Evaluation of caesarean rates according to Robson classification using a newly developed smart phone application in a tertiary centre in Sri Lanka: Comparative study

doi:10.21203/rs.3.rs-4843569/v1

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Research Article

Evaluation of caesarean rates according to Robson classification using a newly developed smart phone application in a tertiary centre in Sri Lanka: Comparative study

https://doi.org/10.21203/rs.3.rs-4843569/v1

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Objective

Caesarean section (CS) rates are increasing in Sri Lanka. More than half of births will occur through CS by 2025. CS should be medically indicated to reduce maternal morbidity. Robson classification is useful in assessing the indications for CS. It is difficult to obtain high-quality prospective data using traditional data collection methods. We intend to assess the use of new technology for this purpose.

Methods

We used the RobsApp® which is a newly developed smart phone application from April to October 2019 at the professorial unit De Soysa Hospital for Women (DSHW) for prospective data collection and analysis of 1712 deliveries according to Robson classification. This data is compared with Robson standards and previous traditional data collection methods.

Results

The quality of data gathered matched the recommendations by Robson guidance. The overall CS rate was 33.0%. The majority of the CS were carried out for Robson category 5a. Breech presentation accounted for 11.6% of CSs. Emergency CS contributed to 49.6% with CTG abnormalities being the most frequent indication.

Conclusions

RobsApp® is a convenient method for prospective data collection which allows achievement of the data quality recommended by the Robson guidance. The CS rates are rising in professorial unit DSHW. Increasingly CS are being performed for reasons other than for past sections.

Robson classification

Sri Lanka

Caesarean section

Smart phone application

In recent years, there has been a concerning surge in the rates of caesarean section (CS) deliveries worldwide, including in Sri Lanka, where the prevalence has notably increased from 32.1% in 2014 to 40.8% in 2018, as documented by the national database.(1) There is a large heterogenicity in reported CS rates in different institutions in Sri Lanka ranging from 23.6–44.2%.(2–4) When statistical modelling is used it is forecasted that more than 50% of babies will be borne through CS by the year 2025.(5)

Establishing an CS rate poses a challenge, yet the international healthcare community, as far back as 1985, suggested a range between 10% and 15% as optimal.(6) Research indicates that exceeding this range, as seen in rising trends globally, has not shown to have any impact on maternal or perinatal outcomes.(7) Conversely, in fact, CS carried out without medical reasons may significantly increase maternal mortality and morbidity.(7) Hence, it is imperative that CS interventions are reserved solely for medically appropriate indications.

Understanding the reasons for CS are important in confirming the medical need and in reducing unnecessary CS. To identify reasons, accurate data collection plays a crucial role. It is recommended to have continuous data collection, processing and interpretation.(8) However, this is difficult to implement at most institutions and is therefore often neglected.(9)

In 2011 the World Health Organization (WHO) conducted a systematic review which concluded that, among the 27 different systems identified to classify CS, women-based classifications, and the 10-Groups Robson classification were the best classifications which will fulfill the current needs.(10) The Robson classification is identified as a simple, robust, reproducible,clinically relevant categorization and a prospective system that increases the quality of the data collected.(11) Therefore, even before the official endorsements by international institutions or formal guidelines, WHO recommended its use in 2015.(12) The categories in Robson classification are shown in Table 1.

Table 1

– Robson 10 group classification with subclassifications
Robson classification group number	Characteristics of the group
1	Nulliparous women with single cephalic pregnancy, ≥ 37 weeks gestation in spontaneous labour
2	Nulliparous women with a single cephalic pregnancy, ≥ 37 weeks gestation who had labour induced or were delivered by CS before labour
2a	Labour induced
2b	Pre-labour CS
3	Multiparous women without a previous CS, with a single cephalic pregnancy, ≥ 37 weeks gestation in spontaneous labour
4	Multiparous women without a previous CS, with a single cephalic pregnancy, ≥ 37 weeks gestation who had labour induced or were delivered by CS before labour
4a	Labour induced
4b	Pre-labour CS
5	All multiparous women with at least one previous CS, with a single cephalic pregnancy, ≥ 37 weeks gestation
5a	With one previous CS
5b	With two or more previous CSs
6	All nulliparous women with a single breech pregnancy
7	All multiparous women with a single breech pregnancy including women with previous CS(s)
8	All women with multiple pregnancies including women with previous CS(s)
9	All women with a single pregnancy with a transverse or oblique lie, including women with previous CS(s)
10	All women with a single cephalic pregnancy < 37 weeks gestation, including women with previous CS(s)

In navigating the complexities of the Robson classification system, challenges like missing data, misclassification of women, and the absence of clear definitions for core variables have emerged as significant hurdles in its implementation and efficacy.(12) Thus, the integrity of this classification hinges greatly on meticulous data collection practices.. Traditional paper-based methods, with their inefficiencies and susceptibility to errors, fall short in capturing the entirety of childbirth data within a unit. Embracing modern technologies becomes imperative to enhance data integrity and streamline processes.

