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Abstract
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How much data are enough? How accurate do they have to be before they are useful? Do data have to be collected from us for them to be relevant to me?
Well, it depends, on a lot of things, but mostly on the questions we are hoping the data will help us address. And even when we have enough data, and they are sufficiently accurate, and they are relevant to us, they are still not much help unless they are the right data and we know how to use them.
Before unpacking these issues, let us first anchor our discussion in the roots of the discipline that underpinned the Journal's establishment: the epidemiological approach to injury prevention. Descriptive epidemiology is the science that grounds public health. As practitioners we cannot address what cannot 'see'. Descriptive epidemiology is the means by which we can elucidate the nature and extent of a problem and describe its distribution by time, person, place, severity, activity, location and mechanism. We can use descriptive data about the burden, opportunity and cost to prioritise our response. Data about availability and quality of preventive services and data about programme process, impact and outcome can help improve the performance of these preventive services. Data can be used to generate hypotheses about the cause, identify risk factors, quantify countermeasure efficacy and determine the effectiveness of programme implementation.1
So how much data are enough? A more useful way of asking this question is 'How much data do I need before I can confidently act?' In 1964, Dr Terry, Surgeon General of the US Public Health Service, named cigarette smoking a cause of lung cancer and laryngeal cancer in men, a probable cause of lung cancer in women and the most important cause of chronic bronchitis.2 How many years after that were vested interests still arguing the need for more data before those claims could be substantiated.3 It would be interesting to examine in the same light many of the calls for more data on a range of contemporary issues.
How accurate do data need to be? This is similar to the 'how much?' question and has the same answer. Data need to be as accurate as they need to be to support confident action. If the work expended to achieve greater and greater data precision is not matched by equal precision of intervention, then the benefits of the increased accuracy may be lost. This is not to say actions should not be evidence based, but the importance of data limitations cannot be judged outside of the context within which data are being used.
The how much/how accurately questions frequently arise together in conversations about the use of routine surveillance data to address post hoc research questions. Routine surveillance data and research data that have been prospectively collected to address a properly formulated research question are as different as drinking tea and chopping wood. To complain that one is not the other makes little sense...
Language: en |