Social Enterprise Model (SEM) for private sector tuberculosis screening and care in Bangladesh

Engaging private providers to enhance tuberculosis detection and notification: evidence from TB REACH-Supported projects

BACKGROUND

Private providers (PPs), rather than public facilities, are often the first point of contact in the health system for people with tuberculosis (TB). However, PP's potential for enhancing TB detection remains underutilized.

METHODS

TB REACH is an initiative of Stop TB Partnership focused on improving TB detection and notification. We analyzed the results of interventions using private provider engagement (PPE) to impact TB detection and notification across four TB REACH funding waves from May 2018 through March 2022.

RESULTS

Overall, 35 projects documented screening of 13,038,586 people for TB, referral of 384,364 (3% of those screened) for diagnostic testing, and testing of 332,266 (86%) people. In total, 64,456 all forms of TB were diagnosed, and 62,830 (97% of those diagnosed) were linked to treatment. To diagnose one person with TB, the overall number needed to screen and test was, respectively, 281 (range across projects: 2-8,705) and 7 (range across projects: 1-24). Twenty-five projects mapped 69,187 PPs, both formal and informal, and engaged 21,206 (31%) providers during the intervention period, 12,211 (58%) of whom actively referred at least one person with TB symptoms during the intervention period. During the implementation period, TB notifications in the intervention areas increased by 25% (n = 61,123; from 246,845 to 307,968), with 20% of the total TB notifications attributed to the PPE projects. The mean and median cost per person started on treatment through the PPE projects was USD 221 and USD 481 (range across projects: 23 - 8,689).

CONCLUSIONS

Our findings suggest that structured and targeted PPE enhances TB case finding and contribute in closing the gap of missing cases. These results emphasize the need for wider implementation and scale-up of PPE in the TB response.

Isoniazid resistance pattern among pulmonary tuberculosis patients in Bangladesh: An exploratory study

OBJECTIVES

In high tuberculosis (TB) burden countries such as Bangladesh, research and policy tend to focus on rifampicin (RIF)-resistant TB patients, leaving RIF-sensitive but isoniazid (INH)-resistant (Hr-TB) patients undiagnosed. Our study aims to determine the prevalence of INH resistance among pulmonary TB patients in selected health care facilities in Bangladesh.

METHODS

This study was conducted across nine TB Screening and Treatment Centres situated in Bangladesh. Sputum samples from 1084 Xpert-positive pulmonary TB patients were collected between April 2021 and December 2022 and cultured for drug susceptibility testing. Demographic and clinical characteristics of Hr-TB and drug-susceptible TB patients were compared.

RESULTS

Among available drug susceptibility testing results of 998 culture-positive isolates, the resistance rate of any INH regardless of RIF susceptibility was 6.4% (64/998, 95% CI: 4.9-8.2). The rate was significantly higher in previously treated (21.1%, 16/76, 95% CI: 12.0-34.2) compared with newly diagnosed TB patients (5.2%, 48/922, 95% CI: 3.8-6.9) (p < 0.001). The rate of Hr-TB was 4.5% (45/998, 95% CI: 3.3-6.0), which was also higher among previously treated patients (6.6%, 5/76, 95% CI: 1.4-13.5) compared with newly diagnosed TB patients (4.3%; 40/922, 95% CI: 3.1-5.9) (p 0.350). Most importantly, the rate of Hr-TB was more than double compared with MDR-TB (4.5%, 45/998, vs. 1.9%, 19/998) found in the current study.

DISCUSSION

This study reveals a high prevalence of Hr-TB, surpassing even that of the multi-drug-resistant TB in Bangladesh. This emphasizes the urgent need to adopt WHO-recommended molecular tools at the national level for rapid detection of INH resistance so that patients receive timely and appropriate treatment.

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries

Background

In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics.

Methods

We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage.

Results

In each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries.

Conclusions

Using AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44263-024-00081-2.

Engagement of private health care facilities in TB management in Lusaka district of Zambia: lessons learned and achievements

BACKGROUND

Globally, at least 3 million TB patients are missed every year. In Zambia, the TB treatment coverage increased from 66% in 2020 to 92% in 2022. Involvement of all levels of health care service delivery is critical to finding all the missing TB patients.

METHODS

A survey was undertaken in 15 private facilities in Lusaka district of Zambia using a structured tool administered by project team and a district health team member. Data collected during the survey was analysed and results were used to determine the type of TB services that were offered as well as barriers and enablers to TB service provision. This was followed by a set of interventions that included; training and mentorship on active case finding and systematic TB screening, increased diagnostic capacity, provision of national recording and reporting tools and provision of TB medication through linkage with the National TB program (NTP). We report findings from the baseline survey and changes in presumptive TB identification and notification following interventions.

