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1.
BMC Pediatr ; 23(Suppl 2): 657, 2024 Jul 08.
Artículo en Inglés | MEDLINE | ID: mdl-38977945

RESUMEN

BACKGROUND: The emergence of COVID-19 precipitated containment policies (e.g., lockdowns, school closures, etc.). These policies disrupted healthcare, potentially eroding gains for Sustainable Development Goals including for neonatal mortality. Our analysis aimed to evaluate indirect effects of COVID-19 containment policies on neonatal admissions and mortality in 67 neonatal units across Kenya, Malawi, Nigeria, and Tanzania between January 2019 and December 2021. METHODS: The Oxford Stringency Index was applied to quantify COVID-19 policy stringency over time for Kenya, Malawi, Nigeria, and Tanzania. Stringency increased markedly between March and April 2020 for these four countries (although less so in Tanzania), therefore defining the point of interruption. We used March as the primary interruption month, with April for sensitivity analysis. Additional sensitivity analysis excluded data for March and April 2020, modelled the index as a continuous exposure, and examined models for each country. To evaluate changes in neonatal admissions and mortality based on this interruption period, a mixed effects segmented regression was applied. The unit of analysis was the neonatal unit (n = 67), with a total of 266,741 neonatal admissions (January 2019 to December 2021). RESULTS: Admission to neonatal units decreased by 15% overall from February to March 2020, with half of the 67 neonatal units showing a decline in admissions. Of the 34 neonatal units with a decline in admissions, 19 (28%) had a significant decrease of ≥ 20%. The month-to-month decrease in admissions was approximately 2% on average from March 2020 to December 2021. Despite the decline in admissions, we found no significant changes in overall inpatient neonatal mortality. The three sensitivity analyses provided consistent findings. CONCLUSION: COVID-19 containment measures had an impact on neonatal admissions, but no significant change in overall inpatient neonatal mortality was detected. Additional qualitative research in these facilities has explored possible reasons. Strengthening healthcare systems to endure unexpected events, such as pandemics, is critical in continuing progress towards achieving Sustainable Development Goals, including reducing neonatal deaths to less than 12 per 1000 live births by 2030.


Asunto(s)
COVID-19 , Mortalidad Infantil , Análisis de Series de Tiempo Interrumpido , Humanos , COVID-19/epidemiología , COVID-19/prevención & control , COVID-19/mortalidad , Recién Nacido , Tanzanía/epidemiología , Kenia/epidemiología , Mortalidad Infantil/tendencias , Malaui/epidemiología , Nigeria/epidemiología , Admisión del Paciente/estadística & datos numéricos , Unidades de Cuidado Intensivo Neonatal , Hospitalización/estadística & datos numéricos , Pandemias , Lactante
2.
BMC Pediatr ; 23(Suppl 2): 632, 2023 12 14.
Artículo en Inglés | MEDLINE | ID: mdl-38098013

RESUMEN

BACKGROUND: Small and sick newborn care (SSNC) is critical for national neonatal mortality reduction targets by 2030. Investment cases could inform implementation planning and enable coordinated resource mobilisation. We outline development of an investment case for Tanzania to estimate additional financing for scaling up SSNC to 80% of districts as part of health sector strategies to meet the country's targets. METHODS: We followed five steps: (1) reviewed national targets, policies and guidelines; (2) modelled potential health benefits by increased coverage of SSNC using the Lives Saved Tool; (3) estimated setup and running costs using the Neonatal Device Planning and Costing Tool, applying two scenarios: (A) all new neonatal units and devices with optimal staffing, and (B) half new and half modifying, upgrading, or adding resources to existing neonatal units; (4) calculated budget impact and return on investment (ROI) and (5) identified potential financing opportunities. RESULTS: Neonatal mortality rate was forecast to fall from 20 to 13 per 1000 live births with scale-up of SSNC, superseding the government 2025 target of 15, and close to the 2030 Sustainable Development Goal 3.2 target of <12. At 85% endline coverage, estimated cumulative lives saved were 36,600 by 2025 and 80,000 by 2030. Total incremental costs were estimated at US$166 million for scenario A (US$112 million set up and US$54 million for running costs) and US$90 million for scenario B (US$65 million setup and US$25 million for running costs). Setup costs were driven by infrastructure (83%) and running costs by human resources (60%). Cost per capita was US$0.93 and the ROI is estimated to be between US$8-12 for every dollar invested. CONCLUSIONS: ROI for SSNC is higher compared to other health investments, noting many deaths averted followed by full lifespan. This is conservative since disability averted is not included. Budget impact analysis estimated a required 2.3% increase in total government health expenditure per capita from US$40.62 in 2020, which is considered affordable, and the government has already allocated additional funding. Our proposed five-step SSNC investment case has potential for other countries wanting to accelerate progress.


