RESEARCH ARTICLE Open Access

Pathways to multidrug-resistanttuberculosis diagnosis and treatmentinitiation: a qualitative comparison ofpatients’ experiences in the era of rapidmolecular diagnostic testsPren Naidoo1*, Margaret van Niekerk1, Elizabeth du Toit1, Nulda Beyers1 and Natalie Leon2

Abstract

Background: Although new molecular diagnostic tests such as GenoType MTBDRplus and Xpert® MTB/RIFhave reduced multidrug-resistant tuberculosis (MDR-TB) treatment initiation times, patients’ experiences ofdiagnosis and treatment initiation are not known. This study aimed to explore and compare MDR-TB patients’experiences of their diagnostic and treatment initiation pathway in GenoType MTBDRplus and Xpert® MTB/RIF-based diagnostic algorithms.

Methods: The study was undertaken in Cape Town, South Africa where primary health-care services providedfree TB diagnosis and treatment. A smear, culture and GenoType MTBDRplus diagnostic algorithm was usedin 2010, with Xpert® MTB/RIF phased in from 2011–2013. Participants diagnosed in each algorithm at fourfacilities were purposively sampled, stratifying by age, gender and MDR-TB risk profiles. We conducted in-depth qualitative interviews using a semi-structured interview guide. Through constant comparative analysiswe induced common and divergent themes related to symptom recognition, health-care access, testing forMDR-TB and treatment initiation within and between groups. Data were triangulated with clinical informationand health visit data from a structured questionnaire.

Results: We identified both enablers and barriers to early MDR-TB diagnosis and treatment. Half the patientshad previously been treated for TB; most recognised recurring symptoms and reported early health-seeking.Those who attributed symptoms to other causes delayed health-seeking. Perceptions of poor public sectorservices were prevalent and may have contributed both to deferred health-seeking and to patient’s use ofthe private sector, contributing to delays. However, once on treatment, most patients expressed satisfactionwith public sector care. Two patients in the Xpert® MTB/RIF-based algorithm exemplified its potential toreduce delays, commencing MDR-TB treatment within a week of their first health contact. However, mostpatients in both algorithms experienced substantial delays. Avoidable health system delays resulted fromproviders not testing for TB at initial health contact, non-adherence to testing algorithms, results not beingavailable and failure to promptly recall patients with positive results.(Continued on next page)

* Correspondence: pnaidoo@icon.co.za1Desmond Tutu TB Centre, Department of Paediatrics and Child Health,Faculty of Medicine and Health Sciences, Stellenbosch University,Stellenbosch, South AfricaFull list of author information is available at the end of the article

© 2015 Naidoo et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Naidoo et al. BMC Health Services Research (2015) 15:488 DOI 10.1186/s12913-015-1145-0

http://crossmark.crossref.org/dialog/?doi=10.1186/s12913-015-1145-0&domain=pdfmailto:pnaidoo@icon.co.zahttp://creativecommons.org/licenses/by/4.0/http://creativecommons.org/publicdomain/zero/1.0/

(Continued from previous page)

Conclusion: Whilst the introduction of rapid tests such as Xpert® MTB/RIF can expedite MDR-TB diagnosisand treatment initiation, the full benefits are unlikely to be realised without reducing delays in health-seekingand addressing the structural barriers present in the health-care system.

Keywords: GenoType MTBDRplus line probe assay, Xpert® MTB/RIF, Pathways to care, Health-seekingbehaviour, Diagnostic and treatment delay, Obstacles to care

BackgroundThe World Health Organisation (WHO) identified the needto address multi-drug resistant tuberculosis (MDR-TB) as apublic health crisis as one of five key priorities [1]. Improv-ing MDR-TB control requires rapid, accurate diagnostics toenable early and appropriate treatment [1, 2] with benefitto both patients and the public through reductions in mor-bidity, mortality and transmission within communities[2, 3]. Advances have been made in the development,evaluation and routine use of rapid, accurate molecu-lar diagnostic tests for MDR-TB. South Africa was anearly adopter of two WHO approved tests, GenoTypeMTBDRplus (Hain Lifescience GmbH, Nehren, Germany)line probe assay (LPA) [4] and Xpert® MTB/RIF (Cepheid,Sunnyvale, CA, USA) (Xpert) [5].Studies have shown that both LPA [6, 7] and Xpert [8]

reduced MDR-TB diagnostic and treatment initiationtimes in comparison to previous tests. Test performance,as well as both patient and health system factors influ-ence the potential of rapid diagnostics to reduce diag-nostic and treatment delays [9]. Although not specific toMDR-TB, studies have found a number of factors associ-ated with patient delay in accessing care in sub-SaharanAfrica [10]. Fear of a positive human immunodeficiencyvirus (HIV) test or the stigma associated with this [11–13],the belief that symptoms, like cough, would resolve spon-taneously or improve with self-medication [11, 13, 14], un-certainty about the cause of their illness and visits tomultiple providers [13–15] all contributed to delays inseeking care. Health provider delays were influenced bythe availability of laboratory resources, initial screen-ing efficacy, timely and correct request for laboratoryinvestigations and the coordination of patient manage-ment between different health-care providers [13, 16, 17].There is a paucity of literature detailing MDR-TB pa-

tients’ experience of diagnosis and treatment initiation.This study aimed to explore and compare MDR-TB pa-tients’ experiences of their pathway to diagnosis and treat-ment initiation in LPA and Xpert-based diagnosticalgorithms. The study was part of a broader PROVE IT(Policy Relevant Outcomes from Validating Evidence onImpacT) (http://www.treattb.org) evaluation that assessedthe impact of new molecular tests on the diagnosis andtreatment of TB in routine operational conditions. Impactanalysis was guided by the Impact Assessment Framework

[18] which provides a systematic, comprehensive approachto generating evidence to support decision-making for newdiagnostics.