RESULTS

Major barriers to TB service delivery were the high cost of TB diagnostic testing and treatment in facilities where services were not supported by the National TB program; the mean cost was 33 (SD 33) and 93 (SD 148) for GeneXpert testing and a full course of treatment respectively. Pre-intervention, presumptive TB identification appeared to increase monthly by 4 (P = 0.000, CI=[3.00-5.00]). The monthly trends of presumptive TB identification during the intervention period increased by 5.32 (P = 0.000, [CI 4.31-6.33. Pre-intervention, the notification of TB appeared to decrease every month by -4.0 (P = 0.114, CI=[-9.00-0.10]) followed by an immediate increase in notifications of 13.94 TB patients (P = 0.001, CI [6.51, 21.36] in the first month on intervention. The monthly trends of notification during the intervention period changed by 0.34 (P = 0.000 [CI 0.19-0.48]). Private facility contribution to TB notification increased from 3 to 7%.

CONCLUSION

Engagement and inclusion of private health facilities in TB service provision through a systems strengthening approach can increase contribution to TB notification by private health facilities.

Dynamics of Social Enterprises in Health Care Delivery: Contexts, Models, and Policy Insights From Malaysia

This qualitative article explores the potential role of health care social enterprises (SEs) as disruptive innovators in improving the availability, accessibility, and affordability of health care delivery. It focuses on the context and mechanisms that enable SEs to produce positive health outcomes. Findings from an in-depth interview with the representatives of SEs and stakeholders in Malaysia reveal that strategies to balance the elements of social and enterprise (business) are the key for SEs to sustain in the market. This is supported with several inclusive business models such as inclusive employment model, cross-subsidization, and flexible fees payment mechanism, as well as collaborative engagement with multiple stakeholders, expert domains, and social workers. This article also highlights several main challenges in health care SEs, namely financial sustainability, impact measurement, scaling up of project, and political influence. This article ends with a few salient policies that focus on nurturing and strengthening health care SEs.

Integrating private health facilities in government-led health systems: a case study of the public-private mix approach in Ethiopia

BACKGROUND

Private health care facilities working in partnership with the public health sector is one option to create sustainable health systems and ensure health and well-being for all in low-income countries. As the second-most populous country in Africa with a rapidly growing economy, demand for health services in Ethiopia is increasing and one-quarter of its health facilities are privately owned. The Private Health Sector Program (PHSP), funded by the United States Agency for International Development, implemented a series of public-private partnership in health projects from 2004 to 2020 to address several public health priorities, including tuberculosis, malaria, HIV/AIDS, and family planning. We assessed PHSP's performance in leadership and governance, access to medicines, health management information systems, human resources, service provision, and finance.

METHODS

The World Health Organization's health systems strengthening framework, which is organized around six health system building blocks, guided the assessment. We conducted 50 key informant interviews and a health facility assessment at 106 private health facilities supported by the PHSP to evaluate its performance.

RESULTS

All six building blocks were addressed by the program and key informants shared that several policy and strategic changes were conducive to supporting the functioning of private health facilities. The provision of free medicines from the public pharmaceutical logistics system, relaxation of strict regulatory policies that restricted service provision through the private sector, training of private providers, and public-private mix guidelines developed for tuberculosis, malaria, and reproductive, maternal, newborn, child, and adolescent health helped increase the use of services at health facilities.

CONCLUSIONS

Some challenges and threats to sustainability remain, including fragile partnerships between public and private bodies, resource constraints, mistrust between the public and private sectors, limited incentives for the private sector, and oversight of the quality of services. To continue with gains in the policy environment, service accessibility, and other aspects of the health system, the government and international communities must work collaboratively to address public-private partnerships in health areas that can be strengthened. Future efforts should emphasize a mechanism to ensure that the private sector is capable, incentivized, and supervised to deliver continuous, high-quality and equitable services.

Comparing different versions of computer-aided detection products when reading chest X-rays for tuberculosis

Computer-aided detection (CAD) was recently recommended by the WHO for TB screening and triage based on several evaluations, but unlike traditional diagnostic tests, software versions are updated frequently and require constant evaluation. Since then, newer versions of two of the evaluated products have already been released. We used a case control sample of 12,890 chest X-rays to compare performance and model the programmatic effect of upgrading to newer versions of CAD4TB and qXR. We compared the area under the receiver operating characteristic curve (AUC), overall, and with data stratified by age, TB history, gender, and patient source. All versions were compared against radiologist readings and WHO's Target Product Profile (TPP) for a TB triage test. Both newer versions significantly outperformed their predecessors in terms of AUC: CAD4TB version 6 (0.823 [0.816-0.830]), version 7 (0.903 [0.897-0.908]) and qXR version 2 (0.872 [0.866-0.878]), version 3 (0.906 [0.901-0.911]). Newer versions met WHO TPP values, older versions did not. All products equalled or surpassed the human radiologist performance with improvements in triage ability in newer versions. Humans and CAD performed worse in older age groups and among those with TB history. New versions of CAD outperform their predecessors. Prior to implementation CAD should be evaluated using local data because underlying neural networks can differ significantly. An independent rapid evaluation centre is necessitated to provide implementers with performance data on new versions of CAD products as they are developed.

