Digital adherence technology for tuberculosis treatment supervision: A stepped-wedge cluster-randomized trial in Uganda

Digital Adherence Technologies and Differentiated Care for Tuberculosis Treatment and Their Acceptability Among Persons With Tuberculosis, Health Care Workers, and Key Informants in the Philippines: Qualitative Interview Study

BACKGROUND

Digital adherence technologies (DATs) are being studied to determine their potential to support tuberculosis (TB) treatment and address the shortcomings of directly observed therapy. Previous research has shown inconclusive results on whether DATs can enhance medication adherence among persons with TB.

OBJECTIVE

This study aims to understand the acceptability of DATs, namely, medication labels and smart pillboxes, among persons with TB, health care workers (HCWs), and key informants (KIs) in the Philippines. The objective is to gain valuable insights that can inform the design and implementation of DATs in the Southeast Asian region, which meet the needs and preferences of end users.

METHODS

Persons with TB, HCWs, and KIs were recruited from intervention facilities to participate in in-depth interviews conducted between March 2022 and January 2023. These interviews were transcribed and translated into English. A thematic analysis was carried out using NVivo software (Lumivero) to identify and analyze themes. Themes were then structured within a modified social-ecological model.

RESULTS

A total of 25 persons with drug-sensitive TB and 20 HCWs or KIs were interviewed. Both groups emphasized that users' technology literacy level, financial conditions, and motivation to be cured determined how they interacted with the DAT. They also acknowledged that DATs helped foster their relationship with HCWs and enabled efficient treatment support. Concerning technology, persons with TB found DATs easy to use and able to reduce clinic visits. HCWs mentioned that DATs added to their workload but also allowed them to support users who missed doses. However, both groups experienced technical challenges with DATs. Regarding program implementation, users appreciated the clear explanations and demonstrations provided by HCWs. Yet, some users reported inconsistencies between DAT settings and the information provided. HCWs stressed the importance of comprehensive training and sufficient resources for effective program implementation in the future. At the community level, both groups noted that DATs and program design protected users' privacy and reduced the risk of stigma. Finally, users and HCWs shared various contextual factors that influenced their experience with DAT, including infrastructure challenges and the impact of the COVID-19 pandemic.

CONCLUSIONS

In the Philippines, persons with TB and HCWs showed a high level of acceptance and satisfaction with the impact of DAT and program design. They expressed a desire for the continuation of DATs. The challenges encountered underscore the need for ongoing technological development to minimize malfunctions, enhance the capacity of health facilities, and improve infrastructure. DATs have demonstrated their ability to strengthen user-HCW relationships and protect users from stigmatization. Additional efforts are required to scale up the DAT program in the Philippines.

User Experience of Persons Using Ingestible Sensor-Enabled Pre-Exposure Prophylaxis to Prevent HIV Infection: Cross-Sectional Survey Study

Background

A digital health technology's success or failure depends on how it is received by users.

objectives

We conducted a user experience (UX) evaluation among persons who used the Food and Drug Administration-approved Digital Health Feedback System incorporating ingestible sensors (ISs) to capture medication adherence, after they were prescribed oral pre-exposure prophylaxis (PrEP) to prevent HIV infection. We performed an association analysis with baseline participant characteristics, to see if "personas" associated with positive or negative UX emerged.

Methods

UX data were collected upon exit from a prospective intervention study of adults who were HIV negative, prescribed oral PrEP, and used the Digital Health Feedback System with IS-enabled tenofovir disoproxil fumarate plus emtricitabine (IS-Truvada). Baseline demographics; urine toxicology; and self-report questionnaires evaluating sleep (Pittsburgh Sleep Quality Index), self-efficacy, habitual self-control, HIV risk perception (Perceived Risk of HIV Scale 8-item), and depressive symptoms (Patient Health Questionnaire-8) were collected. Participants with ≥28 days in the study completed a Likert-scale UX questionnaire of 27 questions grouped into 4 domain categories: overall experience, ease of use, intention of future use, and perceived utility. Means and IQRs were computed for participant total and domain subscores, and linear regressions modeled baseline participant characteristics associated with UX responses. Demographic characteristics of responders versus nonresponders were compared using the Fisher exact and Wilcoxon rank-sum tests.

Results

Overall, 71 participants were enrolled (age: mean 37.6, range 18-69 years; n=64, 90% male; n=55, 77% White; n=24, 34% Hispanic; n=68, 96% housed; and n=53, 75% employed). No demographic differences were observed in the 63 participants who used the intervention for ≥28 days. Participants who completed the questionnaire were more likely to be housed (52/53, 98% vs 8/10, 80%; P=.06) and less likely to have a positive urine toxicology (18/51, 35% vs 7/10, 70%; P=.08), particularly methamphetamine (4/51, 8% vs 4/10, 40%; P=.02), than noncompleters. Based on IQR values, ≥75% of participants had a favorable UX based on the total score (median 3.78, IQR 3.17-4.20), overall experience (median 4.00, IQR 3.50-4.50), ease of use (median 3.72, IQR 3.33-4.22), and perceived utility (median 3.72, IQR 3.22-4.25), and ≥50% had favorable intention of future use (median 3.80, IQR 2.80-4.40). Following multipredictor modeling, self-efficacy was significantly associated with the total score (0.822, 95% CI 0.405-1.240; P<.001) and all subscores (all P<.05). Persons with more depressive symptoms reported better perceived utility (P=.01). Poor sleep was associated with a worse overall experience (-0.07, 95% CI -0.133 to -0.006; P=.03).

