Many health care interventions have costs and benefits that spill over to sectors outside the healthcare sector. Little is known about these inter-sectoral costs and benefits (ICBs). However, to achieve an efficient allocation of scarce resources, insights on ICBs are indispensable. The main objective of this study was to identify the ICBs related to health care and provide a sector-specific classification scheme for these ICBs. For this sector-specific classification scheme mental disorders were taken as an example, as we expect that this is the sector with the most ICBs.

Using PubMed, a literature search was conducted for ICBs of mental disorders and related (psycho)social effects. A policy perspective was used to build the scheme's structure, which was adapted to the outcomes of the literature search. In order to validate the scheme's international applicability inside and outside the mental health domain, semi-structured interviews were conducted with (inter)national experts in the broad fields of health care.

The searched-for items appeared in a total of fifty-two studies. The ICBs found were classified in one of four sectors: “Education”, “Labor and Social Security”, “Household and Leisure” or “Criminal Justice System”. Psycho(social) effects were placed in a separate section under “Individual and Family”. Based on interviews, the scheme remained unadjusted, apart from adding a population-based dimension.

This is the first study which offers a sector-specific classification of ICBs. Given the explorative nature of the study, no guidelines on sector-specific classification of ICBs were available. Nevertheless, the classification scheme was acknowledged by an international audience and could therefore provide added value to researchers and policymakers in the field of health technology assessment. The identification and classification of ICBs offers decision makers supporting information on how to optimally allocate scarce resources. By exploring a new area of research, which has remained largely unexplored until now, the current study has an added value as it may form the basis for the development of a tool which can be used to calculate the ICBs of health care interventions.