National approaches to TB care in adolescents

BACKGROUND: Adolescents bear a large burden of TB but high-prevalence countries differ significantly in their approach to address the specific needs of adolescent patients. We explore the national approaches to TB care in adolescents and compare them to the recommendations of the WHO.METHODS: We conducted a scoping review to describe the country-level guidelines to TB care in adolescents in high-burden countries. These guidelines were obtained through open sources. Information on TB care in adolescents were extracted from guidelines and compared to WHO recommendations.RESULTS: We found a lack of consensus in defining adolescents and that many national guidelines do not address the special healthcare needs of adolescents nor align with the WHO recommendations. Recently updated country guidelines are more likely to recommend short-course regimens for TB preventive treatment and countries with a higher level of income were more likely to follow WHO guidance for microbiological confirmation of TB disease in adolescents.CONCLUSION: A clear understanding of the burden of TB in adolescents that is reflected in disaggregated data reported at the country level is imperative in order to address the specific challenges to care in this high-risk group.

Evaluating novel engagement mechanisms, yields and acceptability of tuberculosis screening at retail pharmacies in Ho Chi Minh City, Viet Nam

Pharmacies represent a key health system entry point for people with TB in Viet Nam, but high fragmentation hinders their broader engagement. Professional networking apps may be able to facilitate pharmacy engagement for systematic TB screening and referral. Between September and December 2019, we piloted the use of a social networking app, SwipeRx, to recruit pharmacists for a TB referral scheme across four districts of Ho Chi Minh City, Viet Nam. We measured chest X-ray (CXR) referrals and TB detection yields at participating pharmacies and fielded 100 acceptability surveys, divided into pharmacists who did and did not make a CXR referral. We then fitted mixed-effect odds proportional models to explore acceptability factors that were associated with making a CXR referral. 1,816 push notifications were sent to pharmacists via the SwipeRx app and 78 indicated their interest in participating; however, only one was within the pilot's intervention area. Additional in-person outreach resulted in the recruitment of 146 pharmacists, with 54 (37.0%) making at least one CXR referral. A total of 182 pharmacy customers were referred, resulting in a total of 64 (35.2%) CXR screens and seven people being diagnosed with TB. Compared to pharmacists who did not make any CXR referrals, pharmacists making at least one CXR referral understood the pilot's objectives more clearly (aOR = 2.6, 95% CI: 1.2-5.8) and they believed that TB screening increased customer trust (aOR = 2.7, 95% CI: 1.2-5.8), benefited their business (aOR = 2.8, 95% CI: 1.3-6.2) and constituted a competitive advantage (aOR = 4.4, 95% CI: 1.9-9.9). They were also more confident in using mHealth apps (aOR = 3.1, 95 CI%: 1.4-6.8). Pharmacies can play an important role in early and increased TB case finding. It is critical to highlight the value proposition of TB referral schemes to their business during recruitment. Digital networking platforms, such as SwipeRx, can facilitate referrals for TB screening by pharmacists, but their ability to identify and recruit pharmacists requires optimization, particularly when targeting specific segments of a nation-wide digital network.

Provision of Decentralized TB Care Services: A Detect-Treat-Prevent Strategy for Children and Adolescents Affected by TB

In this review, we discuss considerations and successful models for providing decentralized diagnosis, treatment, and prevention services for children and adolescents. Key approaches to building decentralized capacity for childhood TB diagnosis in primary care facilities include provider training and increased access to child-focused diagnostic tools and techniques. Treatment of TB disease should be managed close to where patients live; pediatric formulations of both first- and second-line drugs should be widely available; and any hospitalization should be for as brief a period as medically indicated. TB preventive treatment for child and adolescent contacts must be greatly expanded, which will require home visits to identify contacts, building capacity to rule out TB, and adoption of shorter preventive regimens. Decentralization of TB services should involve the private sector, with collaborations outside the TB program in order to reach children and adolescents where they first enter the health care system. The impact of decentralization will be maximized if programs are family-centered and designed around responding to the needs of children and adolescents affected by TB, as well as their families.

