ABSTRACT
BACKGROUND: The National Tuberculosis Elimination Programme (NTEP) of India is aiming to eliminate TB by 2025. The programme has increased its services and resources to strengthen the accurate and early detection of TB. It is important to estimate the cost of TB diagnosis in India considering the advancement and implementation of new diagnostic tools under the NTEP. The objective of this study was to estimate the unit costs of providing TB diagnostic services at different levels of public health facilities with different algorithms implemented under the NTEP in Chennai, Tamil Nadu, South India. METHODS: This costing study was conducted from the perspective of the health system. This study used only secondary data and information that were available in the public domain. Data were collected with the approval of health authorities. The patient's diagnostic path from the point of registration until the final diagnosis was considered in the costing exercise. The unit costs of different diagnostic tools used in the NTEP implemented by Chennai Corporation were calculated. RESULTS: We estimated the unit cost of the eight laboratory tests (Ziehl-Neelsen [ZN], fluorescence microscopy [FM], x-ray, digital x-ray, gene Xpert MTB/RIF (cartridge-based nucleic acid amplification test [NAAT] that identifies rifampicin resistant Mycobacterium Tuberculosis) Mycobacterium Tuberculosis/Rifampicin [MTB/RIF], mycobacteria growth indicator tube [MGIT], line probe assay [LPA] and Lowenstein Jensen [LJ] culture) for diagnosis of drug-sensitive and drug-resistant TB. The unit costs included fixed and variable costs for smear examination by ZN microscopy (â¹ [Indian Rupee] 326 [US${\$}$4.72], FM (â¹104 [US${\$}$1.5]), x-ray (â¹218 [US${\$}$3.15]), digital X-ray (â¹281 [US${\$}$4.07]), gene Xpert MTB/RIF (â¹1137 [US${\$}$16.47]), MGIT (â¹7038 [US${\$}$102]), LPA (â¹6448 [US${\$}$93.44]) and LJ culture (â¹4850 [US${\$}$70.28]). Out of 10 diagnostic algorithms used for TB diagnosis, algorithms using only smear microscopy had the lowest cost, followed by smear microscopy with x-ray for drug-sensitive TB (â¹104 [US${\$}$1.5] to â¹544 [US${\$}$7.88]). Diagnostic algorithms for drug-resistant TB involving LPA and gene Xpert MTB/RIF were the most expensive. CONCLUSIONS: Understanding the various costs contributing to TB diagnosis in India provides crucial evidence for policymakers, programme managers and researchers to optimise programme spending and efficiently use resources.
Subject(s)
Mycobacterium tuberculosis , Tuberculosis, Multidrug-Resistant , Tuberculosis , Humans , India , Sensitivity and Specificity , Sputum , Tuberculosis/diagnosis , Tuberculosis/prevention & control , Tuberculosis, Multidrug-Resistant/diagnosisABSTRACT
INTRODUCTION: Delaying care-seeking for tuberculosis (TB) symptoms is a major contributor to mortality, leading to worse outcomes and spread. To reduce delays, it is essential to identify barriers to care-seeking and target populations most at risk of delaying. Previous work identifies barriers only in people within the health system, often long after initial care-seeking. METHODS: We conducted a community-based survey of 84 625 households in Chennai, India, to identify 1667 people with TB-indicative symptoms in 2018-2019. Cases were followed prospectively to observe care-seeking behaviour. We used a comprehensive survey to identify care-seeking drivers, then performed multivariate analyses to identify care-seeking predictors. To identify profiles of individuals most at risk to delay care-seeking, we segmented the sample using unsupervised clustering. We then estimated the per cent of the TB-diagnosed population in Chennai in each segment. RESULTS: Delayed care-seeking characteristics include smoking, drinking, being employed, preferring different facilities than the community, believing to be at lower risk of TB and believing TB is common. Respondents who reported fever or unintended weight loss were more likely to seek care. Clustering analysis revealed seven population segments differing in care-seeking, from a retired/unemployed/disabled cluster, where 70% promptly sought care, to a cluster of employed men who problem-drink and smoke, where only 42% did so. Modelling showed 54% of TB-diagnosed people who delay care-seeking might belong to the latter segment, which is most likely to acquire TB and least likely to promptly seek care. CONCLUSION: Interventions to increase care-seeking should move from building general awareness to addressing treatment barriers such as lack of time and low-risk perception. Care-seeking interventions should address specific beliefs through a mix of educational, risk perception-targeting and social norms-based campaigns. Employed men who problem-drink and smoke are a prime target for interventions. Reducing delays in this group could dramatically reduce TB spread.