MethodsStudy settingThe study took place in Cape Town, South Africa. CapeTown has a high TB burden with 28,658 TB cases and953 MDR-TB cases notified in 2011 and a TB case noti-fication rate of 752/100,000 population. Free TB diag-nostic services were provided at 142 primary health-care(PHC) facilities offering two different service platforms.Community Health Centres (CHC) were large, busy fa-cilities treating acutely ill adults and most offered onlyTB diagnostic services. Clinics tended to be smaller, fo-cused on disease prevention and offered both TB diag-nostic and treatment services. All TB tests were done ata central laboratory that received daily specimens viacourier and recorded results in a networked, electroniclaboratory database. Rapid, on-site HIV-testing was rou-tinely offered to presumptive TB cases.In 2010, a smear, culture and LPA-based diagnostic algo-

rithm was used (Fig. 1) with LPA done on culture isolatesor clinical specimens of high MDR-TB-risk presumptivecases (those with previous TB, an MDR-TB contact orfrom a congregate setting). Doctors at the TB-hospitalreviewed case records and prescribed MDR-TB treatmentbut patients could initiate treatment at PHC facilities.From 2011–2013, Xpert was phased in, replacing

smear microscopy for all presumptive TB cases (Fig. 1).Full decentralisation of treatment occurred from 2012with doctors at PHC facilities initiating standardisedMDR-TB treatment without the need for prior case re-view at the TB-hospital.

SamplingPatients in this study were part of a PROVE-IT observa-tional cohort in 10 high TB-burden PHC facilities se-lected from a total of 29 that met the criteria of a TBcaseload of >350 in 2009. Health facility and patientsampling details are provided in Fig. 2. We limited thenumber of facilities in this study for logistic reasons andpurposively selected four of these facilities to ensure ra-cial / ethnic representation and a socio-economic mix of

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http://treattb.org

patients from both informal settlements and establishedresidential areas.Eligible patients were >18-years of age, had been diag-

nosed with rifampicin or rifampicin and isoniazid resist-ance from sputa taken and tested in Cape Town betweenJune 2010 and December 2012, and had received MDR-TB treatment at one of the four PHC facilities. Patientswith previous MDR-TB treatment were excluded as theirpathway to care may have been different. Patients withadditional drug-resistance, in hospital or in prison, stillsmear-positive or with loss to follow-up at the time of thescheduled interview were excluded (Fig. 2).Patients diagnosed at the selected facilities were identi-

fied from an electronic laboratory database; those diag-nosed elsewhere, but on treatment at these facilities,were identified through facility registers and clinical re-cords. As patients in each diagnostic algorithm becameeligible, PHC facility nurses enquired whether they werewilling to participate and provided their contact detailsto researchers for structured interviews. We purposivelysampled a subset from the four facilities for qualitativeinterviews, stratifying participants by age, gender andMDR-TB risk profiles. PHC facility nurses asked selectedpatients if they were willing to participate in the secondinterview. Recruitment continued until an appropriaterange of participants was interviewed and saturation wasachieved in terms of key findings in both algorithms andno new themes appeared to emerge. We interviewed 16patients diagnosed in the LPA-based algorithm between

2010 and 2012 and 10 patients diagnosed in the Xpert-based algorithm between 2011 and 2012.

The research teamThe research team comprised a senior social scientist withoversight for this qualitative study (NL), two social sciencefield researchers, two professional nurses, a health sci-ences researcher (MvN), a PhD medical researcher whowas the principal investigator (PN) and a clinician (EdT).None of the researchers were involved in the delivery ofhealth services or care of patients.

Data collectionAs part of the broader PROVE IT study, professionalnurses reviewed clinical records and completed a caserecord form (CRF) with demographic and clinical infor-mation. Three to six months after MDR-TB treatmenthad commenced, field researchers contacted eligible pa-tients, obtained informed consent, interviewed patientsand completed a structured questionnaire (Interview 1)detailing the care-seeking pathway, health-care visits andservices received. Shortly thereafter, field researcherscontacted the patients selected for this study, took in-formed consent again and conducted in-depth qualita-tive interviews in English or the patient’s mother tongue(Interview 2). We elected to use interviews to elicit pa-tients’ first-hand experiences of their pathway to care.For infection control purposes, interviewers and patientswore N95-respirators and interviews were conducted in

Fig. 1 Testing in the LPA and Xpert-based TB diagnostic algorithms. High MDR-TB-risk presumptive cases refer to those with previous TB,an MDR-TB contact or from a congregate setting. In the LPA-based algorithm, only these cases were initially screened for drug susceptibility. LowMDR-risk presumptive TB cases would only be identified when 1st-line TB treatment regimens failed. In the Xpert-based algorithm in comparsion, allpresumptive TB cases were simultaneously screened for TB and rifampicn resistance using Xpert

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well-ventilated, private spaces at PHC facilities. Both theCRF and structured questionnaire were reviewed priorto interviews and the information was used to probe andclarify responses provided by the patients.A semi-structured interview guide with open-ended

questions was used. Patients were asked to provide a de-tailed account of their experiences from symptom onsetto MDR-TB treatment initiation. Aspects of the care path-way explored in detail included patients’ recognition oftheir initial symptoms, their decisions around where theysought medical care, their experience of these health ser-vices and their MDR-TB diagnostic and treatment initi-ation process. All interviews were digitally recorded,translated into English where necessary and transcribed.

Data analysisData analysis was undertaken by three of the authors(PN, MvN, NL). Each analyst read interview transcripts

several times during the course of the study to familiar-ise themselves with their content. Analysts used opencoding to independently identify key issues and themesin each stage of the care pathway with constant compari-son within and between groups. We jointly recorded keyevents and issues for each patient on a treatment journeymatrix based on data from the interview, supplementedby data from the case report forms and structured ques-tionnaires. Consensus was reached through discussion.We used a combination of deductive (having exploredspecific aspects of the care pathway and the motivationbehind patients’ actions) and inductive analysis, identifyingcommon and divergent themes emerging from the datathat were not specifically elicited [33].

EthicsThe City Health Directorate and Western Cape HealthDepartment granted permission to undertake the study.

Fig. 2 Primary health facility and MDR-TB patient selection. Patients in this study were part of a PROVE-IT observational cohort in 10 high TB-burden PHCfacilities selected from a total of 29 that met the criteria of a high TB caseload in 2009. The flowchart indicates the selection of health facilities and patientsfor this study. Data from Interview 1 elicited quantitative information related to duration of illness, health-seeking visits and providers, cost incurred andsocio-economic status data (used for costing purposes, to evaluate delay and to supplement information on patient pathways). Interview 2was an in-depth qualitative interview exploring patients’ perspectives of their pathways to care and formed the basis for this manuscript

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The Health Research Ethics Committee at StellenboschUniversity (IRB0005239) (N10/09/308) and Ethics Advis-ory Group at The International Union Against Tubercu-losis and Lung Disease (59/10) approved the study andprovided a waiver of informed consent for the use ofroutine data. Written informed consent, in the patient’spreferred language, was obtained prior to completion ofthe structured questionnaire and qualitative interviews.Patients were provided with refreshments but were notreimbursed financially for interviews.