Hence, we embarked on a pioneering journey to develop and deploy a smartphone application tailored for data collection and analysis. Notably, no such tools have been described for Robson classification to date. In addition to rectify the drawbacks in traditional data collection and analysis, we describe the use of this application in continuous prospective data collection, to pinpoint areas for improvement in reducing CS rates within the confines of a tertiary referral obstetrics unit in Colombo, Sri Lanka.

Study was conducted at the University unit (ward 3 and 15), De Soysa Hospital for Women (DSHW). from 20^th of April 2019 to 20^th of October 2019. All women giving birth during the study period were included in the study.

RobsAppÒ was used for prospective data collection. RobsAppÒ is a smartphone based webapp designed to run on any device thus ensuring the principles of BYOD (Bring Your Own Device) computer usability principle. Application comprises of only a single page and the functionality is limited to two events; namely data saving and data analysis. The application was validated for the use of data collection for Robson classification.(13)

MBBS graduates were trained to use the RobsAppÒ. The 30-minute training included the access to the RobsAppÒ with a URL and data definitions of the given text fields. All definitions are mentioned in the home page of the application for the operator to refresh memory if in doubt. Following the training, data collection was carried out prospectively looking at patient records at the end of the events of birth. The data collector was able to contact the patient’s attending consultant for any clarifications if needed.

RobsAppÒ is hosted at Siteground servers which are highly customized and based on a Google Cloud infrastructure. The backend software stack is optimized for speed, security and scalability. The developer of the RobsAppÒ has been with the Siteground servers for last 10 years and no security issues were experienced so far. Although the smart phone is used as an appliance for data collection no data is saved in the users' phones. The collected data are saved in a MySql database server at the siteground.com. (version: 5.6.36-82.1-log - Percona Server (GPL), Release 82.1, Revision 1a00d79 on PHP version: 5.6.30). This file was queried using the SQL language and the data outputs are given in the results.

The data gathered from the RobsAppÒ was compared with Robson guidance and MCH and DSHW 2017 results which were done with traditional data collection methods.

Ethical approval for the study was taken from Ethical Review Committee, Faculty of Medicine, University of Colombo on 21/03/2019 (Ref – EC-19-024).

Table 1 – Robson 10 group classification with subclassifications

Robson classification group number	Characteristics of the group
1	Nulliparous women with single cephalic pregnancy, ³ 37 weeks gestation in spontaneous labour
2	Nulliparous women with a single cephalic pregnancy, ≥37 weeks gestation who had labour induced or were delivered by CS before labour
2a	Labour induced
2b	Pre-labour CS
3	Multiparous women without a previous CS, with a single cephalic pregnancy, ≥37 weeks gestation in spontaneous labour
4	Multiparous women without a previous CS, with a single cephalic pregnancy, ≥37 weeks gestation who had labour induced or were delivered by CS before labour
4a	Labour induced
4b	Pre-labour CS
5	All multiparous women with at least one previous CS, with a single cephalic pregnancy, ≥37 weeks gestation
5a	With one previous CS
5b	With two or more previous CSs
6	All nulliparous women with a single breech pregnancy
7	All multiparous women with a single breech pregnancy including women with previous CS(s)
8	All women with multiple pregnancies including women with previous CS(s)
9	All women with a single pregnancy with a transverse or oblique lie, including women with previous CS(s)
10	All women with a single cephalic pregnancy < 37 weeks gestation, including women with previous CS(s)

Total study sample consisted of 1712 patients. Overall, CS rate of the university unit of DSHW in Sri Lanka during the study period was 33%. Instrument delivery rate was 3%. 49.6% of all the caesarean sections were emergency caesarean sections.

