{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T05:51:59Z","timestamp":1791525119030,"version":"4.3.4"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Universal health coverage (UHC) requires broad service coverage and financial protection. Digital connectivity may enable digital public health, but general internet and telecommunications access does not capture the adoption, integration, quality, or equitable use of digital health services. We examined how health financing, connectivity, governance, and online information environments relate to UHC outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We assembled a multi-source country-year panel spanning 2000\u20132024. The principal two-way fixed-effects model included 3,522 observations from 166 countries in 2001 to 2023, with one-year-lagged exposures, country and year fixed effects, and country-clustered standard errors. Supplementary analyses used WHO report-reference-year and interval-change models, joint lag\u2013lead diagnostics, an expanded health-supply composite, a 2023 Global Digital Health Monitor (GDHM) construct comparison, post-2020 tests, and false discovery rate (FDR)-controlled exploratory outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A 1-SD higher out-of-pocket expenditure share was associated with a 1.38-point lower UHC service coverage index (95% CI, \u22122.39 to \u22120.36), whereas government health expenditure share was not independently associated with the index. A 1-SD higher connectivity composite was associated with a 2.98-point lower index (95% CI, \u22124.05 to \u22121.91) in the principal level model. However, this association attenuated across alternative estimands and was null for three-year change (\u22120.17; 95% CI, \u22120.66 to 0.32) and annualized change between WHO reference years (\u22120.17; 95% CI, \u22120.38 to 0.04). FDR-controlled analyses showed heterogeneous domain-specific patterns: connectivity was associated with lower DTP3 and MCV1 coverage but lower neonatal mortality, whereas public financing was associated with higher MCV2 coverage. UHC interactions were null, while immunization interactions varied by government effectiveness and information environment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Connectivity was associated with UHC levels, whereas the three-year and WHO reference-interval change estimates had confidence intervals spanning zero; associations also varied across domain-specific outcomes. Because the exposure captures general infrastructure rather than digital-health implementation, the findings suggest that connectivity alone is insufficient to improve UHC. Its public-health contribution is likely conditioned by financing, governance, organizational capacity, interoperability, workforce readiness, and equitable uptake. Causal interpretation is limited by the ecological design, modeled and interpolated UHC values, and unmeasured health-system characteristics.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1928583","type":"journal-article","created":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T05:32:54Z","timestamp":1791523974000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Health financing, digital connectivity, and universal health coverage: a country-year panel study"],"prefix":"10.3389","volume":"14","author":[{"given":"Guoliang","family":"Lu","sequence":"first","affiliation":[{"name":"School of Journalism and Communication, Chongqing University","place":["Chongqing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyun","family":"Tang","sequence":"additional","affiliation":[{"name":"Institute of Ecological Sociology, Fujian Academy of Social Sciences","place":["Fuzhou, China"]},{"name":"School of Journalism and Communication, Shanghai International Studies University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,9]]},"reference":[{"key":"ref1","volume-title":"Global Strategy on digital Health 2020\u20132025","year":"2021"},{"key":"ref2","volume-title":"Tracking Universal Health Coverage: 2023 Global Monitoring Report","year":"2023"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"e152","DOI":"10.1016\/S2214-109X(17)30472-2","article-title":"Monitoring universal health coverage within the sustainable development goals: development and baseline data for an index of essential health services","volume":"6","author":"Hogan","year":"2018","journal-title":"Lancet Glob Health"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1002\/hec.1157","article-title":"Government health expenditures and health 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