RESEARCH ARTICLE Variations in the quality of tuberculosis care in urban India: A cross-sectional, standardized patient study in two cities Ada Kwan1,2☯, Benjamin Daniels1☯, Vaibhav Saria3, Srinath Satyanarayana4, Ramnath Subbaraman5, Andrew McDowell6, Sofi Bergkvist7, Ranendra K. Das3, Veena Das8, Jishnu Das1,9‡, Madhukar Pai10,11‡* 1 Development Research Group, The World Bank, Washington, District of Columbia, United States of America, 2 University of California at Berkeley, Berkeley, California, United States of America, 3 Institute for a1111111111 Socio-Economic Research on Development and Democracy, Delhi, India, 4 Center for Operational a1111111111 Research, International Union Against TB and Lung Diseases, Paris, France, 5 Department of Public Health a1111111111 and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, United States of a1111111111 America, 6 Centre National de la Recherche Scientifique, Paris, France, 7 ACCESS Health International, a1111111111 New York, New York, United States of America, 8 Department of Anthropology, Johns Hopkins University, Baltimore, Maryland, United States of America, 9 Center for Policy Research, New Delhi, India, 10 McGill International TB Centre, McGill University, Montreal, Canada, 11 Manipal McGill Centre for Infectious Diseases, Manipal Academy of Higher Education, Manipal, India ☯ These authors contributed equally to this work. OPEN ACCESS ‡ These authors are joint senior authors on this work. * madhukar.pai@mcgill.ca Citation: Kwan A, Daniels B, Saria V, Satyanarayana S, Subbaraman R, McDowell A, et al. (2018) Variations in the quality of tuberculosis care in urban India: A cross-sectional, standardized Abstract patient study in two cities. PLoS Med 15(9): e1002653. https://doi.org/10.1371/journal. pmed.1002653 Background Academic Editor: Carlton Evans, Universidad India has the highest burden of tuberculosis (TB). Although most patients with TB in India Peruana Cayetano Heredia, PERU seek care from the private sector, there is limited evidence on quality of TB care or its corre- Received: March 9, 2018 lates. Following our validation study on the standardized patient (SP) method for TB, we Accepted: August 15, 2018 utilized SPs to examine quality of adult TB care among health providers with different qualifi- Published: September 25, 2018 cations in 2 Indian cities. Copyright: © 2018 Kwan et al. This is an open access article distributed under the terms of the Methods and findings Creative Commons Attribution License, which During 2014–2017, pilot programs engaged the private health sector to improve TB man- permits unrestricted use, distribution, and agement in Mumbai and Patna. Nested within these projects, to obtain representative, base- reproduction in any medium, provided the original author and source are credited. line 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 Data Availability Statement: The data and analysis code is available at https://github.com/ diagnostic progression. Between November 2014 and August 2015, the SPs visited repre- qutubproject/plosmed2018. sentatively sampled private providers stratified by qualification: (1) allopathic providers with Funding: This study was funded by Grand Bachelor of Medicine, Bachelor of Surgery (MBBS) degrees or higher and (2) non-MBBS Challenges Canada (S5 0373-01), the Bill & providers with alternative medicine, minimal, or no qualifications. Melinda Gates Foundation (OPP1091843), and the Our main outcome was case-specific correct management benchmarked against the Knowledge for Change Program at the World Bank. Standards for TB Care in India (STCI). Using ANOVA, we assessed variation in correct SS is supported by the Center for Operational Research, The Union (Paris, France). RS is management and quality outcomes across (a) cities, (b) qualifications, and (c) case scenar- supported by a grant from the Bill & Melinda Gates ios. Additionally, 2 micro-experiments identified sources of variation: first, quality in the PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 1 / 22 Quality of tuberculosis care in urban India Foundation via the Arcady group (OPP1154665) presence of diagnostic test results certainty and second, provider consistency for different and a Doris Duke Clinical Scientist Development patients presenting the same case. Award, and acknowledges prior support from a Harvard Center for AIDS Research A total of 2,652 SP–provider interactions across 1,203 health facilities were analyzed. (5P30AI060354-13) and a Harvard Catalyst KL2/ Based on our sampling strategy and after removing 50 micro-experiment interactions, 2,602 CMERIT Award (KL2 TR001100). MP is a recipient interactions were weighted for city-representative interpretation. After weighting, the 473 of a Tier 1 Canada Research Chair from Canadian Patna providers receiving SPs represent 3,179 eligible providers in Patna; in Mumbai, the Institutes of Health Research. The funders had no role in study design, data collection and analysis, 730 providers represent 7,115 eligible providers. Correct management was observed in 959 decision to publish, or preparation of the out of 2,602 interactions (37%; 35% weighted; 95% CI 32%–37%), primarily from referrals manuscript. and ordering chest X-rays (CXRs). Unnecessary medicines were given to nearly all SPs, Competing interests: We have read the journal’s and antibiotic use was common. Anti-TB drugs were prescribed in 118 interactions (4.5%; policy, and the authors of this manuscript have the 5% weighted), of which 45 were given in the case in which such treatment is considered cor- following competing interests: MP is a member of rect management. the Editorial Boards of PLOS Medicine and PLOS ONE and is also an editor of the PLOS Tuberculosis MBBS and more qualified providers had higher odds of correctly managing cases than Channel. MP previously served as a consultant to non-MBBS providers (odds ratio [OR] 2.80; 95% CI 2.05–3.82; p < 0.0001). Mumbai non- the Bill & Melinda Gates Foundation. The other MBBS providers had higher odds of correct management than non-MBBS in Patna (OR authors have no competing interests to declare. 1.79; 95% CI 1.06–3.03), and MBBS providers’ quality of care did not vary between cities Abbreviations: AFB, acid-fast bacillus; AYUSH, (OR 1.15; 95% CI 0.79–1.68; p = 0.4642). In the micro-experiments, improving diagnostic Ayurveda, Yoga, Unani, Siddha, or Homeopathy; CXR, chest X-ray; DOTS, directly observed certainty had a positive effect on correct management but not across all quality dimensions. treatment, short course; DST, drug susceptibility Also, providers delivered idiosyncratically consistent care, repeating all observed actions, test; FQ, fluoroquinolone; HRZE, isoniazid, including mistakes, approximately 75% of the time. The SP method has limitations: it cannot rifampicin, pyrazinamide and ethambutol; INR, account for patient mix or care-management practices reflecting more than one patient– Indian rupee; ISTC, International Standards for TB Care; MBBS, Bachelor of Medicine, Bachelor of provider interaction. Surgery; MDR, multidrug resistant; NSP, National Strategic Plan; OR, odds ratio; PPIA, Private Conclusions Provider Interface Agency; RNTCP, Revised National TB Control Programme; SP, standardized Quality of TB care is suboptimal and variable in urban India’s private health sector. Address- patient; STCI, Standards for TB Care in India; TAG, ing this is critical for India’s plans to end TB by 2025. For the first time, we have rich mea- Technical Advisory Group; TB, tuberculosis; Xpert sures on representative levels of care quality from 2 cities, which can inform private-sector MTB/RIF, Xpert Mycobacterium tuberculosis/ TB interventions and quality-improvement efforts. Rifampicin. Author summary Why was this study done? • India accounts for a quarter of the world’s estimated 10.4 million new tuberculosis (TB) cases per year, nearly a third of the 1.7 million annual TB deaths, and a third of the esti- mated 4 million “missing patients” who are either not diagnosed or are not reported to national TB programs. • The private health sector provides the bulk of primary care in India, serving as the first point of contact for 50% to 70% of patients with TB symptoms. The private sector com- prises a wide range of qualification levels: allopathic providers with Bachelor of Medi- cine, Bachelor of Surgery (MBBS) or higher degrees; Ayurveda, Yoga, Unani, Siddha, or Homeopathy (AYUSH) practitioners (practitioners with degrees in alternative medicine or traditional systems of health); and providers with other or no formal qualifications, who are known to provide a large proportion of primary care. PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 2 / 22 Quality of tuberculosis care in urban India • Little is known about quality of TB care in the private sector; however, the Government of India has prioritized the engagement of the private sector in the National Strategic Plan (NSP) for TB elimination (2017–2025). What did the researchers do and find? • In the 2 Indian cities of Mumbai and Patna, we used a list of all private-sector providers to construct a representative sample for a quality of care surveillance project using the standardized patient (SP) method. • During 2014–2015, the SPs—seemingly healthy adults hired locally and trained to con- vincingly portray symptoms of illness or test results to providers—conducted a total of 2,652 incognito visits among 1,203 health facilities. SPs portrayed cases representing 4 different stages of TB progression and diagnosis and reported the providers’ actions and prescriptions for analysis. • We report 4 novel findings in this publication. First, benchmarked against national and international standards of TB care, only 35% of interactions resulted in standards-com- pliant care during a one-time visit to a healthcare provider. • Second, lack of adherence to TB standards does not represent a typical “alternative” care pattern that would be appropriate for polluted urban environments because providers followed multiple different protocols. • Third, there is a wide range of estimated quality in each qualification stratum, and pro- viders demonstrate consistency with their own previous behaviors. • Finally, providers offer more TB-focused care in cases with higher diagnostic certainty provided by the patient. What do these findings mean? • Although the SP method deployed in this study cannot account for patient mix or care- management practices reflecting more than one patient–provider interaction, we find that quality of TB care is suboptimal and variable in urban India’s private health sector. Therefore, improving quality of TB management in the private sector must be a priority for India’s TB elimination strategy. • With large-scale, city-level representative estimates, these findings can inform specific efforts for private-sector TB interventions and quality improvement. Introduction India accounts for a quarter of the estimated 10.4 million new tuberculosis (TB) cases world- wide annually, nearly a third of the 1.7 million annual TB deaths, and a third of the estimated 4 million “missing patients” who are either not diagnosed or are not reported to national TB programs [1]. Identifying these missing patients with TB, accurately diagnosing patients in a PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 3 / 22 Quality of tuberculosis care in urban India timely manner, and providing all patients with quality treatment is critical for reducing TB incidence and mortality rates [2]. In India, studies have demonstrated that the private health sector provides the bulk of pri- mary care, is the first point of contact for 50% to 70% of patients with TB symptoms [3–5], and prescribes nearly twice the amount of anti-TB drugs compared to the public sector [6]. How- ever, navigating the private health sector can be medically and economically costly: patients with TB who seek care experience a median of 33.5 days of diagnostic and treatment delays, convoluted pathways with multiple visits to an average of 3 providers before diagnosis, and a broken cascade of care even if diagnosed [4,5,7,8]. With the emergence of drug-resistant strains, these deficits may perpetuate disease transmission and hinder control efforts, particu- larly for high-density urban areas [9]. The Government of India now recognizes that engaging the private sector is critical to TB control, and it has included this as an explicit goal in the government’s National Strategic Plan (NSP) for TB elimination (2017–2025). The NSP articulates a commitment to massively expand private provider engagement and calls for a 6-fold increase in TB case notifications from the private sector, to 2 million patients per year by 2020 [10]. One key challenge for any effort that engages the private sector is the wide array of health- care providers, most of whom are not engaged with India’s Revised National TB Control Pro- gramme (RNTCP) [11]. The sector comprises providers trained in biomedicine with Bachelor of Medicine, Bachelor of Surgery (MBBS) or higher degrees (such as MDs and specialized MDs), practitioners of alternative medicine and healthcare (such as those who hold degrees in Ayurveda, Yoga, Unani, Siddha, or Homeopathy [abbreviated AYUSH]), informal providers with minimal or no qualifications, and pharmacists and laboratories. All private providers with MBBS or higher qualifications can provide TB care, and AYUSH practitioners, other non-MBBS providers, and pharmacists generally do not treat TB [12–14]. TB medications are included in Schedule H1, a restricted drug list, in India and therefore can only be dispensed on the basis of prescriptions from MBBS or higher providers. Additional evidence demonstrates that pharmacists do not dispense TB medications over the counter [13,14]. In the private sector, there is no uniform diagnostic algorithm that is practiced, and research demonstrates that providers use diverse approaches (e.g., clinical diagnosis only and clinical diagnosis with chest X-ray [CXR] confirmation, with infrequent use of microbiological tests) [12,15]. Xpert Mycobacterium tuberculosis/Rifampicin (Xpert MTB/RIF), also known as GeneXpert (Cepheid, Sunnyvale, CA), a molecular diagnostic test that detects TB as well as rifampicin-resistant TB, is available in certain private laboratories, and anecdotal evidence sug- gests that providers use these diagnostics selectively based on patients’ ability to pay and patient risk factors, such as suspected drug resistance. Effective private-sector engagement therefore demands a deep understanding of how private providers behave and what predicts their practice patterns [11]. Between 2014 and 2016, the Bill & Melinda Gates Foundation India Country Office, along with city and state governmental partners, funded 2 Private Provider Interface Agency (PPIA) pilot programs in Mumbai and Patna. The PPIA pilots were private-sector engagement efforts to increase case notifications and improve TB management. Our study was a part of this larger effort to improve quality of care in both cities. Using the baseline data from the quality of care surveillance, the objectives of this study are to answer the following 2 research questions: (1) what are city-representative levels of quality of TB care in urban India across private provider qualifications and cities and (2) to what extent can variation in quality of care be explained? In this study, we build on our extensive prior work that validated the use of the standard- ized (or simulated) patient (SP) method for assessing TB care quality and for directly PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 4 / 22 Quality of tuberculosis care in urban India measuring levels of quality of TB care in India, China, and Kenya [12,14,16–18]. The SP method, which is considered the gold standard method to assess provider practice, has been increasingly used to capture levels of quality of care for TB and other health conditions [12,16– 20]. In order to provide city-representative measures on what explains levels of quality, we report data on 2,602 SP–provider interactions across 1,203 representatively sampled health facilities in Mumbai and Patna. We additionally report results from 2 micro-experiments aimed to explain variation in our main outcome of interest: correct case management during a single encounter with a provider. Methods Study settings We conducted this study in Mumbai and urban Patna, when the 2 PPIA pilots were in the first year of implementation [21,22]. Patna is the capital of the state of Bihar, one of the least developed Indian states, with an annual per capita income of 30,000 Indian rupees (INR; US $470), and urban Patna has a population of 2.049 million city inhabitants (2011 census figure). Mumbai is the relatively wealthier port capital of the state of Maharashtra and is home to 12 million inhabitants (2011 census