Conclusions

The UX among persons using IS-enabled PrEP (IS-Truvada) to prevent HIV infection was positive. Association analysis of baseline participant characteristics linked higher self-efficacy with positive UX, more depressive symptoms with higher perceived utility, and poor sleep with negative UX.

Development of a customized m-Health-based intervention to reduce loss to follow-up among patients undergoing treatment for cervical lesions at a rural referral Hospital, South Western Uganda

Background

Loss to follow-up (LTFU) in individuals undergoing cervical cancer treatment is a major challenge in many low resource settings. We describe development of a customized and tailored mHealth intervention for reducing LTFU among patients undergoing cervical cancer treatment at Mbarara Regional Referral Hospital (MRRH).

Methods

We interviewed all health care providers (HCPs) at the cervical cancer clinic of MRRH, between April and May 2023. Transcripts were subsequently derived, reviewed and coded to generate themes and categories using inductive content analytic approach. Four medical experts used this data to develop relevant SMS content, which was incorporated into an app.

Results

HCPs had owned a phone for 13.8 ≤ years, had worked at the clinic for 5 ≤ years, and used text messages regularly. Qualitative data revealed that the main challenge to re-engagement was absence of a reminder mechanism between HCPs and patients. HCPs preferred text and or audio mode of messaging to improve health care responsiveness to LTFUs, awareness, continuity of care, and health service uptake among the majority illiterate population; though with potential constraints of costs and workload. Identified key messaging content included; the importance of attending scheduled follow-ups, follow up visit date and clinic customization and tailoring the message to the intended recipient. SMS content was uploaded onto the cc-follow-up app platform and customized according to preferred language, day, frequency and time of delivery.

Conclusion

Tailoring an mHealth messaging intervention could help re-engage and reduce LTFU through improved information sharing, awareness, responsiveness, care engagement and medical compliance. A pilot study is required for our intervention in South Western Uganda.

Effectiveness of a comprehensive package based on electronic medication monitors at improving treatment outcomes among tuberculosis patients in Tibet: a multicentre randomised controlled trial

BACKGROUND

WHO recommends that electronic medication monitors, a form of digital adherence technology, be used as a complement to directly observed treatment (DOT) for tuberculosis, as DOT is inconvenient and costly. However, existing evidence about the effectiveness of these monitors is inconclusive. Therefore, we evaluated the effectiveness of a comprehensive package based on electronic medication monitors among patients with tuberculosis in Tibet Autonomous Region (hereafter Tibet), China.

METHODS

This multicentre, randomised controlled trial recruited patients from six counties in Shigatse, Tibet. Eligible participants had drug-susceptible tuberculosis and were aged 15 years or older when starting standard tuberculosis treatment. Tuberculosis doctors recruited patients from the public tuberculosis dispensary in each county and the study statistician randomly assigned them to the intervention or control group based on the predetermined randomised allocation sequence. Intervention patients received an electronic medication monitor box. The box included audio medication-adherence reminders and recorded box-opening data, which were transmitted to a cloud-based server and were accessible to health-care providers to allow remote adherence monitoring. A linked smartphone app enabled text, audio, and video communication between patients and health-care providers. Patients were also provided with a free data plan. Patients selected a treatment supporter (often a family member) who was trained to support patients with using the electronic medication monitor and app. Patients in the control group received usual care plus a deactivated electronic medication monitor, which only recorded and transmitted box-opening data that was not made available to health-care providers. The control group also had no access to the app or trained treatment supporters. The primary outcome was a binary indicator of poor monthly adherence, defined as missing 20% or more of planned doses in the treatment month, measured using electronic medication monitor opening data, and verified by counting used medication blister packages during consultations. We recorded other secondary treatment outcomes based on national tuberculosis reporting data. We analysed the primary outcome based on the intention-to-treat population. This trial is registered at ISRCTN, 52132803.

FINDINGS

Between Nov 17, 2018, and April 5, 2021, 278 patients were enrolled into the study. 143 patients were randomly assigned to the intervention group and 135 patients to the control group. Follow-up ended when the final patient completed treatment on Oct 4, 2021. In the intervention group, 87 (10%) of the 854 treatment months showed poor adherence compared with 290 (37%) of the 795 months in the control group. The corresponding adjusted risk difference for the intervention versus control was -29·2 percentage points (95% CI -35·3 to -22·2; p<0·0001). Five of the six secondary treatment outcomes also showed clear improvements, including treatment success, which was found for 133 (94%) of the 142 individuals in the intervention arm and 98 (73%) of the 134 individuals in the control arm, with an adjusted risk difference of 21 percentage points (95% CI 12·4-29·4); p<0·0001.

