Institute of Mental Health, Singapore.
Clinical Research Unit, National Healthcare Group Polyclinics, Singapore.
PLoS One. 2020 Aug 31;15(8):e0238353. doi: 10.1371/journal.pone.0238353. eCollection 2020.
Our aim was to identify the patterns of multimorbidity among a group of patients who visited primary care in Singapore.
A cross-sectional study of electronic medical records was conducted on 437,849 individuals aged 0-99 years who visited National Healthcare Group Polyclinics from 1 Jul 2015 to 30 Jun 2016 for the management of chronic conditions. Patients' health conditions were coded with the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10), and patient records were extracted for analysis. Patients' diagnosis codes were grouped by exploratory factor analysis (EFA), and patterns of multimorbidity were then identified by latent class analysis (LCA).
EFA identified 19 groups of chronic conditions. Patients with at least three chronic conditions were further separated into eight classes based on demographics and probabilities of various diagnoses. We found that older patients had higher probabilities of comorbid hypertension, kidney disease and ischaemic heart disease (IHD), while younger patients had a higher probability of comorbid obesity. Female patients had higher probabilities of comorbid arthritis and anaemia, while male patients had higher probabilities of comorbid kidney diseases and IHD. Indian patients presented with a higher probability of comorbid diabetes than Chinese and Malay patients.
This study demonstrated that patients with multimorbidity in primary care could be classified into eight patterns. This knowledge could be useful for more precise management of these patients in the multiethnic Asian population of Singapore. Programmes for early intervention for at-risk groups can be developed based on the findings.
本研究旨在确定新加坡初级保健就诊患者的共病模式。
本研究对 2015 年 7 月 1 日至 2016 年 6 月 30 日期间在国立医疗保健集团综合诊疗所就诊的年龄在 0 至 99 岁之间、患有慢性疾病的 437849 名患者的电子病历进行了横断面研究。患者的健康状况使用国际疾病分类第 10 版（ICD-10）进行编码，提取患者记录进行分析。采用探索性因子分析（EFA）对患者的诊断代码进行分组，然后采用潜在类别分析（LCA）确定共病模式。
EFA 确定了 19 组慢性疾病。至少患有三种慢性疾病的患者根据人口统计学特征和各种诊断的可能性进一步分为 8 个类别。我们发现，年龄较大的患者患高血压、肾病和缺血性心脏病（IHD）的共病率更高，而年轻患者肥胖的共病率更高。女性患者患关节炎和贫血的共病率更高，而男性患者患肾病和 IHD 的共病率更高。与华人及马来患者相比，印度患者患糖尿病的共病率更高。
本研究表明，初级保健中的共病患者可以分为 8 种模式。这些知识可用于对新加坡多民族亚洲人群中这些患者进行更精确的管理。可以根据研究结果制定针对高危人群的早期干预计划。