ResultsWe interviewed 12 female (6 in each group) and 14 maleparticipants ranging from 20 to 58 years in age. Thirteen

patients had previously been treated for TB and 17 wereco-infected with HIV.We present key themes in four components of the

care-pathway: symptom recognition, health-care access,testing for MDR-TB and MDR-TB treatment initiation.We have combined the description of patients’ experi-ences for both the LPA and Xpert-based algorithms andhave highlighted similarities and differences. We identi-fied both enablers and barriers to early MDR-TB diagno-sis and treatment and summarise these in Table 1.

Symptom recognitionPatients described their symptoms, what they attributedthese to and what led them to seek care. Most described

Table 1 Barriers and enablers in the pathway to early MDR-TB diagnosis and treatment initiation

Enablers Barriers

Symptom recognition •Symptom recognition based on historyof previous TB

•Failure to recognise TB symptoms

•Minimisation or denial of symptoms

•Social contact with TB/MDR-TB patients •Lack of awareness that TB can recur

•Awareness of increased risk of TB amongstHIV-infected patients

•Incorrectly ascribing symptoms toHIV or other medical condition

Accessing health-care •Perceptions of good quality service •Negative perceptions of the public sector (over-burdened;long waiting times; negative staff attitudes; lack of privacy)

•Convenience of free, accessible local services.

•Familiarity with service

•Family support •Fear of an HIV diagnosis

•Responsiveness of provider at first health contact •Social construct of “being aman”, not admitting illness (seen as weakness)

MDR-TB Testing •Attendance at facilities geared towards TB(i.e. offering both TB diagnosis and treatment)

•Entry point to care through the private sector

•Availability of Xpert MTB/RIF •Accessing facilities providing TB diagnostic but not treatment services.

•Screening of all presumptive TB cases fordrug resistance

•Health providers failure to test for TB / MDR-TB at initial health contact

•Patient’s agency in specifically requesting TBscreening services that were not offered

•Health providers’ failure to follow diagnostic algorithms

•Patient’s agency in pursuing diagnosticprocesses after initial negative tests

•Interruptions to the diagnostic process due to dissatisfactionwith the service, work and family commitments

•Lack of money for transport to return to facility

•Insensitive tests that fail to diagnose TB

•Patients diagnosed clinically or on chest x-rayand started on 1st-line TB treatment

•Failure to respond early to clinical deteriorationfor patients on 1st-line TB treatment

Initiating MDR-TBTreatment

•Health provider scheduling earlyreturn visits for MDR-TB test results

•Patients failure to return for follow-up appointments

•Patients returning forscheduled appointments

•Delays in recalling patients

•Availability of decentralisedMDR-TB treatment

•Results not being available at follow-up appointments

•Perceptions that staff cared abouttheir patient’s well-being

•Family commitments preventing a return to facilities

•Cultural beliefs and seeking traditionalhealthcare (often in another province)

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symptoms typically associated with TB such as cough,night sweats, loss of appetite, weight loss, fever, chestpain and general malaise. Some, particularly those withHIV, described symptoms related to their co-morbidityas their primary concern, for example painful feet for apatient on antiretroviral treatment.

The role of previous TB treatment or social contact with TBpatientsHalf the patients had previously been treated for TB andmany recognised their symptoms as a recurrence. Sev-eral responded by quickly seeking help at a PHC facilityas this patient explained: “I had all the symptoms that Ihad the last time when I had TB. So I wanted them tocheck [for TB]” (Xpert-4). Having had TB before did notalways mean that patients recognised recurring symp-toms or sought timely help. One patient explained: “Idid not believe it could be TB again because I completedmy treatment the first time” (Xpert-9). Several patientsreported that contact with someone on TB or MDR-TBtreatment heightened awareness of their symptoms: “Ithought I had TB because I stayed with someone whohad TB and he did not take his treatment” (LPA-15).Another explained: “I did not know much about MDR-TB. My [relative] had MDR-TB and told me to check if Idon’t have it” (Xpert-7).

The interaction with HIVFor some HIV-infected patients, awareness of their in-creased risk of TB motivated their response: “I wascoughing, my bones pained and I was losing weight…Ithought I had TB …I went to the ARV doctor because Ihad an appointment … and told him how I feel. I askedhim to send me for a TB test” (LPA-15). However otherHIV-infected patients incorrectly ascribed their symp-toms to HIV and delayed seeking care. Fear of being di-agnosed with HIV presented a barrier to accessing earlycare as one patient explained “My mother said I must goto the clinic for a TB test. She was worried that I mayhave TB because my [relative] also had TB. I did notwant to go …too scared that if I go for a TB test they willalso test me for HIV” (LPA-2).

Failure to recognise or acknowledge TB symptomsPatients who did not recognise symptoms as TB–related,tended to minimise their significance. Several attributedsymptoms to other factors, including smoking tobaccoand the weather: “I was having a terrible cough and Iwas sweating at night, but this did not ring an alarm forme, because I still thought this was just a fever and thechange of season and that everything was going to befine” (LPA-3). Others mistook symptoms for “flu”,asthma or other medical conditions: “My grandfatherhad TB in 2006. I knew the symptoms of TB are when a

person is coughing and getting very thin…I did not thinkabout TB… I thought it was swine flu…Everyone wastalking about swine flu” (LPA-16).Some patient’s minimised their symptoms to avoid

causing undue worry to their family. Family roles and re-sponsibilities and the expectations that come with thesecontributed, as one patient reported: “at the time when Istarted to feel sick I felt that I had to act a little bitstrong, to not let the family know how weak I really felt. Imust not let them down. Although I could feel some painI felt I must be a man to face this disease” (Xpert-7).Patients tended to show considerable tolerance for

their symptoms, referring to these as “just a cough” or“just losing weight”. A patient who completely dismissedhis symptoms said: “But at all these times I was not sick.It was just a cough, sweat at night and I felt that I wasalso losing weight, nothing else, not a day I ever felt like Iwas sick” (LPA-8). Symptom tolerance or denial resultedin some patients presenting for care when they were ex-tremely ill, having lost substantial weight or being too illto walk.There was wide variation in the time from symptom

onset to seeking health-care. Some, especially those whorecognised they may have TB, took early action. Othersdelayed seeking care, sometimes for several months, untiltheir symptoms were much worse. The stigma of possiblyhaving TB did not emerge as an issue influencing patients’actions. The findings on symptom recognition were simi-lar for patients in both the LPA and Xpert-based algo-rithms. It was interesting to note that none of the patientsin the Xpert group reported a heightened awareness of TBor of the newly introduced test.

