Graduate School of Health Sciences, Hokkaido University, Sapporo, Japan.
Iwamizawa Campus, Hokkaido University of Education, Iwamizawa, Japan.
J Med Internet Res. 2021 Jan 19;23(1):e14794. doi: 10.2196/14794.
An increasing number of people are visiting hospital websites to seek better services and treatments compared to the past. It is therefore important for hospitals to develop websites to meet the needs of their patients. However, few studies have investigated whether and how the current hospital websites meet the patient's needs. Above all, in radiation departments, it may be difficult for patients to obtain the desired information regarding modality and diagnosis because such information is subdivided when described on a website.
The purpose of this study is to suggest a hospital website search behavior model by analyzing the browsing behavior model using a Bayesian network from the perspective of one-to-one marketing.
First, we followed the website access log of Hokkaido University Hospital, which was collected from September 1, 2016, to August 31, 2017, and analyzed the access log using Google Analytics. Second, we specified the access records related to radiology from visitor browsing pages and keywords. Third, using these resources, we structured 3 Bayesian network models based on specific patient needs: radiotherapy, nuclear medicine examination, and radiological diagnosis. Analyzing each model, this study considered why some visitors could not reach their desired page and improvements to meet the needs of visitors seeking radiology-related information.
The radiotherapy model showed that 74% (67/90) of the target visitors could reach their requested page, but only 2% (2/90) could reach the Center page where inspection information, one of their requested pages, is posted. By analyzing the behavior of the visitors, we clarified that connecting with the radiotherapy and radiological diagnosis pages is useful for increasing the proportion of patients reaching their requested page.
We proposed solutions for patient web-browsing accessibility based on a Bayesian network. Further analysis is necessary to verify the accuracy of the proposed model in comparison to other models. It is expected that information provided on hospital websites will be improved using this method.
与过去相比，现在越来越多的人访问医院网站以寻求更好的服务和治疗。因此，医院开发网站以满足患者的需求非常重要。然而，很少有研究调查当前的医院网站是否以及如何满足患者的需求。在放射科，由于网站上描述的信息是细分的，患者可能很难获得有关治疗方式和诊断的所需信息。
本研究旨在通过从一对一营销的角度使用贝叶斯网络分析浏览行为模型，提出一种医院网站搜索行为模型。
首先，我们遵循北海道大学医院的网站访问日志，该日志是从 2016 年 9 月 1 日到 2017 年 8 月 31 日收集的，并使用 Google Analytics 分析访问日志。其次，我们指定了访客浏览页面和关键字相关的访问记录。第三，使用这些资源，我们根据特定患者需求构建了 3 个基于贝叶斯网络的模型：放射治疗、核医学检查和放射诊断。通过分析每个模型，本研究考虑了为什么有些访问者无法到达他们期望的页面，以及如何改进以满足寻求放射科相关信息的访问者的需求。
放射治疗模型显示，74%（67/90）的目标访问者可以到达他们请求的页面，但只有 2%（2/90）可以到达中心页面，该页面发布了他们请求的页面之一检查信息。通过分析访问者的行为，我们清楚地表明，连接放射治疗和放射诊断页面有助于提高到达请求页面的患者比例。
我们基于贝叶斯网络为患者的网络浏览可访问性提出了解决方案。需要进一步分析以验证与其他模型相比，所提出模型的准确性。预计使用这种方法将改善医院网站提供的信息。
