Variations in the quality of tuberculosis care in urban India: A cross-sectional, standardized patient study in two cities.

BACKGROUND: India has the highest burden of tuberculosis (TB). Although most patients with TB in India seek care from the private sector, there is limited evidence on quality of TB care or its correlates. Following our validation study on the standardized patient (SP) method for TB, we utilized SPs to examine quality of adult TB care among health providers with different qualifications in 2 Indian cities. METHODS AND FINDINGS: During 2014-2017, pilot programs engaged the private health sector to improve TB management in Mumbai and Patna. Nested within these projects, to obtain representative, baseline measures of quality of TB care at the city level, we recruited 24 adults to be SPs. They were trained to portray 4 TB "case scenarios" representing various stages of disease and diagnostic progression. Between November 2014 and August 2015, the SPs visited representatively sampled private providers stratified by qualification: (1) allopathic providers with Bachelor of Medicine, Bachelor of Surgery (MBBS) degrees or higher and (2) non-MBBS providers with alternative medicine, minimal, or no qualifications. Our main outcome was case-specific correct management benchmarked against the Standards for TB Care in India (STCI). Using ANOVA, we assessed variation in correct management and quality outcomes across (a) cities, (b) qualifications, and (c) case scenarios. Additionally, 2 micro-experiments identified sources of variation: first, quality in the presence of diagnostic test results certainty and second, provider consistency for different patients presenting the same case. A total of 2,652 SP-provider interactions across 1,203 health facilities were analyzed. Based on our sampling strategy and after removing 50 micro-experiment interactions, 2,602 interactions were weighted for city-representative interpretation. After weighting, the 473 Patna providers receiving SPs represent 3,179 eligible providers in Patna; in Mumbai, the 730 providers represent 7,115 eligible providers. Correct management was observed in 959 out of 2,602 interactions (37%; 35% weighted; 95% CI 32%-37%), primarily from referrals and ordering chest X-rays (CXRs). Unnecessary medicines were given to nearly all SPs, and antibiotic use was common. Anti-TB drugs were prescribed in 118 interactions (4.5%; 5% weighted), of which 45 were given in the case in which such treatment is considered correct management. MBBS and more qualified providers had higher odds of correctly managing cases than non-MBBS providers (odds ratio [OR] 2.80; 95% CI 2.05-3.82; p < 0.0001). Mumbai non-MBBS providers had higher odds of correct management than non-MBBS in Patna (OR 1.79; 95% CI 1.06-3.03), and MBBS providers' quality of care did not vary between cities (OR 1.15; 95% CI 0.79-1.68; p = 0.4642). In the micro-experiments, improving diagnostic certainty had a positive effect on correct management but not across all quality dimensions. Also, providers delivered idiosyncratically consistent care, repeating all observed actions, including mistakes, approximately 75% of the time. The SP method has limitations: it cannot account for patient mix or care-management practices reflecting more than one patient-provider interaction. CONCLUSIONS: Quality of TB care is suboptimal and variable in urban India's private health sector. Addressing this is critical for India's plans to end TB by 2025. For the first time, we have rich measures on representative levels of care quality from 2 cities, which can inform private-sector TB interventions and quality-improvement efforts.

Using the Indian National Sample Survey data in public health research.

The National Sample Survey (NSS), instituted in 1950, was the brainchild of Professor Mahalanobis, widely regarded as the father of Indian statistics.1 His ambition was to obtain and quantify comprehensive information on an annual basis on the socio- economic, demographic, agricultural and other profiles of the country, both at the national and state levels. The NSS is a multi- stage, multi-subject and multi-purpose cross-sectional survey, which is conducted annually and covers topics of current interest.

Use of standardised patients for healthcare quality research in low- and middle-income countries.

The use of standardised patients (SPs)-people recruited from the local community to present the same case to multiple providers in a blinded fashion-is increasingly used to measure the quality of care in low-income and middle-income countries. Encouraged by the growing interest in the SP method, and based on our experience of conducting SP studies, we present a conceptual framework for research designs and surveys that use this methodology. We accompany the conceptual framework with specific examples, drawn from our experience with SP studies in low-income and middle-income contexts, including China, India, Kenya and South Africa, to highlight the versatility of the method and illustrate the ongoing challenges. A toolkit and manual for implementing SP studies is included as a companion piece in the online supplement.

Has the Rajiv Aarogyasri Community Health Insurance Scheme of Andhra Pradesh Addressed the Educational Divide in Accessing Health Care?

