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Impact of involvement of non formal health providers on TB
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NFHP involvement in TB case notification, Competing interests Although SS worked for TB Results. REACH funding arm of the STOP TB Partnership, the agency that funded the project but he neither The project detected 488 Xpert TB cases of whom 466 were administered RNTCP treat. had any role on the funding decision nor any ment This translated into notification of additional 198 new bacteriologically positive cases. special influence on the analysis of the project to RNTCP a 30 notification surge after adjustment for 2 decline in control This meant. results and preparation of the manuscript RHS,was involved in monitoring and evaluation of the. an average quarterly increase in notification of 41 20 20 08 62 31 p 0 001 cases The. project but he did not have any special influence increase was immediate evident from the rise in level in the time series analysis by 50 42. on the analysis and preparation of the manuscript 10 28 90 55 p 0 02 cases. This does not alter our adherence to PLOS ONE,policies on sharing data and materials. Conclusion, Engagement with NFHPs contributed to an increase in TB notification to RNTCP from key.
under reached slum dwelling migrant populations,Introduction. Tuberculosis TB is considered a major public health problem in India with almost 3 million. people developing this infectious disease every year in the country and as many as half a mil. lion Indians succumbing to it annually 1 Despite country wide implementation for more. than a decade of the Revised National Tuberculosis Control Programme RNTCP which is. based on the internationally acclaimed and recommended DOTS strategy India is yet to. reduce its TB burden substantially let alone eliminate this dreadful scourge 1 2 The basic. tenets of RNTCP include diagnosing majority of the TB cases early in the course of their dis. eases and treating them appropriately and completely This is to ensure that majority of the. affected individuals suffer for a relatively shorter period and they do not continue to spread. the infection to other uninfected individuals in the community This has the potential to decel. erate the infection disease cycle and subsequently reduce the TB burden in the society For. this RNTCP primarily depends on voluntary presentation of the TB patients at the local des. ignated health facilities which are overwhelmingly housed within the public health system of. the country and very few within the private clinics 3 Patients who initially seek care from pri. vate healthcare providers or health workers are also sometimes referred to the RNTCP desig. nated facilities, Individuals who present for care at RNTCP facilities are then diagnosed by conventional. sputum microscopy and also chest x rays and other tests if necessary which are provided free. of cost to the care seekers One of the major barriers to the decline of TB burden in India is. some sections of its population remain largely under reached at least in the initial stages of. their diseases to the programme 4 5 In TB policy parlance these groups are referred to as. key populations those with limited access to quality TB services though the services are. offered free by the national TB programmes 6 7, Migrant labourers constitute such an under reached key population in India 7 8 These are. the people who mostly migrate from villages to the burgeoning Indian urban centres and its. industrial patches They mostly find employment in the low skill low wage jobs in the infor. mal sector which has a sizeable presence in the Indian towns and cities These marginalized. people end up living in the overcrowded slums the likes of which are rapidly proliferating in. the urban and industrial landscape of modern India 9. When individuals from this vulnerable group seek healthcare they often find it difficult to. navigate the channels of the public health system of their adopted places This is mainly due to. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 2 16. NFHP involvement in TB case notification, their unfamiliarity with the city health system Moreover the unsuitable location and timing. of the public health facilities in these urban areas often impose substantial access and opportu. nity costs in the form of transportation costs and wage losses on these predominantly impover. ished masses 10, The high end formal private healthcare system which often has a large footprint in the.
Indian cities is mostly out of reach of these poor people because of their prohibitively steep. user fees Hence the sick members of these poor migrant communities often gravitate to. the friendly neighbourhood non formal health providers NFHPs 11 the likes of which. include small medicine shop owners chemists and pharmacists of drug stores practitioners. of alternative systems of medicine unqualified practitioners of allopathic medicine and. members of various community based health organizations The NFHPs mainly prescribe. medicines mostly allopathic for symptomatic relief of the care seekers presenting to them. These NFHPs not only operate within or close to these slums but also provide services at. friendly hours and frequently offer flexi payment options 12 to suit the capacity of their. poor clients But the lack of formal medical training of the NFHPs often lead to inappropri. ate management of grave medical conditions of their clients thereby compounding their suf. ferings 13, Naturally those who develop TB in these communities TB being considerably more com. mon in urban India 1 also often present initially to their neighbourhood NFHPS frequently. with symptoms of prolonged cough