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The big case register

While introducing their review of case register research over the last 50 years, Munk-Jørgensen and colleagues (1) express possibly overpessimistic opinions about this methodology and its application. For example, it is stated that whilst case registers can demonstrate a phenomenon, such as raised mortality or changes in admission rates or duration, they cannot explain underlying reasons for this. However, case registers are no better or worse in this respect than any other observational research design. Indeed, and as acknowledged by Munk-Jørgensen and colleagues, the data they provide have overriding benefits for some questions and may be the only means of addressing these. It is true that limited data quality or availability may preclude some applications in some registers, but these limitations should not be seen as inevitable or as necessarily a ‘feature’ of the case register design. Despite the methodological advantages of the randomized controlled trial, observational data remain fundamental to health research, and much of what we know (or assume we know) is derived from observation rather than experiment. For example, John Snow’s meticulous study of the geographic distribution of cholera cases in 1854 demonstrated that this fitted a model of waterborne transmission more closely than that of airborne transmission, the dominant paradigm at the time. Through a simple piece of well-designed observational research, essentially a ‘case register’, the understanding of the disorder was significantly advanced, around 30 years before Vibrio cholerae was identified as the underlying cause. Although they can contribute to aetiological research, case registers are particularly suited to the investigation of the course and outcome of a disorder, as well as allowing intervention response to be evaluated in large, naturalistic samples and settings. As the mainstay study design in these circumstances (because trials and conventional cohort studies are too limited in size and/or representativeness), there is no intrinsic reason why case registers may not also provide important mechanistic information. Taking mental disorders and mortality as an example, we know that much of the reduced life expectancy is not accounted for by violence and suicide, but it would be negligent to assume that the remainder is no more than an expected product of less healthy lifestyles (smoking, obesity etc.). Even if this were to be the case, there are still important questions on whether mortality is raised in all mental disorders or whether at-risk groups can be defined. Are there symptom profiles, medications, or patterns of health service use/engagement which predict these outcomes? Is premature mortality in severe mental illness distributed equally across geographic areas or does this exhibit the spatial patterning that is seen in the general population? Improvement in life expectancy is unlikely ever to be a feasible outcome for a randomized trial, and biological data are unlikely to be relevant to pathways involving environmentally determined health conditions and issues such as access to, or engagement with, healthcare services. The ‘big’ case register remains the only means to answer these sorts of questions and if we bemoan the limitations of the data, it is surely our task to find ways to improve this. Negative associations are often assumed between the size of the database and the depth of the data available. Whilst quite probably true at an aggregate level (administrative data tend to be ‘shallow’ and administrative databases tend to be large), this does not have to be inevitable. As argued previously (2), electronic health records (EHRs) in mental healthcare represent data which are both large and deep – because in theory, these contain every piece of information that has been recorded in a clinical service about a person’s presentation, symptoms and relevant background history, as well as interventions received and observed outcomes. The challenges lie in accessing this information in a way that is both scientifically useful and ethical / socially acceptable. The fact that these challenges are formidable does not mean that they are necessarily insurmountable. The principal limitation of large case registers lies in the quality and scope of the data most typically available. The first and most widely applied means of addressing this is through data linkage. If a piece of information is not available in mental healthcare data, might that information lie elsewhere in another database? For example, linkages