Quantifying the costs of not taking action

Not intervening to support global mental health is not costless; in addition to immediate adverse impacts on global mental health there are wider longer-term impacts to society, indeed the majority of the economic costs of poor mental health manifest themselves in reduced participation in economic activities, such as employment, education, volunteering and family caring (Christensen et al., Reference Christensen, Lim, Saha, Plana-Ripoll, Cannon, Presley, Weye, Momen, Whiteford, Iburg and McGrath2020).

As part of any economic argument, these short and long-term impacts need to be identified and valued monetarily where feasible. This could be done by collating what is now compelling evidence of the long-term adverse mental and physical health consequences, not just from the trauma experienced by refugees, but also from the ways in which they are welcomed and integrated in relevant host country settings, including their access to routine health care and welfare services. A previous systematic review of HICs found multiple studies associating poor mental health outcomes with restrictions on immigration entry, as well as subsequent restrictions on access to employment and education (Juárez et al., Reference Juárez, Honkaniemi, Dunlavy, Aldridge, Barreto, Katikireddi and Rostila2019). More understanding about these factors, could help strengthen the case for early identification and intervention for at-risk individuals to avoid some of the long-term consequences to health systems, both mental and physical.

Evidence from systematic reviews indicates higher rates of depression and PTSD seen in refugees can last for many years, suggesting the need for long-term support systems (Blackmore et al., Reference Blackmore, Boyle, Fazel, Ranasinha, Gray, Fitzgerald, Misso and Gibson-Helm2020; Hoell et al., Reference Hoell, Kourmpeli, Salize, Heinz, Padberg, Habel, Kamp-Becker, Höhne, Böge and Bajbouj2021). For children especially there may be profound impacts on future life chances if schooling becomes further disrupted because of unaddressed depression, anxiety and PTSD (Blackmore et al., Reference Blackmore, Gray, Boyle, Fazel, Ranasinha, Fitzgerald, Misso and Gibson-Helm2020). There are also physical health consequences, for example, higher rates of cardiovascular disease and hypertension in Vietnamese and Cambodian refugees in the US who still experience trauma due to conflict many decades later (Wagner et al., Reference Wagner, Burke, Kuoch, Scully, Armeli and Rajan2013).

Appropriate local estimates of the costs of health and other services could be combined with information on the increased use of services from literature to give policy makers some sense of the magnitude of the costs of doing nothing. Local data could also be collected as part of evaluations on both short, and where feasible, longer-term outcomes. Standard templates for asking questions about the use of health and services, as well as other impacts including time out of work or the need for informal care, such as the Client Service Receipt Inventory (CSRI), have been adapted to collect information from refugees and displaced people (McCrone et al., Reference McCrone, Bhui, Craig, Mohamud, Warfa, Stansfeld, Thornicroft and Curtis2005; Grochtdreis et al., Reference Grochtdreis, Röhr, Jung, Nagl, Renner, Kersting, Riedel-Heller, König and Dams2021; Acarturk et al., Reference Acarturk, Uygun, Ilkkursun, Yurtbakan, Kurt, Adam-Troian, Senay, Bryant, Cuijpers, Kiselev, McDaid, Morina, Nisanci, Park, Sijbrandij, Ventevogel and Fuhr2022; Spaaij et al., Reference Spaaij, Kiselev, Berger, Bryant, Cuijpers, de Graaff, Fuhr, Hemmo, McDaid, Moergeli, Park, Pfaltz, Schick, Schnyder, Wenger, Sijbrandij and Morina2022). They can also be used to compare wait times, out of pocket costs and time spent receiving health care and other services compared to local populations. In host countries, it might also be feasible to conduct (or add questions to) general population surveys on longer-term health and social outcomes, such as participation in employment and level of earnings. In some HICs, electronic health and welfare record data have also been accessed (Maier et al., Reference Maier, Schmidt and Mueller2010). Impacts on families could also be measured through surveys and electronic service records (Bager et al., Reference Bager, Hansen, Andersen and Wang2018). All of these approaches can be seen in published costing studies, but this evidence base is limited and mainly focused on the experience of refugees living in HICs.