These patients seek symptomatic relief or suggestions. early in the course of their diseases when their TB symptoms are yet to become too severe to. raise alarm in both the sufferers as well as their untrained providers The NFHPS mostly pro. vide inappropriate management to these care seeking early TB symptomatics which may. include injudicious prescription of antibiotics also as they are hardly aware of the diagnostic. and treatment protocols of RNTCP 14 This not only prolongs the sufferings of their TB. patients by delaying their actual diagnosis and treatment initiation as evidence shows 11 but. also enables protracted transmission of infection in the community This fuels the TB epidemic. in these overcrowded environments 8 However some of these poor patients somehow ulti. mately manage to find their way to the RNTCP system 15 after much suffering when their. symptoms become too severe to ignore, Unfortunately the TB programmes worldwide 16 including RNTCP hardly ever. engaged with the NFHPS The public private partnership initiatives of RNTCP were also. mostly directed to the involvement of formally trained medical practitioners albeit many. poor patients present to these NFHPs as their first port of call 17 This insufficient. engagement of RNTCP with this sizeable yet important non formal healthcare sector has. further been compounding the access issues of this key population leading to many TB. patients in these communities remaining under reached 16 All these factors perhaps. underpin the low notification of diagnosed TB cases from many Indian cities notwithstand. ing a higher burden of TB in urban India because many of these cities have substantially. large under reached populations, Therefore a project was conceived whereby a local public health academic institute. would facilitate establishment of linkage between the slum dwelling migrant communities. and RNTCP The project planned to engage with the NFHPs on behalf of RNTCP with an. overarching aim to identify the TB patients emerging from these under reached communi. ties through these providers and lead them to the standardized RNTCP regimen as early in. the course of their diseases as possible The objective of our manuscript is to describe the. project and assess its impact using primarily the evaluation framework of the project and. routine programme data so that its successful components can be identified for future. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 3 16. NFHP involvement in TB case notification,Populations and study design. Two intervention sites Bhubaneswar city and Jajpur town in Odisha state were selected. because these two areas are among those with the highest concentration of slum dwelling. migrant labourer population in the state the primary target of the project Bhubaneswar is. the rapidly growing capital city of this eastern Indian state The industrial corridor of Jajpur. district in Odisha harbours many large to small scale ferro alloy factories These two interven. tion sites are similar in nature in terms of migrant labourers residing in slums that dots these. two areas extensively as well as the care seeking practices of these communities The total pop. ulation of the intervention area hereinafter is called the Evaluation Population EP. The control area that did not receive any intervention from the project but was only used. for comparison consisted of Cuttack city and its outskirts Cuttack a city located 25 kilo. metres away from Bhubaneswar shares similar characteristics with the intervention area It. being the commercial hub of the state also traditionally attracts many migrant labourers to the. numerous commercial and industrial establishments situated in and around the city as well as. the informal service sector allied to them Therefore many slums emerge and continue to pro. liferate also in Cuttack and its outskirts where these migrant communities reside The total. population of the control area is hereinafter referred to as the Control Population CP Histor. ically both the intervention and the control areas experienced low TB case notification to. RNTCP notification failing to attain 50 of the estimated annual incident cases let alone the. prescribed 90 needed to effect a significant decline of TB 18. The demographic and other relevant characteristics of the intervention and control areas. are described in Table 1, We used a quasi experimental before after design with a control group to analyse the.
results of intervention which is frequently employed to evaluate such population level initia. tives or events 19 20,Intervention, In addition to the routine passive case detection services provided by RNTCP the project. engaged in the intervention area with almost all the Non formal Health Providers NFHP. Table 1 The characteristics of intervention and control areas. Intervention area Control area,Bhubaneswar site Jajpur site Cuttack city and. Number of Basic Management Units BMUs providing TB services 2 2 2. Number of designated microscopy centres providing TB diagnostic services 4 4 6. Number of peripheral health institutions or treatment centres providing RNTCP treatment services 6 6 8. Total population 2014 850 000 664 000 1 411 000, Proportion of total population who are mainly migrant labourers dwelling in slums in these areas Approximately Approximately Approximately 35. Average baseline new smear positive case notification rate per 100 000 population per year 1st 37 4 41 2 19 7. quarter 2011 to 3rd quarter 2014, The total population of the intervention area is known as the evaluation population EP 1 514 000 and that of the control area is known as the control population. CP 1 411 000, This was the target population of the project in the intervention area.
