Hayibor, K.M.* ; Kenu, E.* ; Mensah, G.I.* ; Awalime, D.* ; Anaman, J.* ; Asante-Poku, A.* ; Ivanova, O.* ; Abhishek, B.* ; Rachow, A. ; Hanson-Nortey, N.N.*
Scaling up tuberculosis case finding via private providers in Ghana: An impact evaluation using interrupted time series.
Front. Publ. Health 13:1598269 (2025)
BACKGROUND: Although TB services are free in Ghana, TB case detection remains low and mostly limited to public facilities. To address this, a Public-Private Mix (PPM) Directly Observed Therapy (DOT) model was introduced, involving community private healthcare providers and the National Health Insurance Scheme (NHIS) to boost TB case detection rates. METHODS: This impact evaluation focuses on four key interventions targeting vulnerable populations in Ghana's two largest metropolitan areas between the last quarter of 2018 and the first quarter of 2020. Screening and TB register data were collected from implementing facilities, along with TB case notifications from 2015 to 2022 for both intervention and control areas. Comparative interrupted time series (ITS) analysis was used to evaluate the effect of the interventions on quarterly TB case notifications. RESULTS: During the intervention period, a total of 563,868 persons were screened for TB, 12,121 of these were presumptive for TB and 590 persons were diagnosed with TB. Of the diagnosed TB cases, 95.3% (562) were bacteriologically confirmed. The overall TB screening yield was 104.6 cases per 100,000 population. In the intervention area, TB case notifications increased from 1,392 cases in 2018 to 1,462 cases in 2019 while they decreased from 853 to 778 in the control area. The ITS analyses detected positive post-intervention trend differences in all forms of TB and bacteriologically confirmed TB notification case rates between the intervention and control areas. CONCLUSION: Expanding free TB services through a PPM DOT model and sustained community engagement can increase TB case detection in urban areas. National TB programs should adopt and scale this approach to enhance TB surveillance and control.
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Publication type
Article: Journal article
Document type
Scientific Article
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Keywords
Interrupted Time Series; Covid-19; Care; Mix; Tb; Diagnosis; Models; Health; Sector
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Language
english
Publication Year
2025
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0
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2025
ISSN (print) / ISBN
2296-2565
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2296-2565
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Article Number: 1598269
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Frontiers
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Lausanne
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Peer reviewed
Institute(s)
Research Unit Global Health (UGH)
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-540001-003
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Erfassungsdatum
2025-10-13