Quality of Tuberculosis Care in Mumbai, India

By taking advantage of a randomized roll-out design of the PPIA program in Mumbai, this evaluation aims to determine the causal effects of the program on quality of care among private sector health providers. The evaluation is embedded in an existing quality of care surveillance project that uses standardized patients to assess the quality of tuberculosis (TB) care in Mumbai, India. Below is a description of (1) the TB intervention implemented by the PPIA, (2) the quality of TB care (QuTUB) surveillance project, and (3) the randomized roll-out of the PPIA program among a subset of providers in order to isolate the impact of the program on quality of care.

The entire program and its implementation are external to the researchers. To better understand the impact of the program using an already approved surveillance study, the researchers use a stepped-wedge design that involves a sequential roll-out of the program to a subset of providers over a period of time where the order of roll-out is randomized.

1. PPIA intervention: Between January 2014 and December 2016, the pilot PPIA program was independently implemented by the non-governmental organization PATH (Program for Appropriate Technology in Health as it is known formerly) in Mumbai city. In its role as the PPIA in Mumbai, PATH's aim is to strengthen existing efforts to control TB through engagement of the private health sector. Through this network, the objectives are to facilitate early and accurate diagnosis with proper notification of cases and to ensure appropriate treatment and treatment adherence to completion among TB patients in the private sector. In order to achieve these objectives, the PPIA initiated and expanded a private sector network based on a hub-and-spoke model. Hubs are generally private health facilities ("hubs" with an MD Chest Physician and access to a pharmacy and digital X-ray laboratory) and private clinics of MD and MD Chest Physicians. Spokes are generally doctors with a Bachelor of Medicine, Bachelor of Surgery (MBBS) degree, practitioners of alternative medicines (AYUSH practitioners who are trained Ayurveda, Yoga and Naturopathy, Unani, Siddha, or Homeopathy), and informal providers with minimum or no qualifications. The PPIA network also includes chemists/pharmacists and diagnostic laboratories. The pilot in Mumbai will serve as a model for private health sector involvement in national TB control and will be used to inform similar programs nearby and in other urban Indian settings.
2. Quality of care surveillance: The QuTUB project is a part of the PPIA monitoring efforts and runs in parallel to the programs' scale up and expansion. The objective of the QuTUB project is to capture levels of quality of care through standardized patients ("mystery shoppers" or "fake patients"), who are individuals recruited locally and trained to portray four different TB cases. Developed by a Technical Advisory Group and benchmarked against the Standards of TB Care of India, the cases were designed to reflect different stages of TB disease progression, some with previous interactions with the health system upon presentation to a health care provider. Outcomes captured by the standardized patients through an exit questionnaire given to them within 2 hours of their interaction with providers' include: history questions asked by the provider, laboratory tests ordered, medicines dispensed or prescribed, and referrals made.
3. Randomized roll-out evaluation approach: In January 2015, PATH was interested in trying to further understand the causal impact of their program on diagnostic processes, and there was an opportunity to remove the selection bias and attribute differences in quality of care solely to the program by taking advantage of a randomized roll-out expansion plan of the PPIA program among a subset of providers. In collaboration with the PPIA Mumbai team, this study takes an intention-to-treat and instrumental variables evaluation approach through selective enrollment of a subset of providers in the second round of program scale-up in Mumbai city. The researchers note that the subset of providers are those who were not purposively selected in the earlier round of enrollment and therefore may be those who see fewer TB patients, or those who were reluctant to enroll into the program during the first rounds of program expansion. Therefore, the impact of the program on this group may be different from among those who were enrolled previously. Under this approach, it was agreed that for the evaluation eligible AYUSH practitioners would be networked in two purposively selected high TB burden or high slum population wards in Mumbai. For this, the researchers provided PATH with a list of 300 randomly selected practitioners among those who were not already networked into the program. AYUSH practitioners on this list were randomly allocated to two groups: one group (treatment) of 150 eligible AYUSH would be sensitized and networked, and the other group (control) of 150 eligible AYUSH would not be approached for networking after a year or more, when the QuTUB study team is able to complete end-line data collection in 2016. Selection into program roll-out groups was randomized. Standardized patients are sent to both groups before any intervention for baseline measures of quality of care, and the standardized patients would return again before the control group begins to receive the intervention for an end-line measure. The entire intervention in Mumbai is implemented by the PPIA and is separate from the team implementing the quality of care surveillance and evaluation. Care is taken to ensure that the evaluation team will be in the field independently of the implementation.

Analysis:

Intention-to-treat analysis and instrumental variables will be conducted after determining (i) that the treatment assignment can serve as a good instrument by: a strong correlation to the actual enrollment statuses of the providers regardless of treatment assignment, being uncorrelated with the outcomes, and only being connected to the outcomes through actual enrollment in the program, and (ii) balance at baseline between the treatment and control groups.