The estimated new smear positive case incidence is 85 per 100 000 population per year So the baseline annualized new smear positive case detection rate case. notification estimated incidence was 50 in all the areas. https doi org 10 1371 journal pone 0196067 t001, PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 4 16. NFHP involvement in TB case notification, who were embedded within and were providing services to the target population The project. was administered by Asian Institute of Public Health a public health academic institute based. in Bhubaneswar Odisha The project enlisted n 539 enrolled n 447 and then engaged. with the NFHPs n 431 from the target population in September 2014 The project staff. experienced in working with community based organizations and providers used persuasion. and one to one personal engagement with the NFHPs to motivate them to participate in the. project The NFHPS were trained by the project staff to identify the presumptive TB cases. also known as TB symptomatics from their clientele using presence of cough for two weeks. or more as the primary screening criterion as suggested in the Technical Guidelines for. RNTCP The NFHPs were also trained to collect quality sputum samples from these sympto. matics promptly either at their clinics or at the patients homes The NFHPs were also pro. vided supportive supervision by the project staff at regular intervals either through personal. visits or telephonic contacts to monitor the quality of the operations and also to sustain their. morale No NFHP dropped out from the project, The field network of the project transported the samples collected from the NFHP identi. fied suspects to two project laboratories one established at each intervention site Both. laboratories were equipped with Xpert MTB RIF technology a cartridge based nucleic acid. amplification CBNAAT test with 90 sensitivity and specificity 21 22 This technology. simultaneously detects Mycobacterium tuberculosis and resistance to the most important first. line anti TB drug Rifampicin RIF from just one sample of sputum in less than 2 hours. This is in stark contrast to the routine sputum smear microscopy the primary diagnostic test. used by RNTCP which requires TB symptomatics to make at least two visits on two different. days to the designated RNTCP facilities for diagnosis and which is only 50 sensitive 23 24. One Xpert MTB RIF laboratory was set up at the largest government hospital of Bhubanes. war city and the other one was hosted by a health dispensary operated by the steel industry for. the local community in the industrial area of Jajpur district. Those symptomatics screened by the NFHPs who turned out to be positive to Xpert test. Xpert were then supported by the project staff to promptly register for standard anti TB. treatment from the nearest RNTCP health facility The information of their diagnosis was also. conveyed to those NFHPs who initially had identified them The project staff also facilitated. retrieval of the few diagnosed patients who failed or refused to attend the RNTCP clinics for. treatment initiation Fig 1 depicts the flow of the patients through the project and RNTCP. These Xpert TB patients identified by the project were notified to the local Basic Manage. ment Units BMUs of RNTCP Table 2 These cases were then included in the quarterly. RNTCP reports of BMU and therefore in the district and state quarterly RNTCP notification. reports The project was implemented for five quarters from 4th quarter 2014 to 4th quarter. The control population did not receive any intervention from the project and continued to. receive only routine RNTCP services which meant the NFHPs of that area were uninvolved in. The testable hypothesis of this project was that if this initiative through NFHP involvement. succeeded to bring these under reached TB patients within the fold of the programme then. RNTCP case notification rate would increase significantly during the intervention period in. the evaluation population as compared to that in the control population. Number of individuals screened by the NFHPs number of symptomatics identified among. them number of symptomatics undergoing Xpert MTB RIF examination and numbers of. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 5 16. NFHP involvement in TB case notification, Fig 1 Schematic presentation of flow of target patients through the project and RNTCP system. https doi org 10 1371 journal pone 0196067 g001, Xpert among those examined were collected from the laboratory records of the project The.
monthly aggregates of these results were also sent to the RNTCP management information. system every month for integration with the routine RNTCP microscopy services data. The data of the Xpert patients those who registered for RNTCP treatment were also inte. grated with the routine RNTCP case notification data at the BMU level as mentioned above. The number of cases notified by the project marked its yield However the impact of the proj. ect was assessed by the additional cases notified by RNTCP during the intervention period as. compared to the notification data of previous year s The new bacteriologically positive bac. cases which was primarily used to assess the impact included newly diagnosed Xpert cases. from the project plus the routine sputum smear positive cases of RNTCP Total cases included. bacteriologically positive bacteriologically negative but x ray positive and extra pulmonary. cases of both new and retreatment types Quarterly case notification data for both bac and. total cases were collected from the routine RNTCP reports of the BMUs both from the evalu. ation and control populations Few bac cases detected by the project were not new but of. Table 2 The yield of the project,Indicators Numbers. Number of patients checked enquired of TB symptoms by the NFHPs in the evaluation population 253679. Number of TB symptomatics identified 3780 1 49, Number of TB symptomatics examined for TB using Xpert RIF MTB 2800 74. Number of TB symptomatics examined for TB confirmed as Xpert 488 17 4. Number of Xpert RIF Sensitive patients started on RNTCP treatment 466 95 5. https doi org 10 1371 journal pone 0196067 t002, PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 6 16. NFHP involvement in TB case notification, retreatment category They were not included in the analysis of impact as per the project mon. itoring and evaluation guidelines, Population data of the BMUs were collected from the RNTCP reports that used census.
The data used for the analyses were BMU aggregates that were extracted in a completely de. identified format from the routine quarterly RNTCP reporting system No individual level. data was collected from the patients or used in the analyses Hence there was no necessity to. acquire informed consents or anonymize the data further. Statistical analysis, We first used descriptive statistics to report the yield of the project. We then conducted the impact analysis of the project based on additional new bac cases. notified by the project using various methods, 1 New bac cases notified during the five quarters of project implementation period herein. after referred to as the intervention period IP was compared with the cases notified in. the five quarters of pre intervention period PrIP The five quarters of IP spanned from. 4th quarter 2014 starting from 1st October 2014 to 4th quarter 2015 ending at 31st Decem. The notification data of 4th quarter 2013 to 3rd quarter 2014 plus the notification data of 4th. quarter 2013 added again made up the PrIP notification figures The data of 4th quarter. 2013 was added twice to make up the five quarters of PrIP This was done to account for. seasonality so that the five quarters of PrIP closely matched those of IP. The sum of new bac cases notified during the five quarters of IP minus the sum of new. bac cases notified during the five quarters of PrIP gave us the unadjusted increase in case. notification in the evaluation population We estimated the change in notification in the. control population during the same period The change in notification in the evaluation. population minus the change in notification in the control population gave us the control. adjusted increase in case notification in the evaluation population This control adjusted. increase is referred to as the additional cases the primary metric used to study the impact. of intervention The same approach was also adopted for total cases notified see above for. definition of total case, 2 Next we used an Ordinary Least Square OLS regression framework to estimate the. changes in the quarterly average notification of new bac cases between the IP and PrIP. both in the evaluation as well as control population This was done only for new bac cases. as these were the primary focus of the project Then we estimated by how much the average. changes varied between evaluation and control population the difference in difference. DD estimator Eq 1 The OLS framework allowed us to test statistical significance of the. DD estimates conveniently,Y 0 1 pop 2 time 3 pop time 1. Where Y Average new bac cases notified notification rates pop dummy variable repre. senting evaluation population or control population time dummy variable representing IP. or PrIP 0 intercept 1 mean difference in notified new bac cases rates between evalua. tion population and control population 2 mean difference in notified new bac cases. between IP and PrIP 3 DD estimate the parameter of interest error. The DD estimation used five quarters of IP data and five quarters of PrIP data Additionally. five quarters of IP data and fifteen quarters of PrIP 1st quarter 2011 to 3rd quarter 2014. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 7 16. NFHP involvement in TB case notification, data were also considered in a separate estimation model The models were executed with.
