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I shall limit this section to discussing three of the most important of these approaches.

1 Case study approaches: In these, our aim is to focus on a single event or ‘case’ and by doing this we are able to provide a very detailed analysis of this case. Usually, we will combine quantitative and qualitative data in our examination of the case. For example, if we are looking at the impact of change in a GP practice, we would probably collect statistical data on the hours worked, the numbers of patients seen, etc., and we might interview a small number of staff and/or patients to find out what their views and experiences have been. Or we might take an individual patient and analyse them as a case, looking at numbers such as blood pressure, viral counts, etc., as well as qualitative data on the thoughts and feelings of the patient and those around her/him. Thus, we can obtain a full and detailed view of what is going on in this ‘case’. I shall go into depth in these in Chapter 15.

2 Policy analysis: In a policy analysis we are usually concerned with one (or both) of the following questions:What are the forces or pressures which led to the introduction of a new policy?What are the likely, or actual, effects of the introduction of a new policy?As you can imagine these are important issues for the development of health services and take us into more political issues, such as what interest groups might influence a country's decision about whether or not to introduce a new vaccination campaign, etc. Again, we usually deal with both types of data in considering these. I shall go into depth in these in Chapter 16.

3 Multi‐stage studies: There is an increasing trend towards mixing quantitative and qualitative approaches. For example, small‐scale, qualitative studies are often used as pilot studies or feasibility studies to test methodologies and to identify the issues to be addressed in the main, quantitative study. This is very common in survey research. Often, clinical trials will incorporate the collection of qualitative data alongside the quantitative data. For example, the statistics about the effectiveness of a new treatment may be complemented by gathering data about patients' experiences and their feelings about their experiences of it. These are covered in Chapter 17.