Highest number of deliveries occurred in the Robson group 1. 20.2% of CS were carried out for Robson category 5a which is multiparous women with at least one previous caesarean section ≥ 37 weeks. Lowest was category 9 with the second lowest which was 4.6% of all CS were seen in category 4. Table 2 represents the data distribution by the Robson category.

Table 2

– Representation of the data set according to Robson guideline
Robson group	Number of CS in group	Number of women in group	Group size^a (%)	Group caesarean section rate^b (%)	Absolute group contribution to overall CS rate^c (%)	Relative contribution of group to overall CS rate^d (%)
1	82	468	27.3	17.5	4.8	14.5
2a	59	184	10.7	32.1	3.4	10.4
2b	37	41	2.4	90.2	2.1	6.5
3	40	431	25.2	9.3	2.3	7.1
4a	24	138	8.1	17.4	1.4	4.2
4b	2	2	0.1	100	0.1	0.4
5a	114	155	9.1	73.5	6.7	20.2
5b	39	42	2.5	92.9	2.3	6.9
6	37	39	2.3	94.9	2.2	6.5
7	29	34	2.0	85.3	1.7	5.1
8	24	33	1.9	72.7	1.4	4.2
9	5	5	0.3	100	0.3	0.9
10	73	140	8.2	52.1	4.3	12.9
Total	565	1712	100	NA	33.0	100.0
^a Group size (%) = n of women in the group / total N women delivered in the hospital x 100
^b Group CS rate (%) = n of CS in the group / total N of women in the group x 100
^c Absolute contribution (%) = n of CS in the group / total N of women delivered in the hospital x 100
^d Relative contribution (%) = n of CS in the group / total N of CS in the hospital x 100

CTG abnormalities was the highest contributor to the emergency CS. Different indications for emergency CS are shown in Table 3.

Table 3

Indication for emergency caesarean sections
Indications for emergency CS	Frequency	Percentage
Failure to progress in spontaneous labour	40	14.2
Failure to progress in induced labour	44	15.7
2nd stage CS	13	4.6
CTG abnormalities	90	32.1
PET or medical complications	40	14.3
Meconium-stained liquor	24	8.6
Fetal growth restriction (severe)	6	2.1
Labour emergency	14	5.0
Failed trial of labour after caesarean section (TOLAC)	15	5.4
Total	280	100.0

Current study has managed to achieve the recommended data quality as suggested by the Robson manual (Table 4). Table 5 summarizes the study population in our study in comparison to other studies using the Robson classification. Table 6 illustrates the steps of assessing caesarean section rates according to Robson guidance comparing it with WHO multi country survey (MCS) and DSHW study in 2017.

Table 4

– Assessing the quality of the data set according to Robson manual and comparison with other studies
Steps to assess quality	Robson interpretation	MCS population	DSHW 2017	Our study
Total numbers of CS and of women delivered in your hospital		NA	Total CS = 2251 Total deliveries = 7504 Matches with the total numbers	Total CS = 565 Total deliveries = 1712 Matches with the total numbers
Size of the group 9	It should be < 1%	0.4%	0.9%	0.3%
Caesarean section rate in group 9	Should be 100%	88.6%	78.3%	100%

Table 5

– Assessing the type of study population in comparison to Robson guideline and other studies. (Discrepancies from the Robson guidance are highlighted)
Step	Robson guideline^a	MCS reference population^b	DSHW 2017^c	Our findings
Size of group 1 + 2	This usually represents 35–42% of obstetric population of most hospitals.	38.1%	38.1%	40.5%
Size of groups 3 + 4	This usually represents about 30% of women.	46.5%	37.3%	33.4%
Size of group 5		7.2%	10.9%	11.5%
Size of groups 6 + 7	3–4%	2.7%	3.4%	4.3%
Size of group 8	1.5–2%	0.9%	1.1%	1.9%
Size of group 10	< 5%	4.2%	7.8%	8.2%
Ratio of the size of group 1 versus group 2	Ratio 2 or higher	Ratio 3.3	Ratio 1.5	Ratio 2.1
Ratio of size of group 3 versus group 4	Ratio more than 2	Ratio 6.3	Ratio 2.6	Ratio 3.1
Ratio of size of group 6 versus group 7	Ratio usually 2	Ratio 0.8	Ratio 1.2	Ratio 1.1