For example, interviews with 78 asylum seekers in Switzerland, as well as the use of electronic health records, suggest that annual health care costs for refugees are almost double those for the Swiss general population, with a key potential driver being undiagnosed mental disorders; moreover the costs for refugees with a mental health condition may be even greater than for refugees without these conditions (Maier et al., Reference Maier, Schmidt and Mueller2010). Longer-term analysis in Switzerland using health insurance system data also indicates asylum seekers with mental health conditions have increasing health care costs over time compared to asylum seekers without these conditions. A lack of early intervention to identify and refer asylum seekers to appropriate services may contribute to this increasing cost trajectory (Tzogiou et al., Reference Tzogiou, Spycher, Bize, Zozaya, Blaser, Vermeulen, Felappi, Bodenmann and Marti2022).

In Germany, initial annual mental health service use and general health service use for Syrian refugees with untreated PTSD were much lower than for the local population with similar mental health needs, potentially because of barriers such as mental health stigma, language, coverage restrictions and a lack of awareness of services among refugees (Grochtdreis et al., Reference Grochtdreis, Röhr, Jung, Nagl, Renner, Kersting, Riedel-Heller, König and Dams2021). At the same time, another German study indicated rates of hospitalisation due to mental health conditions in asylum seekers were twice as high as those in the general insured population (Bauhoff and Göpffarth, Reference Bauhoff and Göpffarth2018); that study also suggested increased access to primary care led mental health services would reduce costs.

There is some limited evidence on the costs of no intervention from LMICs. For example, interviews with 264 people from the former Yugoslavia who experienced conflict-related PTSD but never received treatment revealed that, on average 11 years later, they still had high levels of PTSD and incurred substantial healthcare-related costs, particularly a need for unpaid informal family care (Priebe et al., Reference Priebe, Matanov, Gavrilović, McCrone, Ljubotina, Knezević, Kucukalić, Francisković and Schützwohl2009). Another study on the Yugoslav conflict also suggests an association between increased long-term health service utilisation/costs (on average 8 years after exposure to conflict) and depression, anxiety and/or PTSD, regardless of whether still living in the Balkans or resettling in western Europe (Sabes-Figuera et al., Reference Sabes-Figuera, McCrone, Bogic, Ajdukovic, Franciskovic, Colombini, Kucukalic, Lecic-Tosevski, Morina, Popovski, Schützwohl and Priebe2012). A cross-sectional survey in Kosovo reported very low utilisation of mental health services by internally displaced or refugee women during the Kosovan war (Morina and Emmelkamp, Reference Morina and Emmelkamp2012); the lack of good quality mental health services may have influenced service utilisation. Elsewhere, other analyses looking at Somali refugees in the UK (McCrone et al., Reference McCrone, Bhui, Craig, Mohamud, Warfa, Stansfeld, Thornicroft and Curtis2005), Syrian refugees in Turkey (Fuhr et al., Reference Fuhr, Acarturk, McGrath, Ilkkursun, Sondorp, Sijbrandij, Ventevogel, Cuijpers, McKee and Roberts2019; Acarturk et al., Reference Acarturk, Uygun, Ilkkursun, Yurtbakan, Kurt, Adam-Troian, Senay, Bryant, Cuijpers, Kiselev, McDaid, Morina, Nisanci, Park, Sijbrandij, Ventevogel and Fuhr2022) and internally displaced people in Georgia (Chikovani et al., Reference Chikovani, Makhashvili, Gotsadze, Patel, McKee, Uchaneishvili, Rukhadze and Roberts2015) all report low levels of contact with mental health services despite mental health needs. While economic evidence on the association between restricted access to health services and longer-term mental health outcomes appears limited in LMICS, reduced, potentially inadequate, levels of contact with services will occur when out of pocket costs and other barriers to service use are introduced, as for instance seen in Jordan after the costs of access to health services for Syrian refugees rose (Abu Siam and Rubio Gómez, Reference Abu Siam and Rubio Gómez2021). These examples of low utilisation of services potentially could increase future risk of more intensive need for health service use.

