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Dedicated outreach service for hard to reach patients with tuberculosis in London: observational study and economic evaluation

Objective To assess the cost effectiveness of the Find and Treat service for diagnosing and managing hard to reach individuals with active tuberculosis. Design Economic evaluation using a discrete, multiple age cohort, compartmental model of treated and untreated cases of active tuberculosis. Setting London, United Kingdom. Population Hard to reach individuals with active pulmonary tuberculosis screened or managed by the Find and Treat service (48 mobile screening unit cases, 188 cases referred for case management support, and 180 cases referred for loss to follow-up), and 252 passively presenting controls from London’s enhanced tuberculosis surveillance system. Main outcome measures Incremental costs, quality adjusted life years (QALYs), and cost effectiveness ratios for the Find and Treat service. Results The model estimated that, on average, the Find and Treat service identifies 16 and manages 123 active cases of tuberculosis each year in hard to reach groups in London. The service has a net cost of £1.4 million/year and, under conservative assumptions, gains 220 QALYs. The incremental cost effectiveness ratio was £6400-£10 000/QALY gained (about €7300-€11 000 or $10 000-$16 000 in September 2011). The two Find and Treat components were also cost effective, even in unfavourable scenarios (mobile screening unit (for undiagnosed cases), £18 000-£26 000/QALY gained; case management support team, £4100-£6800/QALY gained). Conclusions Both the screening and case management components of the Find and Treat service are likely to be cost effective in London. The cost effectiveness of the mobile screening unit in particular could be even greater than estimated, in view of the secondary effects of infection transmission and development of antibiotic resistance.

The mobile screening unit population has shorter delays than those in the passively presenting population (median 29 days for mobile screening unit and 48 days for passively presenting cases). However, if cases presenting asymptomatically are excluded, the mobile screening unit population has longer delays. This is likely to represent the exceedingly hardto-reach nature of those who present via the mobile screening unit, rather than passively.
Although passive controls were chosen for having risk factors, they were by definition cases who presented for treatment, while the mobile screening unit is likely to be reaching cases who would otherwise never present.
Based on these fits, patients were modelled in the following way: one who died of non-tuberculosis-related causes); their times to the outcomes were estimated using simple mean imputation from other cases in the same category. One patient whose date of treatment completion preceded the date of mobile screening unit screening was dropped from the dataset, so the 47 remaining patients were included in the analysis.
An exponential model was fitted to the proportion of cases who were still on treatment, had completed treatment, were lost to follow up and had any other final outcome, by time since their initial mobile screening unit screen (aggregated into 50-day categories). Cases who were still on treatment at the end of their follow up time were distributed proportionately among the four remaining categories, since their actual time to treatment completion was unknown.
The model fitted data well (see Figure 7) apart from data on the first few months after the initial screen. Hence a second model was fitted to the same data but with the assumption that cases would have a 125 day interval before they could complete treatment. The 125 day interval was based on actual treatment length in the identified cases and produced a good fit to data. A delay was not incorporated into the transition to being lost to follow up or other outcomes, since there did not appear to be any a priori reason for such a delay.

Probability of being lost to follow up and re-engagement in the absence of Find and Treat
The risk of being lost to follow up on treatment in the absence of Find and Treat were estimated from a cohort study of tuberculosis cases in Greater London in 2003/4, which found 321 prisoners, homeless and problem drug users out of the cohort of 1941 cases 3 . In this subgroup of cases most similar to the target group for Find and Treat, 9% were lost to follow up within 6 months of starting treatment. Assuming a constant risk of loss to follow up, this translates to a 17.2% risk in the absence of Find and Treat. It was assumed such cases have proportionately lower annual rates of completing treatment and "miscellaneous" outcomes, but the same rates of tuberculosis-related death.
The rate at which cases lost to follow up re-engage with health services without Find and

Clinical outcomes of untreated cases
The prognosis of untreated tuberculosis cases was determined by the fate of cases detected in a 1975 survey in South India, in a region which, at the time, had no organised tuberculosis treatment 4 . Only results from the first survey were used (duration 1½ years), since in subsequent surveys cases were given isoniazid and advised to attend rural health institutions.
The study found that 27.8% of cases identified during the survey were subsequently cured, 30.2% died and 42.0% were still excreting bacilli. Mortality and recovery were assumed to be exponential processes to convert these into one year probabilities.

Probability that cases referred to Find and Treat for loss to follow up, who are returned to service, then become lost to follow up again
To estimate the probability that cases returned to treatment by Find and Treat after being referred for loss to follow up were again lost, we identified 28 cases with a recorded date of starting treatment that occurred after the date of Find and Treat referral. Of these 28 cases, 13 completed treatment, 9 were recorded as lost to follow up at the end of the follow-up period and 6 were still on treatment at the end of this period.
Because of the small sample size and lack of information about the date at which cases became lost to follow up, it was not possible to fit a model to the time to loss to follow up in this group. Hence a simpler approach was taken. Assuming that each loss to follow up event occurred halfway between the time a case was placed on treatment and the end of the follow up period, the total number of days at which the 28 cases were at risk of being lost to follow up was 9475. Since 9 loss to follow up events occurred during this time, the probability that a case would be lost to follow up in a year was estimated to be 34.7%. It was assumed that these cases still had the opportunity to be returned to treatment at the rate that they did before (81.7% a year).

Cases with active tuberculosis referred to Find and Treat for enhanced case management
To analyse the outcomes of the 188 tuberculosis cases referred to Find and Treat for case management support, an exponential model was fitted to the proportion of cases who were still on treatment, had completed treatment, were lost to follow up and had a different outcome, by time since their referral to Find and Treat (aggregated into 50-day categories).
Time was not allocated for the period during which no case can complete treatment as this was not necessary to achieve a good fit, presumably because most of these cases had already been on treatment when they were first engaged by the Find and Treat service.