Strengthen your evaluation by using a mixture of data collection methods to enable you to triangulate your findings.
What and Why
The next steps are to:
- Collect your data
- Analyse the data
How will I collect the data?
Quantitative (numbers) and qualitative (narrative) methods represent different ways data can be collected and used to inform your evaluations. Quantitative data collection methods give numerical results whereas Qualitative data collection methods use narrative or descriptive data rather than numbers. These methods include:
- Quantitative methods: Structured interviews and questionnaires, monitoring forms, performance data and validated measures (such as measures of wellbeing)
- Qualitative methods: Interviews (unstructured and semi-structured), observations, focus groups, document reviews
How will I analyse the data?
Data analysis is a process by which the data you have collected is transformed into meaningful and useful information. It can be a very complex process, with many possible approaches that are specific to the data collection methods used. The trick is to engage your experts and find the right approach to interpreting the data that makes sense in the context in which it is to be used. The most common analysis of qualitative data is observer impression, which is where the observers (you) examine the data and interpret it via forming an impression, or by using more structured approaches such as thematic analysis. The analysis of quantitative data can range from simply counting of the number of occurrences and describing what you see (descriptive statistics) to more complex statistical analysis (inferential statistics). Depending on your own knowledge and skills, the more complex analysis will possibly require the input and support of an experienced researcher, statistician or analyst.
Evaluation Tools & Approaches
This short video covers evaluation tools and approaches in an easy-to-understand format. It was produced by University of the West of England in collaboration with the West of England Academic Health Science Network.
The following tools are either internal resources developed by the BNSSG Research and Evidence Team or external resources we have found useful. Collecting data
- Decision Tree
- BNSSG Research and Evidence Team Guide to Types of data
- BNSSG Research and Evidence Team Guide to Questionnaires
- BNSSG Research and Evidence Team Guide to secondary data sources
- BNSSG Research and Evidence Team guide to interviews and focus groups
- BNSSG Research and Evidence Team Guide to case studies
- Best Practice in the Ethics and Governance of Service Evaluation – full guidelines
- Commissioning intelligence model
- BNSSG Research and Evidence Team Data analysis guide
- Resources for data analysis
- Run charts
- SPC charts
Please note we are not responsible for the content of external sites and are for guidance only.
Build on existing data: There’s no need to add yet another complicated data collection system to the pile. Build on what your organisation already has in place, using existing data, and make tweaks to add more insight if necessary
- Public Health Data i.e. your Joint Strategic Needs Assessment (JSNA) can be accessed via Public Health Analysts in your Public Health teams within your local Council – Check out our EvidenceWorks toolkit for contact details
- Performance/contract or benchmarking data can be accessed from Performance analysts / contract managers
- Statistician or Modelling support from an analyst or statistician you may find these in your CCG, Public Health Team or University
- Patient / User Experience and Satisfaction contact your Patient and Public Involvement (PPI) Lead within your organisation
- Best Practice, Research and Evaluation Evidence – check out our Evidence Works toolkit for more information
- Improvement and clinical audit data contact your Service/Quality Improvement Team or clinical audit department
It is important to identify and utilise existing (secondary) data, where it is available and of good quality, to avoid duplication and unnecessary data collection (and engage and use your analytical experts!)