Quantifying the costs of taking action

It is not enough to identify the costs of not taking action, evidence on effective interventions to mitigate these impacts in different global settings are needed. However, even if effective interventions are available, there will always be difficult choices to be made about the way in which limited resources can be used. An essential pre-cursor to any assessment of cost-effectiveness is to measure resources required to implement any mental health intervention. As part of the evaluation, this means documenting all aspects of intervention implementation, including training and initial set-up costs, time of frontline staff delivering services, any in-kind support received such as free use of venues and the time of volunteers. Travel and waiting time, as well as incidental costs incurred by service recipients and any accompanying family members to receive any intervention, should also be recorded. Ideally, this should be done prospectively as part of evaluation; if this information has not been collected an alternative is to have a subsequent discussion with programme implementers to describe treatment pathways and estimate typical resources required for each step along the care pathway. Once all resources have been identified appropriate locally sourced costs can be attached, such as hourly rates for different health care professionals or a minimum wage or replacement cost value for unpaid volunteer and family care time. Some of this information on resource use and cost may be in routinely prepared financial reports; this can be combined with information on the number of service recipients to generate some information on implementation costs (Jordans et al., Reference Jordans, Komproe, Tol, Susanty, Vallipuram, Ntamatumba, Lasuba and De Jong2011).

Tools have also been developed to aid evaluators and decision-makers in quantifying some of these costs. In Europe, for example, standardised unit costs for services for health, social care, and some other sectors including educational and criminal justice are available (Mayer et al., Reference Mayer, Berger, Konnopka, Brodszky, Evers, Roijen, Guitérrez-Colosia, Salvador-Carulla, Park, Hollingworth, García-Pérez and Simon2022). Other tools have been developed that focus on LMICs (Jeet et al., Reference Jeet, Masaki, Vassall and Prinja2021). They include the OneHealth Tool, a freely available online template which can be used by evaluators and policy makers to estimate resource requirements and costs associated with differing levels of population coverage for different health policy strategies combining one or more elements of packages of care (Chisholm et al., Reference Chisholm, Heslin, Docrat, Nanda, Shidhaye, Upadhaya, Jordans, Abdulmalik, Olayiwola, Gureje, Kizza, Mugisha, Kigozi, Hanlon, Adugna, Sanders, Pretorius, Thornicroft and Lund2017).

Carrying out an economic evaluation

Having quantified the costs of doing nothing and estimated the economic value of interventions, policy makers still need to know whether this represents a good use of resources. This means that in addition to determining whether strategies are effective, and quantifying how much they cost, it is important to determine opportunity costs associated with any impacts, as there are always alternative ways in which resources could be used. This is where economic evaluation, involving an analysis of costs and outcomes achieved from at least one intervention, compared with one or more alternative courses of action, or no action, can be used to help inform policy-making decision on the provision of services.

In many HICs economic evaluation is an integral part of the policy-making process within health systems, helping to determine which interventions, particularly pharmaceuticals, are funded and their eligible populations. Although less used in LMICs, international agencies such as the WHO have promoted the increased use of economic evidence in decision-making, for both country-level policy makers and international donor agencies, for instance highlighting the economic case for tackling depression and anxiety (Chisholm et al., Reference Chisholm, Sweeny, Sheehan, Rasmussen, Smit, Cuijpers and Saxena2016).