Accessing health-carePatients described when and where they first sought careand what motivated their choice of provider. Although thepublic sector was the most common entry-point to care,several (about one third) first visited the private sector.

Public sector as the entry-point to careConvenience, accessibility, familiarity with the servicesand cost were the commonest reasons for patientschoosing the public health sector. Patients accessed andmoved between CHCs and clinics and experiences dif-fered between these. Several patients who first attendeda CHC were treated with antibiotics for an acute chestinfection and were not initially screened for TB; in com-parison, most patients attending clinics were initiallyscreened for TB, although not necessarily for MDR-TB.Previously treated patients tended to return to their

local clinic for care due to familiarity and satisfactionwith the previous service: “I had TB before and knew thesymptoms of TB. I decided to go to the clinic where I stay…Iwas very satisfied with the treatment that I got [previously]”

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(Xpert-7). Several patients chose to go to the clinic or CHCproviding their antiretroviral treatment and requested TBtests at scheduled appointments; others were screened dur-ing antiretroviral treatment re-initiation.A few patients specifically chose a CHC, because of

the services offered, including emergency services andthe availability of chest x-rays. A patient who attendedfor these reasons commented: “I was very worried becauseI could not walk. I thought something serious is wrong withme. My [friend] called the ambulance” (LPA-10). Likeother patients who had attended a CHC, this patient com-mented on the difficulties in accessing care: “[the CHC]was very full. I don’t like [the CHC] and would not like togo there again… Lots of chaos. The nurses rushed me, theydon’t give me time to talk and explain what’s wrong withme. This is not right for me. They don’t care about the pa-tient. Once I was there and the nurses just went on tea,even if the very sick people are waiting on them. I told thenurse about a sick, old man and she said “he must justwait”. They just don’t care about the patients” (LPA-10).Although long waiting times were a common com-

plaint, a few accepted this status quo: “I waited for a longtime before I was attended, but I understand that is theway it is. There are lots of people that need to beattended to everyday here at the clinic. But I knew thatat the end of the day I was going to get assisted. I justtold myself that… I am sick already and I need help andin order for me to get help I must be patient” (LPA-5).In contrast, some patients reported positive experiences:

“…I was sure I was going to stand in a long queue, but I ex-plained to the TB nurse what was wrong with me andwithout me standing in a queue she told me to go to theTB room” (LPA-8). Another explained “I was expectinglong queues and sitting for ages before getting help. I amnot sure what the situation is at the other clinics, but …there was no queue and I got helped within 10 min…Staffin the TB room is very helpful and treats the patients withrespect” (Xpert-9).

Private sector as the entry-point to careSeveral patients first visited the private sector, mostcommonly general practitioners (GP), due to perceptionsof better services. They perceived the public sector to beover-burdened, with long waiting times, negative staff at-titudes and a lack of privacy. Waiting times, in particu-lar, were considered a barrier: “I don’t like coming to theclinic when I’m not feeling well…You wait for a long timebefore they can attend to you…At the doctors room thetreatment and waiting time was very reasonable. I onlyhad to wait for 20 min. Here at the clinic, you wait…youcan wait for 8 hours here” (LPA-4).Having financial resources enabled patients to visit a

GP; however, in some cases, they did not return as rec-ommended due to financial constraints. Reflecting on

their management in the private sector, several patientsfelt that visiting a GP had been a waste of time andmoney. One patient had the following advice for thosewith TB symptoms: “I can advise them all to go to theclinic…. There are much better options at the clinic thanthe private doctors…lots of test which can be taken…lotsof tests which will find out what is wrong with you….Forsomeone to get those things you have to be patientthough” (LPA-6).Patients that first sought help at a pharmacy often

underestimated the seriousness of their symptoms, as-sumed these were self-limiting and self-medicated withcough mixtures.We found no significant differences between the LPA

and Xpert-based algorithms in the point of first health-care access or in patients’ experiences. Despite perceptionsof long waiting times, lack of privacy and poor staff atti-tudes, most patients reported that they would recommendthat family and friends with TB symptoms go directly toPHC facilities, to reduce the cost and time to diagnosis.

Testing for MDR-TBPatients described how they came to be diagnosed withMDR-TB; the steps involved and the time it took. Withthe exception of two patients, most experienced lengthydelays due to providers not testing for TB or MDR-TBat initial visits, failure in the testing technology andpatient-related delays, including interruptions to thediagnostic process and missed follow-up appointments.

Delays due to the first health provider not testing for TBNone of the patients who initially visited a pharmacywere referred for TB tests; a few subsequently visited ageneral practitioner, before eventually being investigatedfor TB at their local PHC facility. This contributed toMDR-TB diagnostic delays. In one extreme example, apatient with persistent cough described visits to thesame pharmacy over a 6-month period: “I went backagain and again to the pharmacy and got different medi-cation every time. I must have gone there five times”(LPA-13).Most patients who visited general practitioners were

diagnosed with acute respiratory infections and treatedwith antibiotics, without TB investigations. Some hadchest x-rays taken and a few had sputum tests. Some pa-tients who did not respond to initial treatment had earlyreferral to PHC facilities; others who could not afford tocontinue with private sector care attended the publicsector when their health deteriorated. Several patientswho visited general practitioners experienced lengthy de-lays as a result of numerous visits and courses of antibi-otics, before seeking or being referred to a PHC facilityfor investigation.