figure), with an annual per capita income of 180,000 INR (US $2,845). Although both cities have government clinics and hospitals for patients, the mostly unregu- lated private sector remains the dominant source of primary healthcare. However, the struc- ture of the private sector is very different across these 2 cities. In Patna, MBBS-qualified providers tend to operate stand-alone, single-provider clinics, whereas in Mumbai, they work in several stand-alone, single-provider clinics as well as multiple multiprovider facilities or in hospitals with a mix of MBBS providers and specialists with higher qualifications. Patna non- MBBS providers tend to be those with other or no qualifications, whereas in Mumbai, non- MBBS providers are predominantly AYUSH practitioners. In this paper, we refer to the group of allopathic providers with MBBS degrees or higher qualifications as “MBBS providers” and to all others as “non-MBBS providers” regardless of the specific qualifications of the providers, in accordance with our sampling stratification. In the TB context, 97,001 patients with TB were officially notified in 2016 in the state of Bihar, and 195,139 cases were notified in the state of Maharashtra [23]. Because, as studies sug- gest, most TB cases are treated in the private sector, many other cases are not notified to national TB authorities, and therefore the above numbers underestimate the extent of the dis- ease burden. The prevalence of drug-resistant TB strains is increasing in both cities, and drug- resistance concerns have been prominent in Mumbai, particularly with the emergence of totally drug-resistant TB strains [24]. Study design The SP survey methodology consists of 3 steps: creating a sampling frame, measuring quality, and analyzing the resulting data. We briefly describe each step here, with additional details in Supporting information (S1–S3 Text). Provider and facility sampling. In both Mumbai and Patna, field officers hired by the PPIAs conducted street-by-street mapping exercises in 2014 to construct a comprehensive, “universe” list of all providers and facilities across the private health sectors of both cities. Pro- viders eligible for the SP study were restricted to those known to see adult outpatients with respiratory symptoms in the private health sector. These include most primary care providers but exclude, for instance, orthopedists, gynecologists, ophthalmologists, and pediatricians. Using the universe list, we then representatively sampled eligible providers from purposively PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 5 / 22 Quality of tuberculosis care in urban India sampled geographical areas within each city, which were identified with implementation part- ners for the SP study in the context of the PPIA pilot programs. Providers were selected with random sampling stratified by PPIA program enrollment status and provider qualification (Table 1). This was done to estimate baseline measures for quality of TB care in these cities and, in ongoing work, evaluate the impact of the programs (see S1 Text) (we note that a strati- fied analysis by PPIA versus non-PPIA is not a focus of this paper but a focus of the larger impact evaluation study that is ongoing). In Mumbai, we sampled 331 MBBS facilities and 500 non-MBBS providers, and in Patna, we sampled 471 MBBS and 120 non-MBBS providers (S7 Fig). To estimate baseline quality measures, the data were weighted according to appropriate sampling proportions in both cities (S2 Text). SP cases were then assigned to providers to ensure that (a) providers of all types would receive a mix of multiple SP case scenarios and (b) the risk of detection would be minimized (i.e., in order to minimize the likelihood of providers being suspicious of SPs or detecting SPs as not real patients, the schedule for SP visits were conducted such that providers would not receive more than 2 SP cases within 5 days of each other and that Case 1 would visit before Cases 2–4 in order to prevent any potential priming effect from a provider seeing a more advanced or obvious TB case before a less advanced one). Interaction completion rates were uniformly high, with only Patna MBBS, non-PPIA pro- viders having less than 85% of initially scheduled providers successfully visited (this proportion was 71%, due to many being discovered as specialized practitioners who did not treat respira- tory conditions). When interactions could not be completed at an initially scheduled provider, they were completed at an identically sampled replacement if possible (S1 Text); therefore, the total number of unique providers in the data is greater than the number initially sampled. Each provider in our sample received up to 4 SP visits at a given location. Measuring quality using SPs. The advantages of SP-based measures of medical care qual- ity in general [16,25] and for TB specifically have been discussed previously [12,14]. For this study, 4 distinct SP cases were developed and agreed upon by a Technical Advisory Group (TAG) made up of clinicians, economists, anthropologists, experts in international and national TB guidelines, and other stakeholders (S1 Text), after which the cases were validated in a pilot study [12]. Our main outcome, correct management, was benchmarked against the Standards for TB Care in India (STCI) and the International Standards for TB Care (ISTC) and was agreed upon by the TAG [26,27] (Table 2). Each case was developed with a standard- ized opening statement and scripted presentation that would advance the provider towards a TB diagnosis and an appropriate case management action, which could include referral, labo- ratory testing, or treatment initiation, depending on the case scenario. Cases 1, 2, and 3 represented adult pulmonary TB at various stages of diagnostic certitude. Case 1 presents as a classic case of pulmonary TB with 2 to 3 weeks of cough and fever. Case 2 is similar to Case 1; however, the SP additionally has completed a 1-week course of broad-spec- trum antibiotics without any improvement and carries an abnormal CXR dated within 2 weeks of the interaction. Case 3 has visited the local government hospital and carries the results of a sputum smear microscopy acid-fast bacillus (AFB) test, which is positive for active TB. Similar to previously published SP studies, the SPs in this study were recruited from the local community, hired, and extensively trained to present the same case to multiple providers. Interaction details were recorded by field supervisors in a structured exit questionnaire within 1 to 2 hours after each visit. For this study, a total of 24 SPs (7 females and 17 males) were recruited, trained, and hired as staff (see S1 Text for a further description). In all scenarios in which the SP carried medical reports or images, the SPs conveyed to the provider that they did not know or understand what the reports showed—thereby varying the PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 6 / 22 Quality of tuberculosis care in urban India Table 1. Sampling and weighting descriptions. Sample Number Sampling Number Case Assignment Case 1 Case 1 Case 2 Case 2 Case 3 Case 3 Case 4 Case 4 Description in City Methodology in Data Interactions Weight Interactions Weight Interactions Weight Interactions Weight Patna: non- 1,074 Random sample 59 Each provider 91 0.00371 20 0.01689 20 0.01689 18 0.01877 MBBS, non- drawn from Patna was assigned 2 PPIA block 34/73 cases. Case 1 was Patna: non- 264 wards, Danapur 60 assigned to all 93 0.00089 20 0.00415 20 0.00415 20 0.00415 MBBS, block 40/40 providers. Then, PPIA wards, Phulwari each provider was Sharif block 28/28 randomly wards and assigned to also stratified by receive Case 2, qualification and Case 3, or Case 4 PPIA status as of (1:1:1 ratio). Non- September 25, MBBS providers 2014. who had already received Case 1 by December 31, 2014 were selected to receive an identical Case 1 (“repeat Case 1 visit”) portrayed by a different SP between January 8, 2015 and February 17, 2015. Patna: 1,642 Random sample 256 Each provider 253 0.00204 70 0.00738 77 0.00671 85 0.00608 MBBS, non- drawn from Patna was assigned 2 PPIA block 34/73 cases. Case 1 was Patna: 199 wards, Danapur 98 assigned to all 136 0.00046 28 0.00224 33 0.00190 35 0.00179 MBBS, block 40/40 providers. Then, PPIA wards, Phulwari each provider was Sharif block 28/28 randomly wards and assigned to also stratified by receive Case 2, qualification and Case 3, or Case 