Collect data on quality of life

Seven of these 11 evaluations estimated changes in quality of life as their primary economic outcome measure, making it easier for decision-makers to compare their cost-effectiveness to that of other alternative health care interventions. Ensuring that future effectiveness studies collect quality of life data as one of their outcomes, even if an economic evaluation is not planned, will also allow this evidence base to expand further, as these data could be used to inform modelling studies. It may also be possible to retrospectively conduct economic evaluation by synthesising available evidence from trials on changes in quality of life, along with intervention costs and changes in patterns of service utilisation.

Assess short, mid and long-term economic impacts

Some of the benefits of investing in better mental health are immediate, but many will accrue over many years. Quantifying the immediate (1 year), mid-term (up to 5 years) and the longer-term (beyond 5 years) economic impacts of intervention may also help strengthen the case for investment. Many of the economic benefits of better mental health are though associated with mid to long-term benefits to society such as improved educational attainment and participation in work, reduced contact with criminal justice, as well as better physical health; all of this in turn will reduce reliance on welfare benefits.

Health economic arguments on their own may not be sufficient to persuade decision-makers to think long-term. Public health policies that recognise the importance of taking a long-term approach to health will also be critical. That said, short and mid-term health and economic impacts of any investment should also not be ignored, as these can be helpful in providing an initial justification for investment, particularly in settings where electoral cycles are short. In the case of refugees and displaced people, we have noted that the lack of early intervention has been argued to be potentially a critical factor in long-term higher health system utilisation and societal costs (Bauhoff and Göpffarth, Reference Bauhoff and Göpffarth2018; Blackmore et al., Reference Blackmore, Boyle, Fazel, Ranasinha, Gray, Fitzgerald, Misso and Gibson-Helm2020; Tzogiou et al., Reference Tzogiou, Spycher, Bize, Zozaya, Blaser, Vermeulen, Felappi, Bodenmann and Marti2022). A regression analysis covering 17 countries has also observed an association between increased overall spending on refugees in general and better mortality outcomes (Tan et al., Reference Tan, Spiegel, Haskew and Greenough2016). Factors such as investment in fair protection and documentation processes, healthcare services, logistics and support, as well as external relations were linked with better outcomes. However, with the exception of one study (Bager et al., Reference Bager, Hansen, Andersen and Wang2018), none of the economic evaluations in Table 1 look at the economic case beyond 15 months. Ideally prospectively collecting data on costs and outcomes over several years as part of evaluations would allow for assessment of short, mid and long-term impacts, but this practically may be difficult to do.

One feasible alternative is to make more use of economic decision modelling approaches, frequently used in health economic evaluation (McDaid, Reference McDaid, Thornicroft and Patel2014), to draw on multiple sources of existing data, including short-term trial outcomes, as well as health and welfare system registries where available, as used in the modelling study in Denmark (Bager et al., Reference Bager, Hansen, Andersen and Wang2018), and/or previous longitudinal analyses following health service use of refugees, to estimate mid and long-term costs and outcomes, potentially over decades. Sensitivity analyses in models could also be used to deal with uncertainty by varying assumptions on model parameters, as well as looking at how the economic case might change for different plausible scenarios, for instance, different levels of intervention uptake, likely long-term effectiveness, differences in access to routine health care services, or even on the level of time that refugees will spend in any host country.

Ensure economic evaluations consider impacts that are of relevance to funders

Economic evaluations need to take account of outcomes and goals that are of particular relevance to their funders. This can be complex, as there may be entirely separate and uncertain funding streams for refugee health services even in HICs, as in Germany where responsibility for funding services is fragmented between different administrative bodies in different regions (Biddle et al., Reference Biddle, Wahedi and Bozorgmehr2022). Many LMICs rely on what can be uncertain and time-limited levels of external donor aid from HICs, as well as direct financial support from the United Nations High Commissioner for Refugees (UNHCR) and other international agencies (Spiegel et al., Reference Spiegel, Chanis and Trujillo2018). There will also be a reliance on non-governmental organisations to deliver and in many cases fund services.

