Risk factors for the accuracy of the initial diagnosis of malaria cases in China: a decision-tree modelling approach

Malaria Journal

Xinyan Cai¹  Donglan Zhang²  Zhuo Chen³  Gang Li⁴  Shangfeng Tang⁴  Xiaoyu Chen⁴  Zhanchun Feng⁴  Da Feng⁵ 

[1] Department of Epidemiology and Biostatistics, University of Georgia, 30602, Athens, GA, USA;Department of Health Policy and Management, College of Public Health, University of Georgia, 30602, Athens, GA, USA;Department of Health Policy and Management, College of Public Health, University of Georgia, 30602, Athens, GA, USA;School of Economics, University of Nottingham Ningbo China, 531200, Ningbo, Zhejiang, China;School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China;School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, Hubei, China;

关键词: Geographic variation;    Health seeking behaviour;    Healthcare institutions;    Decision tree;   

DOI  :  10.1186/s12936-021-04006-4

来源: Springer

【 摘 要 】

BackgroundEarly accurate diagnosis and risk assessment for malaria are crucial for improving patients’ terminal prognosis and preventing them from progressing to a severe or critical stage. This study aims to describe the accuracy of the initial diagnosis of malaria cases with different characteristics and the factors that affect the accuracy in the context of the agenda for a world free of malaria.MethodsA retrospective study was conducted on 494 patients admitted to hospitals with a diagnosis of malaria from January 2014 through December 2016. Descriptive statistics were calculated, and decision tree analysis was performed to predict the probability of patients who may be misdiagnosed.ResultsOf the 494 patients included in this study, the proportions of patients seeking care in county-level, prefecture-level and provincial-level hospitals were 27.5% (n = 136), 26.3% (n = 130) and 8.3% (n = 41), respectively; the proportions of patients seeking care in clinic, township health centre and Centres for Disease Control and Prevention were 25.9% (n = 128), 4.1% (n = 20), and 7.9% (n = 39), respectively. Nearly 60% of malaria patients were misdiagnosed on their first visit, and 18.8% had complications. The median time from onset to the first visit was 2 days (IQR: 0-3 days), and the median time from the first visit to diagnosis was 3 days (IQR: 0–4 days). The decision tree classification of malaria patients being misdiagnosed consisted of six categorical variables: healthcare facilities for the initial diagnosis, time interval between onset and initial diagnosis, region, residence type, insurance status, and age.ConclusionsInsufficient diagnostic capacity of healthcare facilities with lower administrative levels for the first visit was the most important risk factor in misdiagnosing patients. To reduce diagnostic errors, clinicians, government decision-makers and communities should consider strengthening the primary care facilities, the time interval between onset and initial diagnosis, residence type, and health insurance status.

【 授权许可】

CC BY