Evidence map›Paper›PMID 32308448›Full record

ArticleClinicoEconomics and outcomes research : CEOR2020

Cost of Hypertension Illness and Associated Factors Among Patients Attending Hospitals in Southwest Shewa Zone, Oromia Regional State, Ethiopia.

Addisu Bogale Zawudie, Teferi Daba Lemma, Dawit Wolde Daka

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Article in ClinicoEconomics and outcomes research : CEOR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
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11citing papers in PubMed, 2 pooled it
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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

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Addisu Bogale ZawudiePathfinder International Ethiopia, Addis Ababa, Ethiopia.
Teferi Daba LemmaFaculty of Public Health, Department of Health Policy and Management, Jimma University, Jimma, Ethiopia.ORCID 0000-0002-3426-013X
Dawit Wolde DakaFaculty of Public Health, Department of Health Policy and Management, Jimma University, Jimma, Ethiopia.ORCID 0000-0001-5465-6345

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypertension is a common vascular disease and the main risk factor for cardiovascular diseases. Since the incidence of hypertension is rising in Ethiopia, one may expect that the household's cost of healthcare services related to the disease will increase in the near future. Yet the cost associated with the disease is not known. We aimed to estimate the total cost of hypertension illness and identify associated factors among patients attending hospitals in Southwest Shewa zone, Oromia regional state, Ethiopia. PATIENTS AND

methodsAn institution-based cross-sectional study design was employed to conduct the study from 13 August to 2 September 2018. All hypertensive patients aged 18 years and older who were on follow-up were eligible for this study. The total cost of hypertension illness was estimated by summing the direct and indirect costs. Bivariate and multivariate linear regression analyses were performed to identify factors associated with hypertension costs of illnesses.

resultsA total of 349 patients participated in the study. The mean monthly total cost of hypertension illness was US$ 22.3 (95% CI, 21.3-23.3). Direct and indirect costs constitute 51% and 49% of the total cost, respectively. The mean direct cost of hypertension illness per patient per month was US$ 11.39 (95% CI, 10.6-12.1). Out of these, drugs comprised higher cost (31%), followed by food (25%). The mean indirect cost per patient per month was US$ 10.89 (95% CI, 10.4-11.4). In this study, the primary educational status, family size (4-6 and >6), distance from hospital (≥10 km), the presence of a companion and stage of hypertension (stage two) of patients were identified as the predictors of the cost of hypertension illnesses.

conclusionThe cost of hypertension illness was very high when compared to the monthly income of households, exposing patients to catastrophic costs. Hence, the government should give due attention to protect patients from catastrophic health expenditures.

Indexed as

cost of illnessdirect costEthiopiaindirect costtotal cost

Identifiers

PMID32308448
PMCPMC7154006

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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.