4 PPIA status as of (1:1:1 ratio). January 2015. MBBS providers who had already received Case 1 by December 31, 2014 were selected to receive an identical Case 1 (“repeat Case 1 visit”) portrayed by a different SP between January 8, 2015 and February 17, 2015. Mumbai: 3,330 Drawn from 4 418 Each provider 412 0.00114 104 0.00450 103 0.00454 205 0.00228 non-MBBS, purposively was assigned 2 non-PPIA selected high–TB- cases. Each Mumbai: 261 burden and high– 87 provider was 87 0.00042 21 0.00175 22 0.00167 42 0.00087 non-MBBS, slum-population assigned Case 1. PPIA wards and Then, each stratified by provider was qualification and randomly PPIA status as of assigned to January 24, 2014. receive Case 2, Case 3, or Case 4 (1:1:2 ratio). (Continued ) PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 7 / 22 Quality of tuberculosis care in urban India Table 1. (Continued) Sample Number Sampling Number Case Assignment Case 1 Case 1 Case 2 Case 2 Case 3 Case 3 Case 4 Case 4 Description in City Methodology in Data Interactions Weight Interactions Weight Interactions Weight Interactions Weight Mumbai: 3,374 Facility-level: 127 PPIA hubs were 134 0.00354 69 0.00687 28 0.01693 30 0.01580 MBBS, non- PPIA hospital assigned 1 SP PPIA (i.e., “hub”) walk-in, and non- Mumbai: 150 census from 98 PPIA hubs were 171 0.00012 53 0.00040 51 0.00042 51 0.00042 MBBS, entire Mumbai assigned 2 or 3 SP PPIA and comparable walk-ins. PPIA and purposively hubs received SP1 selected non- only for walk-ins. PPIA from 4 Non-PPIA hubs wards (same as were all assigned non-MBBS SP1 walk-ins; a sample wards) random half were with PPIA status assigned SP2; a as of April 2015. random half were Provider-level: assigned SP3, Provider selection with the other to maximize half assigned SP4 sample size drawn without a sputum from PPIA report. Providers hospitals only at networked from 18 high–TB- locations were burden and high– assigned 2–4 SPs slum-population given existing wards and based knowledge at the on PPIA activity time of as of April 2015. scheduling. All providers received SP1, but PPIA providers who saw an SP1 during walk-ins were not assigned another SP1. A random half were assigned SP2. A random half were assigned SP3 with a sputum report and SP4 without a sputum report; the other half received SP4 with a sputum report (the experimental subsample). Abbreviations: MBBS, Bachelor of Medicine, Bachelor of Surgery; PPIA, Private Provider Interface Agency; SP, standardized patient; TB, tuberculosis. https://doi.org/10.1371/journal.pmed.1002653.t001 information available to the provider without altering the patient’s revealed beliefs or expecta- tions. To assess the extent to which provider behavior is consistent across patients with identi- cal presentations, 109 of the Case 1 interactions in Patna were completed at providers who had already completed a Case 1 interaction with a different SP actor. Case 4 presents as an adult multidrug resistant (MDR) TB suspect with 4 weeks of cough and fever. The SP recalls receiving treatment from the government hospital in the past year for a similar condition and, if questioned, admits to not completing the TB treatment during the previous episode. All flags point towards TB recurrence, which should raise concern about drug resistance. Among 50 of the sampled Mumbai MBBS or higher providers, we randomly assigned SPs to present an experimental variant of Case 4, who carried the same TB-positive PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 8 / 22 Quality of tuberculosis care in urban India sputum AFB report as in Case 3. With this variant, we aimed to analyze the effect of a TB-posi- tive diagnostic test signal by comparing quality of care provided to SPs portraying Case 4 with versus without the AFB report. To facilitate outcome assessment for each interaction, labeled medicines and prescriptions given to the SPs were coded into 4 categories: anti-TB drugs, fluoroquinolone (FQ) antibiotics, other broad-spectrum antibiotics, or steroids. Coding was done independently by 2 doctors with expertise in TB (SS) and infectious diseases (RS). We chose to retain FQs as a distinct category of antibiotics because they can mask the presence of TB, rendering diagnosis more difficult, and can lead to delays in diagnosis [28]. Additionally, in Mumbai, providers often dispensed loose, unlabeled pills to the SPs. To properly identify these pills, we employed 2 pharmacists who worked independently to code them. On the basis of their assessments, we determined whether the variety of medicines given for each interaction included at least 1 broad-spectrum antibiotic and/or at least 1 steroid. In addition to reporting the details of case management, each interaction was broadly clas- sified as “correctly managed” or not, according to the STCI [29]. Taking a lenient approach, providers were not penalized for the use of unnecessary or even potentially harmful medicines, and thus the results presented are upper-bound estimates of quality, as measured by adherence to TB standards of care. The definitions of correct management are detailed in Table 2, and the levels of prescribing and dispensing medications are analyzed in the Appendix (S3 Text). S1 Fig elaborates on the “lenient” approach, illustrating the proportion of our “correct man- agement” providers who would have been considered not correct if we had penalized other medications. Table 2. SP case descriptions, patient presentations, and correct management definitions. SP Case Case Description Presentation of Patient Expected Correct Case Management Case 1: Naïve Classic case of presumed TB with 2–3 weeks Presents with presumptive TB, for the first time, Recommendation for sputum testing, chest Suspected TB of cough and fever. to a private healthcare provider, saying “Doctor, radiograph, or referral to a public DOTS center I have a cough that is not getting better and or a private provider or specialist some fever too.” Case 2: Classic case of presumed TB in a patient who Presents after an initial, failed (empirical) Recommendation for sputum testing, chest Suspected TB has had 2–3 weeks of cough and fever. The treatment for symptoms with broad-spectrum radiograph, or referral to a public DOTS center with Abnormal patient has taken a broad-spectrum antibiotic antibiotics and a diagnostic CXR, saying “I have or a private provider or specialist CXR (amoxicillin) given by another healthcare a cough and fever which is not getting better. I provider for 1 week with no improvement. went to a doctor and took the medicines he gave He also carries an abnormal CXR suggestive me and have also had an X-ray done.” The CXR of TB. and blister pack for the antibiotics are shown if the provider asks. Case 3: TB Case Chronic cough with a positive sputum smear Presents with evidence of microbiologically Either referral to a public DOTS center, a private report for TB from a public health facility. confirmed TB, saying “I have had a cough for provider or specialist, or (in the case of a nearly a month now and also have fever. I qualified private provider) initiation of visited [the local government hospital] and they treatment with standard, 4-drug, first-line anti- gave me some medicines and did a sputum test.” TB therapy (HRZE regimen) The sputum report is shown if the provider asks. Case 4: Chronic cough and, if asked, elaborates a Presents as a previously treated patient with TB Recommendation for any DST (culture, line Suspected MDR history of previous, incomplete treatment for with recurrence of the disease (i.e., suspicion of probe assay, or Xpert MTB/RIF) or referral to a TB, which would raise the suspicion of MDR drug resistance), saying “Doctor, I am suffering public DOTS center or to a private provider or TB. from a bad cough. One year ago, I got treatment specialist in [the local public hospital], and it had gotten better. But now I am having cough again.” Abbreviations: CXR, chest X-ray; DOTS, directly observed treatment, short form; DST, drug susceptibility test; HRZE, isoniazid, rifampicin, pyrazinamide, and ethambutol; MDR, multidrug resistant; SP, standardized patient; TB, tuberculosis; Xpert MTB/RIF, Xpert Mycobacterium tuberculosis/Rifampicin. https://doi.org/10.1371/journal.pmed.1002653.t002 PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 9 / 22 Quality of tuberculosis care in urban India Analysis. We report raw proportions for outcomes of interest, with population mean estimates and CIs