Diabetes diagnosis from administrative claims and estimation of the true prevalence of diabetes among 4.2 million individuals of the Veneto region (North East Italy)

被引:30
作者
Longato, Enrico [1 ]
Di Camillo, Barbara [1 ]
Sparacino, Giovanni [1 ]
Saccavini, Claudio [2 ]
Avogaro, Angelo [3 ]
Fadini, Gian Paolo [3 ]
机构
[1] Univ Padua, Dept Informat Engn, Padua, Italy
[2] Arsenal IT, Venetos Res Ctr eHlth Innovat, Treviso, Italy
[3] Univ Padua, Dept Med, Via Giustiniani 2, I-35128 Padua, Italy
关键词
Administrative claims; Diabetes; Health information exchange; Laboratory reports; Prevalence; Undiagnosed diabetes; Veneto; IMPAIRED GLUCOSE-TOLERANCE; CROSS-SECTIONAL SURVEY; POPULATION; MELLITUS; TRENDS;
D O I
10.1016/j.numecd.2019.08.017
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background and aims: Diabetes can often remain undiagnosed or unregistered in administrative databases long after its onset, even when laboratory test results meet diagnostic criteria. In the present work, we analyse healthcare data of the Veneto Region, North East Italy, with the aims of: (i) developing an algorithm for the identification of diabetes from administrative claims (4,236,007 citizens), (ii) assessing its reliability by comparing its performance with the gold standard clinical diagnosis from a clinical database (7525 patients), (iii) combining the algorithm and the laboratory data of the regional Health Information Exchange (rHIE) system (543,520 subjects) to identify undiagnosed diabetes, and (iv) providing a credible estimate of the true prevalence of diabetes in Veneto. Methods and results: The proposed algorithm for the identification of diabetes was fed by administrative data related to drug dispensations, outpatient visits, and hospitalisations. Evaluated against a clinical database, the algorithm achieved 95.7% sensitivity, 87.9% specificity, and 97.6% precision. To identify possible cases of undiagnosed diabetes, we applied standard diagnostic criteria to the laboratory test results of the subjects who, according to the algorithm, had no diabetes-related claims. Using a simplified probabilistic model, we corrected our claims-based estimate of known diabetes (6.17% prevalence; 261,303 cases) to account for undiagnosed cases, yielding an estimated total prevalence of 7.50%. Conclusion: We herein validated an algorithm for the diagnosis of diabetes using administrative claims against the clinical diagnosis. Together with rHIE laboratory data, this allowed to identify possibly undiagnosed diabetes and estimate the true prevalence of diabetes in Veneto. (C) 2019 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:84 / 91
页数:8
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