- Accuracy – to what extent are the data that are present, correct?
- Precision – have appropriate measures of uncertainty been included (e.g. 95% confidence intervals)
- Relevance-to what extent do the data answer the question posed?
- Completeness – how much of the data is missing?
- Timeliness – what period does the data refer to, and how relevant is that to the current position?
- Coverage – is the whole population of interest represented, and if not, what fraction makes up the sample?
- Accessibility – who has access to the data, and is it controlled (e.g. via password-restricted access, public domain)?
- Confidentiality/suppression/disclosure control – there are strict regulations preventing the publication of datasets that might, when used in combination with other available sources, enable individuals to be identified. Are these regulations followed?
- Original purpose of collection/collation – under Data Protection legislation, personal data may only be used for the purposes for which it was collected. NHS data registrations generally include improvement of the health of the population and management of the NHS among their purposes, but non-NHS data may not. In addition, change of purpose may be a source of bias in the data.
- Who undertook the collection/collation? – this may not be available.
- How the data have been collected? – this may not be available.
- Whether what is included in the data set is the actual requirement, or whether it will have to act as a proxy for the real item.
- Is the data set comparative, what are the comparators, and are they appropriate?
- If the dataset presents rates or ratios, have appropriate techniques been used to control for differing population structures? – for example, has direct or indirect standardisation (qv.) been applied?
Public Health Uses of Births and Deaths data
- Health service planning
- Epidemiology
- Monitoring and evaluation
- Audit
- Screening programmes (breast and ovarian cancer, immunisation take up)
- Confidential enquiries and register checking
- Inequalities analysis (postcode enables precise geographical analysis of population and patients).
- Assessing progress against targets (e.g. infant mortality, life expectancy).