BACKGROUND: Equity of access to healthcare remains a major challenge with families continuing to face financial and non-financial barriers to services. Lack of education has been shown to be a key risk factor for 'catastrophic' health expenditure (CHE), in many countries including India. Consequently, ways to address the education divide need to be explored. We aimed to assess whether the innovative state-funded Rajiv Aarogyasri Community Health Insurance Scheme of Andhra Pradesh state launched in 2007, has achieved equity of access to hospital inpatient care among households with varying levels of education. METHODS: We used the National Sample Survey Organization 2004 survey as our baseline and the same survey design to collect post-intervention data from 8623 households in the state in 2012. Two outcomes, hospitalisation and CHE for inpatient care, were estimated using education as a measure of socio-economic status and transforming levels of education into ridit scores. We derived relative indices of inequality by regressing the outcome measures on education, transformed as a ridit score, using logistic regression models with appropriate weights and accounting for the complex survey design. FINDINGS: Between 2004 and 2012, there was a 39% reduction in the likelihood of the most educated person being hospitalised compared to the least educated, with reductions observed in all households as well as those that had used the Aarogyasri. For CHE the inequality disappeared in 2012 in both groups. Sub-group analyses by economic status, social groups and rural-urban residence showed a decrease in relative indices of inequality in most groups. Nevertheless, inequalities in hospitalisation and CHE persisted across most groups. CONCLUSION: During the time of the Aarogyasri scheme implementation inequalities in access to hospital care were substantially reduced but not eliminated across the education divide. Universal access to education and schemes such as Aarogyasri have the synergistic potential to achieve equity of access to healthcare.

Use of standardised patients to assess antibiotic dispensing for tuberculosis by pharmacies in urban India: a cross-sectional study.

BACKGROUND: India's total antibiotic use is the highest of any country. Patients often receive prescription-only drugs directly from pharmacies. Here we aimed to assess the medical advice and drug dispensing practices of pharmacies for standardised patients with presumed and confirmed tuberculosis in India. METHODS: In this cross-sectional study in the three Indian cities Delhi, Mumbai, and Patna, we developed two standardised patient cases: first, a patient presenting with 2-3 weeks of pulmonary tuberculosis symptoms (Case 1); and second, a patient with microbiologically confirmed pulmonary tuberculosis (Case 2). Standardised patients were scheduled to present each case once to sampled pharmacies. We defined ideal management for both cases a priori as referral to a health-care provider without dispensing antibiotics or steroids or both. FINDINGS: Between April 1, 2014, and Nov 29, 2015, we sampled 622 pharmacies in Delhi, Mumbai, and Patna. Standardised patients completed 1200 (96%) of 1244 interactions. We recorded ideal management (defined as referrals without the use of antibiotics or steroids) in 80 (13%) of 599 Case 1 interactions (95% CI 11-16) and 372 (62%) of 601 Case 2 interactions (95% CI 58-66). Antibiotic use was significantly lower in Case 2 interactions (98 [16%] of 601, 95% CI 13-19) than in Case 1 (221 [37%] of 599, 95% CI 33-41). First-line anti-tuberculosis drugs were not dispensed in any city. The differences in antibiotic or steroid use and number of medicines dispensed between Case 1 and Case 2 were almost entirely attributable to the difference in referral behaviour. INTERPRETATION: Only some urban Indian pharmacies correctly managed patients with presumed tuberculosis, but most correctly managed a case of confirmed tuberculosis. No pharmacy dispensed anti-tuberculosis drugs for either case. Absence of a confirmed diagnosis is a key driver of antibiotic misuse and could inform antimicrobial stewardship interventions. FUNDING: Grand Challenges Canada, Bill & Melinda Gates Foundation, Knowledge for Change Program, and World Bank Development Research Group.

Private sector participation in delivering tertiary health care: a dichotomy of access and affordability across two Indian states.

UNLABELLED: Poor quality care in public sector hospitals coupled with the costs of care in the private sector have trapped India's poor in a vicious cycle of poverty, ill health and debt for many decades. To address this, the governments of Andhra Pradesh (AP) and Maharashtra (MH), India, have attempted to improve people's access to hospital care by partnering with the private sector. A number of government-sponsored schemes with differing specifications have been launched to facilitate this strategy. AIMS: This article aims to compare changes in access to, and affordability and efficiency of private and public hospital inpatient (IP) treatments between MH and AP from 2004 to 2012 and to assess whether the health financing innovations in one state resulted in larger or smaller benefits compared with the other. METHODS: We used data from household surveys conducted in 2004 and 2012 in the two states and undertook a difference-in-difference (DID) analysis. The results focus on hospitalization, out-of-pocket expenditure and length of stay. RESULTS: The average IP expenditure for private hospital care has increased in both states, but more so in MH. There was also an observable increase in both utilization of and expenditure on nephrology treatment in private hospitals in AP. The duration of stay recorded in days for private hospitals has increased slightly in MH and declined in AP with a significant DID. The utilization of public hospitals has reduced in AP and increased in MH. CONCLUSION: The state of AP appears to have benefited more than MH in terms of improved access to care by involving the private sector. The Aarogyasri scheme is likely to have contributed to these impacts in AP at least in part. Our study needs to be followed up with repeated evaluations to ascertain the long-term impacts of involving the private sector in providing hospital care.

