George Mbevi
Biographic Data
| ID | 9064229 |
|---|---|
| NAME | George Mbevi |
| GIVEN NAMES | George |
| FAMILY NAME | Mbevi |
| SIGNATURE | MBEVI G |
| AFFILIATIONS | Kenya Medical Research Institute |
| ORCID | 0000-0003-1533-9800 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Improving in-patient neonatal data quality as a pre-requisite for monitoring and improving quality of care at scale
The objectives of this study were to (1)explore the quality of clinical data generated from hospitals providing in-patient neonatal care participating in a clinical information network (CIN) and whether data improved over time, and if data are adequate, (2)characterise accuracy of prescribing for basic treatments provided to neonatal in-patients over time. This was a retrospective cohort study involving neonates ≤28 days admitted between January …
Neonatal mortality in Kenyan hospitals
BACKGROUND: Most of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals. METHODS: Continuously collected routine patients' data from structured paper r…
The indirect impact of Covid-19 pandemic on inpatient admissions in 204 Kenyan hospitals
The first case of severe acute respiratory coronavirus 2 (SARS-CoV-2) was identified in March 2020 in Kenya resulting in the implementation of public health measures (PHM) to prevent large-scale epidemics. We aimed to quantify the impact of COVID-19 confinement measures on access to inpatient services using data from 204 Kenyan hospitals. Data on monthly admissions and deliveries from the District Health Information Software version 2 (DHIS 2) we…
Data for tracking SDGs
Background: Target 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports on its use for collecting neonatal hospital data that are of increasing importance as births within facilities increase. To address this gap, we invest…
No prominent works on this page.
Data for tracking SDGs
Background: Target 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports on its use for collecting neonatal hospital data that are of increasing importance as births within facilities increase. To address this gap, we invest…
Neonatal mortality in Kenyan hospitals
BACKGROUND: Most of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals. METHODS: Continuously collected routine patients' data from structured paper r…
The indirect impact of Covid-19 pandemic on inpatient admissions in 204 Kenyan hospitals
The first case of severe acute respiratory coronavirus 2 (SARS-CoV-2) was identified in March 2020 in Kenya resulting in the implementation of public health measures (PHM) to prevent large-scale epidemics. We aimed to quantify the impact of COVID-19 confinement measures on access to inpatient services using data from 204 Kenyan hospitals. Data on monthly admissions and deliveries from the District Health Information Software version 2 (DHIS 2) we…
Improving in-patient neonatal data quality as a pre-requisite for monitoring and improving quality of care at scale
The objectives of this study were to (1)explore the quality of clinical data generated from hospitals providing in-patient neonatal care participating in a clinical information network (CIN) and whether data improved over time, and if data are adequate, (2)characterise accuracy of prescribing for basic treatments provided to neonatal in-patients over time. This was a retrospective cohort study involving neonates ≤28 days admitted between January …
Medicine (4 works) · Emergency Medicine (3 works) · Global Maternal and Child Health (3 works) · Maternal and Neonatal Healthcare (3 works) · Public health (3 works) · Cohort (2 works) · Environmental health (2 works) · Kenya (2 works) · Medical emergency (2 works) · Nursing (2 works)