INTERPRETATION

The interventions were effective at improving tuberculosis treatment adherence and outcomes, and the trial suggests that a comprehensive package involving electronic medication monitors might positively affect tuberculosis programmes in high-burden and low-resource settings.

FUNDING

TB REACH.

How Integrated Digital Tools Can Improve Tuberculosis Medication Adherence: A Longitudinal Study in China

Background: Poor medication adherence remains one of the major problems in the treatment of tuberculosis (TB) patients, while digital technologies have been proven effective to improve the treatment results. However, reports on the effectiveness of comprehensive practice integrating different intervention methods and technologies are limited. The aim of this study is to evaluate the effectiveness of an integrated digital adherence intervention for TB patients. Methods: We developed a digital adherence intervention platform integrating instant WeChat message, electronic medication monitors (EMMs), and manual reminders. The primary goal of the platform was to improve the accessibility of digital adherence technologies, and thus improve treatment adherence. TB patients were newly diagnosed at 10 TB-designated hospitals and came from 220 communities, from January to June 2022. The basic characteristics and treatment adherence of TB patients in WeChat, EMM, and conventional groups were compared, and the influencing factors of high medication adherence were analyzed by logistic regression. Results: A total of 2,498 TB patients were enrolled in the study, 14.5% were managed by digital technologies, 9.5% by WeChat, and 5.0% by EMM, respectively. After intervention, the median medication rate of TB patients was significantly higher in the WeChat group (95.3%) and EMM group (95.7%) compared with that of the conventional group (83.8%). On the contrary, the median number of missed medications among patients of the conventional group (nine times) was significantly higher than that in the WeChat (three times) group and EMM (three times) group. The proportion of high adherence (adherence medication rate ≥90%) among TB patients was 64.7%, 64.5%, and 43.2% in WeChat, EMM, and conventional group, respectively. Conclusions: The application of the integrated digital adherence intervention platform could significantly improve medication adherence among TB patients. The accessibility of digital adherence technologies could be improved by integrating complementary technologies in practice.

Impact of the 99DOTS digital adherence technology on tuberculosis treatment outcomes in North India: a pre-post study

BACKGROUND

99DOTS is a cellphone-based digital adherence technology. The state of Himachal Pradesh, India, made 99DOTS available to all adults being treated for drug-sensitive tuberculosis (TB) in the public sector in May 2018. While 99DOTS has engaged over 500,000 people across India, few studies have evaluated its effectiveness in improving TB treatment outcomes.

METHODS

We compared treatment outcomes of adults with drug-sensitive TB before and after Himachal Pradesh's 99DOTS launch using data from India's national TB database. The pre-intervention group initiated treatment between February and October 2017 (N = 7722), and the post-intervention group between July 2018 and March 2019 (N = 8322). We analyzed engagement with 99DOTS and used multivariable logistic regression to estimate impact on favorable treatment outcomes (those marked as cured or treatment complete).

RESULTS

In the post-intervention group, 2746 (33.0%) people called 99DOTS at least once. Those who called did so with a wide variation in frequency (< 25% of treatment days: 24.6% of callers; 25-50% of days: 15.1% of callers, 50-75% of days: 15.7% of callers; 75-100% of days: 44.6% of callers). In the pre-intervention group, 7186 (93.1%) had favorable treatment outcomes, compared to 7734 (92.9%) in the post-intervention group. This difference was not statistically significant (OR = 0.981, 95% CI [0.869, 1.108], p = 0.758), including after controlling for individual characteristics (adjusted OR = 0.970, 95% CI [0.854, 1.102]).

CONCLUSIONS

We found no statistically significant difference in treatment outcomes before and after a large-scale implementation of 99DOTS. Additional work could help to elucidate factors mediating site-wise variations in uptake of the intervention.

A machine learning approach to explore individual risk factors for tuberculosis treatment non-adherence in Mukono district

Despite the availability and implementation of well-known efficacious interventions for tuberculosis treatment by the Ministry of Health, Uganda (MoH), treatment non-adherence persists. Moreover, identifying a specific tuberculosis patient at risk of treatment non-adherence is still a challenge. Thus, this retrospective study, based on a record review of 838 tuberculosis patients enrolled in six health facilities, presents, and discusses a machine learning approach to explore the individual risk factors predictive of tuberculosis treatment non-adherence in the Mukono district, Uganda. Five classification machine learning algorithms, logistic regression (LR), artificial neural networks (ANN), support vector machines (SVM), random forest (RF), and AdaBoost were trained, and evaluated by computing their accuracy, F1 score, precision, recall, and the area under the receiver operating curve (AUC) through the aid of a confusion matrix. Of the five developed and evaluated algorithms, SVM (91.28%) had the highest accuracy (AdaBoost, 91.05% performed better than SVM when AUC is considered as evaluation parameter). Looking at all five evaluation parameters globally, AdaBoost is quite on par with SVM. Individual risk factors predictive of non-adherence included tuberculosis type, GeneXpert results, sub-country, antiretroviral status, contacts below 5 years, health facility ownership, sputum test results at 2 months, treatment supporter, cotrimoxazole preventive therapy (CPT) dapsone status, risk group, patient age, gender, middle and upper arm circumference, referral, positive sputum test at 5 and 6 months. Therefore, machine learning techniques, specifically classification types, can identify patient factors predictive of treatment non-adherence and accurately differentiate between adherent and non-adherent patients. Thus, tuberculosis program management should consider adopting the classification machine learning techniques evaluated in this study as a screening tool for identifying and targeting suited interventions to these patients.

mHealth to improve implementation of TB contact investigation: a case study from Uganda

BACKGROUND

Implementation science offers a systematic approach to adapting innovations and delivery strategies to new contexts but has yet to be widely applied in low- and middle-income countries. The Fogarty Center for Global Health Studies is sponsoring a special series, "Global Implementation Science Case Studies," to address this gap.