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In the public sector too, particularly at CHCs, somepatients with a chronic cough were treated with severalcourses of antibiotics before a TB test was done. Afteran initial general practitioner visit one patient reported:“I was at [the CHC] for 24 hours in December …they toldme that I had infection in my lungs and gave me the dripand antibiotics…In the same month I didn’t feel so wellso I went back… and they gave me the same drip andantibiotics” (LPA-16).In the most extreme example of missed diagnostic op-

portunities a young woman was started on MDR-TBtreatment 15 months after first seeking health-care. Des-pite repeated visits to both the private and public sector,the patient was not adequately evaluated for TB, includ-ing during pregnancy. She was diagnosed several months

after her baby’s birth with serious consequences includ-ing her baby contracting MDR-TB (see Fig. 3).

Delays due to the first health provider not testing for drugsusceptibilityIn the LPA-based algorithm, low MDR-TB risk patientsdid not have initial drug susceptibility tests (DST); this wasdone only when 1st-line TB treatment failed, resulting insubstantial delays to MDR-TB treatment. In comparison,in the Xpert-based algorithm, all presumptive TB caseswere required to have an Xpert test and were concurrentlyevaluated for tuberculosis and rifampicin resistance, theor-etically reducing these delays. In both algorithms however,there were many instances where the correct tests werenot initially done, contributing to diagnostic delays.

Fig. 3 Delayed access to treatment - in their own words

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Patients who experienced delays commented on the dis-tress they felt whilst on 1st-line TB treatment. For one pa-tient, diagnosed on smear microscopy by a generalpractitioner and referred to a PHC facility, a series ofhealth service failures contributed to delay. The patientwas at high MDR-TB-risk and despite the clinician request-ing an Xpert test, only smear microscopy was done and thepatient was started on 1st-line TB treatment. Nurses didnot respond to the patient’s complaint of worsening symp-toms. After sputa were taken to evaluate response to treat-ment the patient reported: “When the results came backthey told me I do not take my tablets. I told them ‘but I takemy pills every day’. They could not understand why my re-sults were 3-plus positive. I told them ‘my [spouse] seeswhen I take my tablets in the morning’. This made me verytroublesome… In all the time that I took the treatment I feltthe same. The treatment did not help….I started to give uphope” (Xpert-6). The patient started MDR-TB treatment al-most 5-months after initial tests; following routine screen-ing the patient’s child was also diagnosed with MDR-TB.

Delays due to initial negative or invalid testsPatients in both algorithms were sometimes diagnosedon chest x-ray after negative initial smear or Xpert testsand commenced on 1st-line TB treatment as this patientexplained: “So finally after three days the results cameback.… and a few days later they said I was negative,but I was still getting sicker.” (Xpert-8). This patient per-sisted, seeking care from another facility: “I went to [theCHC] again like someone who does not know what’swrong with them. I told the doctor ‘I already gave spu-tum’ and I went for x-rays and that’s when she saw thex-ray and sent me straight here and they … put me ontreatment”. As per policy, this HIV-negative patient didnot have an initial sputum culture test; this was onlydone two months after 1st-line TB treatment was started,contributing to a 4-month delay in MDR-TB treatment.In comparison, a patient who was investigated for TB

shortly after commencing antiretroviral treatment re-ported: “I gave in the sputum and came back to the clinicafter 3 days. The result was negative…I went again to theARV clinic and they sent me for chest x-ray .My chest x-ray was also negative….I went back to work. [One day] Iwas preparing to go to work. My phone rang and it wasthe clinic that said I must come to them immediately”(Xpert-5). The patient was diagnosed on a culture test,resulting in a 6-week delay to MDR-TB treatment.

Patients’ rolesPatient narratives presented several examples of theiragency in persisting with the diagnostic process whensymptoms did not resolve and in requesting tests thatshould have been offered but were not. One patient ex-plained: “I knew I was HIV positive, and that made me

more worried when I felt sick. Even when my TB resultswere negative…I went again for a TB test” (LPA-14).Whilst not playing a major role, patient factors contrib-uted to delays during the diagnostic process due, for ex-ample, to work and family commitments and beingunable to pay for transport to return to facilities.

A comparison between the LPA and Xpert-based AlgorithmsThere were many examples of remarkably similar pa-tients’ experiences between the LPA and Xpert-based al-gorithms, with a 1–2 month delay between submittingthe MDR-TB test sputum and treatment initiation. De-lays overall were longer for patients in whom initial testswere negative with 1st-line TB treatment started on clin-ical or chest x-ray findings.With Xpert, there were two examples of rapid MDR-

TB diagnosis where a test submitted at the first healthcontact diagnosed rifampicin resistance (see Fig. 4). Apatient elucidated: “At the clinic I was given the bottle togive sputum… After that I was given a follow-up date tocome the following week for my results, and when I cameback I was told that it looks like I have TB and that thisTB is not like the first one…. I was told that I needed tosee the doctor because I have a “big TB, MDR-TB” amore serious TB, not the normal one” (Xpert-2).

MDR-TB treatment initiationPatients described their experiences of receiving test re-sults and initiating treatment. We identified both healthsystem and patient factors contributing to delays.

Health system factors contributing to delayProblems were experienced with facilities failing to re-ceive laboratory results, resulting in multiple returntrips, as one patient explained: “After returning for myresults and waiting for a long time, I was told that Ineeded to come back again after two days. After anothertwo days I was told my results were not received due to abroken fax machine. After this day I decided not to comeback because I was waiting too long in the queue for myresults and I was feeling better at this stage” (LPA-5).Once the PHC facility received the MDR-TB test re-

sult, there were delays in recalling patients, althoughfrom patient accounts, the reasons for this were not al-ways clear. Several patients indicated that a healthworker was able to contact them telephonically or visitedtheir home. Some indicated that the PHC facility struggledto contact them initially, for instance, when messages werenot relayed to them. Substantial delays occurred in recal-ling some patients. One patient who tested smear-negativein April and went to visit family in another province to re-cuperate reported: “In mid-August the ..clinic phoned me tocheck when I will be back home. They did not say why. Ionly went back at the .end of August and was informed…

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that I have MDR-TB. This was another shock for me. I wasvery disturbed that the clinic [had] not told me this while Iwas [away]. I was living unaware of this very contagiousdisease…I think this was very irresponsible of the clinic. Itold them… when they explained the seriousness of MDR-TB to me….I was a danger to my family and could havebeen on treatment 2-weeks earlier“ (Xpert-9). In this ex-treme example, the patient was not aware that her resultswere in fact available three months prior to the patient be-ing contacted.

