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      Effectiveness of Electronic Reminders to Improve Medication Adherence in Tuberculosis Patients: A Cluster-Randomised Trial

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          Abstract

          Background

          Mobile text messaging and medication monitors (medication monitor boxes) have the potential to improve adherence to tuberculosis (TB) treatment and reduce the need for directly observed treatment (DOT), but to our knowledge they have not been properly evaluated in TB patients. We assessed the effectiveness of text messaging and medication monitors to improve medication adherence in TB patients.

          Methods and Findings

          In a pragmatic cluster-randomised trial, 36 districts/counties (each with at least 300 active pulmonary TB patients registered in 2009) within the provinces of Heilongjiang, Jiangsu, Hunan, and Chongqing, China, were randomised using stratification and restriction to one of four case-management approaches in which patients received reminders via text messages, a medication monitor, combined, or neither (control). Patients in the intervention arms received reminders to take their drugs and reminders for monthly follow-up visits, and the managing doctor was recommended to switch patients with adherence problems to more intensive management or DOT. In all arms, patients took medications out of a medication monitor box, which recorded when the box was opened, but the box gave reminders only in the medication monitor and combined arms. Patients were followed up for 6 mo. The primary endpoint was the percentage of patient-months on TB treatment where at least 20% of doses were missed as measured by pill count and failure to open the medication monitor box. Secondary endpoints included additional adherence and standard treatment outcome measures. Interventions were not masked to study staff and patients. From 1 June 2011 to 7 March 2012, 4,292 new pulmonary TB patients were enrolled across the 36 clusters. A total of 119 patients (by arm: 33 control, 33 text messaging, 23 medication monitor, 30 combined) withdrew from the study in the first month because they were reassessed as not having TB by their managing doctor (61 patients) or were switched to a different treatment model because of hospitalisation or travel (58 patients), leaving 4,173 TB patients (by arm: 1,104 control, 1,008 text messaging, 997 medication monitor, 1,064 combined). The cluster geometric mean of the percentage of patient-months on TB treatment where at least 20% of doses were missed was 29.9% in the control arm; in comparison, this percentage was 27.3% in the text messaging arm (adjusted mean ratio [aMR] 0.94, 95% CI 0.71, 1.24), 17.0% in the medication monitor arm (aMR 0.58, 95% CI 0.42, 0.79), and 13.9% in the combined arm (aMR 0.49, 95% CI 0.27, 0.88). Patient loss to follow-up was lower in the text messaging arm than the control arm (aMR 0.42, 95% CI 0.18–0.98). Equipment malfunction or operation error was reported in all study arms. Analyses separating patients with and without medication monitor problems did not change the results. Initiation of intensive management was underutilised.

          Conclusions

          This study is the first to our knowledge to utilise a randomised trial design to demonstrate the effectiveness of a medication monitor to improve medication adherence in TB patients. Reminders from medication monitors improved medication adherence in TB patients, but text messaging reminders did not. In a setting such as China where universal use of DOT is not feasible, innovative approaches to support patients in adhering to TB treatment, such as this, are needed.

          Trial Registration

          Current Controlled Trials, ISRCTN46846388

          Abstract

          In a cluster-randomized controlled trial, Katherine Fielding and colleagues examine the effectiveness of electronic reminders for improving tuberculosis medication adherence.

          Editors' Summary

          Background

          Tuberculosis—a contagious bacterial disease that usually infects the lungs—is a major global public health problem. Every year, about 9 million people develop tuberculosis and at least 1.3 million people die as a result. Mycobacterium tuberculosis, the organism that causes tuberculosis, is spread in airborne droplets when people with tuberculosis cough or sneeze. The symptoms of tuberculosis include cough, weight loss, and fever. Diagnostic tests for tuberculosis include sputum smear microscopy (microscopic analysis of mucus coughed up from the lungs), the growth of M. tuberculosis from sputum samples, and chest X-rays. Tuberculosis can be cured by taking antibiotics daily for several months (usually isoniazid, rifampicin, ethambutol, and pyrazinamide for two months followed by isoniazid and rifampicin for a further four months), but the emergence of multidrug-resistant M. tuberculosis is making tuberculosis increasingly hard to treat.

          Why Was This Study Done?