METHODS

We developed a case study for this series describing our approach and lessons learned while conducting a prospective, multi-modal study to design, implement, and evaluate an implementation strategy for TB contact investigation in Kampala, Uganda. The study included formative, evaluative, and summative phases that allowed us to develop and test an adapted contact investigation intervention involving home-based sample collection for TB and HIV testing. We concurrently developed a multi-component mHealth implementation strategy involving fingerprint scanning, electronic decision support, and automated reporting of test results via text message. We then conducted a household-randomized, hybrid implementation-effectiveness trial comparing the adapted intervention and implementation strategy to usual care. Our assessment included nested quantitative and qualitative studies to understand the strategy's acceptability, appropriateness, feasibility, fidelity, and costs. Reflecting on this process with a multi-disciplinary team of implementing researchers and local public health partners, we provide commentary on the previously published studies and how the results influenced the adaptation of international TB contact investigation guidelines to fit the local context.

RESULTS

While the trial did not show improvements in contact investigation delivery or public health outcomes, our multi-modal evaluation strategy helped us identify which elements of home-based, mHealth-facilitated contact investigation were feasible, acceptable, and appropriate and which elements reduced its fidelity and sustainability, including high costs. We identified a need for better tools for measuring implementation that are simple, quantitative, and repeatable and for greater attention to ethical issues in implementation science.

CONCLUSIONS

Overall, a theory-informed, community-engaged approach to implementation offered many learnings and actionable insights for delivering TB contact investigation and using implementation science in low-income countries. Future implementation trials, especially those incorporating mHealth strategies, should apply the learnings from this case study to enhance the rigor, equity, and impact of implementation research in global health settings.

Implementation, feasibility, and acceptability of 99DOTS-based supervision of treatment for drug-susceptible TB in Uganda

99DOTS is a low-cost digital adherence technology that allows people with tuberculosis (TB) to self-report treatment adherence. There are limited data on its implementation, feasibility, and acceptability from sub-Saharan Africa. We conducted a longitudinal analysis and cross-sectional surveys nested within a stepped-wedge randomized trial at 18 health facilities in Uganda between December 2018 and January 2020. The longitudinal analysis assessed implementation of key components of a 99DOTS-based intervention, including self-reporting of TB medication adherence via toll-free phone calls, automated text message reminders and support actions by health workers monitoring adherence data. Cross-sectional surveys administered to a subset of people with TB and health workers assessed 99DOTS feasibility and acceptability. Composite scores for capability, opportunity, and motivation to use 99DOTS were estimated as mean Likert scale responses. Among 462 people with pulmonary TB enrolled on 99DOTS, median adherence was 58.4% (inter-quartile range [IQR] 38.7-75.6) as confirmed by self-reporting dosing via phone calls and 99.4% (IQR 96.4-100) when also including doses confirmed by health workers. Phone call-confirmed adherence declined over the treatment period and was lower among people with HIV (median 50.6% vs. 63.7%, p<0.001). People with TB received SMS dosing reminders on 90.5% of treatment days. Health worker support actions were documented for 261/409 (63.8%) people with TB who missed >3 consecutive doses. Surveys were completed by 83 people with TB and 22 health workers. Composite scores for capability, opportunity, and motivation were high; among people with TB, composite scores did not differ by gender or HIV status. Barriers to using 99DOTS included technical issues (phone access, charging, and network connection) and concerns regarding disclosure. 99DOTS was feasible to implement and highly acceptable to people with TB and their health workers. National TB Programs should offer 99DOTS as an option for TB treatment supervision.

Digital adherence technologies to improve tuberculosis treatment outcomes in China: a cluster-randomised superiority trial

BACKGROUND

Drug-sensitive tuberculosis treatment requires 6 months of therapy, so adherence problems are common. Digital adherence technologies might improve tuberculosis treatment outcomes. We aimed to evaluate the effect of a daily reminder medication monitor, monthly review of adherence data by the health-care provider, and differentiated care for patients with adherence issues, on tuberculosis treatment adherence and outcomes.