computed using inverse probability weighting. Based on the universe of private-sector providers listed from the mapping exercise in both cities (S1 and S2 Text), these weights are calculated such that each of the 8 city–case combinations contribute equally to overall estimates. Within each city–case combination, individual interactions are weighted based on the actual proportion of providers enrolled and not enrolled in the PPIA in that city’s provider sampling list within both the MBBS and non-MBBS strata versus the realized sample. Therefore, the percentages reported for case management behaviors represent the esti- mated likelihood of the outcome occurring if a provider were chosen at random from the citywide population of providers rather than the percentage of interactions in our sample in which the behavior was observed. In addition to using these weights to estimate popula- tion likelihoods, we use them to calculate weighted odds ratios (ORs) in logistic regressions comparing variation in quality of care across provider types, city settings, and SP case scenarios. In Supporting information (S3 Text), we present an ANOVA analysis, which was not pre- specified, to determine how well our primary stratification characteristics explain variations in SP management. Among the sampled providers who received repeat Case 1 visits in Patna, we assess the level of consistency that those providers displayed across identical SP Case 1 visits using a different SP actor. We then use a quality proxy—checklist of history questions—to illustrate the amount of variation in provider behavior within each city–case combination. In addition to the ANOVA analysis, we include the outcome of whether an SP was asked to return, which was not prespecified and requested during peer review. Considering that the data for this analysis are a subset of the data generated from a larger research project, we did not encounter any other deviations from the stated prospective analysis plan within the research protocol submitted to the ethics committees (S4 Text). All analyses and programs were written in Stata 14 (Stata, College Station, TX). Ethical approvals Ethical approvals for this study were granted by the McGill University Health Centre in Montreal, Canada (REB No. 14-137-BMB) and the Subcommittee for the Ethical Approval of Projects at the Institute for Socioeconomic Research on Development and Democracy in Delhi, India. All SPs were hired as staff and received training and refresher trainings to pro- tect themselves from potentially harmful events, such as injections during their interactions. For this study, a waiver of provider informed consent was sought with particular attention to the research ethics provisions under the Government of Canada Panel on Research Ethics, as well as a recent study by Rhodes and colleagues (2012) on ethical aspects of simulated patient studies commissioned by the US Department of Health and Human Services [30]. Supported by findings from the validation of the SP method for TB in urban India as reported in Das and colleagues (2015) [12], both ethics committees approved a waiver of provider informed consent in Mumbai and Patna because (1) the combination of informed consent and congregation of providers during association meetings and in the implementa- tion of TB interventions that occurred during the study period posed threats to the scientific validity of the study objectives as well as to the risk of SP detection and (2) there is no more than minimal risk of participation to the SPs or providers [12]. Additional information on— including the rationale behind and approval of—the waiver of provider informed consent is detailed in S1 Text. PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 10 / 22 Quality of tuberculosis care in urban India Results The results are presented in 3 sections. In the first section, we describe overall standards of care, focusing on correct case management, medicine use, and laboratory tests. In the second section, we document variation in the data by provider qualification and city. In the third sec- tion, we document variation across SP cases, focusing on the role of diagnostic certainty. Practice quality overview In our study, 1,288 distinct provider practices were successfully visited by SPs at 1,203 health facilities across both cities. Among these providers, the majority were male (88%), had a clinic assistant (65%), and fell into the age category of 30–50 years (71%), which were all characteris- tics observed by SPs during the interactions. Fig 1 illustrates our main city-level estimates of average case management outcomes among the city-representative sample, with proportions estimated with weights to represent the estimated likelihood of the outcome occurring if a pro- vider was visited by a patient at random from the citywide population of providers. Among 2,602 SP interactions, 959 were correctly managed (35%; 95% CI 32%–37%), and 536 of 2,602 interactions (29%; 95% CI 26%–31%) had any diagnosis given to the patient. Among the 959 correctly managed interactions, 260 (37%; 95% CI 32%–42%) received any diagnosis. Among the correctly managed interactions, a greater proportion of providers ordered a CXR (677 of 959 [53%; 95% CI 48%–57%]) or referred the SP for further care (194 of 959 [36%; 95% CI 31%–40%]) than ordered a microbiological test for diagnosis (318 of 959 Fig 1. City-representative quality of care estimates. City-level estimates of quality of care for each of our case scenarios. These proportions represent the estimated frequency with which the action would be observed if the standardized case scenario was presented to a provider randomly selected from the sampling frame. These estimates are calculated using inverse probability weights corresponding to the sample frame as detailed in S2 Text for every city–qualification–PPIA–case combination in the data. N = 2,602. AFB, acid-fast bacilli; PPIA, Private Provider Interface Agency; TB, tuberculosis; Xpert MTB/RIF, Xpert Mycobacterium tuberculosis/Rifampicin, also known as GeneXpert. https://doi.org/10.1371/journal.pmed.1002653.g001 PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 11 / 22 Quality of tuberculosis care in urban India [31%; 95% CI 27%–36%]). Among the 194 referrals, 52% were to the private and 48% to the public sector. Microbiological testing, including drug susceptibility testing (DST), was relatively infre- quent across all case scenarios. Sputum smear testing was ordered in 389 of 2,602 (18%; 95% CI 16%–20%), sputum culture in 28 of 2,602 (2%; 95% CI 1%–3%), and Xpert MTB/RIF in 108 of 2,602 interactions (2%; 95% CI 1%–3%). For Case 2, when the SP carried an abnormal CXR suggestive of TB, 45 of 385 SP interactions (7%; 95% CI 4%–10%) resulted in any DST, while 99 of 385 were ordered a new CXR (25%; 95% CI 20%–30%). Similarly, of 486 interactions in which the SP presented with recurrent TB and suspected MDR-TB (Case 4), 26 were recom- mended any DST (3%; 95% CI 1%–5%). Medicines were very frequently prescribed or dispensed, and we did not count the use of additional or unnecessary medications against the provision of correct management. At least 1 medication was prescribed or dispensed in 2,239 of 2,602 interactions (79%; 95% CI 76%– 82%), with an average of 3.11 medications per interaction (95% CI 2.99%–3.23%). Across all 2,602 interactions, broad-spectrum antibiotics other than FQs were given in 1,227 (39%; 95% CI 36%–42%), FQ antibiotics in 328 (15%; 95% CI 13%–17%), and steroids in 164 interactions (6%; 95% CI 5%–7%). The use of anti-TB medications was minimal and was mostly limited to MBBS-qualified providers. Anti-TB medications were prescribed in 118 of 2,602 interactions (5%; 95% CI 4%– 6%), with MBBS or higher providers accounting for 112 of those 118 instances. Among the 118 TB prescriptions, 113 included correct isoniazid, rifampicin, pyrazinamide and ethambu- tol (HRZE) prescriptions—1 of these additionally included the second-line drug clofazimine, and 2 also included streptomycin. Among the 5 instances that did not include HRZE, 4 were HRE, and 1 was the second-line medication cycloserine prescribed alone. In contrast with correctly managed interactions, interactions in which correct case manage- ment was not observed did not demonstrate any kind of consistent “alternate” protocol that could theoretically be justified in a polluted urban environment that can result in non-specific respiratory symptoms