Economic threshold analysis of delivering a task-sharing treatment for common mental disorders at scale: the Friendship Bench, Zimbabwe

Analytical approach

The threshold analysis was undertaken within a ‘cost-utility’ framework with treatment benefit quantified as the avoidance of years lost due to disability (YLD)12 associated with CMD. The YLD measure forms part of the disability-adjusted life year (DALY) approach to estimating disease burden and treatment impact.12 We chose this metric to capture treatment benefit because it has a wide usage in economic evaluations carried out in a global health context.12 DALY is conventionally defined as the sum of years of life lost due to premature death and the YLD attributable to CMD. We focus on the YLD component as a measure of treatment benefit given uncertainty over the direct causal component of a substantial proportion of the excess mortality linked to CMD.13

Modelling was undertaken to estimate the YLD avoided through treating CMD using the FB rather than a usual care comparator. This used evidence and data on treatment effect and treatment contacts from the FB clinical trial described elsewhere.4 We use this single source of evidence given that the trial was conducted within the same geographical and service-related context within which the wider scale-up of the FB took place. Usual care was assumed to comprise the type and frequency of health professional contacts self-reported by participants allocated to the control group of the trial. We estimated YLD over a 2-year time horizon to avoid uncertainty with projections of service user outcome over lengthier periods. Following convention, YLD in year 2 are discounted at a recommended rate of 3%.12 Costs are quantified from a payer perspective: 70%–80% of the FB programme, including scale-up, has been funded through non-governmental finance, with the remainder resourced from local city health department budgets.

We identify the level of treatment coverage (annual number treated) required for the investment in the scale-up of the FB to be considered cost-effective based on a prespecified cost-effectiveness threshold (CET). We refer to the cost-effective treatment coverage as the ‘number needed to treat’ (NNT). To evaluate the NNT, the annual fixed costs of delivering the FB programme in Zimbabwe were estimated inclusive of resource inputs invested in the initial implementation of the scale-up and programme infrastructure required to sustain the programme year-on-year (excluding the variable costs of clinical assessment and treatment-related activity with service users). We then convert these fixed costs into their ‘opportunity cost’ equivalent (C)—the quantity of YLD that could have been averted had the resources subsumed within the programme’s fixed costs been invested in alternative health promotional activity. This is calculated as:

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where ‘ λ ’ is a CET appropriate for Zimbabwe. The CET is intended to approximate the additional dollar expenditure on healthcare inputs sufficient to produce a one-unit reduction in disease burden, thereby indicating the maximum a health system should be willing to pay to avert a single YLD.14 We adopt a CET of US$600 per YLD averted, equivalent to 50% of the gross national income (GNI) per capita in Zimbabwe at 2019 price levels.15 This follows the recommendations on threshold determination in LMIC settings, reflecting the principle of opportunity cost and affordability within resource-poor contexts.16 17 The value of ‘C’ is relevant to this analysis because it identifies the minimum quantity of annual treatment benefit (total YLD averted) the FB would need to generate compared with usual care to justify fixed costs. The NNT value required for cost-effective scale-up is then:

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where ‘INB’ is the incremental net benefit per service user of FB treatment, equal to the YLD avoided through replacement of usual care with the FB less the opportunity cost of additional LHW time inputted to FB treatment-related activity: clinical assessments, PST sessions, indirect costs (defined below), case assessment work and peer group attendance. The opportunity cost of treatment activity is again expressed as the YLD that would otherwise be averted (if LHW time was used elsewhere) and is estimated using the same method applied to fixed costs.

In addition to the NNT we also report the incremental cost-effectiveness ratio (ICER) for the FB programme (additional cost per YLD averted):

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The base case ICER is calculated assuming an annual level of treatment coverage equivalent to the recorded number of patients seen by the FB during 2020 (obtained from programme management information).

A Markov model was used to estimate the YLD that could be avoided if a cohort presenting with CMD received FB treatment in place of usual care. A Markov approach was selected because it is amenable to projecting service user outcomes over extended time horizons.18 Outcomes are simulated over 24 1-month cycles for FB and usual care treatment scenarios. For simplicity the analysis only considers outcomes relating to a single treatment episode.

A visual description of the model is provided in the online supplemental appendix. In summary, the model assumes that service users spend time in one of two health states characterised by a unique disability weighting: a CMD and a remission state. Disability weights (table 1) were obtained by transforming (see table 1 footnote) Zimbabwean-specific ‘utility’ scores applicable to self-reported health states for participants in the FB clinical trial.4 19 Health states were identified through administration of the EQ5D-5L health-related quality of life instrument.20 Over a series of monthly post-treatment ‘cycles’, a percentage of the model cohort are expected to either transition into the remission state or remain in the CMD state. Of those who remit, a percentage are assumed to relapse back to the CMD state during each cycle, with a further proportion of those who relapse transitioning back to the remission state.