Patient factors contributing to delayDelays occurred when patients failed to return forscheduled appointments and had to be recalled. For afew, seeking traditional health-care at their family homein another province contributed to delays, as did familycommitments. One patient explained: “The day..I wastold I have MDR-TB, my family phoned…with the newsthat my sister passed away. Everything then went crazy.All I could think about then was the fastest way to get[home.] I am the eldest son and must make all the prep-aration and decisions for the funeral. I left very early thenext morning…not thinking about my MDR-TB treat-ment, maybe because my mind was very occupied with

my family responsibilities and also because I did not feelthat sick” (LPA-12).

The impact of an MDR-TB diagnosisPatients spoke at length about the range of emotions theyexperienced on receiving an MDR-TB diagnosis. Althoughdevastating for most patients, the diagnosis was often ac-companied by a sense of relief at finally knowing what waswrong with them. For many experiencing financial andother hardships, diagnostic delays exacerbated their diffi-culties. There were also feelings of guilt about infectingothers, especially children: “ it hurts me a lot, I don’t evenwant to go there, I am feeling very bad, very, very bad, be-cause if this was detected earlier I was not going to gothrough some difficulties that I went through. You know…when I think that I even infected my child it makes me feelvery bad. Because if this was detected early and [I was]started on the right treatment, maybe some of the problemswould have been eliminated” (LPA-3). Overall, six childrenin the households of the 26 patients interviewed were di-agnosed with MDR-TB.

DiscussionLimited data are available on the impact of new molecu-lar diagnostic tests on MDR-TB patients. Two studies

Fig. 4 Expedited access to treatment - in their own words

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comparing conventional DST to LPA showed reductionsin median treatment commencement times from 72 to24 days [6] and 80 to 55 days [7] respectively. ThePROVE-IT evaluation found a reduction from 43 days inthe LPA-based algorithm to 17 days in the Xpert-basedalgorithm [8]. These findings however provide a limitedview, excluding the period prior to MDR-TB tests beingtaken and do not explain, for example, why it takes17 days to get a patient onto treatment despite a labora-tory turn-around time of

both private and public sector providers, especially thosenot providing TB treatment, to ensure appropriate testing.An advantage of the Xpert-based algorithm is that by

targeting all presumptive TB cases and not only those athigh MDR-TB risk, it should diminish the problem ofpatients with primary MDR-TB being placed on 1st-lineTB treatment and the ensuing suffering that patients de-scribed as their health deteriorated.The potential of an Xpert-based algorithm to substan-

tially reduce delay is highlighted by two examples ofrapid initiation of MDR-TB treatment, within 6 and8 days of the first health contact, respectively. Early ac-cess to treatment was enabled by the correct tests beingrequested which yielded a positive result, results beingavailable when patients returned and decentralised treat-ment being available. In comparison, the earliest accessfor three patients in the LPA-based algorithm was within31–38 days of the first health contact, reflecting the timetaken for a culture and DST result with LPA.However, more often than not, health system factors

including failure to adhere to testing algorithms, prob-lems with receiving the results, scheduling follow-upvisits and recalling patients with positive results, all con-tributed to substantial delays. The introduction of rapiddiagnostics therefore needs to be coupled with measuresthat address these structural barriers and minimizeorganizational delay [20, 32]. Patient-related delays (dueto missed follow-up appointments, competing family de-mands and seeking traditional health-care) contributedto a lesser extent.Our findings highlight not only the factors influencing

the pathway to MDR-TB treatment, but also the impacton the lives of patients. Patients described how theirphysical and emotional suffering during the long andsometimes, tortuous pathway to treatment initiationcompounded already difficult socio-economic and familycircumstances. For some, the impact on their familieswas experienced as devastating, in particular, when chil-dren were infected. There was recognition (and anger)amongst some, that reducing diagnostic delays may haveaverted some of these infections.

Limitations and strengthsThe study has limitations. It was undertaken in CapeTown which is urban, relatively well resourced and withdecentralized MDR-TB care. Obstacles to care may begreater in poorly resourced areas, in rural settings andwith centralized care. The study does not reflect the ex-perience of the sickest MDR-TB patients (those in hospitalor still smear positive), those not initiating MDR-TB treat-ment and those who were lost to follow-up, and maytherefore present a more optimistic view of pathways tocare. One of the major strengths of this study is that wewere able to increase the validity of patient reports by

triangulating data from interviews with clinical informa-tion and data from a structured questionnaire on healthvisits and services received. This also provided importantcontext to patient’s narratives and deepened our under-standing of pathways to care. Whilst the small sample in-cluded in the study may not have been statisticallyrepresentative of all MDR-TB patients, we felt that we hadcaptured an adequate range of experiences. Qualitative re-search, where patients are required to convey their experi-ences and the meaning they attribute to these [33]contributes important evidence on the impact of molecu-lar diagnostic tests.

ConclusionThe history of TB control efforts around the world hasshown that having the right technology will not by itselfresolve complex medical and public health challenges[34, 35]. We are likely to confront a range of barriers inmaking the most of new diagnostic technologies [36].Whilst the introduction of Xpert clearly has the poten-tial to reduce MDR-TB diagnostic and treatment delays,this alone does not suffice. Addressing patient delays inhealth-seeking is important. However, unless the struc-tural barriers to care (correct evaluation at the firsthealth contact, appropriate referral between sectors, de-veloping patient-friendly health systems that are betterorganised to access results and commence treatment)are also addressed, the potential of rapid molecular diag-nostic tests such as Xpert are unlikely to be fully rea-lised. We hope that patients’ perspectives will be a callto action to address the obstacles identified in the path-way to MDR-TB treatment initiation.

AbbreviationsCHC: Community health centre; CRF: Case record form; DST: Drug susceptibilitytest; GP: General practitioner; HIV: Human immunodeficiency virus;LPA: GenoType® MTBDRplus line probe assay; MDR-TB: Multidrug-resistanttuberculosis; MTB: Mycobacterium tuberculosis; PHC: Primary health-care;TB: Tuberculosis; Xpert: Xpert® MTB/RIF; XDR-TB: Extensively drug resistanttuberculosis.

Competing interestsThe authors declare that they have no financial or non-financial competinginterests.

Authors' contributionsAll authors designed the study. MVN and EDT identified study participants.MVN, EDT and NL supervised the field researchers. PN, MVN and NLreviewed interview transcripts and undertook analysis. PN wrote themanuscript and MVN, EDT, NB and NL contributed to the first andsubsequent drafts and approved the submission.