          Because tuberculosis treatment is long and unpleasant, patients often fail to take all their drugs. To improve medication adherence, the World Health Organization recommends that health care workers supervise patients while they take their medication (directly observed treatment, DOT). However, DOT can be hard to implement. In China, for example, where 11% of tuberculosis cases occur, DOT cannot be implemented in many parts of the country, and the national tuberculosis control policy permits self-administered treatment and treatment monitored by family members. It is estimated that over half of individuals with tuberculosis in China self-administer their treatment, but, in 2010, 20% of patients treated using nationally recommended case-management approaches were lost to follow-up or failed to take their medications regularly. In this pragmatic cluster-randomized trial, the researchers investigate whether reminders delivered by mobile phone or by medication monitor boxes (which provide audio reminders to patients and record when the box is opened) might improve tuberculosis medication adherence in China. A pragmatic trial asks whether an intervention works under real-life conditions; a cluster-randomized trial randomly assigns groups of people (here, people living in different counties/districts) to receive alternative interventions and compares outcomes in the differently treated “clusters.”

          What Did the Researchers Do and Find?

          The researchers assigned people newly diagnosed with tuberculosis in counties/districts to receive reminders about taking their antibiotics and about monthly follow-up visits via text messaging, a medication monitor, or both text messaging and a medication monitor (the intervention arms), or to receive standard nationally recommended care without electronic reminders (the control arm). All the trial participants (about 1,000 per arm) took their drugs out of a medication monitor box, but the box’s audio reminder function was switched off in the text messaging only and control arms. In the intervention arms, doctors were advised to switch participants with poor medication adherence (evaluated at follow-up visits) to either more intensive management or DOT, depending on the level of missed treatment doses. Compared to the control arm, the percentage of patient-months with at least 20% of the drug doses missed (called “poor adherence” and measured by pill counts and data from the medication monitor) was not significantly reduced in the text messaging arm, whereas poor adherence was significantly reduced by 42% and 51% in the medication monitor and the combined arms, respectively (a significant reduction is unlikely to have happened by chance). Notably, fewer patients were switched to intensive management or DOT than expected based on medication adherence evaluations.

          What Do These Findings Mean?

          These findings show that, in China, the use of an electronic medication monitor box to remind patients to take their anti-tuberculosis drugs improved medication adherence. Interestingly, text messaging alone, which has been shown to improve adherence to antiretroviral therapy among HIV-positive individuals, did not improve medication adherence among patients with tuberculosis, possibly because the messages were too frequent or too impersonal, although this intervention (but none of the others) did reduce patient loss to follow-up. Battery problems with the medication monitor may have resulted in over-estimation of poor adherence to treatment. Moreover, the researchers’ assumption that opening the medication monitor box is synonymous with taking the medication may have introduced some inaccuracies into these findings. Despite these limitations and the underuse of more intensive case management in patients with poor adherence, these findings suggest that using medication monitors to deliver electronic drug reminders to patients might improve medication adherence among patients with tuberculosis in China and in other settings.

          Additional Information

          This list of resources contains links that can be accessed when viewing the PDF on a device or via the online version of the article at http://dx.doi.org/10.1371/journal.pmed.1001876.

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          Most cited references11

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          Tuberculosis prevalence in China, 1990-2010; a longitudinal analysis of national survey data.

