92 research outputs found

    The number of privately treated tuberculosis cases in India: an estimation from drug sales data

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    Background Understanding the amount of tuberculosis managed by the private sector in India is crucial to understanding the true burden of the disease in the country, and thus globally. In the absence of quality surveillance data on privately treated patients, commercial drug sales data offer an empirical foundation for disease burden estimation. Methods We used a large, nationally representative commercial dataset on sales of 189 anti-tuberculosis products available in India to calculate the amount of anti-tuberculosis treatment in the private sector in 2013–14. We corrected estimates using validation studies that audited prescriptions against tuberculosis diagnosis, and estimated uncertainty using Monte Carlo simulation. To address implications for numbers of patients with tuberculosis, we explored varying assumptions for average duration of tuberculosis treatment and accuracy of private diagnosis. Findings There were 17·793 million patient-months (95% credible interval 16·709 million to 19·841 million) of anti-tuberculosis treatment in the private sector in 2014, twice as many as the public sector. If 40–60% of private-sector tuberculosis diagnoses are correct, and if private-sector tuberculosis treatment lasts on average 2–6 months, this implies that 1·19–5·34 million tuberculosis cases were treated in the private sector in 2014 alone. The midpoint of these ranges yields an estimate of 2·2 million cases, two to three times higher than currently assumed. Interpretation India's private sector is treating an enormous number of patients for tuberculosis, appreciably higher than has been previously recognised. Accordingly, there is a re-doubled need to address this burden and to strengthen surveillance. Tuberculosis burden estimates in India and worldwide require revision

    Using the Technology Acceptance Model (TAM) in SAP Fiori

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    This article presents a case study that was carried out in two companies that have implemented SAP Fiori. The As-Is and To-Be description of the process in which SAP Fiori was implemented was performed. The advantages and disadvantages of using SAP Fiori were also identified. The Technology Acceptance Model (TAM) has been used in order to understand the aspects that most influence users to consider SAP Fiori as an added value, and how it optimizes the tasks of users. TAM has two variables that will influence the acceptance of a technology, which are: perceived ease of use and perceived utility.info:eu-repo/semantics/acceptedVersio

    Bottom-up or top-down: unit cost estimation of tuberculosis diagnostic tests in India.

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    SETTING: Of 18 sites that participated in an implementation study of the Xpert® MTB/RIF assay in India, we selected five microscopy centres and two reference laboratories. OBJECTIVE: To obtain unit costs of diagnostic tests for tuberculosis (TB) and drug-resistant TB. DESIGN: Laboratories were purposely selected to capture regional variations and different laboratory types. Both bottom-up and the top-down methods were used to estimate unit costs. RESULTS: At the microscopy centres, mean bottom-up unit costs were respectively US0.83(rangeUS0.83 (range US0.60-US1.10)andUS1.10) and US12.29 (US11.61US11.61-US12.89) for sputum smear microscopy and Xpert. At the reference laboratories, mean unit costs were US1.69forthedecontaminationprocedure,US1.69 for the decontamination procedure, US9.83 for a solid culture, US11.06foraliquidculture,US11.06 for a liquid culture, US29.88 for a drug susceptibility test, and US18.18foralineprobeassay.Topdownmeanunitcostestimateswerehigherforalltests,andforsputumsmearmicroscopyandXperttheseincreasedtorespectivelyUS18.18 for a line-probe assay. Top-down mean unit cost estimates were higher for all tests, and for sputum smear microscopy and Xpert these increased to respectively US1.51 and US$13.58. The difference between bottom-up and top-down estimates was greatest for tests performed at the reference laboratories. CONCLUSION: These unit costs for TB diagnostics can be used to estimate resource requirements and cost-effectiveness in India, taking into account geographical location, laboratory type and capacity utilisation

    Tuberculosis treatment in the private healthcare sector in India: An analysis of recent trends and volumes using drug sales data

