AIMS: To conduct a systematic review to identify types and implications of incorrect or incomplete coding or classification within diabetes or between diabetes and other conditions; also to determine the availability of evidence regarding frequency of occurrence. METHODS: Medical Subject Headings (MeSH) and free-text terms were used to search relevant electronic databases for papers published to the end of August 2008. Two researchers independently reviewed titles and abstracts and, subsequently, the full text of potential papers. Reference lists of selected papers were also reviewed and authors consulted. Three reviewers independently extracted data. RESULTS: Seventeen eligible studies were identified, including five concerned with distinguishing between Type 1 and Type 2 diabetes. Evidence was also identified regarding: the distinction between diabetes and no-diabetes, failure to specify type of diabetes, and diagnostic errors or difficulties involving maturity-onset diabetes of the young, latent autoimmune diabetes in adults, pancreatic diabetes, persistence of foetal haemoglobin and acquired immune deficiency syndrome (AIDS). The sample was too heterogeneous to derive accurate information about frequency, but our findings suggested that misclassification occurs most commonly in young people. Implications relating to treatment options and risk management were highlighted, in addition to psychological and financial implications and the potential impact on the validity of quality of care evaluations and research. CONCLUSIONS: This review draws attention to the occurrence and implications of incorrect or incomplete coding or classification of diabetes, particularly in young people. A pragmatic and clinically relevant approach to classification is needed to assist those involved in making decisions about types of diabetes.
AIMS: To conduct a systematic review to identify types and implications of incorrect or incomplete coding or classification within diabetes or between diabetes and other conditions; also to determine the availability of evidence regarding frequency of occurrence. METHODS: Medical Subject Headings (MeSH) and free-text terms were used to search relevant electronic databases for papers published to the end of August 2008. Two researchers independently reviewed titles and abstracts and, subsequently, the full text of potential papers. Reference lists of selected papers were also reviewed and authors consulted. Three reviewers independently extracted data. RESULTS: Seventeen eligible studies were identified, including five concerned with distinguishing between Type 1 and Type 2 diabetes. Evidence was also identified regarding: the distinction between diabetes and no-diabetes, failure to specify type of diabetes, and diagnostic errors or difficulties involving maturity-onset diabetes of the young, latent autoimmune diabetes in adults, pancreatic diabetes, persistence of foetal haemoglobin and acquired immune deficiency syndrome (AIDS). The sample was too heterogeneous to derive accurate information about frequency, but our findings suggested that misclassification occurs most commonly in young people. Implications relating to treatment options and risk management were highlighted, in addition to psychological and financial implications and the potential impact on the validity of quality of care evaluations and research. CONCLUSIONS: This review draws attention to the occurrence and implications of incorrect or incomplete coding or classification of diabetes, particularly in young people. A pragmatic and clinically relevant approach to classification is needed to assist those involved in making decisions about types of diabetes.
Authors: Kamlesh Khunti; Mark D Danese; Lucie Kutikova; David Catterick; Francisco Sorio-Vilela; Michelle Gleeson; Sreenivasa Rao Kondapally Seshasai; Jack Brownrigg; Kausik K Ray Journal: JAMA Netw Open Date: 2018-12-07