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Systematic review of atopic dermatitis disease definition in studies using routinely collected health data
Author(s) -
Dizon M.P.,
Yu A.M.,
Singh R.K.,
Wan J.,
Chren M.M.,
Flohr C.,
Silverberg J.,
Margolis D.J.,
Langan S.M.,
Abuabara K.
Publication year - 2018
Publication title -
british journal of dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.304
H-Index - 179
eISSN - 1365-2133
pISSN - 0007-0963
DOI - 10.1111/bjd.16749
Subject(s) - atopic dermatitis , medicine , medical diagnosis , medical record , disease , diagnosis code , medline , family medicine , health care , dermatology , pathology , surgery , environmental health , population , political science , law , economics , economic growth
Summary Atopic dermatitis (AD) is a skin disease that involves dry, itchy skin and scaly rashes. It is a common disease, especially in children, and is often simply referred to as ‘eczema’. In recent years, researchers have used medical records stored electronically and information from insurance claims to study AD. Because these databases are designed for clinical care and billing purposes and not explicitly for research, correctly identifying patients with AD in these data can be challenging. If patients are not correctly identified, studies using these databases may find misleading results. This study, conducted by a group of researchers from the United States, Canada, and United Kingdom, sought to find out how researchers identify patients with AD in data routinely collected by hospitals and health organizations. We systematically searched three large databases (PubMed, EMBASE, and Web of Science) and identified 59 studies which used routinely collected data to find out how common AD is in different populations. We found that researchers identified patients with AD in a variety of different ways. For example, patients’ records are often given numerical codes to represent medical diagnoses, and researchers used different sets of codes. Researchers also varied in whether they used information about patients’ medications and number of hospital or clinic visits related to AD. In addition, researchers rarely showed that their approach to identifying AD patients was accurate. Results from studies of AD will be difficult to interpret and compare if researchers do not have reliable ways of identifying AD patients in electronic medical records and insurance claims. Going forward, more studies are needed to develop and test strategies for identifying AD patients in these types of data so that the approaches used by researchers will be standardized. The authors offer suggestions for how to describe the approaches so that they will be more comparable.