The journey of lung cancer patients from symptoms to diagnosis in Greece. A mixed methods approach

希腊肺癌患者从出现症状到确诊的历程:一项混合方法研究

阅读:2

Abstract

The early diagnosis of lung cancer improves the probability of successful treatment. However, patients and physicians face several difficulties that can considerably delay the diagnostic process. A mixed-methods study that would follow the patient's journey throughout the diagnostic process could alleviate these difficulties. This study aimed to (a) track the patients' journey from the onset of symptoms until diagnosis and, (b) explore the patients' perspective of the journey until diagnosis, on the largest island of Greece. A convergent mixed-methods study was conducted with 94 patients with lung cancer. Patients completed a self-report questionnaire and were interviewed about their symptoms and journey through the healthcare system before their diagnosis. Our findings revealed several problems and delays in the diagnostic process. Both quantitative and qualitative data showed that patients did not recognize their symptoms and sought medical advice in time because they overlooked or attributed their symptoms to 'simpler'/'more common' causes. Furthermore, most patients were diagnosed 1-3 months after their first visit to a physician for their symptoms. Qualitative data analysis revealed three broad categories of problems that delayed diagnosis: (1) physician missteps, (2) administrative problems, and (3) the effect of the Covid-19 pandemic. This study found that major issues and delays prolong the diagnostic process for lung cancer. Therefore, optimization of diagnostic processes at each level of healthcare and interspecialty cooperation programs are needed. Furthermore, population-based interventions and patient education can help lung cancer patients be diagnosed early and improve their quality of life and disease outcomes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。