In my country one can no longer do health research without considering matters of equity. This is a good thing. Because of inequities in the health system much of the data - including in research data sets - will reflect those inequities. Risk models, clinical decision pathways and the like derived from that data will likely reflect and even reinforce those inequities - usually to the detriment of minority groups. Knowing this I want to develop a suite of analytical tools to assess for inequity and to try to minimise reflecting inequities in any models I develop. I would very much appreciate suggestions of approaches/techniques at the various stages of the research process, namely:
- Epidemiological tools for assessing inequities in existing health data
- Tools for use when sampling that may account for underlying inequity
- Modelling methods which may account for inequities
- Analysis techniques which assess model performance in sub-groups
- At the implementation stages any special techniques to ensure fairness
I don’t want to pre-empt this with my own suggestions - simply initiate a discussion. It would help if any replies state which of the five stages a tool may apply.