          China scaled up a tuberculosis control programme (based on the directly observed treatment, short-course [DOTS] strategy) to cover half the population during the 1990s, and to the entire population after 2000. We assessed the effect of the programme. In this longitudinal analysis, we compared data from three national tuberculosis prevalence surveys done in 1990, 2000, and 2010. The 2010 survey screened 252,940 eligible individuals aged 15 years and older at 176 investigation points, chosen by stratified random sampling from all 31 mainland provinces. All individuals had chest radiographs taken. Those with abnormal radiographs, persistent cough, or both, were classified as having suspected tuberculosis. Tuberculosis was diagnosed by chest radiograph, sputum-smear microscopy, and culture. Trained staff interviewed each patient with tuberculosis. The 1990 and 2000 surveys were reanalysed and compared with the 2010 survey. From 1990 to 2010, the prevalence of smear-positive tuberculosis decreased from 170 cases (95% CI 166-174) to 59 cases (49-72) per 100,000 population. During the 1990s, smear-positive prevalence fell only in the provinces with the DOTS programme; after 2000, prevalence decreased in all provinces. The percentage reduction in smear-positive prevalence was greater for the decade after 2000 than the decade before (57% vs 19%; p<0.0001). 70% of the total reduction in smear-positive prevalence (78 of 111 cases per 100,000 population) occurred after 2000. Of these cases, 68 (87%) were in known cases-ie, cases diagnosed with tuberculosis before the survey. Of the known cases, the proportion treated by the public health system (using the DOTS strategy) increased from 59 (15%) of 370 cases in 2000 to 79 (66%) of 123 cases in 2010, contributing to reduced proportions of treatment default (from 163 [43%] of 370 cases to 35 [22%] of 123 cases) and retreatment cases (from 312 [84%] of 374 cases to 48 [31%] of 137 cases; both p<0.0001). In 20 years, China more than halved its tuberculosis prevalence. Marked improvement in tuberculosis treatment, driven by a major shift in treatment from hospitals to the public health centres (that implemented the DOTS strategy) was largely responsible for this epidemiological effect. Chinese Ministry of Health. Copyright © 2014 Elsevier Ltd. All rights reserved.
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            Identification and Assessment of Adherence-Enhancing Interventions in Studies Assessing Medication Adherence Through Electronically Compiled Drug Dosing Histories: A Systematic Literature Review and Meta-Analysis

            Background Non-adherence to medications is prevalent across all medical conditions that include ambulatory pharmacotherapy and is thus a major barrier to achieving the benefits of otherwise effective medicines. Objective The objective of this systematic review was to identify and to compare the efficacy of strategies and components thereof that improve implementation of the prescribed drug dosing regimen and maintain long-term persistence, based on quantitative evaluation of effect sizes across the aggregated trials. Data sources MEDLINE, EMBASE, CINAHL, the Cochrane Library, and PsycINFO were systematically searched for randomized controlled trials that tested the efficacy of adherence-enhancing strategies with self-administered medications. The searches were limited to papers in the English language and were included from database inception to 31 December 2011. Study selection Our review included randomized controlled trials in which adherence was assessed by electronically compiled drug dosing histories. Five thousand four hundred studies were screened. Eligibility assessment was performed independently by two reviewers. A structured data collection sheet was developed to extract data from each study. Study appraisal and synthesis methods The adherence-enhancing components were classified in eight categories. Quality of the papers was assessed using the criteria of the Cochrane Handbook for Systematic Reviews of Interventions guidelines to assess potential bias. A combined adherence outcome was derived from the different adherence variables available in the studies by extracting from each paper the available adherence summary variables in a pre-defined order (correct dosing, taking adherence, timing adherence, percentage of adherent patients). To study the association between the adherence-enhancing components and their effect on adherence, a linear meta-regression model, based on mean adherence point estimates, and a meta-analysis were conducted. Results Seventy-nine clinical trials published between 1995 and December 2011 were included in the review. Patients randomized to an intervention group had an average combined adherence outcome of 74.3 %, which was 14.1 % higher than in patients randomized to the control group (60.2 %). The linear meta-regression analysis with stepwise variable selection estimated an 8.8 % increase in adherence when the intervention included feedback to the patients of their recent dosing history (EM-feedback) (p < 0.01) and a 5.0 % increase in adherence when the intervention included a cognitive-educational component (p = 0.02). In addition, the effect of interventions on adherence decreased by 1.1 % each month. Sensitivity analysis by selecting only high-quality papers confirmed the robustness of the model. The random effects model in the meta-analysis, conducted on 48 studies, confirmed the above findings and showed that the improvement in adherence was 19.8 % (95 % CI 10.7–28.9 %) among patients receiving EM-feedback, almost double the improvement in adherence for studies that did not include this type of feedback [10.3 % (95 % CI 7.5–13.1 %)] (p < 0.01). The improvement in adherence was 16.1 % (95 % CI 10.7–21.6 %) in studies that tested cognitive-educational components versus 10.1 % (95 % CI 6.6–13.6 %) in studies that did not include this type of intervention (p = 0.04). Among 57 studies measuring clinical outcomes, only 8 reported a significant improvement in clinical outcome. Limitations Despite a common measurement, the meta-analysis was limited by the heterogeneity of the pooled data and the different measures of medication adherence. The funnel plot showed a possible publication bias in studies with high variability of the intervention effect. Conclusions Notwithstanding the statistical heterogeneity among the studies identified, and potential publication bias, the evidence from our meta-analysis suggests that EM-feedback and cognitive-educational interventions are potentially effective approaches to enhance patient adherence to medications. The limitations of this research highlight the urgent need to define guidelines and study characteristics for research protocols that can guide researchers in designing studies to assess the effects of adherence-enhancing interventions. Electronic supplementary material The online version of this article (doi:10.1007/s40265-013-0041-3) contains supplementary material, which is available to authorized users.
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              Progress in tuberculosis control and the evolving public-health system in China