absolute numbers of cases notified as well as annualized case notification rates 100 000. population, 3 DD estimate is based on a parallel trend or common trend assumption which assumes. that in the absence of any intervention the new bac case notification trends in the evalua. tion population would have followed that of the control population This assumption could. not be tested using the methodology described in 1 where we used the averages of notifi. cation of five quarters each from both IP and PrIP not accounting for the prior trends. Since the violation of this assumption can substantially bias the estimates 20 we examined. prior trends for previous fifteen quarters as mentioned above The visual examination. showed very little difference between the evaluation and control population in terms of. prior notification trends Fig 2 Additionally we also conducted interrupted time series. analysis with a comparison group using segmented linear regression 25 Eq 2 whereby. the differences between the evaluation and control population were estimated in terms of. their pre post differences in slopes signifying long term effect of intervention and inter. cepts signifying immediate effect of intervention Eq 2. Y t 0 1 T t 2 X t 3 X t T t 4 Z 5 ZT t 6 ZX t 7 ZX t T t t 2. Yt new bac cases notified notification rates at equally spaced time pointt i e quarters Tt. identifiers of quarters Xt dummy variable representing IP or PrIP Z dummy variable rep. resenting evaluation or control population Parameters of interest included 6 that repre. sented the estimator of difference in level changes marking the immediate effect and 7. that represented the estimator of difference in slope changes. 95 confidence intervals CI of all the parameter estimates were constructed and their sta. tistical significances tested at 5 The analysis was conducted using R statistical software 26. version 3 3 0,Sensitivity analysis, We repeated the analysis 2 with eleven PrIP quarters instead of fifteen PrIP quarters as it. may be argued that our choice of fifteen quarters was somewhat arbitrary. Ethical approval, Clearance for implementation of the project was received from State TB Cell Department of. Health and Family Welfare Government of Odisha dated 28th January 2014 Letter No 136. The NFHPs checked 256 379 clients for TB symptoms in the evaluation population during. the five quarters of intervention of which approximately 1 5 were TB symptomatics cases. n 3780 Of all the symptomatics 74 could be subjected to Xpert testing under the. project out of whom 488 17 4 were diagnosed as Xpert cases Ninety five percent of these. Xpert cases n 466 could be registered for RNTCP treatment in the local BMUs covering. the evaluation population Table 2 Only three of these 488 bac patients tested positive for. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 8 16. NFHP involvement in TB case notification, Fig 2 Interrupted time series analysis of new bac cases. https doi org 10 1371 journal pone 0196067 g002, rifampicin resistance and they were referred to the designated drug resistant TB treatment.
centre of RNTCP for further management,Additional cases notified. During the five quarters of intervention period IP there was an increase in notification of 198. new bac cases as compared to five quarters of pre intervention period PrIP A 28 unad. justed increase in new bac case notification and after accounting for 2 decline in notifica. tion in the control population during the same period a control adjusted 30 increase in. notification was registered by the intervention area For total cases that include all types of. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 9 16. NFHP involvement in TB case notification, Table 3 Differences in additional new bac cases and total cases notified five quarters of PrIP vs five quarter of. IP by the evaluation population evaluation population and control population control population and the dif. ference in difference estimates, Change in notified cases in the Changes in notified cases in the DD estimate 95 CI. Evaluation Population Control Population p value,New bac 199 28 7 2 41 20 20 08 62 31. cases p 0 001,Total cases 192 10 89 8 20 60 12 86 54 06.
