ObjectivesThis study aimed at describing the use of a prospective database on hospital deliveries for analysing caesarean section (CS) practices according to the WHO manual for Robson classification, and for developing recommendations for improving the quality of care (QoC).DesignObservational study.SettingUniversity Obstetric Unit at De Soysa Hospital for Women, the largest maternity unit in Sri Lanka.Data collection and analysisFor each childbirth, 150 variables were routinely collected in a standardised form and entered into a database. Data were routinely monitored for ensuring quality. Information on deliveries occurring from July 2015 to June 2017 were analysed according the WHO Robson classification manual. Findings were discussed internally to develop quality improvement recommendations.Results7504 women delivered in the hospital during the study period and at least one maternal or fetal pathological condition was reported in 2845 (37.9%). The CS rate was 30.0%, with 11.9% CS being performed prelabour. According to the Robson classification, Group 3 and Group 1 were the most represented groups (27.0% and 23.1% of population, respectively). The major contributors to the CS rate were group 5 (29.6%), group 1 (14.0%), group 2a (13.3%) and group 10 (11.5%). The most commonly reported indications for CS included abnormal cardiotocography/suspected fetal distress, past CS and failed progress of labour or failed induction. These suggested the need for further discussion on CS practices. Overall, 18 recommendations were agreed on. Besides updating protocols and hands-on training, activities agreed on included monitoring and supervision, criterion-based audits, risk management meetings and appropriate information for patients, and recommendations to further improve the quality of data.ConclusionsThis study provides an example on how the WHO manual for Robson classification can be used in an action-oriented manner for developing recommendations for improving the QoC, and the quality of data collected.

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ObjectivesThis study was aimed at piloting a prospective individual patient database on hospital deliveries in Colombo, Sri Lanka, and at exploring its use for developing recommendations for improving quality of care (QoC).DesignObservational study.SettingDe Soysa Maternity Hospital, the largest referral hospital for maternity care in Sri Lanka.Data collection and analysisFrom July 2015 to June 2017, 150 variables were collected for each delivery using a standardised form and entered into a database. Data were analysed every 8 months, and the results made available to local staff. Outcomes of the study included: technical problems; data completeness; data accuracy; key database findings; and use of data.Results7504 deliveries were recorded. No technical problem was reported. Data completeness exceeded that of other existing hospital recording systems. Less than 1% data were missing for maternal variables and less than 3% for newborn variables. Mistakes in data collection and entry occurred in 0.01% and 0.09% of maternal and newborn data, respectively. Key QoC indicators identified in comparison with international standards were: relatively low maternal mortality (0.053%); relatively high maternal near-miss cases (3.4%); high rate of induction of labour (24.6%), caesarean section (30.0%) and episiotomy (56.1%); relatively high rate of preterm births (9.4%); low birthweight rate (16.5%); stillbirth (0.97%); and of total deaths in newborn (1.98%). Based on key indicators identified, a list of recommendations was developed, including the use checklists to standardise case management, training, clinical audits and more information for patients. A list of lessons learnt with the implementation of the data collection system was also drawn.ConclusionsThe study shows that the implemented system of data collection can produce a large quantity of reliable information. Most importantly, this experience provides an example on how database findings can be used for discussing hospital practices, identifying gaps and to agree on recommendations for improving QoC.

Person-centered maternity care (PCMC) is defined as care which is respectful of and responsive to women’s and families’ preferences, needs, and values. In this cross-sectional study we aimed to evaluate the correlations among the degree of PCMC implementation, key indicators of provision of care, and women’s satisfaction with maternity care in Sri Lanka. Degree of PCMC implementation was assessed using a validated questionnaire. Provision of good key practices was measured with the World Health Organization (WHO) Bologna Score, whose items include: 1) companionship in childbirth; 2) use of partogram; 3) absence of labor stimulation; 4) childbirth in non-supine position; 5) skin-to-skin contact. Women’s overall satisfaction was assessed on a 1–10 Likert scale. Among 400 women giving birth vaginally, 207 (51.8%) had at least one clinical risk factor and 52 (13.0%) at least one complication. The PCMC implementation mean score was 42.3 (95%CI 41.3–43.4), out of a maximum score of 90. Overall, while 367 (91.8%) women were monitored with a partogram, and 293 (73.3%) delivered non-supine, only 19 (4.8%) did not receive labour stimulation, only 38 (9.5%) had a companion at childbirth, and 165 (41.3%) had skin-to-skin contact immediately after birth. The median total satisfaction score was 7 (IQR 5–9). PCMC implementation had a moderate correlation with women’s satisfaction (r = 0.58), while Bologna score had a very low correlation both with satisfaction (r = 0.12), and PCMC (r = 0.20). Factors significantly associated with higher PCMC score were number of pregnancies (p = 0.015), ethnicity (p<0.001), presence of a companion at childbirth (p = 0.037); absence of labor stimulation (p = 0.019); delivery in non-supine position (p = 0.016); and skin-to-skin contact (p = 0.005). Study findings indicate evidence of poor-quality care across several domains of mistreatment in childbirth in Sri Lanka. In addition, patient satisfaction as an indicator of quality care is inadequate to inform health systems reform.

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