Use of standardised patients to assess quality of tuberculosis care: a pilot, cross-sectional study.

BACKGROUND: Existing studies of the quality of tuberculosis care have relied on recall-based patient surveys, questionnaire surveys of knowledge, and prescription or medical record analysis, and the results mostly show the health-care provider's knowledge rather than actual practice. No study has used standardised patients to assess clinical practice. Therefore we aimed to assess quality of care for tuberculosis using such patients. METHODS: We did a pilot, cross-sectional validation study of a convenience sample of consenting private health-care providers in low-income and middle-income areas of Delhi, India. We recruited standardised patients in apparently good health from the local community to present four cases (two of presumed tuberculosis and one each of confirmed tuberculosis and suspected multidrug-resistant tuberculosis) to a randomly allocated health-care provider. The key objective was to validate the standardised-patient method using three criteria: negligible risk and ability to avoid adverse events for providers and standardised patients, low detection rates of standardised patients by providers, and data accuracy across standardised patients and audio verification of standardised-patient recall. We also used medical vignettes to assess providers' knowledge of presumed tuberculosis. Correct case management was benchmarked using Standards for Tuberculosis Care in India (STCI). FINDINGS: Between Feb 2, and March 28, 2014, we recruited and trained 17 standardised patients who had 250 interactions with 100 health-care providers, 29 of whom were qualified in allopathic medicine (ie, they had a Bachelor of Medicine & Surgery [MBBS] degree), 40 of whom practised alternative medicine, and 31 of whom were informal health-care providers with few or no qualifications. The interactions took place between April 1, and April 23, 2014. The proportion of detected standardised patients was low (11 [5%] detected out of 232 interactions among providers who completed the follow-up survey), and standardised patients' recall correlated highly with audio recordings (r=0·63 [95% CI 0·53-0·79]), with no safety concerns reported. The mean consultation length was 6 min (95% CI 5·5-6·6) with a mean of 6·18 (5·72-6·64) questions or examinations completed, representing 35% (33-38) of essential checklist items. Across all cases, only 52 (21% [16-26]) of 250 were correctly managed. Correct management was higher among MBBS-qualified doctors than other types of health-care provider (adjusted odds ratio 2·41 [95% CI 1·17-4·93]; p=0·0166). Of the 69 providers who completed the vignette, knowledge in the vignettes was more consistent with STCI than their actual clinical practice-eg, 50 (73%) ordered a chest radiograph or sputum test during the vignette compared with seven (10%) during the standardised-patient interaction; OR 0·04 (95% CI 0·02-0·11); p<0·0001. INTERPRETATION: Standardised patients can be successfully implemented to assess tuberculosis care. Our data suggest a big gap between private provider knowledge and practice. Additional work is needed to substantiate our pilot data, understand the know-do gap in provider behaviour, and to identify the best approach to measure and improve the quality of tuberculosis care in India. FUNDING: Grand Challenges Canada, the Bill & Melinda Gates Foundation, Knowledge for Change Program, and the World Bank Development Research Group.

Changes in addressing inequalities in access to hospital care in Andhra Pradesh and Maharashtra states of India: a difference-in-differences study using repeated cross-sectional surveys.

OBJECTIVES: To compare the effects of the Rajiv Aarogyasri Health Insurance Scheme of Andhra Pradesh (AP) with health financing innovations including the Rashtriya Swasthya Bima Yojana (RSBY) in Maharashtra (MH) over time on access to and out-of-pocket expenditure (OOPE) on hospital inpatient care. STUDY DESIGN: A difference-in-differences (DID) study using repeated cross-sectional surveys with parallel control. SETTING: National Sample Survey Organisation of India (NSSO) urban and rural 'first stratum units', 863 in AP and 1008 in MH. METHODS: We used two cross-sectional surveys: as a baseline, the data from the NSSO 2004 survey collected before the Aarogyasri and RSBY schemes were launched; and as postintervention, a survey using the same methodology conducted in 2012. PARTICIPANTS: 8623 households in AP and 10 073 in MH. MAIN OUTCOME MEASURES: Average OOPE, large OOPE and large borrowing per household per year for inpatient care, hospitalisation rate per 1000 population per year. RESULTS: Average expenditure, large expenditures and large borrowings on inpatient care had increased in MH and AP, but the increase was smaller in AP across these three measures. DIDs for average expenditure and large borrowings were significant and in favour of AP for the rural and the poorest households. Hospitalisation rates also increased in both states but more so in AP, although the DID was not significant and the subgroup analysis presented a mixed picture. CONCLUSIONS: Health innovations in AP had a greater beneficial effect on inpatient care-related expenditures than innovations in MH. The Aarogyasri scheme is likely to have contributed to these impacts in AP, at least in part. However, OOPE increased in both states over time. Schemes such as the Aarogyasri and RSBY may result in some positive outcomes, but additional interventions may be required to improve access to care for the most vulnerable sections of the population.