https doi org 10 1371 journal pone 0196067 t003, cases the corresponding increase was 192 against the backdrop of an increase of 198 new bac. cases This signifies that except new bac cases which registered an increase in notification. the other types of TB cases for instance smear negative extra pulmonary and retreatment. cases collectively registered a marginal decline of 6 cases during the intervention period. The control adjusted DD estimate for the same period was 41 20 20 68 62 31 which sig. nifies the average quarterly increase in notified cases in the evaluation population after adjust. ing for changes in control population Table 3, When compared with 15 quarters of PrIP the control adjusted DD estimates for quarterly. average change of absolute notification and notification rates were 41 26 18 83 63 68. p 0 001 and 9 86 4 05 13 30 p 0 001 respectively, The results of segmented regression of the interrupted time series of notification rates are. illustrated in Fig 2 Almost parallel prior trends in PrIP though with different levels could be. observed In the evaluation population a substantial increase in the level was observed imme. diately after the intervention was introduced the so called immediate effect There was no. such change in the control population The estimate of the immediate effect in terms of abso. lute notification was 50 42 10 28 90 55 and the notification rate was 13 36 100 000 popula. tion 2 78 23 93 Table 4 However the immediate change was not accompanied by any. significant longer term changes in trends Table 4,Sensitivity analysis. The parameter estimates of interest hardly changed when the PrIP period was shortened to. eleven quarters from fifteen The control adjusted DD estimates for quarterly average change. Table 4 Results of interrupted time series analysis of new bac cases notified and notification rates 100 000. population, Indicators Estimate numbers 95 CI p Estimate rates 95 CI p.
value value, Change in level immediate effect in the 52 72 18 85 86 58 p 0 007 14 51 6 07 22 94. Evaluation Population p 0 003, Change in slope in the Evaluation Population 6 11 16 29 2 53 p 0 17 1 32 3 66 1 02 p 0 28. Change in level immediate effect in the Control 2 30 19 23 23 83 p 0 83 1 14 5 23 7 52 p 0 72. Population, Change in slope in the Control Population 0 38 6 36 5 59 p 0 91 0 10 1 87 1 66 p 0 91. Estimate of difference in level changes Immediate 50 42 10 28 90 55 p 0 02 13 36 2 78 23 93 p 0 02. Estimate of difference in slope changes 6 49 17 64 4 65 p 0 26 1 21 4 14 1 72 p 0 42. statistically significant,https doi org 10 1371 journal pone 0196067 t004. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 10 16. NFHP involvement in TB case notification, of absolute notification and notification rates were 41 13 18 14 64 37 p 0 001 and 9 42.
3 93 14 70 p 0 0015 respectively in the sensitivity analysis. Discussion, There was an increase in new bacteriologically positive case notification from the evaluation. population by 198 cases during the five quarters of intervention a 30 increase from the cor. responding five quarters prior to intervention The difference in difference estimates showed. an increase of approximately 41 cases on an average for each quarter of intervention in the. evaluation population This estimate remained consistent when five quarters of intervention. was compared either with five quarters or fifteen quarters of pre intervention era Although. the control population was similar to the evaluation population during this period it showed a. marginal decline 2 in new bac case notification These two trends imply that the surge in. new bac case notification in the evaluation population during the intervention period was. largely attributable to the intervention This increase of notification in the evaluation popula. tion was achieved against the backdrop of slow decline of notification in the pre intervention. period both in the evaluation and control population This indicates that the notification. trend in the evaluation population was significantly bucked that too almost immediately as. soon as the project was implemented confirmed by the significant changes in the level in the. interrupted time series analysis Fig 2 It cannot be entirely ruled out that there might have. been contributions to this surge from other intensified case finding initiatives in the evaluation. population being implemented during that period albeit anecdotally there is no such evidence. of that Therefore the broad conclusion that the surge in the case notification in the evaluation. population was mainly due to the intervention project will not be inaccurate. This increase in case notification was achieved by the project through inclusion and. involvement of the non formal health providers NFHP within the operational framework of. RNTCP This is because the target population of the project that is the slum dwelling migrant. labourer population living in Bhubaneswar and Jajpur industrial areas of Odisha presented to. these providers in large numbers and not to the public health system Therefore as the project. implementers functioned as a go between the RNTCP and the NFHP network it facilitated. early and convenient access of the TB patients from the target population to standardized TB. care of RNTCP through the NFHPs resulting in the observed increase in case notification. The project is likely to have benefitted considerably from the use of Xpert MTB RIF tech. nology as the first line of test in its diagnostic algorithm a divergence from the currently. existing RNTCP policy 3 Consequently the bacteriologically positive case pick up rate. from the TB symptomatics examined by the project was 17 as often found in such projects. employing Xpert MTB RIF as the first line of diagnostic test 27 29 This was considerably. higher than that achieved by the routine programme tools i e smear microscopy the positiv. ity rate of which is roughly 10 in Odisha Moreover the short turnaround time taken to. diagnose cases through this technology also helped to avoid significant loss of diagnosed TB. cases from the treatment system However similar projects using Xpert MTB RIF as a pri. mary diagnostic tool instead of sputum microscopy have been found to increase the notifi. cation of more bacteriologically confirmed TB cases but without enhancing the notification. of total TB cases 29 27 28 30 The reason is many such projects fail to tap into the pool of. under reached populations but just tend to bacteriologically confirm through the use of. Xpert MTB RIF technology the sputum negative TB cases those who anyway would have. been diagnosed by X ray or empirically 31 by the programme Therefore they just tend to. shift some bacteriologically unconfirmed cases to the bacteriologically confirmed category. and therefore only increase notification of positive cases but fail to impact total notification. