Evidence map›Paper›PMID 29499709›Full record

ArticleBMC health services research2018

Selling my sheep to pay for medicines - household priorities and coping strategies in a setting without universal health coverage.

Kristine Husøy Onarheim, Mitike Molla Sisay, Muluken Gizaw, Karen Marie Moland, Ole Frithof Norheim, Ingrid Miljeteig

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
8.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 52 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 3 countries.

Kristine Husøy OnarheimDepartment of Global Public Health and Primary Care, University of Bergen, P.O. Box 7804, 5020, Bergen, Norway. kristine.onarheim@uib.no.
Mitike Molla SisaySchool of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia.
Muluken GizawSchool of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia.
Karen Marie MolandDepartment of Global Public Health and Primary Care, University of Bergen, P.O. Box 7804, 5020, Bergen, Norway.
Ole Frithof NorheimDepartment of Global Public Health and Primary Care, University of Bergen, P.O. Box 7804, 5020, Bergen, Norway.
Ingrid MiljeteigDepartment of Global Public Health and Primary Care, University of Bergen, P.O. Box 7804, 5020, Bergen, Norway.
University of Bergen · NOAddis Ababa University · ETHarvard University · US

Funding

Norwegian Research Council Global Health Priorities 2020 project (Project Number: 218694/H10)Universitetet i Bergen Personal PhD stipend
6 · The paper itself

Abstract

backgroundThe first month of life is the period with the highest risk of dying. Despite knowledge of effective interventions, newborn mortality is high and utilization of health care services remains low in Ethiopia. In settings without universal health coverage, the economy of a household is vulnerable to illness, and out-of-pocket payments may limit families' opportunities to seek health care for newborns. In this paper we explore intra-household resource allocation, focusing on how families prioritize newborn health versus other household needs and their coping strategies for managing these priorities.

methodsA qualitative study was conducted in 2015 in Butajira, Ethiopia, comprising observation, semi-structured interviews, and focus group discussions with household members, health workers, and community members. Household members with hospitalized newborns or who had experienced neonatal death were primary informants.

resultsIn this predominantly rural and poor district, households struggled to pay out-of-pocket for services such as admission, diagnostics, drugs, and transportation. When newborns fell ill, families made hard choices balancing concerns for newborn health and other household needs. The ability to seek care, obtain services, and follow medical advice depended on the social and economic assets of the household. It was common to borrow money from friends and family, or even to sell a sheep or the harvest, if necessary. In managing household priorities and high costs, families waited before seeking health care, or used cheaper traditional medicines. For poor families with no money or opportunity to borrow, it became impossible to follow medical advice or even seek care in the first place. This had fatal health consequences for the sick newborns.

conclusionsWhile improving neonatal health is prioritized at policy level in Ethiopia, poor households with sick neonates may prioritize differently. With limited money at hand and high direct health care costs, families balanced conflicting concerns to newborn health and family welfare. We argue that families should not be left in situations where they have to choose between survival of the newborn and economic ruin. Protection against out-of-pocket spending is key as Ethiopia moves towards universal health coverage. A necessary step is to provide prioritized newborn health care services free of charge.

Indexed as

Adaptation, PsychologicalFamily CharacteristicsHealth ExpendituresResource AllocationAdolescentAdultAgedCatastrophic IllnessEthiopiaFemaleHealth Services AccessibilityHospitalizationHumansInfantInfant MortalityInfant, NewbornCatastrophic health expenditureEthiopiaHealth care seekingIntra-household decision makingNewborn healthOut-of-pocket expensesPovertyResource allocationUniversal health coverage

Identifiers

PMID29499709
PMCPMC5833112
OpenAlexW2790886963

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.