We found that implementation of ICF by the announcement screen method in a large HIV clinic led to a 76% increase in the number of TB suspects identified, with only a 30% increase in newly diagnosed TB cases. PCF during the post-ICF period continued to identify a similar number of TB suspects compared with the pre-ICF period, even though ICF was performed at an earlier stage of the clinic visit than PCF. Different subsets of patients were identified through the two parallel screening methods.
The reported yield of new TB cases identified by ICF varies greatly, depending on the HIV prevalence in the population at risk studied, the country-specific TB prevalence and the method of screening used (symptom-based or not). According to a recent meta-analysis of studies of ICF in HIV-infected people in resource-limited settings, it ranged from 2.2% in contact-tracing exercises to 8.2% in medical and antiretroviral clinics [11]. Factors associated with a higher yield of ICF included the screening of all patients regardless of symptoms, and ICF in countries with higher TB prevalence. Screening strategies also vary widely and usually involve a set of questions. Absence of current cough, night sweats, weight loss and fever was associated with a low probability of active TB disease [12], although this was dependent on the prevalence of TB in the screened population with the negative predictive value decreasing from 99.7% to 92.3% with an increase in TB prevalence from 1% to 20%.
The yield of our symptom-based screening method was lower: at 1.4% and 1.7% of the active attending patient population in the pre-ICF and post-ICF period, respectively. In Uganda, prevalence estimates of newly diagnosed TB identified by symptom-based ICF screening programmes vary between 7.2% in a rural cohort of ART initiators, 3.6% in a rural cohort of patients screened for ART eligibility and 1.4% among new patients enrolling in an HIV clinic in the same hospital complex [13–15]. Our study population represents the population of a “mature” HIV clinic, with the majority of patients on ART and therefore less likely to have unrecognized TB. Also, regular TB screening via PCF may have already reduced the burden of infectious patients and thus the nosocomial transmission of TB, leading to a reduced TB incidence in our patient population. Other explanations for the low yield found in our study include an inefficient method of screening with missing of TB suspects (possibly also due to stigma, evidenced by the large proportion of TB suspects identified by PCF after ICF had been implemented), or a substandard laboratory performance, although regular external quality control has not shown this to be the case. The contribution of missed smear-negative, culture-positive TB is unclear: we diagnosed smear-negative pulmonary TB among 12% of coughing TB suspects in both the pre- and post-ICF period, which was lower than an estimated 19% smear-negative, culture-positive TB diagnosed among IDI pulmonary TB suspects in an earlier study (unpublished data from [16]). The effect of routine use of TB culture or Xpert MTB/RIF in confirming these empirically treated TB cases should be investigated, as well as the cost-effectiveness of such strategies.
We attempted to implement ICF in a methodical and feasible way using a method based on announcements. The individual screening method would possibly have led to identification of more suspects, but at a greater cost, both monetary and human resource. We show that this method is feasible, but less effective than PCF. The population of TB suspects identified by this method of ICF was different from the one identified through ongoing PCF in the same period, as evidenced by their differing baseline characteristics and the higher TB suspect to case ratio in ICF versus PCF suspects. This could have been due to inadequate screening by the peer supporters, or to a higher likelihood of more “experienced” patients presenting themselves for screening. This correlates with our finding that only one-fifth of TB suspects who were newly enrolled in HIV care were identified through ICF. Conversely, considering that the suspects identified through PCF in both periods were relatively similar but differed from those of the suspects identified through ICF, ICF might have identified an additional subset of TB patients which otherwise would have remained undiagnosed and therefore infectious. Our results cannot confirm or exclude this possibility, however. Additionally, stigma attached to TB may result in the patient presenting to the clinician when being asked the screening questions rather than approaching the peer supporter in the waiting area. Incomprehension of the message may also be a cause; either due to a language barrier or because of the manner in which the message is delivered. Our ICF method was very dependent on how the person charged with giving the announcements did this, and how he/she emphasized the importance of knowing one’s “TB status”. The individual screening method may arguably have fewer of these problems. Lastly, the announcements could possibly have made PCF more effective, by sensitizing patients and making them more likely to volunteer their symptoms during their clinician visit.