METHODS

We did a cluster-randomised superiority trial across four prefectures in China. 24 counties or districts (clusters) were randomly assigned (1:1) to intervention or control groups. We enrolled patients aged 18 years or older with GeneXpert-positive, rifampicin-sensitive pulmonary tuberculosis, who were receiving daily fixed-dose combination treatment. Patients in the intervention group received a medication monitor for daily drug-dosing reminders, monthly review of adherence data by health-care provider, and management of poor adherence; and patients in the control group received routine care (silent-mode monitor-measured adherence). Only the independent endpoints review committee who assessed endpoint data for some participants were masked to study group assignment. Patients were followed up (with sputum solid culture) at 12 and 18 months. The primary outcome was a composite of death, loss to follow-up, treatment failure, switch to multidrug-resistant tuberculosis treatment, or tuberculosis recurrence by 18 months from treatment start, analysed in the intention-to-treat population. Analysis accounted for study design with multiple imputation for the primary outcome. This trial is now complete and is registered with ISRCTN, 35812455.

FINDINGS

Between Jan 26, 2017, and April 3, 2019, 15 257 patients were assessed for eligibility and 3074 were enrolled, 2686 (87%) of whom were included in the intention-to-treat population. 1909 (71%) of 2686 patients were male, 777 (29%) were female, and the median age was 44 years (IQR 29-58). By 18 months from treatment start, using multiple imputation for missing outcomes, 239 (16% [geometric mean of cluster-level proportion]) of 1388 patients in the control group and 224 (16%) of 1298 in the intervention group had a primary composite outcome event (289 [62%] of 463 events were loss to follow-up during treatment and 42 [9%] were tuberculosis recurrence). The intervention had no effect on risk of the primary composite outcome (adjusted risk ratio 1·01, 95% CI 0·73-1·40).

INTERPRETATION

Our digital medication monitor intervention had no effect on unfavourable outcomes, which included loss to follow-up during treatment, tuberculosis recurrence, death, and treatment failure. There was a failure to change patient management following identification of treatment non-adherence at monthly reviews. A better understanding of adherence patterns and how they relate to poor outcomes, coupled with a more timely review of adherence data and improved implementation of differentiated care, may be required.

FUNDING

Bill & Melinda Gates Foundation.

Evaluating the equity impact and cost-effectiveness of digital adherence technologies with differentiated care to support tuberculosis treatment adherence in Ethiopia: protocol and analysis plan for the health economics component of a cluster randomised trial

BACKGROUND

Tuberculosis remains a leading infectious cause of death in resource-limited settings. Effective treatment is the cornerstone of tuberculosis control, reducing mortality, recurrence and transmission. Supporting treatment adherence through facility-based observations of medication taking can be costly to providers and patients. Digital adherence technologies (DATs) may facilitate treatment monitoring and differentiated care. The ASCENT-Ethiopia study is a three-arm cluster randomised trial assessing two DATs with differentiated care for supporting tuberculosis treatment adherence in Ethiopia. This study is part of the ASCENT consortium, assessing DATs in South Africa, the Philippines, Ukraine, Tanzania and Ethiopia. The aim of this study is to determine the costs, cost-effectiveness and equity impact of implementing DATs in Ethiopia.

METHODS AND DESIGN

A total of 78 health facilities have been randomised (1:1:1) into one of two intervention arms or a standard-of-care arm. Approximately 50 participants from each health facility will be enrolled on the trial. Participants in facilities randomised to the intervention arms are offered a DAT linked to the ASCENT adherence platform for daily adherence monitoring and differentiated response for those who have missed doses. Participants at standard-of-care facilities receive routine care. Treatment outcomes and resource utilisation will be measured for each participant. The primary effectiveness outcome is a composite index of unfavourable end-of-treatment outcomes (lost to follow-up, death or treatment failure) or treatment recurrence within 6 months of end-of-treatment. For the cost-effectiveness analysis, end-of-treatment outcomes will be used to estimate disability-adjusted life years (DALYs) averted. Provider and patient cost data will be collected from a subsample of 5 health facilities per study arm, 10 participants per facility (n = 150). We will conduct a societal cost-effectiveness analysis using Bayesian hierarchical models that account for the individual-level correlation between costs and outcomes as well as intra-cluster correlation. An equity impact analysis will be conducted to summarise equity efficiency trade-offs.

DISCUSSION

Trial enrolment is ongoing. This paper follows the published trial protocol and describes the protocol and analysis plan for the health economics work package of the ASCENT-Ethiopia trial. This analysis will generate economic evidence to inform the implementation of DATs in Ethiopia and globally.

TRIAL REGISTRATION

Pan African Clinical Trial Registry (PACTR) PACTR202008776694999. Registered on 11 August 2020,  https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=12241 .

Effectiveness of digital adherence technologies in improving tuberculosis treatment outcomes in four countries: a pragmatic cluster randomised trial protocol

INTRODUCTION

Successful treatment of tuberculosis depends to a large extent on good adherence to treatment regimens, which relies on directly observed treatment (DOT). This in turn requires frequent visits to health facilities. High costs to patients, stigma and burden to the health system challenged the DOT approach. Digital adherence technologies (DATs) have emerged as possibly more feasible alternatives to DOT but there is conflicting evidence on their effectiveness and feasibility. Our primary objective is to evaluate whether the implementation of DATs with daily monitoring and a differentiated response to patient adherence would reduce poor treatment outcomes compared with the standard of care (SOC). Our secondary objectives include: to evaluate the proportion of patients lost to follow-up; to compare effectiveness by DAT type; to evaluate the feasibility and acceptability of DATs; to describe factors affecting the longitudinal engagement of patients with the intervention and to use a simple model to estimate the epidemiological impact and cost-effectiveness of the intervention from a health system perspective.

