Critical care capacity in Addis Ababa, Ethiopia: A citywide survey of public hospitals

Laytin, Adam D.; Sultan, Menbeu; Debebe, Finot; Walelign, Yenegeta; Fisseha, Gete; Gebreyesus, Alegnta

doi:10.1016/j.jcrc.2021.01.010

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…As part of the SSA country, Ethiopia shares the burden of HF. In addition, the country is complicated by a shortage of hospital beds, infrastructure, and intensive care units (9,10). It also has the lowest health workforce density in Africa, five times below the WHO minimum threshold of 4.45 per 1000 population to meet the Sustainable Development Goal(SDG) health targets (11).…”

Section: Introductionmentioning

confidence: 99%

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Anleye

Kumar

Endris

2022

Preprint

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Background: The burden of heart failure increases over time and is a leading cause of unplanned readmissions worldwide. In addition, its impact has doubled in countries with limited health resources, including Ethiopia. Identifying and preventing the possible contributing factors is crucial to reduce unplanned hospital readmission and to improve clinical outcomes. Method: A hospital-based retrospective cohort study design was employed from January 1, 2016, to December 30, 2020. The data was collected from 572 randomly selected medical records using data extraction checklists. Data were entered in Epi-data version 4.6 and analyzed with Stata version 17. The Kaplan-Meier and log-rank tests were used to estimate and compare the survival failure time. A Cox proportional hazard analysis was computed to identify predictors of readmission. Finally, the statistical significance level was declared at a p-value <0.05 with an adjusted odds ratio and a 95% confidence interval. Result: In this study, a total of 151 (26.40%) heart failure patients were readmitted within 30 days of discharge. In the multivariate cox proportional hazards analysis being an age (>65 years) (AHR: 3.172, 95%CI:.21, 4.55), rural in residency (AHR: 2.47, 95%CI: 1.44, 4.24), Asthma/COPD (AHR: 1.62, 95%CI: 1.11, 2.35), HIV/AIDS (AHR: 1.84, 95%CI: 1.24, 2.75), Haemoglobin level 8-10.9 g/dL (AHR: 6.20, 95%CI: 3.74, 10.28), and Mean platelet volume >9.1fl (AHR: 2.08, 95%CI: 1.27, 3.40) were identified as independent predictors of unplanned hospital readmission. Conclusion: The incidence of unplanned hospital readmission was relatively high among heart failure patients. Elderly patients, rural residency, comorbidity, higher mean platelet volume, and low hemoglobin level were independent predictors of readmission. Therefore, working on these factors will help to reduce the hazard of unplanned hospital readmission.

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Section: Introductionmentioning

confidence: 99%

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Anleye

Kumar

Endris

2022

Preprint

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“…In addition, the Interagency Integrated Triage Tool has been tested in Papua New Guinea to improve patient triage, flow and data management for emergency presentations [ 105 ]. Multiple resource assessment tools targeted toward critical care have also been developed and piloted in low-income settings [ 36 , 38 , 41 , 43 , 68 , 70 , 84 , 106 ]. The WHO Quick Check tool designed to rapidly identify patients with severe illness in low-income settings has been evaluated in Uganda [ 46 ].…”

Section: Definitionsmentioning

confidence: 99%

“…Surveys in several low-resource sub-Saharan countries have found a lack of essential equipment, disposable materials and medications (oxygen, vasopressors, sedatives, antibiotics) as frequent barriers to the provision of effective critical care [ 63 , 64 , 68 , 106 , 114 ]. Complex and parallel logistical pathways and financial limitations contribute to long supply times and chronic shortages of core items [ 130 ].…”

Section: Definitionsmentioning

confidence: 99%

“…Although equipment is available in some hospitals [ 36 ], the infrastructure and expertise for maintenance and repair are frequently lacking as is training for effective use [ 26 ]. For example, a survey across 15 ICUs in Ethiopia found that 80% of units had blood gas analysers but only one had the reagents needed [ 68 ]. A lack of technological solutions is frequently cited by staff as a major limitation in care [ 135 ], but such investments may also lead to complacency and detract from the basic quality of care.…”

Section: Definitionsmentioning

confidence: 99%

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A health systems approach to critical care delivery in low-resource settings: a narrative review

et al. 2023

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There is a high burden of critical illness in low-income countries (LICs), adding pressure to already strained health systems. Over the next decade, the need for critical care is expected to grow due to ageing populations with increasing medical complexity; limited access to primary care; climate change; natural disasters; and conflict. In 2019, the 72nd World Health Assembly emphasised that an essential part of universal health coverage is improved access to effective emergency and critical care and to “ensure the timely and effective delivery of life-saving health care services to those in need”. In this narrative review, we examine critical care capacity building in LICs from a health systems perspective. We conducted a systematic literature search, using the World Heath Organisation (WHO) health systems framework to structure findings within six core components or “building blocks”: (1) service delivery; (2) health workforce; (3) health information systems; (4) access to essential medicines and equipment; (5) financing; and (6) leadership and governance. We provide recommendations using this framework, derived from the literature identified in our review. These recommendations are useful for policy makers, health service researchers and healthcare workers to inform critical care capacity building in low-resource settings. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-023-07136-2.

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Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems

et al. 2023

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Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media–conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide.

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Critical care capacity in Addis Ababa, Ethiopia: A citywide survey of public hospitals

Cited by 3 publications

References 13 publications

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

A health systems approach to critical care delivery in low-resource settings: a narrative review

Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems

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