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    Background There is a pressing need for systematic approaches for monitoring how much TB treatment is ongoing in the private sector in India: both to cast light on the true scale of the problem, and to help monitor the progress of interventions currently being planned to address this problem. Methods We used commercially available data on the sales of rifampicin-containing drugs in the private sector, adjusted for data coverage and indication of use. We examined temporal, statewise trends in volumes (patient-months) of TB treatment from 2013 to 2016. We additionally analysed the proportion of drugs that were sold in combination packaging (designed to simplify TB treatment), or as loose pills. Results Drug sales suggest a steady trend of TB treatment dispensed by the private sector, from 18.4 million patient-months (95% CI 17.3–20.5) in 2013 to 16.8 patient-months (95% CI 15.5–19.0) in 2016. Overall, seven of 29 states in India accounted for more than 70% of national-level TB treatment volumes, including Uttar Pradesh, Maharashtra and Bihar. The overwhelming majority of TB treatment was dispensed not as loose pills, but in combination packaging with other TB drugs, accounting for over 96% of private sector TB treatment in 2017. Conclusions Our findings suggest consistent levels of TB treatment in the private sector over the past 4 years, while highlighting specific states that should be prioritized for intervention. Drug sales data can be helpful for monitoring a system as large, disorganised and opaque as India’s private sector

    Piloting Upfront Xpert MTB/RIF Testing on Various Specimens under Programmatic Conditions for Diagnosis of TB & DR-TB in Paediatric Population

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    India accounts for one-fifth of the global TB incidence. While the exact burden of childhood TB is not known, TB remains one of the leading causes of childhood mortality in India. Bacteriological confirmation of TB in children is challenging due to difficulty in obtaining quality specimens, in the absence of which diagnosis is largely based on clinical judgement. While testing multiple specimens can potentially contribute to higher proportion of laboratory confirmed paediatric TB cases, lack of high sensitivity tests adds to the diagnostic challenge. We describe here our experiences in piloting upfront Xpert MTB/RIF testing, for diagnosis of TB in paediatric population in respiratory and extra pulmonary specimens, as recently recommended by WHO.Xpert MTB/RIF testing was offered to all paediatric (0-14 years) presumptive TB cases (both pulmonary and extra-pulmonary) seeking care at public and private health facilities in the project areas covering 4 cities of India.Under this pilot project, 8,370 paediatric presumptive TB & presumptive DR-TB cases were tested between April and-November 2014. Overall, 9,149 specimens were tested, of which 4,445 (48.6%) were non-sputum specimens. Xpert MTB/RIF gave 9,083 (99.2%, CI 99.0-99.4) valid results. Of the 8,143 presumptive TB cases enrolled, 517 (6.3%, CI 5.8-6.9) were bacteriologically confirmed. TB detection rates were two fold higher with Xpert MTB/RIF as compared to smear microscopy. Further, a total of 60 rifampicin resistant TB cases were detected, of which 38 were detected among 512 presumptive TB cases while 22 were detected amongst 227 presumptive DR-TB cases tested under the project.Xpert MTB/RIF with advantages of quick turnaround testing-time, high proportion of interpretable results and feasibility of rapid rollout, substantially improved the diagnosis of bacteriologically confirmed TB in children, while simultaneously detecting rifampicin resistance

    Building a tuberculosis-free world: The Lancet Commission on tuberculosis

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    ___Key messages___ The Commission recommends five priority investments to achieve a tuberculosis-free world within a generation. These investments are designed to fulfil the mandate of the UN High Level Meeting on tuberculosis. In addition, they answer

    Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

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    18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016

    Distributed generation opportunity under availability based tariff and reliability considerations

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    Availability Based Tariff (ABT) has been implemented in all the regional grids of India for improving grid discipline by frequency dependent pricing. Currently it is limited to short-term energy transactions between the beneficiary States and Central generating stations without the need for negotiations on price or quantum in real time. In the present scenario, Independent Power Producers (IPP), Captive Power Plants (CPP), small Distributed Generation (DG) like mini-turbine, fuel cell, etc., are not considered under ABT. DG units are normally modular in size and they can be placed close to consumers so as to reduce the T&D costs and losses. Hence, they need to be encouraged so as to meet the ever-increasing electricity demands of Indian power sector within the financial constraints. In this paper, impact of IPPs, CPPs and DGs on intra-State ABT is studied. This paper also proposes to study the impact of grid connected DG on network availability and reliability. The improvement in system reliability is studied after evaluating reliability indices like SAIFI, SAIDI, etc., with the inclusion of DG
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