METHODS AND ANALYSIS

This is a pragmatic two-arm cluster-randomised trial in the Philippines, South Africa, Tanzania and Ukraine, with health facilities as the unit of randomisation. Facilities will first be randomised to either the DAT or SOC arm, and then the DAT arm will be further randomised into medication sleeve/labels or smart pill box in a 1:1:2 ratio for the smart pill box, medication sleeve/label or the SOC respectively. We will use data from the digital adherence platform and routine health facility records for analysis. In the main analysis, we will employ an intention-to-treat approach to evaluate treatment outcomes.

ETHICS AND DISSEMINATION

The study has been approved by the WHO Research Ethics Review Committee (0003296), and by country-specific committees. The results will be shared at national and international meetings and will be published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ISRCTN17706019.

Improving cascade outcomes for active TB: A global systematic review and meta-analysis of TB interventions

BACKGROUND

To inform policy and implementation that can enhance prevention and improve tuberculosis (TB) care cascade outcomes, this review aimed to summarize the impact of various interventions on care cascade outcomes for active TB.

METHODS AND FINDINGS

In this systematic review and meta-analysis, we retrieved English articles with comparator arms (like randomized controlled trials (RCTs) and before and after intervention studies) that evaluated TB interventions published from January 1970 to September 30, 2022, from Embase, CINAHL, PubMed, and the Cochrane library. Commentaries, qualitative studies, conference abstracts, studies without standard of care comparator arms, and studies that did not report quantitative results for TB care cascade outcomes were excluded. Data from studies with similar comparator arms were pooled in a random effects model, and outcomes were reported as odds ratio (OR) with 95% confidence interval (CI) and number of studies (k). The quality of evidence was appraised using GRADE, and the study was registered on PROSPERO (CRD42018103331). Of 21,548 deduplicated studies, 144 eligible studies were included. Of 144 studies, 128 were from low/middle-income countries, 84 were RCTs, and 25 integrated TB and HIV care. Counselling and education was significantly associated with testing (OR = 8.82, 95% CI:1.71 to 45.43; I2 = 99.9%, k = 7), diagnosis (OR = 1.44, 95% CI:1.08 to 1.92; I2 = 97.6%, k = 9), linkage to care (OR = 3.10, 95% CI = 1.97 to 4.86; I2 = 0%, k = 1), cure (OR = 2.08, 95% CI:1.11 to 3.88; I2 = 76.7%, k = 4), treatment completion (OR = 1.48, 95% CI: 1.07 to 2.03; I2 = 73.1%, k = 8), and treatment success (OR = 3.24, 95% CI: 1.88 to 5.55; I2 = 75.9%, k = 5) outcomes compared to standard-of-care. Incentives, multisector collaborations, and community-based interventions were associated with at least three TB care cascade outcomes; digital interventions and mixed interventions were associated with an increased likelihood of two cascade outcomes each. These findings remained salient when studies were limited to RCTs only. Also, our study does not cover the entire care cascade as we did not measure gaps in pre-testing, pretreatment, and post-treatment outcomes (like loss to follow-up and TB recurrence).

CONCLUSIONS

Among TB interventions, education and counseling, incentives, community-based interventions, and mixed interventions were associated with multiple active TB care cascade outcomes. However, cost-effectiveness and local-setting contexts should be considered when choosing such strategies due to their high heterogeneity.

Can digital adherence technologies reduce inequity in tuberculosis treatment success? Evidence from a randomised controlled trial

INTRODUCTION

Tuberculosis (TB) is a global health emergency and low treatment adherence among patients is a major barrier to ending the TB epidemic. The WHO promotes digital adherence technologies (DATs) as facilitators for improving treatment adherence in resource-limited settings. However, limited research has investigated whether DATs improve outcomes for high-risk patients (ie, those with a high probability of an unsuccessful outcome), leading to concerns that DATs may cause intervention-generated inequality.

METHODS

We conducted secondary analyses of data from a completed individual-level randomised controlled trial in Nairobi, Kenya during 2016-2017, which evaluated the average intervention effect of a novel DAT-based behavioural support programme. We trained a causal forest model to answer three research questions: (1) Was the effect of the intervention heterogeneous across individuals? (2) Was the intervention less effective for high-risk patients? nd (3) Can differentiated care improve programme effectiveness and equity in treatment outcomes?

RESULTS

We found that individual intervention effects-the percentage point reduction in the likelihood of an unsuccessful treatment outcome-ranged from 4.2 to 12.4, with an average of 8.2. The intervention was beneficial for 76% of patients, and most beneficial for high-risk patients. Differentiated enrolment policies, targeted at high-risk patients, have the potential to (1) increase the average intervention effect of DAT services by up to 28.5% and (2) decrease the population average and standard deviation (across patients) of the probability of an unsuccessful treatment outcome by up to 8.5% and 31.5%, respectively.