like cough. Given a patient with a 2- or 3-week cough in a polluted city like Patna, providers could, for example, be observed to adopt a “wait-and-see” approach by offering palliative symptomatic care and asking the patient to return after a few days, even though this practice technically falls short of the international and national standards of TB care we used to benchmark management in this study. We do not observe this type of concentration on a single alternative protocol in our data. For example, of the 834 Case 1 interactions that were not correctly managed (Fig 2), 183 (22%) received only a non-FQ broad-spectrum antibiotic; 294 (35%) received a non-FQ broad-spec- trum antibiotic as well as an FQ, steroid, and/or cough syrup; 185 (22%) received 1 or more of those medications without a non-FQ broad-spectrum antibiotic; and 172 (21%) received something else entirely (or nothing at all). Variation by qualification and setting One potential explanation is that the wide variation in management reflects systematic practice variation by qualification and/or setting, and we turn to this hypothesis next. Fig 3 reports ORs for differences in quality of care outcomes by qualification (top panel) and by city strati- fied by qualification (middle and bottom panels). MBBS providers, who make up 58% of all providers in the Patna sampling list and 50% of all providers in the Mumbai list, were more likely than non-MBBS providers to correctly manage cases (weighted OR 2.80; 95% CI 2.05– 3.82; p < 0.0001), ask for CXR and/or sputum tests, and initiate anti-TB treatment. Despite providing relatively higher-quality care, MBBS providers only correctly managed 709 of 1,304 PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 12 / 22 Quality of tuberculosis care in urban India Fig 2. Management of Case 1 when no correct treatment was given. Frequency in which Case 1 was managed with possible combinations of steroids, cough syrups, broad-spectrum antibiotics, and FQs, when no correct management was given. There were N = 834 Case 1 interactions that did not meet the criteria for correct management, and 172 interactions resulted in none of these case management behaviors. FQ, fluoroquinolone. https://doi.org/10.1371/journal.pmed.1002653.g002 interactions (54% of interactions; 95% CI 52%–57%). MBBS providers were also more likely than others to prescribe unnecessary or harmful antibiotics, including FQs, although their use of steroids was notably lower. Additional analysis in S6 Fig shows that the differences between AYUSH and other non- MBBS providers in Patna, where both practice, were surprisingly small. In fact, AYUSH pro- viders were less likely than others to manage or refer cases according to STCI, although the others gave more unnecessary antibiotics. Use of nonallopathic medications was also diverse. For example, although most non-MBBS providers in our Mumbai sample are AYUSH, only 63 of 996 non-MBBS SP interactions in Mumbai (6%; 95% CI 4%–8%) involved explicitly labeled homeopathic or Ayurvedic medicines. By contrast, non-MBBS providers in Patna used labeled Ayurvedic or homeopathic medicines in 113 of 302 interactions (41%; 95% CI 33%–49%). PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 13 / 22 Quality of tuberculosis care in urban India Fig 3. Quality of care differences by provider qualification and location. Estimated ORs between various groups of providers, for the frequency in which the indicated management action is observed across all case scenarios. Panel A reports differences by MBBS qualification level, pooled across all observations. This regression includes controls for city setting and case scenario (N = 2,602). Panels B and C report similar ORs estimated across cities, stratified by MBBS qualification (N = 1,448 and 1,154, respectively). These regressions include controls for case scenario. AFB, acid-fast bacilli; MBBS, Bachelor of Medicine, Bachelor of Surgery; OR, odds ratio; TB, tuberculosis; Xpert MTB/RIF, Xpert Mycobacterium tuberculosis/Rifampicin, also known as GeneXpert. https://doi.org/10.1371/journal.pmed.1002653.g003 PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 14 / 22 Quality of tuberculosis care in urban India Differences in case management were smaller across the 2 cities. Across all cases, Mumbai non-MBBS providers were more likely than Patna non-MBBS providers to correctly manage cases (weighted OR 1.79; 95% CI 1.06–3.03; p = 0.0293), primarily by ordering CXR (weighted OR 3.62; 95% CI 1.85–7.10; p = 0.0002). Most other behaviors were not significantly different across the cities. MBBS-qualified providers were even more similar across cities in terms of correct management (weighted OR 1.15; 95% CI 0.79–1.68; p = 0.4642), with the notable exception that Mumbai MBBS providers utilized Xpert MTB/RIF testing much more fre- quently than MBBS providers in Patna (weighted OR 8.60; 95% CI 2.83–26.10; p = 0.0001). Both MBBS and non-MBBS providers in Mumbai were less likely to prescribe FQs than Patna providers (weighted OR 0.4; 95% CI 0.24–0.66; p = 0.0004, and 0.25; 95% CI 0.15–0.45; p < 0.0001, respectively), and the dispensing or prescribing of steroids and broad-spectrum antibiotics did not differ systematically across the 2 cities. ANOVA decomposition (S3 Fig) shows that our primary stratification characteristics of qualification and setting typically predicted less than 25% of the observed variation in each of our primary case management outcomes with the exception of correct case management and ordering a CXR (for which 25%–50% of observed variation was predicted). By contrast, in a subsample in which 109 Patna providers received a repeat Case 1 interaction (S4 Fig), consis- tency levels between the 2 visits were near 75% for all behaviors. Therefore, we observe that practice is highly variable across providers, but setting and qualification strata can explain only a fraction of the wide variety in management practices. Using essential-history checklist completion as a proxy for the distribution of individual- ized quality levels (S5 Fig), our results suggest that there is a substantial and unexplained idio- syncratic component to quality that varies widely even within each city and qualification level. Rather than tight clustering around the group means, in all cases, we observe a “fat tail” of both low- and high-quality MBBS and non-MBBS providers in each city. Thus, moving beyond averages to full distributions of quality yields important and nuanced additional results for the estimation of “average” outcome quality, both by city and by qualification. When do providers perform better? Variation by SP case The final source of variation we assess is the SP case presentation itself. In our previous work [14], we found that pharmacists were more likely to correctly manage a case if SPs carried a TB-positive diagnostic test, even as the SP made it clear that she did not know what the results of the test meant. The SP cases presented in this study reflect a similar design, with the varied presentation intended to exogenously adjust the providers’ initial degree of certainty about the patient’s true diagnosis. When the SP carried either an abnormal CXR (Case 2) or an AFB-pos- itive sputum report (Case 3), providers were observed to be more likely to order tests consis- tent with a suspicion of TB compared to the Case 1 presentation. In Case 2, in which the SP carried an abnormal CXR, a second CXR (which would ostensi- bly provide no new information) was ordered in 99 of 385 instances (25%; 95% CI 20%–30%). In Case 3, in which the SP carried a TB-positive sputum AFB report, 208 of 354 were recom- mended a CXR (56%; 95% CI 49%–63%), and 54 of 354 were ordered a new AFB smear (16%; 95% CI 11%–21%). In terms of inappropriate behaviors, variation across SP case had some impact on the use of inappropriate medications, but it did not reduce it anywhere close to 0 in any case (S1 Fig). Prescribing unnecessary medicines ranged from 284 of 385 instances in Case 2 (72%; 95% CI 67%–77%) to 1,290 of 1,377 instances in Case 1 (93%; 95% CI 91%–95%). Use of broad-spectrum antibiotics ranged from 105 of 385 Case 2 interactions (29%; 95% CI 23%– 34%) to 799 of 1,377 Case 1 interactions (53%; 95% CI 50%–57%), and use of FQs ranged from PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 15 / 22 Quality of tuberculosis care in urban India Fig 4. Quality of care differences between SP case scenarios. Estimated ORs