The direct role of LMICs in using their own resources to funding refugee health services remains limited, although if refugees are allowed to work they may then contribute to national health (or other) insurance schemes, as has been the case in Iran for Afghan refugees (Spiegel et al., Reference Spiegel, Chanis and Trujillo2018). Some longer-term funding from international agencies is conditional on the provision of specific services, as for instance is the case with the Global Concessional Financing Facility, a scheme that has provided access to cheap long-term loans as well as grants to support health and wider welfare of both refugees and host communities to LMICs, including Lebanon (Global Concessional Financing Facility, 2022).

The objectives of these funders may be much broader than mental health; identifying and valuing any additional benefits of intervention for physical health and general functioning of target populations may be important, given that funders may have to balance the physical health as well as mental health needs of displaced populations. Some may be interested in wider issues of economic development. Donor organisations may also be more interested in determining how best they can use their limited resources to support the victims of different geo-political crises, so it may be useful to compare the relative cost-effectiveness of interventions in different settings, or consider how they could be adapted to be used in other settings.

External funders may wish also to look at the cost-effectiveness of health system versus non-health system interventions such as welfare/development assistance; for instance organisations such as the World Bank have advocated for more use of cash transfers programmes (Özler, Reference Özler2017) and there is a growing body of research looking at whether interventions that help alleviate poverty, including pandemic-related impacts and/or encourage young people to remain in education may be more effective and cost-effective in improving mental health compared to psychological interventions alone (Bauer et al., Reference Bauer, Garman, McDaid, Avendano, Hessel, Díaz, Araya, Lund, Malvasi, Matijasevich, Park, Paula, Ziebold, Zimmerman and Evans-Lacko2021; Zimmerman et al., Reference Zimmerman, Garman, Avendano-Pabon, Araya, Evans-Lacko, McDaid, Park, Hessel, Diaz, Matijasevich, Ziebold, Bauer, Paula and Lund2021; Zaneva et al., Reference Zaneva, Guzman-Holst, Reeves and Bowes2022).

Broaden economic evaluations beyond health outcomes to look at impacts that are of key interest to host country policy makers

There are further challenges in making any economic case to local policy makers to fund services that are not targeted at their local populations. In the case of refugees and asylum seekers, there may be considerable uncertainty on how long they will remain in the host country; they may be able to return home or alternatively may wish to transit to a final destination country. If they are likely to move on to another country, policy makers may feel that any long-term mental health and wider socio-economic benefits will be gained in these other countries rather than their own. Policy makers, particularly in LMICs, may also feel that any support for externally displaced persons means that they are having divert their own very limited mental health resources away from their own population’s health. These concerns over pressure on health systems can also be visible in HICs, who may be reluctant to even receive refugees, despite their legal obligations. Domestic politics might also play a role, with a reluctance of some politicians to be seen to be funding services for refugees (Biddle et al., Reference Biddle, Wahedi and Bozorgmehr2022).

All of these factors may mean that in designing economic evaluations, particularly in low-resource settings, it is important to assess not only the potential costs and benefits to the intervention target population, but to also look at potential wider impacts in the short, as well as long-term, for the local population. Modelling analyses could be used to estimate the economic benefit for extending coverage of an effective intervention to the local population; for instance, policy makers in Lebanon may be more willing to endorse the provision of brief psychological interventions for refugees if there is evidence that these would also have benefits for the mental health and life chances, for example, participation in work or education, of the local population affected by the Beirut port explosions and the ongoing economic crisis (Farran, Reference Farran2021).

In HICs similarly identifying other population groups that might benefit from similar interventions could include military veterans and aid workers who have also been exposed to conflict-related trauma. This may also help to sustain the capacity and maintain skills for delivering interventions, as there will be fluctuations over time in the need to support refugees and internally displaced people. Psychological and other interventions targeted at refugees are now being adapted to support the mental health of high-risk population groups during the COVID-19 and future pandemics, for example, health and social care workers (Hooper et al., Reference Hooper, Saulsman, Hall and Waters2021; Ottisova et al., Reference Ottisova, Gillard, Wood, Langford, Bastien, Haris, Wild, Bloomfield and Robertson2022).

