Frankfurt Reference Centre for Rare Diseases, Goethe University Frankfurt, University Hospital, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.
Institute of Medical Informatics (IMI), Goethe University Frankfurt, University Hospital, Theodor Stern Kai 7, 60590, Frankfurt am Main, Germany.
Orphanet J Rare Dis. 2024 Sep 12;19(1):340. doi: 10.1186/s13023-024-03347-y.
The Pareto Principle asserts that a large portion of results can be achieved with a small amount of effort. Wakap et al. found that around 80% of individuals with rare diseases (RD) suffer from one of 149 specific rare diseases. A significant challenge in the RD domain is the lack of information, compounded by the fact that most RD are not specifically codifiable in the ICD-10, leading to a deficit in reliable epidemiological data. Additionally, time constraints in medical education hinder the comprehensive teaching of all RD, contributing to the diagnostic odyssey problem through failure of recognizing diseases. We identified the most and second most prevalent RD (prevalences of 1-5/10,000 and 1-9/100,000, respectively) from the Orphanet Epidemiology File, totaling 454 diseases. We investigated the feasibility of specific coding using ICD-10-GM and whether these diseases were explicitly listed in the subject catalog (GK) of the second state examination in human medicine in Germany. A two-sided chi-square test was employed to identify statistically significant differences between prevalence groups.
Out of 454 diseases, a total of 34% could be specifically coded in ICD-10-GM, with 49% of diseases in the 1-5/10,000 prevalence range (153 RD) and 26% in the 1-9/100,000 range (301 RD) having specific codes. Approximately 15% of all investigated diseases were part of the GK, with 25% of the most prevalent and 10% of the second most prevalent RD group, respectively. Statistically significant differences were observed between prevalence groups concerning the presence of a specific ICD-10-GM code and inclusion in the GK.
Only 49% of the most prevalent RD can be specifically coded, highlighting the challenge of limited epidemiological data on RD. In Germany, the Alpha-ID was introduced in addition to ICD-10 in the inpatient setting to obtain more valid epidemiological data on RD. Recognizing the Pareto Principle's applicability, the study emphasizes the importance of including the most common rare diseases in medical education. While recognizing the limitations, especially in covering ultra-rare diseases, the study underscores the potential benefits of enhancing medical curricula to improve rare disease awareness and diagnostic accuracy.
帕累托法则认为,少量的努力可以产生大量的结果。Wakap 等人发现,大约 80%的罕见病(RD)患者患有 149 种特定罕见病之一。RD 领域的一个重大挑战是信息匮乏,再加上大多数 RD 在 ICD-10 中无法具体编码,导致可靠的流行病学数据不足。此外,医学教育中的时间限制阻碍了对所有 RD 的全面教学,导致通过未能识别疾病而出现诊断奥德赛问题。我们从孤儿病流行病学文件中确定了最常见和第二常见的 RD(患病率分别为 1-5/10000 和 1-9/100000),共计 454 种疾病。我们研究了使用 ICD-10-GM 进行特定编码的可行性,以及这些疾病是否明确列入德国人类医学第二次国家考试的主题目录(GK)。采用双侧卡方检验来确定患病率组之间的统计学差异。
在 454 种疾病中,共有 34%可以在 ICD-10-GM 中进行专门编码,1-5/10000 患病率范围内的疾病中有 49%(153 种 RD),1-9/100000 患病率范围内的疾病中有 26%(301 种 RD)具有特定编码。大约 15%的调查疾病属于 GK,其中最常见的 RD 占 25%,其次常见的 RD 占 10%。在是否存在特定 ICD-10-GM 编码和是否包含在 GK 方面,患病率组之间存在统计学显著差异。
只有 49%的最常见 RD 可以进行专门编码,这突出了 RD 流行病学数据有限的挑战。在德国,除了 ICD-10 之外,在住院环境中还引入了 Alpha-ID 以获取更多关于 RD 的有效流行病学数据。认识到帕累托法则的适用性,该研究强调了将最常见的罕见病纳入医学教育的重要性。尽管认识到存在局限性,特别是在涵盖超罕见疾病方面,该研究强调了增强医学课程以提高对罕见病的认识和诊断准确性的潜在好处。