Schmidt-Mende Katharina, Feychting Maria, Chen Eric, Louro Javier, Modig Karin
Academic Primary Health Care Centre, Stockholm Region, Stockholm, Sweden.
Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.
Sci Rep. 2025 Sep 17;15(1):32583. doi: 10.1038/s41598-025-19621-3.
Nordic countries have a long-standing tradition of using administrative healthcare data from specialist and hospital settings to study disease frequency and etiological associations. While similar data are increasingly available elsewhere, large-scale primary care data remain limited. Understanding how data source affects disease identification is therefore critical. We conducted a register-based study including all individuals aged ≥ 60 years residing in Region Stockholm, Sweden, from 2017 to 2022. ICD-10 codes from primary care, specialist outpatient, and hospital care were grouped into 60 disease categories. One-year cumulative incidence and prevalence were estimated and compared. Disease patterns were broadly similar across care settings, with hypertension being the most common diagnosis. However, underestimation was generally greater for incidence than for prevalence. Hospital and specialist care data primarily captured acute and severe conditions, e.g., stroke, ischemic heart disease, falls, and cancer, while primary care data more effectively identified chronic risk factors such as diabetes, hypertension, hyperlipidemia, and psychiatric disorders, particularly for incident cases. Age-related differences in underestimation varied by disease but showed no consistent pattern. Primary, specialist, and hospital care data each capture distinct aspects of the disease landscape in older adults. Excluding primary care data leads to systematic underestimation of many common and chronic conditions, especially for newly diagnosed cases. This study provides guidance for epidemiological research using administrative health registers and highlights the importance of integrating data from multiple levels of care to improve the accuracy of disease burden estimates in epidemiological research using administrative health registers.
北欧国家长期以来一直有利用专科和医院环境中的行政医疗数据来研究疾病频率和病因关联的传统。虽然其他地方也越来越多地能获取类似数据，但大规模的初级保健数据仍然有限。因此，了解数据来源如何影响疾病识别至关重要。我们进行了一项基于登记册的研究，纳入了2017年至2022年居住在瑞典斯德哥尔摩地区、年龄≥60岁的所有个体。将初级保健、专科门诊和医院护理中的国际疾病分类第十版（ICD - 10）编码归为60种疾病类别。估计并比较了一年的累积发病率和患病率。不同护理环境下的疾病模式大致相似，高血压是最常见的诊断。然而，发病率的低估通常比患病率的低估更为严重。医院和专科护理数据主要记录急性和严重疾病，如中风、缺血性心脏病、跌倒和癌症，而初级保健数据能更有效地识别慢性风险因素，如糖尿病、高血压、高脂血症和精神障碍，尤其是对于新发病例。低估方面与年龄相关的差异因疾病而异，但没有一致的模式。初级、专科和医院护理数据各自捕捉了老年人疾病情况的不同方面。排除初级保健数据会导致对许多常见慢性病的系统性低估，尤其是对于新诊断的病例。本研究为使用行政健康登记册的流行病学研究提供了指导，并强调了整合多层次护理数据对于提高使用行政健康登记册的流行病学研究中疾病负担估计准确性的重要性。