AcknowledgementsThis research was supported by a United States Agency for InternationalDevelopment (USAID) Cooperative Agreement (TREAT TB – Agreement No.GHN-A-00-08-00004-00). The contents are the responsibility of the authorsand do not necessarily reflect the views of USAID. The support of Cape TownCity Health Directorate staff is acknowledged. We are grateful to the patientswho shared their experiences with us.

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Author details1Desmond Tutu TB Centre, Department of Paediatrics and Child Health,Faculty of Medicine and Health Sciences, Stellenbosch University,Stellenbosch, South Africa. 2Health Systems Research Unit, South AfricanMedical Research Council, Cape Town, South Africa.

Received: 4 November 2014 Accepted: 12 October 2015

References1. World Health Organisation. Global Tuberculosis Report 2013. © World

Health Organization 2013. WHO/HTM/TB/2013.11. Available fromhttp://apps.who.int/iris/bitstream/10665/91355/1/9789241564656_eng.pdf..

2. Dowdy DW, Chaisson RE, Maartens G, Corbett EL, Dorman SE. Impact ofenhanced tuberculosis diagnosis in South Africa: a mathematical model ofexpanded culture and drug susceptibility testing. Proc Natl Acad Sci U S A.2008;105:11293–8.

3. Dye C. Doomsday postponed? Preventing and reversing epidemics ofdrug-resistant tuberculosis. Nat Rev Microbiol. 2009;7:81–7.

4. World Health Organisation. Molecular Line Probe Assays For RapidScreening Of Patients At Risk Of Multidrug-Resistant Tuberculosis, PolicyStatement. 2008. Available from http://www.who.int/tb/features_archive/policy_statement.pdf?ua=1.

5. World Health Organisation. Automated Real-Time Nucleic Acid AmplificationTechnology for Rapid and Simultaneous Detection of Tuberculosis andRifampicin Resistance: Xpert MTB / RIF System. Policy Statement. 2011.© World Health Organization 2011. WHO/HTM/TB/2011.4. Available fromhttp://apps.who.int/iris/bitstream/10665/44586/1/9789241501545_eng.pdf.

6. World Health Organisation. Molecular Line Probe Assays For RapidScreening Of Patients At Risk Of Multidrug-Resistant Tuberculosis. ExpertGroup Report. 2008. Available from http://www.who.int/tb/features_archive/expert_group_report_june08.pdf.

7. Jacobson KR, Theron D, Kendall E, Franke MF, Barnard M, van HeldenPD, et al. Implementation of genotype MTBDRplus reduces time tomultidrug-resistant tuberculosis therapy initiation in South Africa. ClinInfect Dis. 2013;56:503–8.

8. Naidoo P, du Toit E, Dunbar R, Lombard C, Caldwell J, Detjen A, et al.A Comparison of Multidrug-Resistant Tuberculosis Treatment CommencementTimes in MDRTBPlus Line Probe Assay and Xpert® MTB/RIF-Based Algorithms ina Routine Operational Setting in Cape Town. PLoS One. 2014;9, e103328.

9. Dowdy DW, Cattamanchi A, Steingart KR, Pai M. Is scale-up worth it?Challenges in economic analysis of diagnostic tests for tuberculosis.PLoS Med. 2011;8, e1001063.

10. Finnie RKC, Khoza LB, van den Borne B, Mabunda T, Abotchie P, Mullen PD.Factors associated with patient and health care system delay in diagnosisand treatment for TB in sub-Saharan African countries with high burdens ofTB and HIV. Trop Med Int Health. 2011;16:394–411.

11. Mavhu W, Dauya E, Bandason T, Munyati S, Cowan FM, Hart G, et al.Chronic cough and its association with TB-HIV co-infection: factorsaffecting help-seeking behaviour in Harare, Zimbabwe. Trop Med IntHealth. 2010;15:574–9.

12. Mochache LN, Nyamongo IK. Factors influencing tuberculosis managementin rural south-west. Kenya. 2009;13:895–9.

13. Skordis-Worrall J, Hanson K, Mills A. Confusion, caring and tuberculosisdiagnostic delay in Cape Town. South Africa. 2010;14:171–80.

14. Yimer S, Bjune G, Alene G. Diagnostic and treatment delay amongpulmonary tuberculosis patients in Ethiopia: a cross sectional study.BMC Infect Dis. 2005;5:112. doi:10.1186/1471-2334-5-112. Availablefrom: http://www.biomedcentral.com/1471-2334/5/112. Downloaded 30April 2013.

15. Godfrey-Faussett P, Kaunda H, Kamanga J, van Beers S, van Cleeff M,Kumwenda-Phiri R, et al. Why do patients with a cough delay seekingcare at Lusaka urban health centres? A health systems researchapproach. Int J Tuberc Lung Dis. 2002;6:796–805.

16. Cowan J, Greenberg Cowan J, Barnhart S, Demamu S, Fiseha D, Graham W, et al.A qualitative assessment of challenges to tuberculosis management andprevention in Northern Ethiopia. Int J Tuberc lung Dis. 2013;17:1071–5.

17. Millen SJ, Uys PW, Hargrove J, van Helden PD, Williams BG. The effect ofdiagnostic delays on the drop-out rate and the total delay to diagnosis oftuberculosis. PLoS One. 2008;3(4):e1933. doi:10.1371/journal.pone.0001933.Downloaded 02 May 2013.

18. Mann G, Squire SB, Bissell K, Eliseev P, Du Toit E, Hesseling A, et al. Beyondaccuracy : creating a comprehensive evidence base for tuberculosisdiagnostic tools. IJTLD. 2010;14:1518–24.

19. Demissie M, Lindtjorn B, Berhane Y. Patient and health service delay in thediagnosis of pulmonary tuberculosis in Ethiopia. BMC Public Health2002;2(1):23 Avaialble from http://www.biomedcentral.com/content/pdf/1471-2458-2-23.pdf.

20. Lambert ML, Van der Stuyft P. Delays to tuberculosis treatment: shall wecontinue to blame the victim? Trop Med Int Health. 2005;10:945–6.

