Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: The adverse selection theory speculates a high level of demand for health insurance by people with vulnerable health conditions. However, the COVID-19 pandemic changed the prevailing narratives and pattern of healthcare utilization in many African countries. This study estimated the effects of household member's disability and presence of serious illness on the probability of National Hospital Insurance Fund (NHIF) subscription with the average treatment effect (ATE) and average treatment effect on the treated (ATET).
Methods: The data were collected telephonically in 2020 using the sampling frame of the United Nations High Commission on Refugees (UNHCR). The respondents were refugees with active phone numbers who were registered by the UNHCR in Nairobi, Mombasa and Nakuru cities. A total of 2,438 completed the surveys. The data were analysed with Treatment Effects Probit regression model using the regression adjustment estimator.
Results: The results showed that 24.89% of the respondents had health insurance. Also, 3.28%, 1.39% and 2.46%, respectively suffered from physical, cognitive and sensory disability, while 8.28% had some form of serious illness. The Probit regression results showed that probability of being health insured significantly increased (p < 0.05) with membership of community-based organizations (CBO), asset index, possession of bank savings account, residence in Nairobi and household size, while residence in Nakuru reduced it. The ATE for physical and cognitive disabilities were significant (p < 0.05) with 0.1100 and 0.1816, respectively, while that for serious illness was 0.1046 (p < 0.01). The ATET for physical disability and serious illness were also significant (p < 0.05) with 0.1251 and 0.0996, respectively.
Conclusion: It was concluded that efforts to facilitate NHIF subscriptions among the refugees should be channelled among people with disability and serious illness. In addition, there is the need to promote refugees' welfare through employment that can induce formal savings and promote less reliance on informal borrowing. The operational mechanisms and differences in healthcare service distribution between the three cities should be considered along some salient interventions for health insurance subscription that are channelled through some CBOs.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11590370 | PMC |
http://dx.doi.org/10.1186/s12889-024-20794-1 | DOI Listing |
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