              Summary China has the world's second largest tuberculosis epidemic, but progress in tuberculosis control was slow during the 1990s. Detection of tuberculosis had stagnated at around 30% of the estimated total of new cases, and multidrug-resistant tuberculosis was a major problem. These signs of inadequate tuberculosis control can be linked to a malfunctioning health system. The spread of severe acute respiratory syndrome (SARS) in 2003, brought to light substantial weaknesses in the country's public-health system. After the SARS epidemic was brought under control, the government increased its commitment and leadership to tackle public-health problems and, among other efforts, increased public-health funding, revised laws that concerned the control of infectious diseases, implemented the world's largest internet-based disease reporting system, and started a programme to rebuild local public-health facilities. These measures contributed to acceleration in efforts to control tuberculosis. By 2005, the detection of cases of tuberculosis had increased to 80% of the estimated total new cases, permitting China to achieve the 2005 global tuberculosis control targets. At the same time, specific efforts to improve tuberculosis control also contributed to strengthening of the public-health system. We examine how the strengthening of a disease control programme and the public-health system worked together to achieve a desired health outcome.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                15 September 2015
                September 2015
                : 12
                : 9
                : e1001876
                Affiliations
                [1 ]National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
                [2 ]MRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, United Kingdom
                [3 ]Jiangsu Province Center for Disease Control and Prevention, Nanjing, Jiangsu, China
                [4 ]Chongqing Provincial Tuberculosis Dispensary, Chongqing, Chongqing, China
                [5 ]Heilongjiang Provincial Tuberculosis Dispensary, Harbin, Heilongjiang, China
                [6 ]Hunan Provincial Tuberculosis Dispensary, Changsha, Hunan, China
                [7 ]Dafeng County Center for Disease Control and Prevention, Dafeng, Jiangsu, China
                [8 ]China Office, Bill & Melinda Gates Foundation, Beijing, China
                University of California, San Francisco, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: XL JJL HZ JL XLi SH SC LW SJ DPC KLF. Performed the experiments: XL HZ WL SZ GZ LB JL XLi HC JLu. Analyzed the data: XL JJL HZ JL XLi HC ML RC JC SH SC LW SJ DPC KLF. Wrote the first draft of the manuscript: XL JJL DPC KLF. Contributed to the writing of the manuscript: XL JJL HZ WL SZ GZ LB JL XLi HC ML RC JC JLu SH SC LW SJ DPC KLF. Enrolled patients: WL SZ GZ LB JLu. Agree with the manuscript’s results and conclusions: XL JJL HZ WL SZ GZ LB JL XLi HC ML RC JC JLu SH SC LW SJ DPC KLF. All authors have read, and confirm that they meet, ICMJE criteria for authorship. SZ was unable to confirm for himself and all other authors have confirmed on his behalf that he meets ICMJE authorship criteria.

                ‡ Author Shun Zhang was unable to confirm his authorship contributions. On his behalf, all other authors have reported his contributions to the best of their knowledge.

                Article
                PMEDICINE-D-15-00471
                10.1371/journal.pmed.1001876
                4570796
                26372470
                9928181b-06f0-4950-adb4-5eedaf44d039
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 13 February 2015
                : 5 August 2015
                Page count
                Figures: 2, Tables: 4, Pages: 18
                Funding
                The study was funded by the Bill & Melinda Gates Foundation, grant number 51914 ( http://www.gatesfoundation.org/). The funders (DPC, SH) contributed to design, running of the trial, and preparation of manuscript.
                Categories
                Research Article
                Custom metadata
                Data are available in the LSHTM Data Compass repository, http://dx.doi.org/10.17037/DATA.4.

                Medicine
                Medicine

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