A Research of Big Data Generation and Utilization Model in Healthcare Field in the Post-Corona Era

Gang-Hoon, Kim; Kim, Hoon

doi:10.22143/hss21.12.1.144

Cited by 3 publications

(1 citation statement)

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“…This can help them analyze large data sets of patient data and identify different clusters from and correlations between data sets [27]. The use of health big data with artificial intelligence technologies such as machine learning and deep learning can further facilitate innovation in health care services, such as individual clinical decision support systems and real-time precision diagnosis [28,29]. Organizations can use big data based on artificial intelligence to address cost and efficiency problems emerging during drug trials [9].…”

Section: Principal Findingsmentioning

confidence: 99%

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

Lee¹,

Jang²,

Lee³

2023

JMIR Form Res

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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.

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Section: Principal Findingsmentioning

confidence: 99%

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

Lee¹,

Jang²,

Lee³

2023

JMIR Form Res

View full text Add to dashboard Cite

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

Lee¹,

Jang²,

Lee³

2023

Preprint

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BACKGROUND This study focuses on the potential of health big data in the Korean context. Despite the availability of health big data and pan-government efforts to increase data use, the use of health big data is restricted to public institutions that hold big data and conduct public interest. In order to increase the use of health big data, it is necessary to identify and develop measures to meet various demands for health big data from individuals, private companies, and research institutes. Despite the need to enhance the usefulness of health big data and develop a system for supporting health big data analysis and use, there has been limited research on the subject. OBJECTIVE To identify the perceptions of and demands for health big data analysis and use among workers in healthcare-related occupations and clarify the obstacles to the use of health big data. METHODS From May 8 to May 18, 2022, we conducted an online survey among 390 healthcare-related workers in Korea. We used the chi-square test to estimate the differences between occupations. We expressed the results analysis by item in frequency and percentage and expressed the difficulties in analyzing health big data in mean and standard deviation. RESULTS The respondents revealing the need to use health big data, and low utilization of health big data in work-related fields accounted for 86.4% and 38.2%, respectively. The respondents who never used health big data accounted for 65.6%. The lack of awareness about the source of the desired data was the most cited reason for non-use by 39.6% of the respondents. Among the respondent users, the most cited obstacle to using health big data was the “difficulty in data integration and expression unit matching,” followed by “missing value processing and noise removal” and “data removal and type conversion that did not fit the purpose.” The respondents who were willing to use a system supporting big data analysis and use accounted for 91.8%. Healthcare service development was most cited as the application area for health big data by 21% of the respondents. CONCLUSIONS These findings indicate respondents’ high awareness of and demand for health big data. However, they also reveal the low utilization of health big data and the need to support health care workers in their analysis and use of health big data. Hence, this study recommends the development of a customized support system that meets specific requirements of big data analysis by users such as individuals, non-governmental agencies, and academia.

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Perceptions Related to Nursing and Nursing Staff in Long-Term Care Settings during the COVID-19 Pandemic Era: Using Social Networking Service

Shin

Jung

Park

et al. 2021

IJERPH

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Purpose: The purpose of this study was to investigate what opinions and perceptions people have about nursing and the role of nursing staff in nursing homes (NHs) on Social Networking Service (SNS) by analyzing large-scale data through social big-data analysis. Methods: This study investigated changes in perception related to nursing and nursing staff in NHs during the COVID-19 pandemic era using target channels (blogs, cafes, Instagram, communities, Twitter, etc.). Data were collected on the channel from 12 September 2019 to 11 September 2020, 6 months before and after 12 March 2020 when the COVID-19 pandemic was declared. Selected keywords included “nursing,” “nurse,” and “nursing staff,” and included words were “long-term care settings,” “geriatric hospital,” and “nursing home.” Text mining, opinion mining, and social network analysis were conducted. Results: After the COVID-19 pandemic, the frequency of keywords increased about 1.5 times compared to before. In March 2020 when the COVID-19 pandemic was declared, the negative phrase “be infected” ranked number one, resulting in a sharp 8% rise in the percentage of negative words in that month. The related words that have risen in rank significantly, or were newly ranked in the Top 30 after the pandemic, were related with COVID-19. Conclusion: The public began to realize the role of nursing staff in the prevention and management of mass infection in NHs and the importance of nursing staff after the pandemic. Further studies should examine the perceptions of those who have received nursing services and include a wide range of foreign channels.

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A Research of Big Data Generation and Utilization Model in Healthcare Field in the Post-Corona Era

Cited by 3 publications

References 0 publications

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

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

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

Perceptions Related to Nursing and Nursing Staff in Long-Term Care Settings during the COVID-19 Pandemic Era: Using Social Networking Service

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