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 11 16. NFHP involvement in TB case notification, However additional 198 bacteriologically confirmed cases notified by this project led to an. increase in notification of total patients by 192 This indicates that the additional new bac. case notification attributed to the project intervention were actually from the under reached. population who otherwise would not have been diagnosed at least during that time period. if the project was not implemented, National TB programmes including RNTCP will eventually strengthen their country wide. diagnostic network with Xpert MTB RIF technology However just replacing routine smear. microscopy by more sensitive molecular technology may not help the programme to diagnose. majority of the TB cases from the key under reached populations as barriers to access will con. tinue to plague routine passive case finding strategies To reach out to these key populations. which is central to TB elimination strategy of India external community based programme. partners may be needed to establish the all important connections between RNTCP and the. vulnerable communities and their community based healthcare providers 32 as this project. has demonstrated Recent mathematical models have also shown that involvement of private. healthcare sector both formal and informal among all other intervention strategies will have. maximum impact on TB control especially if complemented by large scale roll out of Xpert. MTB RIF across the country 32 33, The analyses also illustrates some weaknesses in the project initiative and also perhaps in. the impact evaluation framework 34 We observe that 466 Xpert positive cases were diag. nosed by the project and facilitated by it to register for RNTCP treatment but only 198 43. cases were actually additional new bac cases among them It illustrates that perhaps more. than half of the Xpert cases detected by the project would have anyway accessed RNTCP and. would have been detected by routine smear microscopy or chest x ray This was further evi. dent from the post intervention trends which experienced a sharp immediate rise in case noti. fication but then the slope flattened which means further increase after the initial surge could. not be sustained Moreover the case detection could only be increased to 55 from the base. line 42 of the estimated incident cases indicating perhaps an unfulfilled potential of the. project This was most likely due to inability of the project to quickly move on to new under. reached populations living in untapped slums If that could have been done a greater number. of under reached population could have been reached and more additional TB cases could. have been detected with the same project yield over the same period Some of these weakness. may be ascribed to lack of time as the project was implemented for five quarters only There. fore the project failed to quickly manoeuvre from one slum to another. Secondly some of the cases detected by the project were of retreatment category but since. the entire impact evaluation framework was focused on the additional notification of new. cases only additional notification in the retreatment category was not considered perhaps a. missed opportunity to apportion some of this credit to the project. Another gap in the project was 26 of the TB symptomatics identified by the NFHPs. could not be subjected to sputum examination and 5 of the TB cases diagnosed by the proj. ect could not be initiated on RNTCP treatment Dropping out of the diagnosis and treatment. system of TB programmes by a proportion of symptomatics and patients is not uncommon. The target population of the project being migrant in nature few of them failed to comply. with its diagnosis and treatment protocols despite the persuasion by the providers and the. project staff Otherwise the impact of the project could have been more with the same effort. Some of the initial defaulters those who failed to initiate treatment after diagnosis may. have ended up receiving RNTCP treatment from their original places of residence but the. project had no means to reconcile that information However the proportion of initial. defaulters encountered in the project was less than what has been the overall experience of. RNTCP in these areas, PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 12 16.
NFHP involvement in TB case notification, The analysis has the usual limitations as well the strengths of implementation research. using quasi experimental design The control population was perhaps not an exact match of. the evaluation population though the similarity was remarkable as described above However. the case notification from the control area had historically been even lower than that of the. evaluation population Therefore had there been any state wide initiative from the routine. RNTCP system to enhance case notifications it would have had greater impact on the control. population due to its lower base But in reality the control area showed a slight decline in noti. fication during the intervention period in stark contrast to the 28 increase in notification in. the intervention area Additionally the before after design and the difference in difference. analysis framework also addressed some of these unmeasured differences if any robustly. enough 25 The interrupted time series analysis with a comparison group also validated the. parallel trend assumption of this design and also helped to identify the timing of the impact of. the project The minimum change in the sensitivity analysis further strengthened our analyti. cal approaches Finally we did not conduct any economic evaluation of the project as well as. assessment of delay in diagnosis That would have thrown light into the cost and burden. reduction implications of the initiative which could have strengthened its future scale up. potentials, In spite of all the weaknesses results from our project provide robust evidence that case. detection in key slum dwelling migrant labourer populations can be increased through. involvement of non formal providers and that too within a short period Such efforts of involv. ing NFHPs exclusively of which there are few other evidences from India and similar settings. 35 33 is very much aligned to the Global Plan to End TB of the Stop TB Partnership It is. likely that if it is scaled up it may help RNTCP to reach a large section of the under reached. populations in the urban slums and bend the TB epidemic curve in the country by helping to. severe the infection disease cycle in such overcrowded environments This may enable the. country to achieve the key objectives of WHO s End TB Strategy of 2015 36 The results of. the project were obtained in routine field conditions hence they may be replicable at least in. similar urban and industrial area settings The simple design of this intervention also under. scores its wide scalability across different geographical regions Studies of patent medicine. vendors of Nigeria 37 involvement of rural informal doctors in Bangladesh 38 and models. of informal provider involvement in West Bengal demonstrate advantages of mainstreaming. the NFHPs with defined roles 13 but little evidence exists from their exclusive involvement. around urban slums and in TB control albeit some evidence from other disease control. domains exist 39 This signifies the importance of our work as a template for such similar. future anti TB initiatives, To conclude this work presents a proof of concept that by involving the community. embedded non formal health providers through external partners under reached cases from. the key migrant labourer populations living in the slums can be diagnosed quickly in num. bers Scaling up of such models in areas with such large key vulnerable populations may be a. way forward for the programme to diagnose majority of the cases from these underserved. communities This will not only reverse the TB epidemic in those sub populations and hence. the entire country 33 but also protect this marginalized community from far reaching unfa. vourable economic consequences of TB 40,Acknowledgments. We thank the officials and the staff of the State TB Cell Department of Health and Family. Welfare Government of Odisha for providing us support to implement the project and collect. programme data for evaluation of the impact of the project We also acknowledge the roles. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 13 16. NFHP involvement in TB case notification, played by the many non formal health providers who were the backbone of the project and.