Table 1

Modelling assumptions

The per cent of service users entering remission during each monthly cycle (table 1) was inferred using the reported proportion of participants with CMD at 6-month follow-up in the FB clinical trial control group combined with the reported prevalence ratio for CMD between intervention and control participants.4 The presence of CMD was defined according to whether a trial participant scored ≥9 on the Shona Symptom Questionnaire (SSQ-14), a locally validated assessment tool for CMD used routinely to determine treatment eligibility.21 We present an assessment of the impact on the NNT value of using less favourable assumptions regarding CMD prevalence ratios in sensitivity analysis.

The monthly per cent of remitters who relapse (table 1) was estimated using 12-month relapse outcomes reported in a rare example of published research into the duration of remission following low-intensity psychological therapy (in this case cognitive–behavioural therapy delivered in a British primary care service).22 Relapse rates for FB treatment and usual care are assumed to be equivalent, an assumption that has been employed in similar economic analysis of depression outcomes in an LMIC setting.8 The monthly per cent of further remission after relapse was estimated using evidence from a Zimbabwean observational study that examined remission outcomes for a cohort of cases with a CMD attending community health facilities and traditional practitioners.23

Over each modelling cycle a percentage of the cohort are also assumed to die (effectively exiting the model; table 1). This was estimated using annual survival probabilities contained in life tables for Zimbabwe,24 adjusted by a relative mortality risk reported for populations with depression.25 As our analysis excludes avoidance of years of life lost as a treatment benefit, mortality risk is fixed at the same level for both remission and time spent in a CMD state.

Costs

All cost-related assumptions are detailed in table 1. Annual fixed costs were obtained from programme-level financial data. The cost of the programme scale-up came from financial planning data for 2016 detailing anticipated expenditures across multiple activities. Data on actual expenditures were unavailable. The FB scale-up strategy consisted of three phases: a needs assessment, LHW training in PST and a final ‘implementation’ phase. Cost estimates relate to the hiring of venues and accommodation, purchase of equipment, transportation, payments for trainer time, training of research assistants and purchase of wooden benches (for PST sessions). Costs were converted to an annual fixed cost equivalent assuming a 10-year programme lifetime and a discount rate of 3%.

Central programme overhead costs included payment for staff involved with programme management and related activities (eg, analytical and administrative support), building space used to house central programme activities and associated running costs. The annual cost of used building space was estimated using the purchase value of the property converted to an annualised cost, applying a discount rate of 3% and an asset lifetime of 80 years. As central overhead costs are shared across other non-FB activities, the central programme team estimated that 40% of overheads would be attributable directly to the FB.

The number of clinical assessments undertaken to determine treatment eligibility for every service user treated was inferred based on fieldwork data received from all clinics, collected as part of wider ongoing research on programme implementation, identifying the mean percentage of patients clinically assessed who had at least one FB session (36%); and an assumed 39% case detection rate through clinical screening as observed within the FB clinical trial.4 Each clinical assessment was assumed to require 60 min of LHW time.

The duration of LHW time allocated to PST sessions was estimated using the mean frequency of sessions reported in the FB trial data, assuming 45 min per session. For every minute of LHW direct treatment time, we assumed an additional minute would be required for preparatory and other clinical and administrative tasks (we refer to these as ‘indirect costs’). Time spent by LHW and supervisors reviewing patients was assumed to take an average of 13.5 min per patient. These assumptions were informed by treatment resource requirements reported by Araya et al,1 in relation to a task-sharing intervention delivered in Chile. Time allocated by LHWs to attendance at peer group meetings was based on data from the FB clinical trial. It was assumed that LHWs would be expected to attend one in every six peer group meetings, with attendance lasting 60 min.

LHWs are expected to engage in patient ‘mobilisation’. This typically consists of a talk given in a clinic waiting area promoting mental health awareness and the FB. Time allocated to mobilisation was estimated based on the mean number of mobilisation sessions over 1 month reported by a sample of LHWs interviewed during fieldwork for wider ongoing research. A group mobilisation talk was assumed to last 15 min. City health department district health promotion officers provide supervisory input to the FB programme. In consultation with programme leads, this was assumed to consist of a weekly 30 min visit to each clinic providing the FB.

The cost of usual care was estimated using health professional contact data self-reported over follow-up by participants in the control group of the FB clinical trial (unpublished data; D.Chibanda et al. (2016)). Assumptions regarding the quantity of time allocated to each contact are found in the footnote to table 1. The cost of LHW and other staff time allocated to the FB and usual care was valued using staff salaries provided by the FB programme.

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