CONCLUSION

This DAT-based intervention can improve outcomes among high-risk patients, reducing inequity in the likelihood of an unsuccessful treatment outcome. In resource-limited settings where universal provision of the intervention is infeasible, targeting high-risk patients for DAT enrolment is a worthwhile strategy for programmes that involve human support sponsors, enabling them to achieve the highest possible impact for high-risk patients at a substantially improved cost-effectiveness ratio.

Social Determinants of Adherence to Treatment for Tuberculosis Infection and Disease Among Children, Adolescents, and Young Adults: A Narrative Review

Global efforts to eliminate tuberculosis (TB) must address the unique barriers that children (ages 0 through 9 years) and adolescents/young adults (AYA; ages 10 through 24 years) face in adhering to treatment for TB infection and disease. We conducted a narrative review to summarize current knowledge on the social determinants of treatment adherence among these age groups to guide efforts and policy to address their unique needs. Our findings revealed that research on TB treatment adherence among children and AYA is still in its nascent stage. The current literature revealed structural/community-, health system-, household-, and individual-level factors that influence treatment adherence and varied with developmental stage. There is a need to develop multilevel interventions to address the unique challenges that children and AYA face in adhering to TB treatment.

Effectiveness of a digital medication event reminder and monitor device for patients with tuberculosis (SELFTB): a multicenter randomized controlled trial

BACKGROUND

Tuberculosis remains the leading cause of death from a single infectious disease worldwide. Trials evaluating digital adherence technologies for tuberculosis in low- and middle-income countries are urgently needed. We aimed to assess whether a digital medication event reminder and monitor (MERM) device-observed self-administered therapy improves adherence and treatment outcomes in patients with tuberculosis compared with the standard in-person directly observed therapy (DOT).

METHODS

We did a two-arm, attention-controlled, effectiveness-implementation type 2 hybrid, randomized controlled trial in ten healthcare facilities in Addis Ababa, Ethiopia. We included adults with new or previously treated, bacteriologically confirmed, drug-sensitive pulmonary tuberculosis who were eligible to start anti-tuberculosis therapy. Participants were randomly assigned (1:1) to receive a 15-day tuberculosis medication supply in the evriMED500® MERM device to self-administer and return every 15 days (intervention arm) or visit the healthcare facilities each day to swallow their daily dose with DOT by healthcare providers (control arm). Both arms were followed throughout the standard two-month intensive treatment phase (2RHZE). For control participants, some provider-approved take-home doses might be allowed for extenuating circumstances in real-world practice. Data were collected on patient information (demographic, socioeconomic, behavioral, social, and clinical information), medication adherence measures (MERM vs. DOT records, IsoScreenTM urine colorimetric isoniazid test, and adherence self-report), and clinical measures (pre-post treatment sputum Xpert MTB/RIF assay or microscopy, and adverse treatment outcomes). The intention-to-treat (ITT) primary endpoints were (1) individual-level percentage adherence over the two-month intensive phase measured by adherence records compiled from MERM device vs. DOT records that also considered all take-home doses as having been ingested and (2) sputum smear conversion following the standard two-month intensive phase treatment. Secondary endpoints were (1) individual-level percentage adherence over the two-month intensive phase measured by adherence records compiled from the MERM device vs. DOT records that considered all take-home doses as not ingested, (2) negative IsoScreen urine isoniazid test, (3) adverse treatment outcome (having at least one of the three events: treatment not completed; death; or loss to follow-up), and (4) self-reported adherence. The MERM device has an electronic module and a medication container that records adherence, stores medication, emits audible and visual on-board alarms to remind patients to take their medications on time and refill, and enables providers to download the data and monitor adherence.

RESULTS

Participants were enrolled into the study between 02 June 2020 and 15 June 2021, with the last participant completing follow-up on 15 August 2021. A total of 337 patients were screened for eligibility, of whom 114 were randomly assigned and included in the final analysis [57 control and 57 intervention participants]. Participants were 64.9% male, 15% with HIV, 10.5% retreatment, and 5.3% homeless. Adherence to TB medication was comparable between the intervention arm [geometric mean percentage (GM%) 99.01%, geometric standard deviation (GSD) 1.02] and the control arm [GM% 98.97%, GSD 1.04] and was within the prespecified margin for non-inferiority [mean ratio (MR) 1.00 (95% CI 0.99-1.01); p = 0.954]. The intervention arm was significantly superior to the control arm in the secondary analysis that considered all take-home doses in the control were not ingested [control GM% 77.71 (GSD 1.57), MR 1.27 (95% CI 1.33-1.43)]. Urine isoniazid testing was done on 443 (97%) samples from 114 participants; 13 participants had at least one negative result; a negative test was significantly more common among the control group compared with the intervention group [11/57 (19.3%) vs 2/57 (3.5%); p = 0.008]. There was no significant difference between the control and intervention arms for smear conversion [55 (98.2%) vs 52 (100%); p>0.999], adverse treatment outcomes [0 vs 1 (1.9%); p = 0.48], and self-report non-adherence [5 (8.9%) vs 1 (1.9%); p = 0.21].