Asunto(s)
Mortalidad Infantil , Desarrollo Sostenible , Recién Nacido , Humanos , Tanzanía
3.
BMC Pediatr ; 23(Suppl 2): 568, 2023 11 15.
Artículo en Inglés | MEDLINE | ID: mdl-37968606

RESUMEN

BACKGROUND: Thirty million small and sick newborns worldwide require inpatient care each year. Many receive antibiotics for clinically diagnosed infections without blood cultures, the current 'gold standard' for neonatal infection detection. Low neonatal blood culture use hampers appropriate antibiotic use, fuelling antimicrobial resistance (AMR) which threatens newborn survival. This study analysed the gap between blood culture use and antibiotic prescribing in hospitals implementing with Newborn Essential Solutions and Technologies (NEST360) in Kenya, Malawi, Nigeria, and Tanzania. METHODS: Inpatient data from every newborn admission record (July 2019-August 2022) were included to describe hospital-level blood culture use and antibiotic prescription. Health Facility Assessment data informed performance categorisation of hospitals into four tiers: (Tier 1) no laboratory, (Tier 2) laboratory but no microbiology, (Tier 3) neonatal blood culture use < 50% of newborns receiving antibiotics, and (Tier 4) neonatal blood culture use > 50%. RESULTS: A total of 144,146 newborn records from 61 hospitals were analysed. Mean hospital antibiotic prescription was 70% (range = 25-100%), with 6% mean blood culture use (range = 0-56%). Of the 10,575 blood cultures performed, only 24% (95%CI 23-25) had results, with 10% (10-11) positivity. Overall, 40% (24/61) of hospitals performed no blood cultures for newborns. No hospitals were categorised as Tier 1 because all had laboratories. Of Tier 2 hospitals, 87% (20/23) were District hospitals. Most hospitals could do blood cultures (38/61), yet the majority were categorised as Tier 3 (36/61). Only two hospitals performed > 50% blood cultures for newborns on antibiotics (Tier 4). CONCLUSIONS: The two Tier 4 hospitals, with higher use of blood cultures for newborns, underline potential for higher blood culture coverage in other similar hospitals. Understanding why these hospitals are positive outliers requires more research into local barriers and enablers to performing blood cultures. Tier 3 facilities are missing opportunities for infection detection, and quality improvement strategies in neonatal units could increase coverage rapidly. Tier 2 facilities could close coverage gaps, but further laboratory strengthening is required. Closing this culture gap is doable and a priority for advancing locally-driven antibiotic stewardship programmes, preventing AMR, and reducing infection-related newborn deaths.


Asunto(s)
Antibacterianos , Cultivo de Sangre , Recién Nacido , Humanos , Antibacterianos/uso terapéutico , Estudios Transversales , Kenia , Pacientes Internos , Malaui , Tanzanía , Nigeria , Hospitales
4.
BMC Pediatr ; 23(Suppl 2): 566, 2023 11 15.
Artículo en Inglés | MEDLINE | ID: mdl-37968613

RESUMEN

BACKGROUND: High-quality neonatal care requires sufficient functional medical devices, furniture, fixtures, and use by trained healthcare workers, however there is lack of publicly available tools for quantification and costing. This paper describes development and use of a planning and costing tool regarding furniture, fixtures and devices to support scale-up of WHO level-2 neonatal care, for national and global newborn survival targets. METHODS: We followed a systematic process. First, we reviewed planning and costing tools of relevance. Second, we co-designed a new tool to estimate furniture and device set-up costs for a default 40-bed level-2 neonatal unit, incorporating input from multi-disciplinary experts and newborn care guidelines. Furniture and device lists were based off WHO guidelines/norms, UNICEF and national manuals/guides. Due to lack of evidence-based quantification, ratios were based on operational manuals, multi-country facility assessment data, and expert opinion. Default unit costs were from government procurement agency costs in Kenya, Nigeria, and Tanzania. Third, we refined the tool by national use in Tanzania. RESULTS: The tool adapts activity-based costing (ABC) to estimate quantities and costs to equip a level-2 neonatal unit based on three components: (1) furniture/fixtures (18 default but editable items); (2) neonatal medical devices (16 product categories with minimum specifications for use in low-resource settings); (3) user training at device installation. The tool was used in Tanzania to generate procurement lists and cost estimates for level-2 scale-up in 171 hospitals (146 District and 25 Regional Referral). Total incremental cost of all new furniture and equipment acquisition, installation, and user training were US$93,000 per District hospital (level-2 care) and US$346,000 per Regional Referral hospital. Estimated cost per capita for whole-country district coverage was US$0.23, representing 0.57% increase in government health expenditure per capita and additional 0.35% for all Regional Referral hospitals. CONCLUSION: Given 2.3 million neonatal deaths and potential impact of level-2 newborn care, rational and efficient planning of devices linked to systems change is foundational. In future iterations, we aim to include consumables, spare parts, and maintenance cost options. More rigorous implementation research data are crucial to formulating evidence-based ratios for devices numbers per baby. Use of this tool could help overcome gaps in devices numbers, advance efficiency and quality of neonatal care.


Asunto(s)
Diseño Interior y Mobiliario , Muerte Perinatal , Lactante , Recién Nacido , Femenino , Humanos , Tanzanía , Kenia , Nigeria
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