21. Storla DG, Yimer S, Bjune GA. A systematic review of delay in the diagnosisand treatment of tuberculosis. BMC Public Health. 2008;8:15. doi:10.1186/1471-2458-8-15. Available from http://www.biomedcentral.com/1471-2458/8/15. Downloaded 30 April 2013.

22. Rajeswari R, Chandrasekaran V, Suhadev M, Sivasubramaniam S, SudhaG, Renu G. Factors associated with patient and health system delays inthe diagnosis of tuberculosis in South India. Int J Tuberc Lung Dis.2002;6:789–95.

23. Kasse Y, Jasseh M, Corrah T, Donkor S, Antonnio M, Jallow A, et al. Healthseeking behaviour, health system experience and tuberculosis case findingin Gambians with cough. BMC Public Health. 2006;6:143. doi:10.1186/1471-2458-6-143. Available from http://www.biomedcentral.com/1471-2458/6/143. Downloaded 27 August 2014.

24. Luis SF, Kamp N, Mitchell EMH, Henriksen K, van Leth F. Health-seekingnorms for tuberculosis symptoms in southern Angola: implications forbehaviour change communications. Int J Tuberc Lung Dis. 2011;15:943–8.

25. Senbeto M, Tadesse S, Tadesse T, Melesse T. Appropriate health-seekingbehavior and associated factors among people who had cough for at least twoweeks in northwest Ethiopia: a population-based cross-sectional study. BMCPublic Health. 2013;13:1222. Available from http://www.biomedcentral.com/1471-2458/13/1222. Downloaded 27 August 2014.

26. Verver S, Warren RM, Beyers N, Richardson M, van der Spuy GD, BorgdorffMW, et al. Rate of reinfection tuberculosis after successful treatment ishigher than rate of new tuberculosis. Am J Respir Crit Care Med.2005;171:1430–5.

27. Glynn JR, Murray J, Bester A, Nelson G, Shearer S, Sonnenberg P. High ratesof recurrence in HIV-infected and HIV-uninfected patients with tuberculosis.J Infect Dis. 2010;201:704–11.

28. Needham DM, Foster SD, Tomlinson G, Godfrey-Faussett P. Socio-economic,gender and health services factors affecting diagnostic delay fortuberculosis patients in urban Zambia. Trop Med Int Health. 2001;6:256–9.

29. Pronyk RM, Makhubele MB, Hargreaves JR, Tollman SM, Hausler HP. Assessinghealth seeking behaviour among tuberculosis patients in rural South Africa. IntJ Tuberc Lung Dis. 2001;5:619–27.

30. Fochsen G, Deshpande K, Diwan V, Mishra A, Diwan VK, Thorson A. Healthcare seeking among individuals with cough and tuberculosis: a population-based study from rural India. Int J Tuberc Lung Dis. 2006;10:995–1000.

31. Hoa NP, Thorson A, Long NH, Diwan V. Knowledge of tuberculosis andassociated health-seeking behaviour among rural Vietnamese adultswith a cough for at least three weeks. Scand J Public Health.2003;31:59–65.

32. Nathanson E, Nunn P, Uplekar M, Floyd K, Jaramillo E, Lönnroth K, et al.MDR Tuberculosis - Critical Steps for Prevention and Control. N Engl JMed. 2010;363:1050–8.

33. Pope C, Mays N. Qualitative Methods in Health Research. In Qual Res HealCare. Blackwell Publishing Ltd; 2007; pp1–11.

34. Lönnroth K, Jaramillo E, Williams BG, Dye C, Raviglione M. Drivers of tuberculosisepidemics: the role of risk factors and social determinants. Soc Sci Med.2009;68:2240–6.

35. Raviglione MC, Pio A. Evolution of WHO policies for tuberculosis control,1948–2001. Lancet. 2002;359:775–80.

36. Zumla A, Cobelens F. Operational research and MDG tuberculosis controltargets. Lancet Infect Dis. 2012;12:262–3.

Naidoo et al. BMC Health Services Research (2015) 15:488 Page 13 of 13

http://apps.who.int/iris/bitstream/10665/91355/1/9789241564656_eng.pdfhttp://www.who.int/tb/features_archive/policy_statement.pdf?ua=1http://www.who.int/tb/features_archive/policy_statement.pdf?ua=1http://apps.who.int/iris/bitstream/10665/44586/1/9789241501545_eng.pdfhttp://www.who.int/tb/features_archive/expert_group_report_june08.pdfhttp://www.who.int/tb/features_archive/expert_group_report_june08.pdfhttp://dx.doi.org/10.1186/1471-2334-5-112http://www.biomedcentral.com/1471-2334/5/112http://dx.doi.org/10.1371/journal.pone.0001933http://www.biomedcentral.com/content/pdf/1471-2458-2-23.pdfhttp://www.biomedcentral.com/content/pdf/1471-2458-2-23.pdfhttp://dx.doi.org/10.1186/1471-2458-8-15http://dx.doi.org/10.1186/1471-2458-8-15http://www.biomedcentral.com/1471-2458/8/15http://www.biomedcentral.com/1471-2458/8/15http://dx.doi.org/10.1186/1471-2458-6-143http://dx.doi.org/10.1186/1471-2458-6-143http://www.biomedcentral.com/1471-2458/6/143http://www.biomedcentral.com/1471-2458/6/143http://www.biomedcentral.com/1471-2458/13/1222http://www.biomedcentral.com/1471-2458/13/1222

AbstractBackgroundMethodsResultsConclusion

BackgroundMethodsStudy settingSamplingThe research teamData collectionData analysisEthics

ResultsSymptom recognitionThe role of previous TB treatment or social contact with TB patientsThe interaction with HIVFailure to recognise or acknowledge TB symptoms

Accessing health-carePublic sector as the entry-point to carePrivate sector as the entry-point to care

Testing for MDR-TBDelays due to the first health provider not testing for TBDelays due to the first health provider not testing for drug susceptibilityDelays due to initial negative or invalid testsPatients’ rolesA comparison between the LPA and Xpert-based Algorithms

MDR-TB treatment initiationHealth system factors contributing to delayPatient factors contributing to delayThe impact of an MDR-TB diagnosis

DiscussionSymptom recognitionHealth-care accessTesting for MDR-TB and treatment initiationLimitations and strengths

ConclusionAbbreviationsCompeting interestsAuthors' contributionsAcknowledgementsAuthor detailsReferences