CONCLUSIONS

In this randomized trial of patients with drug-sensitive pulmonary tuberculosis, medication adherence among participants assigned to MERM-observed self-administered therapy was non-inferior and superior by some measures when compared with the standard in-person DOT. Further research is needed to understand whether adherence in the intervention is primarily driven by allowing self-administered therapy which reduced challenges of repeated clinic visits or by the adherence support provided by the MERM system. To avoid contributing to patient barriers with DOT, tuberculosis medical programs should consider alternatives such as medication event monitors.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04216420.

Cost and Cost-Effectiveness of a Digital Adherence Technology for Tuberculosis Treatment Support in Uganda

OBJECTIVES

Digital adherence technologies like 99DOTS are increasingly considered as an alternative to directly observed therapy for tuberculosis (TB) treatment supervision. We evaluated the cost and cost-effectiveness of 99DOTS in a high-TB-burden setting.

METHODS

We assessed the costs of implementing 99DOTS in Uganda through a pragmatic, stepped-wedge randomized trial. We measured costs from the health system perspective at 5 of 18 study facilities. Self-reported service activity time data were used to assess activity-based service costs; other costs were captured from budgets and key informant discussions using standardized forms. We estimated costs and effectiveness considering the 8-month study period ("trial specific") and using a 5-year time horizon ("extended activities"), the latter including a "marginal clinic" expansion scenario that ignored above-site implementation costs. Cost-effectiveness was assessed as cost per patient successfully completing treatment, using Monte Carlo simulation, cost-effectiveness acceptability curves, and sensitivity analyses to evaluate uncertainty and robustness of results.

RESULTS

The total cost of implementing 99DOTS in the "trial-specific" scenario was $99 554 across 18 clinics (range $3771-$6238 per clinic). The cost per treatment success in the "trial-specific" scenario was $355 (range $229-$394), falling to $59 (range $50-$70) assuming "extended activities," and $49 (range $42-$57) in the "marginal clinic" scenario. The incremental cost-effectiveness of 99DOTS in the "extended-activity" scenario was $355 per incremental treatment success.

CONCLUSIONS

Costs and cost-effectiveness of 99DOTS were influenced by the degree to which infrastructure is scaled over time. If sustained and scaled up, 99DOTS can be a cost-effective option for TB treatment adherence support in high-TB-burden settings like Uganda.

Evaluation of implementation and effectiveness of digital adherence technology with differentiated care to support tuberculosis treatment adherence and improve treatment outcomes in Ethiopia: a study protocol for a cluster randomised trial

Background

Digital adherence technologies (DATs) are recommended to support patient-centred, differentiated care to improve tuberculosis (TB) treatment outcomes, but evidence that such technologies improve adherence is limited. We aim to implement and evaluate the effectiveness of smart pillboxes and medication labels linked to an adherence data platform, to create a differentiated care response to patient adherence and improve TB care among adult pulmonary TB participants. Our study is part of the Adherence Support Coalition to End TB (ASCENT) project in Ethiopia.

Methods/Design

We will conduct a pragmatic three-arm cluster-randomised trial with 78 health facilities in two regions in Ethiopia. Facilities are randomised (1:1:1) to either of the two intervention arms or standard of care. Adults aged ≥ 18 years with drug-sensitive (DS) pulmonary TB are enrolled over 12 months and followed-up for 12 months after treatment initiation. Participants in facilities randomised to either of the two intervention arms are offered a DAT linked to the web-based ASCENT adherence platform for daily adherence monitoring and differentiated response to patient adherence for those who have missed doses. Participants at standard of care facilities receive routine care. For those that had bacteriologically confirmed TB at treatment initiation and can produce sputum without induction, sputum culture will be performed approximately 6 months after the end of treatment to measure disease recurrence. The primary endpoint is a composite unfavourable outcome measured over 12 months from TB treatment initiation defined as either poor end of treatment outcome (lost to follow-up, death, or treatment failure) or treatment recurrence measured 6 months after the scheduled end of treatment. This study will also evaluate the effectiveness, feasibility, and cost-effectiveness of DAT systems for DS-TB patients.

Discussion

This trial will evaluate the impact and contextual factors of medication label and smart pillbox with a differentiated response to patient care, among adult pulmonary DS-TB participants in Ethiopia. If successful, this evaluation will generate valuable evidence via a shared evaluation framework for optimal use and scale-up.

Trial registration: Pan African Clinical Trials Registry PACTR202008776694999, https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=12241, registered on August 11, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06833-x.

Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India

Background

Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures.

Methods

We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, 4-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure's operating characteristics, with particular interest in specificity-that is, the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing.

Results

Compared with urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (area under the curve [AUC], 0.65; specificity, 70%; 95% CI, 58%-81%), 99DOTS patient- and provider-reported doses (AUC, 0.61; specificity, 33%; 95% CI, 22%-45%), pill estimate (AUC, 0.55; specificity, 21%; 95% CI, 12%-32%), 4-day recall (AUC, 0.60; specificity, 23%; 95% CI, 14%-34%), and last missed dose question (AUC, 0.65; specificity, 52%; 95% CI, 40%-63%).

Conclusions

Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.