Table 6

Steps to assess CS rates according to Robson guidance. Findings are compared with MCS reference population and DSHW 2017 study. (Findings beyond the Robson guidance are highlighted)
Step	Robson guidance^a	MCS reference population^b	DSHW 2017^c	Our study
CS rate for group 1	Rates under 10% are achievable	9.8%	18.0%	17.5%
CS rate for group 2	Consistently around 20–35%	39.9%	41.0%	42.7%
CS rate in group 3	Normally no higher than 3%	3%	5.2%	9.3%
CS rate in group 4	Rarely should be higher than 15%	23.7%	16.8%	18.6%
CS rate in group 5	Rates of 50–60% are considered appropriate provided you have good maternal and perinatal outcome	74.4%	81.8%	77.7%
CS rate in group 8	Usually around 60%	57.7%	80.9%	72.7%
CS rate in group 10	In most populations usually around 30%	25.1%	41.1%	52.1%
contribution of Groups 1, 2 and 5 to the overall CS rate	These three groups combined normally contribute to 2/3 (66%) of all CS performed in most hospitals.	63.7%	63.9%	58.5%
Contribution of Group 5 to the overall CS rate		28.9%	29.6%	27.1%

Evaluation of cesarean section (CS) rates requires consideration of every childbirth as the denominator, posing challenges in many international (14)(15) and Sri Lankan studies due to retrospective data use to catergorize deliveries according to Robson Classification. While some studies focused solely on patients who underwent CS (2, 3), our study utilized prospective data collection through RobsApp®, enabling the inclusion of almost all deliveries. However, categorizing according to Robson classification may encounter missing or illegible core variables, emphasizing the importance of adhering to the Robson manual.(12) The WHO multicountry survey (MCS) and a study done by Senanayake et al. at DSHW followed Robson protocol and gathered data propectively but suffered from data quality issues due to paper-based collection. Our study, utilizing the smartphone application RobsApp®, in which patient information was entered at the bedside and all the fields had to be entered before closing the data entry for an individual, thereby ensured high data quality by eliminating missing data and reducing entry errors through automated transfer. (Table 4)

One of the other important aspects is continuous data collection which poses challenges, particularly in resource-limited settings like Sri Lanka as the hopitals will not have the resources to employ secretaries for orthodox data collection methods. This is a lesson learnt at DSHW. Senanyake et al study was discontinued in 2017 at the university unit DSHW due to this limitation. We propose the use of RobsApp® which is less cumbersone and user-friendly and offers a sustainable solution for continuous data collection compared to traditional methods.

The heterogeneity of data complicates CS rate comparisons across setups and countries. While the WHO multicountry (MCS) provides a “reference population” to compare CS rates, caution is needed in generalizing its findings as the reference population included 42,637 women from 66 heterogeneous health facilities in 22 countries. (16)(17) EBCOG suggests national data collection for meaningful comparisons, advocating for Robson classification analysis. (18)

Even within a country, although dividing into levels of care is one way of reducing heterogeneity, the provision of care differs based on the referrals and available resources. Despite of the linked referral system between the primary and tertiary health care facility, the patients can bypass this system and decide where they wish to have their delivery. Such within-country facility differences underscore the importance of temporal analysis within the same healthcare facility to draw recommendations. Comparing our results with a previous study done by Senanayake et al. revealed a significant increase in CS rates from 30.0% in 2017 to 33% in 2020 at the same unit (p < 0.01).(4)

When analyzing our study population, we observed a higher prevalence of women with at least one previous cesarean section (CS) compared to the multi-country survey (MCS) population. This proportion has increased from 10.9% in 2017 to 11.5% in 2020, possibly reflecting the recent rise in CS rates among nulliparous women. The findings suggest that our unit is now serving a higher-risk population, as evidenced by the elevated number of multiple pregnancies, which surpasses the upper limit of the Robson guidance in our study population (1.9%), which is much higher than the MCS reference population (0.9%) and DSHW 2017 study (1.1%). Overall, it can be speculated that there is a rising trend in higher-risk pregnant mothers attending for delivery at the unit.

Groups 3 and 4, representing multiparous women without a previous CS scar, constitute 33.4% of our population, significantly lower than in the MCS and the 2017 study. Therefore, our unit currently cares for a higher proportion of nulliparous women and women with scarred uteri.

Examining the proportion of CS in various groups, we found that 42.7% of inductions in our study group resulted in CS, exceeding the Robson reference and rates observed in 2017. Therefore, a reassessment of the induction protocol at our unit is warranted.