Costs per TB case identified rose from 12 to 22 USD after implementation of ICF using the announcement screen method. The increase was mainly due to the higher suspect to case ratio and to the cost of the peer supporters performing the screening. These were relative costs, comparing costs pre- and post-ICF implementation. Absolute costs of screening programmes are highly dependent on the work-up of TB suspects and comparisons across settings and countries are therefore difficult to make. We lacked both cost and clinical inputs to do a formal cost-effectiveness analysis. Our analysis was simple in nature and therefore did not take staff time or treatment costs into account. The TB-HIV clinic staff including the peer supporters would only have helped out in the regular ART clinic on an ad-hoc basis. A formal cost-effectiveness analysis is needed to inform practice and should include the effect of ICF on TB transmission. The cost-effectiveness of screening of the whole population regardless of (the duration of) symptoms, as proposed by some [11, 17], would have to be established. This would not be feasible in our clinic without a comprehensive restructuring of the health care delivery at IDI and without a significant increase in resources for personnel and investigations.
Our findings raise the question how best to optimize ICF in a setting like ours. As the majority of TB cases were found among patients newly enrolled into HIV care, it seems advisable to screen that part of the patient population systematically, possibly using an individual screening method. For patients in care for a longer period of time, the optimal screening strategy is less obvious. As clinicians are less likely to think of TB in stable patients, there is a need for some form of additional screening, especially if it would sensitize the patient to report TB-symptoms during the formal encounter with the HIV clinician. Targeted announcements such as in our study might work for this category of patients. Optimal screening frequencies should be established, for example by comparing a strategy of screening at each clinic visit with 3-monthly, 6-monthly or even yearly TB screening.
Noteworthy was the high retention rate of TB suspects: 95% and 96% underwent investigations. This was substantially higher than in a similar screening programmed in Swaziland, where this was only 53% [18].
Limitations of our study were the retrospective study design and the use of routinely collected data with missing data as a result. The 50 excluded patients who were identified by ICF but did not qualify as a TB suspect on arrival at the clinic, added to the increase in workload after ICF implementation. Some of these were misidentified by the peer supporters, highlighting the need for continuous retraining of lay health care workers. Others purposefully reported TB symptoms at screening to ensure being seen by a clinician in the TB-HIV clinic. Interestingly, 32 patients were identified as TB suspects by the peer supporter but were never seen in the TB clinic, possibly due to long waiting times or to stigma associated with TB. The potential TB suspects for whom no data was available (n = 56) possibly belong to the same category. Both point towards a possible systems issue absorbing these patients in the TB-HIV clinic. Although we tried to highlight differences in study population, changes due to time-trends are a limitation of the before-after study design. We feel that the limited period of time in which the study was conducted was unlikely to have a major impact on the results.
Sputum samples were investigated by light microscopy using Ziehl-Neelsen staining in the pre-ICF period, while an in-house LED-based fluorescence microscopy was established at the start of the post-ICF period. However, we do not believe the 10% sensitivity difference to have influenced our case-detection in both periods greatly [19]. We made assumptions of the numbers of investigations ordered for the costing analysis; however, as the investigations did not differ hugely in price, we believe that using the actual numbers would not change our estimate markedly. We also assumed a flat cost of 5,000 UGX (2.16 USD) for sputum smear microscopy, while the in-house test implemented in the post-ICF period was cheaper (true costs were not available). Our costing analysis was therefore conservative.
Lastly, this method of ICF implementation would not have been possible in a large clinic without resources for the additional lay health care workers and investigations. The IDI has more available tests for diagnosis and better follow-up of the patients compared to most health care settings in sub-Saharan Africa. Also, the on-site fluorescence microscopy services could handle the additional sputum smears in a timely fashion. For ICF to be implemented countrywide in Uganda and in other resource limited settings, there would have to be a scale-up of resources in order to train health care and lay workers and to equip the laboratory systems to handle the extra workload.