who helped to identify presumptive TB cases during the project implementation period thus. helping many individuals and families affected by TB. Author Contributions, Conceptualization Ambarish Dutta Suvanand Sahu Rajendra Panigrahi Krushna Chandra. Sahoo Pinaki Panigrahi Daisy Lekharu Robert H Stevens. Data curation Ambarish Dutta,Formal analysis Ambarish Dutta. Investigation Ambarish Dutta Rajendra Choudhury P R Mishra. Methodology Ambarish Dutta Pritish Nanda, Project administration Ambarish Dutta Sarthak Pattanaik Rajendra Choudhury Pritish. Supervision Ambarish Dutta Sarthak Pattanaik Rajendra Choudhury Pritish Nanda P R. Mishra Robert H Stevens,Validation Robert H Stevens. Writing original draft Ambarish Dutta Sarthak Pattanaik Robert H Stevens. Writing review editing Ambarish Dutta Sarthak Pattanaik Rajendra Choudhury Pritish. Nanda Suvanand Sahu Rajendra Panigrahi Bijaya K Padhi Krushna Chandra Sahoo. P R Mishra Pinaki Panigrahi Daisy Lekharu Robert H Stevens. References, 1 WHO WHO Global tuberculosis report 2016 Internet WHO 2016 2015 http www who int tb.
publications global report en, 2 Sachdeva KS Kumar A Dewan P Kumar A Satyanarayana S New vision for Revised National Tuber. culosis Control Programme RNTCP Universal access reaching the un reached Indian J Med. Res 2012 135 690 4 Available http www ncbi nlm nih gov pubmed 22771603 PMID 22771603. 3 Ministry of Health Family Welfare Government of India Revised National TB Control Programme. Techincal and Operational Guidelines for Tuberculosis Control in India 2016 2016. 4 Mullan Z Reaching the unreached and expecting the unexpected Lancet Glob Heal 2014 2 2014. https doi org 10 1016 S2214 109X 14 70214 1, 5 World Health Organization TB Reach the 3 Million FIND TREAT CURE TB Geneva 2014. 6 Stop TB Partnership Key Populations Brief Urban Populations Geneva 2015. 7 Global Fund Key populations action plan 2014 2017 2014. 8 Marimuthu P Tuberculosis prevalence and socio economic differentials in the slums of four metropoli. tan cities of India Indian J Tuberc 2016 63 167 170 https doi org 10 1016 j ijtb 2016 08 007 PMID. 9 UN HABITAT State of the World Cities 2012 2013 Propsperity of Cities New York Routledge 2013. 10 Adams AM Islam R Ahmed T Who serves the urban poor A geospatial and descriptive analysis of. health services in slum settlements in Dhaka Bangladesh Health Policy Plan 2015 30 i32 i45. https doi org 10 1093 heapol czu094 PMID 25759453, 11 Bronner Murrison L Ananthakrishnan R Swaminathan A Auguesteen S Krishnan N Pai M et al How. do patients access the private sector in Chennai India An evaluation of delays in tuberculosis diagno. sis Int J Tuberc Lung Dis 2016 20 544 51 https doi org 10 5588 ijtld 15 0423 PMID 26970166. 12 Key Populations Brief Urban Populations Geneva STOP TB Partnership 2015. 13 Sudhinaraset M Ingram M Lofthouse HK Montagu D What Is the Role of Informal Healthcare Provid. ers in Developing Countries A Systematic Review Derrick GE editor PLoS One 2013 8 e54978. https doi org 10 1371 journal pone 0054978 PMID 23405101. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 14 16. NFHP involvement in TB case notification, 14 Islam QS Ahmed SM Islam MA Chowdhury AS Siddiquea BN Husain MA Informal allopathic pro. vider knowledge and practice regarding control and prevention of TB in rural Bangladesh Int Health. 2014 6 225 31 https doi org 10 1093 inthealth ihu025 PMID 24938278. 15 Wells WA Uplekar M Pai M Achieving Systemic and Scalable Private Sector Engagement in Tubercu. losis Care and Prevention in Asia PLoS Med 2015 12 https doi org 10 1371 journal pmed 1001842. PMID 26103555, 16 Kaboru BB Uplekar M Lonnroth K Engaging informal providers in TB control what is the potential in.
