesarean Section Rates: Global, Regional and National Estimates: 1990-2014. PLoS One. 2016;11(2):e0148343.

Tontus HO, Nebioglu S. Improving the Caesarean Decision by Robson Classification: A Population-Based Study by 5,323,500 Livebirth Data. Ann Glob Health. 2020;17;86(1):101.

Vogel JP, Betrán AP, Vindevoghel N, Souza JP, Torloni MR, Zhang J, et al. Use of the Robson classification to assess caesarean section trends in 21 countries: a secondary analysis of two WHO multicountry surveys. Lancet Glob Health. 2015;3(5):e260-70.

Abdulrahman M, Abdullah SS, Alaani AFK, AlAbdool NH, Sherif FEY, Ahmed ZS, et al. Exploring Obstetrical Interventions and Stratified Cesarean Section Rates Using the Robson Classification in Tertiary Care Hospitals in the United Arab Emirates. Rev Bras Ginecol Obstet. 2019;41(3):147-54.

Homer CS, Kurinczuk JJ, Spark P, Brocklehurst P, Knight M. A novel use of a classification system to audit severe maternal morbidity. Midwifery. 2010;26(5):532-6.

Robson M, Murphy M, Byrne F. Quality assurance: The 10 Group Classification System (Robson’s Classification), induction of labor, and Caesarean delivery Int J Gynecol and Obstet. 2015;131(1):23-7.

Betrán AP, Gulmezoglu AM, Robson M, Merialdi M, Souza JP, Wojdyla D, et al. WHO global survey on maternal and perinatal health in Latin America: classifying caesarean sections. Reprod Health. 2009;29;6:18.

Nimmolrat A, Sutham K, Thinnukool O. Patient triage system for supporting the operation of dispatch centres and rescue teams. BMC Med Inform Decis Mak. 2021;68:1-16.

Vogel JP, Betrán AP, Vindevoghel N, Souza JP, Torloni MR, Zhang J, et al. WHO Multi-Country Survey on Maternal and Newborn Health Research Network. Use of the Robson classification to assess caesarean section trends in 21 countries: a secondary analysis of two WHO multicountry surveys. Lancet Glob Health. 2015;3(5):e260-70.