between specific case scenarios for the frequency with which the indicated management action is observed. Panel A reports estimated ORs between Case 1 and Case 3, including only those providers who received both cases (N = 759 interactions). Panel B reports estimated ORs between Mumbai MBBS providers who received the experimental version of Case 4 that carried the same sputum report against a comparable sample who received the ordinary Case 4 presentation (as described in S1 Text; N = 101 interactions). AFB, acid-fast bacillus; MBBS, Bachelor of Medicine, Bachelor of Surgery; OR, odds ratio; SP, standardized patient; TB, tuberculosis; Xpert MTB/RIF, Xpert Mycobacterium tuberculosis/Rifampicin, also known as GeneXpert. https://doi.org/10.1371/journal.pmed.1002653.g004 43 of 385 Case 2 interactions (12%; 95% CI 8%–16%) to 52 of 354 Case 3 interactions (19%; 95% CI 13%–25%). Fig 4 highlights selected cross-case variation using logistic regressions. The figure reports estimated differences between Case 1 and Case 3, using only providers who received both cases. It also reports differences observed in Case 4 against our alternate version of Case 4 car- rying the same TB-positive sputum AFB report at identically randomly sampled MBBS-quali- fied providers in Mumbai, in which the variation in diagnostic certainty is causally identified through the use of random assignment of the AFB report in an otherwise-identical case presentation. Carrying a positive sputum report in Case 3 was associated with an increase in the fre- quency of CXRs (OR 3.13; 95% CI 1.98–4.96; p < 0.0001) and sputum AFB tests (OR 2.45; 95% CI 1.34–4.47; p = 0.0035), as well as a nonsignificant increase in Xpert MTB/RIF tests (OR 3.88; 95% CI 0.81–18.49; p = 0.0888) and referrals (OR 8.69; 95% CI 3.25–23.2; p < 0.0001) compared to the same providers’ behavior in the Case 1 interactions. In the experimental com- parison in which only the diagnostic information was varied for SPs portraying Case 4 while carrying versus not carrying a TB-positive sputum report (S1 Text), we use the fact that the report was randomly assigned as indicative of causal impact. Among the 50 instances in which Case 4 SPs carried a sputum report, the provider saw the report in 45 instances (90%) and asked detailed questions about the past treatment in 38% of interactions. The results are broadly similar although nonsignificant: when the Case 4 SP carried the sputum report, correct PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 16 / 22 Quality of tuberculosis care in urban India management increased from 29% to 48% (OR 2.22; 95% CI 0.98–5.02; p = 0.0569), largely due to greater provider use of appropriate DST. Providers’ use of medication also decreased from 86% to 72%, though this was not significant (OR 0.41; 95% CI 0.15–1.12; p = 0.0824). However, quality improvements were not consistent across all dimensions: the use of first-line anti-TB medicine, which is not considered correct treatment for a suspected drug-resistant case and could contribute to greater drug resistance, increased from 2% to 18% when the report was presented (OR 10.98; 95% CI 1.33–90.24; p = 0.0258). Discussion TB is a persistent health challenge for India and is one of the top 5 causes of death between the age of 30 to 69 [31]. With India’s goal of eliminating TB by 2025 as stated in the NSP, the suc- cess of this plan heavily depends on whether India’s large, unregulated, and diverse private sec- tor can be effectively engaged to identify missing patients with TB and ensure that all patients with TB receive quality TB care [32]. This study extends the evidence from our pilot study that validated the use of the SP method for assessing TB quality of care in an urban India setting [12] and from our research on TB-management practices of pharmacists assessed with SPs across 4 Indian cities [13,14]. Our validation study assessed quality of TB care from a purposive provider sample, and with this study, we were able to further apply the SP method for TB to analyze representative levels and variation of quality among MBBS and non-MBBS providers in the private health sector of 2 cities. In addition, 2 micro-experiments allow us to better understand the drivers of quality of care in this setting. Our city-representative study shows significant deficits in the average provider’s manage- ment of TB cases in both study cities. This low quality is characterized by underuse of appro- priate diagnostics and widespread use of unnecessary medications, including antibiotics and contraindicated FQs. Even though MBBS-qualified providers managed the SP cases better on average, there was still considerable variation within qualification in each setting and rela- tively little difference between the 2 cities on average. We further observed that TB-specific management increased with diagnostic certainty. We also present suggestive evidence that spe- cific providers adhere consistently to an idiosyncratic protocol when faced with repeated iden- tical cases. Because providers are making the same mistakes consistently, the SP method provides novel information to TB-control programs on the specific actions that need to be improved. Representing the quality variation during the first year of city-wide private-sector engage- ment efforts, our data further underscore the need to work with the private sector to improve quality of TB care. These study results, complemented with the 4-city analysis on pharmacist behaviors, provides new multicity, qualification-specific information for TB control in India. It remains to be seen the extent to which private-sector engagement efforts—such as the PPIA pilots—will make an impact on quality and be able to sustain improvements in quality of care. Incorporating quality measures alongside program implementation is the first step, particu- larly as aspects of the PPIA model are being scaled up in more than 40 Indian cities, supported by the Global Fund. We emphasize that the low observed proportions of correctly managed interactions do not fit a hypothesis in which providers followed an alternate protocol that reflects “what is good for the patient but not for society” (such as a wait-and-see approach for a patient with persis- tent cough). Providers treated the SPs in idiosyncratically different ways without a consistent protocol. Neither are the data consistent with the view that very high patient loads are respon- sible for low quality. Of the weighted 2,602 interactions, 45% had no other patients waiting, PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 17 / 22 Quality of tuberculosis care in urban India 65% had a queue of 1 or fewer, 75% had 2 or fewer, and 95% had 10 or fewer. This is similar to what has been observed in previous SP studies as well as time-and-motion studies in health clinics [33]. We consider, instead, the following 2 broad classes of explanations for this behavior: (a) providers have a difficult time diagnosing TB appropriately, and (b) private providers devi- ate from established standards for financial gain. There is evidence for both types of behavior, implying that quality deficits are not driven by either knowledge gaps or financial incentives alone. In favor of an explanation driven by poor diagnostic skills, we find that improving cer- tainty about the diagnosis had a positive effect on quality of care (although the results are not statistically significant in the Case 4 comparison because of the small sample size, they are quantitatively as large as those in the Case 1 to Case 3 comparison). However, lack of diagnos- tic certainty was not the only indicator of poor quality we observed in our study, nor did qual- ity improve across every dimension when the test results were provided to the provider. Increasing diagnostic certitude improved correct case management but had smaller effects on reducing inappropriate medicine use. This suggests that financial considerations and poor diagnostic ability may both play a role in explaining the patterns we observe and mirror previous findings with pharmacists in 4 urban Indian locations [14,34]. Across settings, we find that these diagnostic practices are highly predictive of whether the provider offers correct management in a given interaction, but we cannot “force” providers to take detailed histories from their patients because a good history and physical is an essential indicator of quality in and of itself. Our study has several strengths