| 1. |
- Hossain, Aniqa T., et al.
(författare)
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Measuring coverage and quality of supportive care for inpatient neonatal infections : EN-BIRTH multi-country validation study
- 2022
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Ingår i: Journal of Global Health. - : International Global Health Society. - 2047-2978 .- 2047-2986. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Background: An estimated 7 million episodes of severe newborn infections occur annually worldwide, with half a million newborn deaths, most oc-curring in low-and middle-income countries. Whilst injectable antibiotics are necessary to treat the infection, supportive care is also crucial in ending preventable mortality and morbidity. This study uses multi-country data to assess gaps in coverage, quality, and documentation of supportive care, considering implications for measurement.Methods: The EN-BIRTH study was conducted in five hospitals in Bangla-desh, Nepal, and Tanzania (July 2017-July 2018). Newborns with an ad-mission diagnosis of clinically-defined infection (sepsis, meningitis, and/or pneumonia) were included. Researchers extracted data from inpatient case notes and interviews with women (usually the mothers) as the primary fam-ily caretakers after discharge. The interviews were conducted using a struc-tured survey questionnaire. We used descriptive statistics to report coverage of newborn supportive care components such as oxygen use, photothera-py, and appropriate feeding, and we assessed the validity of measurement through survey-reports using a random-effects model to generate pooled estimates. In this study, key supportive care components were assessment and correction of hypoxaemia, hyperbilirubinemia, and hypoglycaemia.Results: Among 1015 neonates who met the inclusion criteria, 89% had an admission clinical diagnosis of sepsis. Major gaps in documentation and care practices related to supportive care varied substantially across the par-ticipating hospitals. The pooled sensitivity was low for the survey-reported oxygen use (47%; 95% confidence interval (CI) = 30%-64%) and moderate for phototherapy (60%; 95% CI = 44%-75%). The pooled specificity was high for both the survey-reported oxygen use (85%; 95% CI = 80%-89%) and phototherapy (91%; 95% CI = 82%-97%).Conclusions: The women's reports during the exit survey consistently un-derestimated the coverage of supportive care components for managing infection. We have observed high variability in the inpatient documents across facilities. A standardised ward register for inpatient small and sick newborn care may capture selected supportive care data. However, tracking the detailed care will require standardised individual-level data sets linked to newborn case notes. We recommend investments in assessing the im-plementation aspects of a standardised inpatient register in resource-poor settings.
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| 2. |
- Hossain, Aniqa T, et al.
(författare)
-
Measuring coverage and quality of supportive care for inpatient neonatal infections: EN-BIRTH multi-country validation study.
- 2022
-
Ingår i: Journal of global health. - : International Global Health Society. - 2047-2986 .- 2047-2978. ; 12
-
Tidskriftsartikel (refereegranskat)abstract
- An estimated 7 million episodes of severe newborn infections occur annually worldwide, with half a million newborn deaths, most occurring in low- and middle-income countries. Whilst injectable antibiotics are necessary to treat the infection, supportive care is also crucial in ending preventable mortality and morbidity. This study uses multi-country data to assess gaps in coverage, quality, and documentation of supportive care, considering implications for measurement.The EN-BIRTH study was conducted in five hospitals in Bangladesh, Nepal, and Tanzania (July 2017-July 2018). Newborns with an admission diagnosis of clinically-defined infection (sepsis, meningitis, and/or pneumonia) were included. Researchers extracted data from inpatient case notes and interviews with women (usually the mothers) as the primary family caretakers after discharge. The interviews were conducted using a structured survey questionnaire. We used descriptive statistics to report coverage of newborn supportive care components such as oxygen use, phototherapy, and appropriate feeding, and we assessed the validity of measurement through survey-reports using a random-effects model to generate pooled estimates. In this study, key supportive care components were assessment and correction of hypoxaemia, hyperbilirubinemia, and hypoglycaemia.Among 1015 neonates who met the inclusion criteria, 89% had an admission clinical diagnosis of sepsis. Major gaps in documentation and care practices related to supportive care varied substantially across the participating hospitals. The pooled sensitivity was low for the survey-reported oxygen use (47%; 95% confidence interval (CI) = 30%-64%) and moderate for phototherapy (60%; 95% CI = 44%-75%). The pooled specificity was high for both the survey-reported oxygen use (85%; 95% CI = 80%-89%) and phototherapy (91%; 95% CI = 82%-97%).The women's reports during the exit survey consistently underestimated the coverage of supportive care components for managing infection. We have observed high variability in the inpatient documents across facilities. A standardised ward register for inpatient small and sick newborn care may capture selected supportive care data. However, tracking the detailed care will require standardised individual-level data sets linked to newborn case notes. We recommend investments in assessing the implementation aspects of a standardised inpatient register in resource-poor settings.
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| 3. |
- Shamba, Donat, et al.
(författare)
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Barriers and enablers to routine register data collection for newborns and mothers: EN-BIRTH multi-country validation study.
- 2021
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Ingår i: BMC pregnancy and childbirth. - : Springer Science and Business Media LLC. - 1471-2393. ; 21:Suppl 1
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Tidskriftsartikel (refereegranskat)abstract
- Policymakers need regular high-quality coverage data on care around the time of birth to accelerate progress for ending preventable maternal and newborn deaths and stillbirths. With increasing facility births, routine Health Management Information System (HMIS) data have potential to track coverage. Identifying barriers and enablers faced by frontline health workers recording HMIS source data in registers is important to improve data for use.The EN-BIRTH study was a mixed-methods observational study in five hospitals in Bangladesh, Nepal and Tanzania to assess measurement validity for selected Every Newborn coverage indicators. We described data elements required in labour ward registers to track these indicators. To evaluate barriers and enablers for correct recording of data in registers, we designed three interview tools: a) semi-structured in-depth interview (IDI) guide b) semi-structured focus group discussion (FGD) guide, and c) checklist assessing care-to-documentation. We interviewed two groups of respondents (January 2018-March 2019): hospital nurse-midwives and doctors who fill ward registers after birth (n = 40 IDI and n = 5 FGD); and data collectors (n = 65). Qualitative data were analysed thematically by categorising pre-identified codes. Common emerging themes of barriers or enablers across all five hospitals were identified relating to three conceptual framework categories.Similar themes emerged as both barriers and enablers. First, register design was recognised as crucial, yet perceived as complex, and not always standardised for necessary data elements. Second, register filling was performed by over-stretched nurse-midwives with variable training, limited supervision, and availability of logistical resources. Documentation complexity across parallel documents was time-consuming and delayed because of low staff numbers. Complete data were valued more than correct data. Third, use of register data included clinical handover and monthly reporting, but little feedback was given from data users.Health workers invest major time recording register data for maternal and newborn core health indicators. Improving data quality requires standardised register designs streamlined to capture only necessary data elements. Consistent implementation processes are also needed. Two-way feedback between HMIS levels is critical to improve performance and accurately track progress towards agreed health goals.
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