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La micro-assurance santé en Afrique sub-saharienne: une opportunité pour améliorer l'accès aux soins obstétricaux d'urgence?
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Delayed treatment of tuberculosis patients in rural areas of Yogyakarta province, Indonesia
No full textBackground
In year 2000, the entire population in Indonesia was 201 million and 57.6 percent of that was living in rural areas. This paper reports analyses that address to what extent the rural structure influence the way TB patients seek care prior to diagnosis by a DOTS facility.
Methods
We documented healthcare utilization pattern of smear positive TB patients prior to diagnosis and treatment by DOTS services (health centre, chest clinic, public and private hospital) in Yogyakarta province. We calculated the delay in treatment as the number of weeks between the onset of symptoms and the start of DOTS treatment. Statistical analysis was carried out with Epi Info version 3.3 (October 5, 2004).
Results
The only factor which was significantly associated with total delay was urban-rural setting (p = < 0.0001). The median total delay for TB patients in urban districts was 8 (1st Quartile = 4; 3rd Quartile = 12) weeks compared to 12 (1st Quartile = 7; 3rd Quartile = 23) weeks for patients in rural districts. Multivariate analysis suggested no confounding between individual factors and urban-rural setting remained as the main factor for total delay (p = < 0.0001). Primary health centre was the first choice provider for most (38.7%) of these TB patients. Urban-rural setting was also the only factor which was significantly associated with choice of first provider (p = 0.03).
Conclusion
Improving access to DOTS services in rural areas is an area of vital importance in aiming to make progress toward achieving TB control targets in Indonesia
Policymaking in transitional economies: poverty reduction and health care in Cambodia and Laos
No full textBetween profit and legitimacy; a case study of two successful township health centers in rural China
No full textThe policy process and context of the rural new cooperative medical scheme and medical financial assistance in China
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La réforme du secteur de la santé en Bolivie: une réponse pour améliorer l'accès aux soins obstétricaux
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Bayesian latent class models with conditionally dependent diagnostic tests: a case study
No full textIn the assessment of the accuracy of diagnostic tests for infectious diseases, the true disease status of the subjects is often unknown due to the lack of a gold standard test. Latent class models with two latent classes, representing diseased and non-diseased subjects, are often used to analyze this type of data. In its basic format, latent class analysis requires the observed outcomes to be statistically independent conditional on the disease status. In most diagnostic settings, this assumption is highly questionable. During the last decade, several methods have been proposed to estimate latent class models with conditional dependence between the test results. A class of flexible fixed and random effects models were described by Dendukuri and Joseph in a Bayesian framework. We illustrate these models using the analysis of a diagnostic study of three field tests and an imperfect reference test for the diagnosis of visceral leishmaniasis. We show that, as observed earlier by Albert and Dodd, different dependence models may result in similar fits to the data while resulting in different inferences. Given this problem, selection of appropriate latent class models should be based on substantive subject matter knowledge. If several clinically plausible models are supported by the data, a sensitivity analysis should be performed by describing the results obtained from different models and using different priors