CS rates in multiparous women without a previous CS, with a single cephalic pregnancy, and ≥ 37 weeks gestation in spontaneous labour are three times higher in our population compared to the Robson guidance. This upward trend in CS rates over time, compared to the DSHW 2017 study, highlights the need for targeted interventions to reduce unnecessary CS, facilitated by using quality data classified into Robson groups.

More than half of preterm births in our study population resulted in CS, possibly due to a higher proportion of pre-labour CS for fetal growth restriction or pregnancy complications. The contribution to all CS by this group is 12.9% which is higher than DSHW 2017 indicating a shift towards a higher-risk population served over time. As these CS may be deemed necessary it may not be a priority group for interventions targeted at reducing CS rates.

A notable observation is the decreasing contribution of Group 5 (multiparous women with at least one previous CS, with a single cephalic pregnancy, and ≥ 37 weeks gestation) to total CS from 29.6% to 27.1 from 2020, reflecting an increase in CS for reasons other than a previous CS. This trend is expected to further elevate CS rates in the future.

The contribution of Group 6 + 7 (all women with a single breech presentation) to total CSs increased from 9.1–11.6%, possibly influenced by a rise in preterm deliveries. However, a high percentage (90.4%) of breech presentations resulted in CS which was much lower (80.3%) in 2017, indicating potential issues with performing external cephalic versions (ECVs) or achieving success with ECVs over time. Even in the multiparous breech group, the CS rate is high (85.3%). This higher percentage may be due to reducing expertise in breech delivery over time, thus more and more multiparous women having CSs rather than breech vaginal deliveries.

CS rates in multiparous women with at least one previous CS, with a single cephalic pregnancy, and ≥ 37 weeks gestation have reduced compared to the 2017 study but remain higher than the Robson guidance. This improvement may be attributed to higher success rates in the trial of labour after cesarean section (TOLAC). Additionally, CS rates in twins have decreased since 2017 but still exceed the Robson guidance, suggesting room for further improvement.

Our analysis reveals that almost half of the CS carried out at our unit are emergency CS, with fetal distress being the highest contributor (32.1%) followed by failure to progress in induced labour(15.7%). These findings underscore the need for interventions to reduce medically unnecessary CS and address issues related to labor progression and fetal distress.

RobsApp® is a convenient method of prospective data collection of childbirths in line with Robson classification. It can achieve high quality in the collected data set but yet heterogeinity of data mandatorily needs a temporal analysis which coul be achieved by RobsApp which aids continuous data collection. Over time CS rates are rising in the professorial unit of DSHW. TOLAC success rates are getting higher. However, increasing CS is being performed for reasons other than for past sections. The expertise in managing breech delivery and ECV has been reduced. Emergency CS accounts for half of all CS in this study group. CTG abnormalities are the highest contributor for emergency CS followed by caesarean sections performed due to failed induction. Induction protocols should be reassessed and intervention should be taken to minimize unnecessary CS.

Valid and acceptable caesarean section rates on each category of the Robson classification should be obtained for each institution as well as for the country. This is only possible with multicenter survey of CS according to Robson categories and analysis of them at the national level.

Conflicts of interest

Authors declare no conflicts of interests.

Ethical approval

for the study was taken from Ethical Review Committee, Faculty of Medicine, University of Colombo on 21/03/2019 (Ref – EC-19-024). This is not a clinical trial. The study included looking at patient records prior to sending it for archives without any patient identifiable details. Therefore, individual patient consent for participation was not taken.

Funding

This was an investigator-funded project.

Author Contribution

CJ, AJ were involved with concept of the project. AP and CJ contributed to the development of RobsApp and conducting the study. IP, CJ and AJ were involved with data analysis and writing of the manuscript. IP, CJ, AJ and AP had all contributed for the final article.

Acknowledgement

We acknowledge the ward staff, the data collectors and the record room staff for their valuable support.

Data Availability

The data is available with the corresponding author and will be released on request.

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No competing interests reported.

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You are reading this latest preprint version

Evaluation of caesarean rates according to Robson classification using a newly developed smart phone application in a tertiary centre in Sri Lanka: Comparative study

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Abstract

Objective

Methods

Results

Conclusions

Introduction

Method

Results

Discussion

Conclusions

Declarations

Conflicts of interest

Ethical approval

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1