Multi-criteria assessement (MCA), as its name implies, is a way of evaluating and comparing options on the basis of a number of  different criteria or objectives.  The ways to do this are varied, and there is no single, established procedure for MCA, so it is better seen as an approach, underpinned by a set of general principles, than as a specific methodology.  

In broad terms, MCA can be seen as a three stage process, as follows:

1. A set of criteria are first defined, reflecting the policy (or other) objectives that need to be achieved;
2. The different strategies (e.g. assessment scenarios) are then scored against each of these criteria;
3. The scores for each criterion are then aggregated (with or without weighting of some kind) to provide an overall assessment of each option, which can be used to rank the option in terms of their performance.

Defining the criteria

Selecting the criteria is clearly a crucial part in this process, for these set thew framework within which the assessment is done.  In most MCA, this is done by an expert team, though other stakeholders can be involved to ensure that their various interests are taken into account.  For the most part, criteria selection is therefore done by standard group-consultation techniques, such as questionniares, Delphi surveys, brain-storming meetings and structured meetings of various types, suppplemented as appropriate by rerviews of relevant literature.  To be effective, the criteria thus selected need both to reflect the objectives or ambitions of those concerned (and the people they represent), and to be amenable to judgement in some at least semi-quantiative way.  

In the context of environmental health impact assessment, it is evident that criteria selection is to a large extent carried out as an inherant part of the initial issue-framing, for this stage includes clear specification of the issue that is to be assessed, the scenarios to be used and the indicators that will provide the means of describing the outcomes.  If well-conceived, the outcome indicators should therefore be the criteria.  

Scoring the scenarios

The second step in MCA is to score each option (i.e. assessment scenario) against these criteria.  This can be done either qualitatively or quantitatively, usually by filling in a 'performance matrix' dimensioned to show the criteria on one axis and the options on the other.  In the case of integrated environmental health impact assessment, the materials needed for this matrix come directly from the analysis, for the assessment is designed to provide estimates for each impact indicator.  In some cases, however, the indicators may need to be reversed (to ensure that they all run in the same direction), or transformed (e.g. to a log scale) to adjust for non-linearity.

Aggregation

The third stage comprises aggregation of the scores for each option (scenario) to provide an overall measure of performance.  This can be done simply additively (without weighting), though the obvious weakness of this is that each criterion is assumed to have equal importance (whether it relates to mortality or morbity, and no matter what units it is measured in).  Alternatively, some means of weighting is required, to translate the different criteria onto equivalent (and additive) value scales.  A wide range of methods may be used for this purpose.  One of the most widely used. sometimes referred to as swing-weighting, involves making comparisons between the best and worst scores for each pair of criteria, selecting in each case the one with the larger perceived importance, and elimiating the other.  This process continues until only one criterion (the most important remains).  Participants then score all the other criteria against this reference. 

However obtained, the weights are then applied to the scores, and the results summed to provide an overall measure of performance for each option:

Pi = Σ S_ij*W_j

where: S_ijis the score for criterion j on option i, and W_j is the weight attached to criterion j.

The different scenarios can then be ranked on the basis of these scores to identify that which offers the greatest health gain (or minimum loss).  If appropriate, sensitivity analyses may also be carried out to determine how robust the final ranking is in the face of changes in the weights. 

Advantages and limitations

MCA has a number of strengths as a means of comparison and ranking.  In particular it is highly flexible, enabling both quantitative and non-quantitative measures to be combined, and for health, monetary and other (e.g. exposure) measures to be used.  Because weights are defined by the stakeholders themselves (or their representatives), the method also helps to ensure that the aggregation procedure reflects the preferences and interests of those concerned.  By the same token, it helps the stakeholders understand the aggregation process, and is thus likely to engender greater trust in its results. 

At the same time, there are a number of limitations and weaknesses.  Its success depends, for example, on how effective the process of stakeholder engagement is: biases in this process are likely to feed through into the results.  Localisation of the aggregation to these stakeholders may also mean that the weights applied may differ greatly from those used in other situations, making comparison between studies or areas difficult.   Reproducibility of the resuts may also be low, both between different stakeholder groups and between the same stakeholders at different times.  For the most part, therefore, the approach is most appropriate where relatively local issues are being assessed which affect a clearly defined group of stakeholders.