JMIR Publications

ABSTRACT

Background:

Public reporting not only helps patients make informed choices regarding healthcare providers but also supports healthcare organizations in improving their services. Furthermore, appropriately designed public reporting information can enhance the reputation of organizations. Reporting systems that meet the diverse information needs of different users are critical for effective information utilization across all healthcare domains, including patients, providers, and other stakeholders.

Objective:

This study analyzes the City of Helsinki public reporting website in Finland, focusing on the readability dimension, with the primary aim of understanding how the website supports the information needs of different user groups.

Methods:

Using machine learning and cross-country comparative approaches, the study evaluated the City of Helsinki website based on a structured web framework, with particular attention to visualization aspects. By comparing different user groups and the composition of websites across countries, the study ultimately selected the readability of the textual content of the core city website as the primary research focus.

Results:

Previous studies have compared public reporting websites across countries using structured frameworks, but few have conducted in-depth examinations of individual websites. Building on this approach, the present study employs machine learning to conduct a detailed analysis of the City of Helsinki website, specifically assessing whether readability and reading literacy adequately meet the needs of actual users.

Conclusions:

The study examines how the structured presentation of information and free-form content on the website aligns with the information needs of different users. Based on these findings, practical recommendations for website design are proposed to improve usability and better support diverse user groups.