the implementation of the WHO Stop TB Strategy A discussion paper World Heal Popul 2011 12 5. 13 Available http www ncbi nlm nih gov pubmed 21677530. 17 Kapoor SK Raman AV Sachdeva KS Satyanarayana S How did the TB patients reach DOTS ser. vices in Delhi a study of patient treatment seeking behavior PLoS One 2012 7 https doi org 10. 1371 journal pone 0042458 PMID 22879990, 18 Stop TB Partnership THE PARADIGM SHIFT Global Plan to End TB Internet 2015 22 August 2016. 19 Crown WH Propensity score matching in economic analyses comparison with regression models. instrumental variables residual inclusion differences in differences and decomposition methods Appl. Health Econ Health Policy 2014 12 7 18 https doi org 10 1007 s40258 013 0075 4 PMID. 20 Zhou H Taber C Arcona S Li Y Difference in Differences Method in Comparative Effectiveness. Research Utility with Unbalanced Groups Appl Health Econ Health Policy 2016 14 419 429 https. doi org 10 1007 s40258 016 0249 y PMID 27371369, 21 Boehme CC Nabeta P Hillemann D Nicol MP Shenai S Krapp F et al Rapid molecular detection of. tuberculosis and rifampin resistance N Engl J Med 2010 363 1005 15 https doi org 10 1056. NEJMoa0907847 PMID 20825313, 22 Blakemore R Story E Helb D Kop J Banada P Owens MR et al Evaluation of the analytical perfor. mance of the Xpert MTB RIF assay J Clin Microbiol 2010 48 2495 501 https doi org 10 1128 JCM. 00128 10 PMID 20504986, 23 Steingart KR Schiller I Horne DJ Pai M Boehme CC Dendukuri N Xpert MTB RIF assay for pulmo. nary tuberculosis and rifampicin resistance in adults Cochrane database Syst Rev 2014 CD009593. https doi org 10 1002 14651858 CD009593 pub3 PMID 24448973. 24 Friedrich SO Rachow A Saathoff E Singh K Mangu CD Dawson R et al Assessment of the sensitiv. ity and specificity of Xpert MTB RIF assay as an early sputum biomarker of response to tuberculosis. treatment Lancet Respir Med 2013 1 462 70 https doi org 10 1016 S2213 2600 13 70119 X. PMID 24429244, 25 Lopez Bernal J Cummins S Gasparrini A Interrupted time series regression for the evaluation of public.
health interventions a tutorial Int J Epidemiol 2016 dyw098 https doi org 10 1093 ije dyw098 PMID. 26 R Core Team R A language and environment for statistical computing Internet Vienna Austria R. Foundation for Statistical Computing 2016 https www r project org. 27 McNerney R Zumla A Impact of the Xpert MTB RIF diagnostic test for tuberculosis in countries with a. high burden of disease Curr Opin Pulm Med 2015 21 304 8 https doi org 10 1097 MCP. 0000000000000161 PMID 25764020, 28 Durovni B Saraceni V van den Hof S Trajman A Cordeiro Santos M Cavalcante S et al Impact of. replacing smear microscopy with Xpert MTB RIF for diagnosing tuberculosis in Brazil a stepped wedge. cluster randomized trial PLoS Med 2014 11 e1001766 https doi org 10 1371 journal pmed. 1001766 PMID 25490549, 29 Khanal S Baral S Shrestha P Puri M Kandel S Lamichanne B et al Yield of intensified tuberculosis. case finding activities using Xpert MTB RIF among risk groups in Nepal Public Heal Action 2016 6. 136 141 https doi org 10 5588 pha 16 0015 PMID 27358808. 30 Hanrahan CF Clouse K Bassett J Mutunga L Selibas K Stevens W et al The patient impact of point. of care vs laboratory placement of Xpert MTB RIF Int J Tuberc Lung Dis 2015 19 811 6 https. doi org 10 5588 ijtld 15 0013 PMID 26056107, 31 Creswell J Rai B Wali R Sudrungrot S Adhikari LM Pant R et al Introducing new tuberculosis diag. nostics The impact of Xpert MTB RIF testing on case notifications in Nepal Int J Tuberc Lung Dis. 2015 19 545 551 https doi org 10 5588 ijtld 14 0775 PMID 25868022. 32 Salje H Andrews JR Deo S Satyanarayana S Sun AY Pai M et al The Importance of Implementation. Strategy in Scaling Up Xpert MTB RIF for Diagnosis of Tuberculosis in the Indian Health Care System. A Transmission Model PLoS Med 2014 11 https doi org 10 1371 journal pmed 1001674 PMID. PLOS ONE https doi org 10 1371 journal pone 0196067 May 23 2018 15 16.


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