Obstacles to Health Big Data Utilization Based on the Perceptions and Demands of Health Care Workers in South Korea: Web-Based Survey Study.

Background: This study focuses on the potential of health big data in the South Korean context. Despite huge data reserves and pan-government efforts to increase data use, the utilization is limited to public interest research centered in public institutions that have data. To increase the use of health big data, it is necessary to identify and develop measures to meet the various demands for such data from individuals, private companies, and research institutes.

Objective: The aim of this study was to identify the perceptions of and demands for health big data analysis and use among workers in health care-related occupations and to clarify the obstacles to the use of health big data.

Methods: From May 8 to May 18, 2022, we conducted a web-based survey among 390 health care-related workers in South Korea. We used Fisher exact test and analysis of variance to estimate the differences among occupations. We expressed the analysis results by item in frequency and percentage and expressed the difficulties in analyzing health big data by mean and standard deviation.

Results: The respondents who revealed the need to use health big data in health care work-related fields accounted for 86.4% (337/390); 65.6% (256/390) of the respondents had never used health big data. The lack of awareness about the source of the desired data was the most cited reason for nonuse by 39.6% (153/386) of the respondents. The most cited obstacle to using health big data by the respondents was the difficulty in data integration and expression unit matching, followed by missing value processing and noise removal. Thus, the respondents experienced the greatest difficulty in the data preprocessing stage during the health big data analysis process, regardless of occupation. Approximately 91.8% (358/390) of the participants responded that they were willing to use the system if a system supporting big data analysis was developed. As suggestions for the specific necessary support system, the reporting and provision of appropriate data and expert advice on questions arising during the overall process of big data analysis were mentioned.

Conclusions: Our findings indicate respondents' high awareness of and demand for health big data. Our findings also reveal the low utilization of health big data and the need to support health care workers in their analysis and use of such data. Hence, we recommend the development of a customized support system that meets the specific requirements of big data analysis by users such as individuals, nongovernmental agencies, and academia. Our study is significant because it identified important but overlooked failure factors. Thus, it is necessary to prepare practical measures to increase the utilization of health big data in the future.