The Agreement Between Diagnoses as Stated by Patients and Those Contained in Routine Health Insurance Data.

IF 6.5 2区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Felicitas Vogelgesang, Roma Thamm, Timm Frerk, Thomas G Grobe, Joachim Saam, Catharina Schumacher, Julia Thom
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Abstract

Background: The frequency of medical diagnoses is a figure of central importance in epidemiology and health services research. Prevalence estimates vary depending on the underlying data. For a better understanding of such discrepancies, we compared patients' diagnoses as reported by themselves in response to our questioning with their diagnoses as stated in the routine data of their health insurance carrier.

Methods: For 6558 adults insured by BARMER, one of the statutory health insurance carriers in Germany, we compared the diagnoses of various illnesses over a twelve-month period, as reported by the patients themselves in response to our questioning (October to December 2021), with their ICD-10-based diagnosis codes (Q4/2020-Q3/2021). The degree of agreement was assessed with two kappa values, sensitivity, and specificity.

Results: The patients' stated diagnoses of diabetes and hypertension agreed well or very well with their diagnosis codes, with kappa and PABAK values near 0.8, as well as very high sensitivity and specificity. Moderately good agreement with respect to kappa was seen for the diagnoses of heart failure (0.4), obesity, anxiety disorder, depression, and coronary heart disease (0.5 each). The poorest agreement (kappa ≤ 0.3) was seen for posttraumatic stress disorder, alcohol-related disorder, and mental and somatoform disorder. Agreement was worse with increasing age.

Conclusion: Diagnoses as stated by patients often differ from those found in routine health insurance data. Discrepancies that can be considered negligible were found for only two of the 11 diseases that we studied. Our investigation confirms that these two sources of data yield different estimates of prevalence. Age is a key factor; further reasons for the discrepancies should be investigated, and avoidable causes should be addressed.

患者陈述的诊断与常规健康保险数据中包含的诊断之间的一致性--数据链接研究的结果》(The Agreement between Diagnoses as Stated by Patients and Those Contained in Routine Health Insurance Data-Results of a Data Linkage Study)。
背景:在流行病学和医疗服务研究中,医疗诊断的频率是一个至关重要的数字。流行率的估计值会因基础数据的不同而有所差异。为了更好地理解这种差异,我们将患者在回答我们的问题时所报告的诊断与他们在医疗保险公司的常规数据中所陈述的诊断进行了比较:我们对德国法定医疗保险公司之一 BARMER 投保的 6558 名成年人进行了调查,比较了患者本人在回答我们的询问时所报告的 12 个月期间(2021 年 10 月至 12 月)的各种疾病诊断与基于 ICD-10 的诊断代码(2020 年第四季度至 2021 年第三季度)。用两个卡帕值、灵敏度和特异性评估了一致程度:结果:患者陈述的糖尿病和高血压诊断与他们的诊断代码吻合很好或非常好,卡帕值和 PABAK 值接近 0.8,灵敏度和特异性也非常高。心力衰竭(0.4)、肥胖症、焦虑症、抑郁症和冠心病(均为 0.5)的诊断卡帕值的一致性为中等偏上。创伤后应激障碍、酒精相关障碍以及精神和躯体形式障碍的一致性最差(kappa ≤ 0.3)。年龄越大,一致性越差:结论:患者提出的诊断往往与常规医疗保险数据中的诊断不同。在我们研究的 11 种疾病中,仅有两种疾病的诊断结果存在可忽略不计的差异。我们的调查证实,这两种数据来源产生了不同的患病率估计值。年龄是一个关键因素;应进一步调查造成差异的原因,并解决可避免的原因。
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来源期刊
Deutsches Arzteblatt international
Deutsches Arzteblatt international 医学-医学:内科
CiteScore
4.10
自引率
5.20%
发文量
306
审稿时长
4-8 weeks
期刊介绍: Deutsches Ärzteblatt International is a bilingual (German and English) weekly online journal that focuses on clinical medicine and public health. It serves as the official publication for both the German Medical Association and the National Association of Statutory Health Insurance Physicians. The journal is dedicated to publishing independent, peer-reviewed articles that cover a wide range of clinical medicine disciplines. It also features editorials and a dedicated section for scientific discussion, known as correspondence. The journal aims to provide valuable medical information to its international readership and offers insights into the German medical landscape. Since its launch in January 2008, Deutsches Ärzteblatt International has been recognized and included in several prestigious databases, which helps to ensure its content is accessible and credible to the global medical community. These databases include: Carelit CINAHL (Cumulative Index to Nursing and Allied Health Literature) Compendex DOAJ (Directory of Open Access Journals) EMBASE (Excerpta Medica database) EMNursing GEOBASE (Geoscience & Environmental Data) HINARI (Health InterNetwork Access to Research Initiative) Index Copernicus Medline (MEDLARS Online) Medpilot PsycINFO (Psychological Information Database) Science Citation Index Expanded Scopus By being indexed in these databases, Deutsches Ärzteblatt International's articles are made available to researchers, clinicians, and healthcare professionals worldwide, contributing to the global exchange of medical knowledge and research.
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