Xpert MTB/RIF Ultra assay for the detection of Mycobacterium tuberculosis in people with negative conventional Xpert MTB/RIF but chest imaging suggestive of tuberculosis in Dhaka, Bangladesh: Xpert Ultra for M. tuberculosis detection in Xpert-negative PTB presumptives

BACKGROUND

World Health Organization is considering substitution of Xpert MTB/RIF (Xpert) by Xpert MTB/RIF Ultra (Ultra) for tuberculosis (TB) diagnosis, but supportive evidence is scarce, particularly among people more likely to have paucibacillary pulmonary TB (PTB).

METHODS

During January-July 2018, PTB presumptives visiting TB Screening and Treatment Centres of Dhaka for routine chest X-ray (CXR) and conventional Xpert were enrolled. Sputum specimens were additionally tested with microscopy, culture and Ultra. Specimens with "Trace call" by Ultra (Ultra-trace) were retested. Yield and diagnostic accuracy using various approaches to Ultra-trace and concordance of Ultra with bacteriological-positive PTB were assessed.

RESULTS

1,083 participants (104 'Xpert-positive'; 979 'Xpert-negative and CXR-suggestive') were enrolled. All Xpert-positives and 900 (92%) Xpert-negatives displayed concordance with Ultra. Seventy-nine (8.1%) Xpert-negative specimens tested positive with Ultra, of which 37 (46.8%) were categorically positives and 42 (53.2%) were Ultra-trace. Sixteen of 42 were retested, of whom eight (50.1%) Ultra-trace turned categorically positive, leading to 45 (4.6%) additionally detected by Ultra. Ultra sensitivity and specificity was 93.9% and 94.6%, and it additionally detected 5.4% more TB patients with concordance 94.6% (kappa, ꓗ=0.78) compared to any bacteriologically positive specimen (microscopy, culture or Xpert).

CONCLUSION

Ultra exhibited improved detection and accuracy among Xpert-negatives in a cohort with a high likelihood of PTB.

Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms

BACKGROUND

Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance compares with each other and with radiologists. We aimed to evaluate five commercial AI algorithms for triaging tuberculosis using a large dataset that had not previously been used to train any AI algorithms.

METHODS

Individuals aged 15 years or older presenting or referred to three tuberculosis screening centres in Dhaka, Bangladesh, between May 15, 2014, and Oct 4, 2016, were recruited consecutively. Every participant was verbally screened for symptoms and received a digital posterior-anterior chest x-ray and an Xpert MTB/RIF (Xpert) test. All chest x-rays were read independently by a group of three registered radiologists and five commercial AI algorithms: CAD4TB (version 7), InferRead DR (version 2), Lunit INSIGHT CXR (version 4.9.0), JF CXR-1 (version 2), and qXR (version 3). We compared the performance of the AI algorithms with each other, with the radiologists, and with the WHO's Target Product Profile (TPP) of triage tests (≥90% sensitivity and ≥70% specificity). We used a new evaluation framework that simultaneously evaluates sensitivity, proportion of Xpert tests avoided, and number needed to test to inform implementers' choice of software and selection of threshold abnormality scores.

FINDINGS

Chest x-rays from 23 954 individuals were included in the analysis. All five AI algorithms significantly outperformed the radiologists. The areas under the receiver operating characteristic curve were 90·81% (95% CI 90·33-91·29) for qXR, 90·34% (89·81-90·87) for CAD4TB, 88·61% (88·03-89·20) for Lunit INSIGHT CXR, 84·90% (84·27-85·54) for InferRead DR, and 84·89% (84·26-85·53) for JF CXR-1. Only qXR (74·3% specificity [95% CI 73·3-74·9]) and CAD4TB (72·9% specificity [72·3-73·5]) met the TPP at 90% sensitivity. All five AI algorithms reduced the number of Xpert tests required by 50% while maintaining a sensitivity above 90%. All AI algorithms performed worse among older age groups (>60 years) and people with a history of tuberculosis.

INTERPRETATION

AI algorithms can be highly accurate and useful triage tools for tuberculosis detection in high-burden regions, and outperform human readers.

FUNDING

Government of Canada.

Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh

We developed a novel method to align two data sources (TB notifications and the Demographic Health Survey, DHS) captured at different geographic scales. We used this method to identify sociodemographic indicators – specifically population density – that were ecologically correlated with elevated TB notification rates across wards (~100 000 people) in Dhaka, Bangladesh. We found population density was the variable most closely correlated with ward-level TB notification rates (Spearman's rank correlation 0.45). Our approach can be useful, as publicly available data (e.g. DHS data) could help identify factors that are ecologically associated with disease burden when more granular data (e.g. ward-level TB notifications) are not available. Use of this approach might help in designing spatially targeted interventions for TB and other diseases in settings of weak existing data on disease burden at the subdistrict level.