SUMMARY Objective To systematically review Indian literature on delays in TB diagnosis and treatment. Methods We searched multiple sources for studies on delays in pulmonary TB and chest symptomatic patients. Studies were included if numeric data on any delay were reported. Patient delay was defined as the time interval between onset of symptoms and the patient’s first contact with a healthcare provider. Diagnostic delay was defined as the time interval between the first consultation with a healthcare provider and diagnosis. Treatment delay was defined as the time interval between diagnosis and initiation of anti-TB treatment. Total delay was defined as time interval from the onset of symptoms until treatment initiation. Results Among 541 potential citations identified, 23 studies met our inclusion criteria. Included studies used a variety of definitions for onset of symptoms and delays. Median (IQR) estimates of patient, diagnostic and treatment delay were 18.4 (14.3-27.0), 31.0 (24.5-35.4) and 2.5 days (1.9-3.6), respectively, for TB and chest symptomatic patients combined. The median total delay was 55.3 days (46.5-61.5). About 48% of all patients first consulted private providers and 2.7 healthcare providers, on average, were consulted before diagnosis. Number and type of provider first consulted were the most important risk factors for delay. Conclusions These findings underscore the need to develop novel strategies for reducing patient and diagnostic delays and engaging first-contact healthcare providers.

SUMMARY Background Existing studies on quality of tuberculosis care mostly reflect knowledge, not actual practice. Methods We conducted a validation study on the use of standardized patients (SPs) for assessing quality of TB care. Four cases, two for presumed TB and one each for confirmed TB and suspected MDR-TB, were presented by 17 SPs, with 250 SP interactions among 100 consenting providers in Delhi, including qualified (29%), alternative medicine (40%) and informal providers (31%). Validation criteria were: (1) negligible risk and ability to avoid adverse events for providers and SPs; (2) low detection rates of SPs by providers, and (3) data accuracy across SPs and audio verification of SP recall. We used medical vignettes to assess provider knowledge for presumed TB. Correct case management was benchmarked using Standards for TB Care in India (STCI). Findings SPs were deployed with low detection rates (4.7% of 232 interactions), high correlation of recall with audio recordings (r=0.63; 95% CI: 0.53 – 0.79), and no safety concerns. Average consultation length was 6 minutes with 6.2 questions/exams completed, representing 35% (95% confidence interval [CI]: 33%–38%) of essential checklist items. Across all cases, only 52 of 250 (21%; 95% CI: 16%–26%) were correctly managed. Correct management was higher among MBBS doctors (adjusted OR=2.41, 95% CI: 1.17–4.93) as compared to all others. Provider knowledge in the vignettes was markedly more consistent with STCI than their practice. Interpretation The SP methodology can be successfully implemented to assess TB care. Our data suggest a big gap between provider knowledge and practice.

BackgroundIndia has 23% of the global burden of active tuberculosis (TB) patients and 27% of the world’s “missing” patients, which includes those who may not have received effective TB care and could potentially spread TB to others. The “cascade of care” is a useful model for visualizing deficiencies in case detection and retention in care, in order to prioritize interventions.Methods and FindingsThe care cascade constructed in this paper focuses on the Revised National TB Control Programme (RNTCP), which treats about half of India’s TB patients. We define the TB cascade as including the following patient populations: total prevalent active TB patients in India, TB patients who reach and undergo evaluation at RNTCP diagnostic facilities, patients successfully diagnosed with TB, patients who start treatment, patients retained to treatment completion, and patients who achieve 1-y recurrence-free survival. We estimate each step of the cascade for 2013 using data from two World Health Organization (WHO) reports (2014–2015), one WHO dataset (2015), and three RNTCP reports (2014–2016). In addition, we conduct three targeted systematic reviews of the scientific literature to identify 39 unique articles published from 2000–2015 that provide additional data on five indicators that help estimate different steps of the TB cascade. We construct separate care cascades for the overall population of patients with active TB and for patients with specific forms of TB—including new smear-positive, new smear-negative, retreatment smear-positive, and multidrug-resistant (MDR) TB.The WHO estimated that there were 2,700,000 (95%CI: 1,800,000–3,800,000) prevalent TB patients in India in 2013. Of these patients, we estimate that 1,938,027 (72%) TB patients were evaluated at RNTCP facilities; 1,629,906 (60%) were successfully diagnosed; 1,417,838 (53%) got registered for treatment; 1,221,764 (45%) completed treatment; and 1,049,237 (95%CI: 1,008,775–1,083,243), or 39%, of 2,700,000 TB patients achieved the optimal outcome of 1-y recurrence-free survival.The separate cascades for different forms of TB highlight different patterns of patient attrition. Pretreatment loss to follow-up of diagnosed patients and post-treatment TB recurrence were major points of attrition in the new smear-positive TB cascade. In the new smear-negative and MDR TB cascades, a substantial proportion of patients who were evaluated at RNTCP diagnostic facilities were not successfully diagnosed. Retreatment smear-positive and MDR TB patients had poorer treatment outcomes than the general TB population. Limitations of our analysis include the lack of available data on the cascade of care in the private sector and substantial uncertainty regarding the 1-y period prevalence of TB in India.ConclusionsIncreasing case detection is critical to improving outcomes in India’s TB cascade of care, especially for smear-negative and MDR TB patients. For new smear-positive patients, pretreatment loss to follow-up and post-treatment TB recurrence are considerable points of attrition...

BackgroundWhile diabetes mellitus (DM) is a known risk factor for tuberculosis, the prevalence among TB patients in India is unknown. Routine screening of TB patients for DM may be an opportunity for its early diagnosis and improved management and might improve TB treatment outcomes. We conducted a cross-sectional survey of TB patients registered from June–July 2011 in the state of Kerala, India, to determine the prevalence of DM.Methodology/Principal FindingsA state-wide representative sample of TB patients in Kerala was interviewed and screened for DM using glycosylated hemoglobin (HbA1c); patients self-reporting a history of DM or those with HbA1c ≥6.5% were defined as diabetic. Among 552 TB patients screened, 243(44%) had DM – 128(23%) had previously known DM and 115(21%) were newly diagnosed - with higher prevalence among males and those aged >50years. The number needed to screen(NNS) to find one newly diagnosed case of DM was just four. Of 128 TB patients with previously known DM, 107(84%) had HbA1c ≥7% indicating poor glycemic control.Conclusions/SignificanceNearly half of TB patients in Kerala have DM, and approximately half of these patients were newly-diagnosed during this survey. Routine screening of TB patients for DM using HbA1c yielded a large number of DM cases and offered earlier management opportunities which may improve TB and DM outcomes. However, the most cost-effective ways of DM screening need to be established by futher operational research.