Explore how costs of implementation may be contained

The costs associated with effective implementation also need to be carefully measured; these include any potential resource requirements and costs for cultural adaptation, as well as translation/interpretation for interventions, and initial training for service deliverers. There may however be ways in which these costs could be reduced and thereby strengthen the economic case for investment. Economic modelling analyses could be used to look at how cost-effectiveness changes using different delivery mechanisms, comparing online versus face-to-face interventions, or ongoing training and supervision provided by local rather than external experts.

There may also be considerable differences in budgetary impact depending on who is delivering any mental health intervention; task-shifting away from mental health specialists so that interventions are facilitated in primary care potentially by lay community health workers or refugee peers may reduce costs considerably. It may also have an impact on the level of uptake of services, for instance, some refugees may prefer to be supported by someone from their country, who shares a common language and culture.

Placing economic evaluation within a broader systems context

It is important not to see economic evaluation as a tool that should be used in isolation, but one that can be used alongside other sources of evidence. We have noted broad eco-system challenges that refugees and other displaced people face in host countries. In many settings, including but not only LMICs, there may be substantial barriers to mental (and other) health service access for refugees and displaced people, even where these countries are considered to have some form of the universal health coverage and have integrated some services (Spiegel et al., Reference Spiegel, Chanis and Trujillo2018; Satinsky et al., Reference Satinsky, Fuhr, Woodward, Sondorp and Roberts2019; Pollard and Howard, Reference Pollard and Howard2021). Factors can include the overall limited provision of mental health services, high levels of out-of-pocket payments, lack of cultural adaptation and trained staff, as well as stigma around mental health.

One qualitative systematic review focused on how context influenced implementation of non-pharmacological interventions for refugee mental health in LMICS. This identified that interventions that provided work or education opportunities for refugees were received favourably. It also emphasised the importance of the cultural context on intervention delivery (Jannesari et al., Reference Jannesari, Lotito, Turrini, Oram and Barbui2021). Other contextual factors that can have an impact long term mental health recovery and related economic outcomes in both permanent and transitional host countries, include the legal rules in place concerning access to employment and education (Juárez et al., Reference Juárez, Honkaniemi, Dunlavy, Aldridge, Barreto, Katikireddi and Rostila2019; Posselt et al., Reference Posselt, Eaton, Ferguson, Keegan and Procter2019).

This means it is important to undertake process evaluations to better understand the implementation process, as well as situational analyses to better understand the contexts in which mental health interventions are being delivered. These wider types of information were not considered in the economic evaluations we have identified, although one ongoing study is making use of exactly this type of data in making the economic case for scaling up access to mental health services for Syrian refugees in Europe and the Middle East (Sijbrandij et al., Reference Sijbrandij, Acarturk, Bird, Bryant, Burchert, Carswell, de Jong, Dinesen, Dawson, El Chammay, van Ittersum, Jordans, Knaevelsrud, McDaid, Miller, Morina, Park, Roberts, van Son, Sondorp, Pfaltz, Ruttenberg, Schick, Schnyder, van Ommeren, Ventevogel, Weissbecker, Weitz, Wiedemann, Whitney and Cuijpers2017).

An intervention may appear cost-ineffective because of wider contextual factors in a setting, for instance, the cost and time needed to reach a service, or perhaps because of long-term uncertainty on achieving settled legal status. If these adverse factors can be identified, then they can potentially be taken into account in economic analysis, for instance modelling the costs and benefits of additional measures to overcome implementation issues. Examples could include additional investment in cultural adaptation, additional training, language support and the use of lower-cost interventions, for example, peer delivery. In the same way, the impacts of legislative measures that allow for refugee employment and/or the ability to be covered by national health insurance systems could be considered.