Implementation of an individual patient prospective database of hospital births in Sri Lanka and its use for improving quality of care

Abstract

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.

Nutritional services for children in Beira, Mozambique: a study reporting on participatory use of data to generate quality improvement recommendations

“…Notably, the high HIV prevalence among children with malnutrition in our sample (about one-third) may have affected results. However, similarly low recovery rates (around 50%) were recently observed in other settings, such as Uganda, where HIV prevalence in malnourished children is almost negligible (about 1%)38 thus suggesting that other factors affected the health outcomes.…”

“…Other systems of data gathering, such as direct evaluations of case management, or prospective data collection by on site data collectors, have other serious risk of bias (eg, the presence of external evaluators/data collectors can affect the QoC delivered, usually by increasing it compared with the ‘standard’). Literature shows that investment in strengthening data collection can be important drivers in quality improvement projects 38. Supportive supervision should also be implemented, with the aim of both monitoring practices—including data quality—and providing direct technical support.…”

Improving quality and use of routine health information system data in low- and middle-income countries: A scoping review

“…Out of the total of 20 studies on data quality, 14 were conducted in Africa, mostly in Sub-Saharan Africa [25,[29][30][31][32][33][34][35][36][37][38][39][40][41], three in Asia (India, Pakistan, Sri Lanka) [42][43][44], and the remaining three in South America (Brazil, Mexico &Peru and Haiti) [45][46][47]. Out of the 16 articles included in the review of data use, ten were from Africa [25,30,36,37,39,[48][49][50][51][52], mostly the Sub-Saharan region, five were from Asia (Philippines, Sri Lanka, India, and Iran) [43,44,[53][54][55], and one from the Caribbean (Haiti) [56].…”

“…A majority of the articles on the use of data were case studies [25,43,48,52,55,56,58], two had used a mixed-methods approach [36,54], three were qualitative studies [37,50,53], and two claimed evaluation designs that were not described [30,36]. The target population for the data quality interventions was mainly health facilities at the district level and or their staff, including health care providers and data generators [29,31,33,35,[38][39][40][41][42]44]. Other studies targeted both the health facilities at the district level and the district management team [25,34,46,47], and two reports solely focused on the district management team [30,32].…”

“…The studies on data use also tested combinations of interventions. Eleven studies reported improvement in data use [25,30,37,39,43,44,48,50,52,54,57]. The study by Braa and colleagues in Zanzibar tested quarterly five-days use-of-data workshops for district health management teams included a peer review of performance on common data quality issues, after each team presenting their data.…”