and contributes to the literature in several ways. First, we representatively sampled large numbers of private health providers in 2 Indian cities, and after weighting to the city universe of providers, we provide precise estimates of provider behavior at the city level. Because the analysis is representative of these 2 Indian cities, caution is war- ranted when generalizing to a context outside of urban India. Second, by using unannounced SPs, we captured actual provider behavior, as opposed to self-reported knowledge or practices. Given our prior work showing a big “know-do gap” (the gap between what providers know and what they do in actual practice) [12], the SP methodology better reflects reality for patients than any other existing method used to measure quality of care. Third, our study included MBBS-qualified providers, as well as AYUSH providers and those with other or no qualifica- tions, capturing the complexity of training within the Indian private healthcare sector. Fourth, by developing 4 different SP case presentations, we studied how providers dealt with various stages of TB disease and varying levels of diagnostic certainty. Lastly, by assessing outcomes by city, provider qualification, and type of case, we assessed the most important sources of varia- tion in quality of care. While previous studies showed suboptimal quality of care, our study was able to explore the role of provider qualifications on quality using 2 city-wide, representa- tive samples. Our study has limitations. First, because we do not observe how patients actually choose providers, patient sorting by qualification, geography, personal relationships, price, reputa- tion, or other unobserved signals of quality prevents extrapolation to the likely outcomes for actual patients with TB. This remains an important area for future work. Second, our cases are designed as one-time interactions, and the SP data do not reflect follow-up visit path- ways, which have been shown by other studies to be long and convoluted and had various forms in our data (S2 Fig). For instance, we cannot say, from this study, what the doctor would do after the patient has returned after completing a CXR as ordered. To the extent that doctor behavior is different when the patient comes with a CXR that the doctor herself recommended (rather than with a CXR ordered by another doctor), our approximations of provider behavior under different scenarios may be erroneous. The ability for the SP method PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 18 / 22 Quality of tuberculosis care in urban India to measure quality of care measures in follow-up visits with the same SP individual in similar settings has not been published to our knowledge, and—given the frequency of providers asking for patients to return exhibited in this study—it could be worthwhile to explore the potential for the method to assess whether the likelihood of receiving better care increases when a patient returns. With this, it would be important to understand the extent to which real patients return upon a provider’s request, as well as the necessary work needed so that SPs are not detected. While not a limitation per se, we also highlight that our definition of correct case manage- ment follows national and international TB standards of care. We have chosen to use these def- initions because they allow for comparability across studies and disciplines our analyses of the data using a clearly prespecified protocol. But our data could also raise questions about the via- bility and validity of these standards. For instance, it is reasonable to ask whether—in cities with air pollution, which can cause respiratory symptoms—healthcare providers should be asked to send a patient with a 3-week cough for a sputum test rather than giving them symp- tomatic therapy and asking them to follow up as required. Our data are not consistent with the idea that providers were following a single alternate protocol because virtually every combination of drug classes was used for the SP cases. Never- theless, there could be justifiable reasons why providers still choose to deviate from estab- lished standards of care. One way, then, to interpret our findings and our use of the term “correct case management” is as an ordinal ranking rather than adherence to a standard: pro- viders who follow the standards are of higher quality, but this does not imply that those who do not follow the standards necessarily provide “incorrect” care. Instead of imposing alter- nate standards, we have chosen to present the full set of management practices for each SP case to allow readers to make their own more nuanced judgments. We have also made the data publicly available so that researchers can simulate correct management under alternate standards, in turn stimulating debate around whether these standards themselves require fur- ther revision. Despite the limitations, our large-scale, 2-city quality of care study provides accurate and representative estimates of provider behavior that may inform not only quality-improvement efforts in health but also interventions to improve TB care and reduce transmission in the community. Supporting information S1 Text. Fieldwork details. Description of SP case scenarios; SP recruitment, script develop- ment, and training; rationale for approved waiver of provider informed consent; provider sam- pling; assignment of SP cases to providers. SP, standardized patient. (PDF) S2 Text. Statistical methods. (PDF) S3 Text. Supplementary results. Assessing variation in provider management of cases; ANOVA decomposition of explained variance; consistency of individual providers across vis- its; distributions of providers within city-qualification groups. (PDF) S4 Text. Pre-analysis plan from study protocol. Study design and methods, and data analysis plan. (PDF) PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 19 / 22 Quality of tuberculosis care in urban India S1 Fig. Correct management of SP case scenarios, with alternate definitions. SP, standard- ized patient. (PDF) S2 Fig. Follow-up requests from providers by case management outcome, with alternate definitions. (PDF) S3 Fig. ANOVA decomposition of quality correlates. (PDF) S4 Fig. Consistency of providers in repeated Case 1 visits. (PDF) S5 Fig. Distributions of checklist completion in Case 1 visits. (PDF) S6 Fig. Comparison between AYUSH and non-AYUSH treatment outcomes. AYUSH, Ayurveda, Yoga, Unani, Siddha, or Homeopathy. (PDF) S7 Fig. Sampling flowcharts by primary strata. (PDF) S1 Checklist. STROBE statement. (PDF) Acknowledgments We thank Puneet Dewan, Sameer Kumta, Shibu Vijayan, Sirisha Papineni, and Nita Jha for useful input on implementation, analysis, and interpretation; Rajan Singh, Purshottam, Chinar Singh, Geeta, Devender, Varun Kumar, Anand Kumar, Babloo, and Charu Nanda, who super- vised and implemented the ISERDD field work; all the standardized patients for their dedica- tion and hard work; and Caroline Vadnais for excellent administrative support. The findings, interpretations, and conclusions expressed here are those of the authors and do not necessarily represent the views of the World Bank, its executive directors, or the gov- ernments they represent. Author Contributions Conceptualization: Jishnu Das, Madhukar Pai. Data curation: Ada Kwan, Benjamin Daniels, Vaibhav Saria, Srinath Satyanarayana, Ramnath Subbaraman, Andrew McDowell, Sofi Bergkvist, Veena Das. Formal analysis: Ada Kwan, Benjamin Daniels, Vaibhav Saria, Andrew McDowell. Funding acquisition: Jishnu Das, Madhukar Pai. Methodology: Ada Kwan, Benjamin Daniels, Ranendra K. Das, Veena Das, Jishnu Das, Mad- hukar Pai. Project administration: Ada Kwan, Sofi Bergkvist, Madhukar Pai. Supervision: Ada Kwan, Benjamin Daniels, Ranendra K. Das, Veena Das, Jishnu Das, Madhu- kar Pai. PLOS Medicine | https://doi.org/10.1371/journal.pmed.1002653 September 25, 2018 20 / 22 Quality of tuberculosis care in urban India Validation: Srinath Satyanarayana, Ramnath Subbaraman. Visualization: Benjamin Daniels. Writing – original draft: Ada Kwan, Benjamin Daniels. Writing – review & editing: Ada Kwan, Benjamin Daniels, Vaibhav Saria, Srinath Satyanar- ayana, Ramnath Subbaraman, Andrew McDowell, Sofi Bergkvist, Ranendra K. Das, Veena Das, Jishnu Das, Madhukar Pai. References 1. World Health Organization. Global Tuberculosis Report 2017. Geneva: WHO; 2017. 2. 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