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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Objective: To develop a framework and index for measuring universal health coverage (UHC) at the district level in India and to assess progress towards UHC in the districts.
Methods: We adapted the framework of the World Health Organization and World Bank to develop a district-level UHC index (UHC ). We used routinely collected health survey and programme data in India to calculate UHC for 687 districts from geometric means of 24 tracer indicators in five tracer domains: reproductive, maternal, newborn and child health; infectious diseases; noncommunicable diseases; service capacity and access; and financial risk protection. UHC is on a scale of 0% to 100%, with higher scores indicating better performance. We also assessed the degree of inequality within districts using a subset of 14 tracer indicators. The disadvantaged subgroups were based on four inequality dimensions: wealth quintile, urban-rural location, religion and social group.
Findings: The median UHC was 43.9% (range: 26.4 to 69.4). Substantial geographical differences existed, with districts in southern states having higher UHC than elsewhere in India. Service coverage indicator levels were greater than 60%, except for noncommunicable diseases and for service capacity and access. Health insurance coverage was limited, with about 10% of the population facing catastrophic and impoverishing health expenditure. Substantial wealth-based disparities in UHC were seen within districts.
Conclusion: Our study shows that UHC can be measured at the local level and can help national and subnational government develop prioritization frameworks by identifying health-care delivery and geographic hotspots where limited progress towards UHC is being made.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362688 | PMC |
http://dx.doi.org/10.2471/BLT.23.290854 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!