Journal of Technologic Dentistry 2024; 46(2): 42-48
Published online June 30, 2024
https://doi.org/10.14347/jtd.2024.46.2.42
© Korean Academy of Dental Technology
류재경, 김남중, 김소민, 이선경
신한대학교 치기공학과
Jae-Kyung Ryu , Nam-Joong Kim
, So-Min Kim
, Sun-Kyoung Lee
Department of Dental Technology, College of Biotechnology and Health, Shinhan University, Uijeongbu, Korea
Correspondence to :
Sun-Kyoung Lee
Department of Dental Technology, College of Biotechnology and Health, Shinhan University, 95 Hoam-ro, Uijeongbu 11644, Korea
E-mail: oksk3737@hanmail.net
https://orcid.org/0000-0001-7025-7483
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Purpose: The purpose of this study is to investigate the applications and prospects of big data in digital dental healthcare.
Methods: The study included 30 participants in the dental field (dentists, technicians, professors, and graduate students). From June 25 to 30, 2023, the contents of the study were thoroughly explained, consent was obtained from the research subjects, and a questionnaire was administered via an internet service. The questionnaires of 28 participants who responded completely were used for analysis. The collected data were statistically processed using IBM SPSS Statistics ver. 22.0 (IBM).
Results: The use of big data in digital dental healthcare, digital dental health system, mobile dental health, dental health analysis, and telehealthcare were all heavily surveyed, with an average score of 3.97 or higher on a 5-point Likert scale. The areas where big data can be utilized in digital dental healthcare are as follows. The utilization rate for three-dimensional digital product development via linkage with big data systems and industrial field manufacturing technology was found to be 4.11±0.67, and the analysis of trends by age in the occurrence of various oral diseases was found to be 4.00±0.98.
Conclusion: In the future, research into the viability of big data’s success in the medical data field, which is directly related to human life, is needed. Additionally, social policies and regulations regarding big data–related information and standards in dental healthcare are necessary.
Keywords: Big data, Dental healthcare, Dental technicians, Digital
Journal of Technologic Dentistry 2024; 46(2): 42-48
Published online June 30, 2024 https://doi.org/10.14347/jtd.2024.46.2.42
Copyright © Korean Academy of Dental Technology.
류재경, 김남중, 김소민, 이선경
신한대학교 치기공학과
Jae-Kyung Ryu , Nam-Joong Kim
, So-Min Kim
, Sun-Kyoung Lee
Department of Dental Technology, College of Biotechnology and Health, Shinhan University, Uijeongbu, Korea
Correspondence to:Sun-Kyoung Lee
Department of Dental Technology, College of Biotechnology and Health, Shinhan University, 95 Hoam-ro, Uijeongbu 11644, Korea
E-mail: oksk3737@hanmail.net
https://orcid.org/0000-0001-7025-7483
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Purpose: The purpose of this study is to investigate the applications and prospects of big data in digital dental healthcare.
Methods: The study included 30 participants in the dental field (dentists, technicians, professors, and graduate students). From June 25 to 30, 2023, the contents of the study were thoroughly explained, consent was obtained from the research subjects, and a questionnaire was administered via an internet service. The questionnaires of 28 participants who responded completely were used for analysis. The collected data were statistically processed using IBM SPSS Statistics ver. 22.0 (IBM).
Results: The use of big data in digital dental healthcare, digital dental health system, mobile dental health, dental health analysis, and telehealthcare were all heavily surveyed, with an average score of 3.97 or higher on a 5-point Likert scale. The areas where big data can be utilized in digital dental healthcare are as follows. The utilization rate for three-dimensional digital product development via linkage with big data systems and industrial field manufacturing technology was found to be 4.11±0.67, and the analysis of trends by age in the occurrence of various oral diseases was found to be 4.00±0.98.
Conclusion: In the future, research into the viability of big data’s success in the medical data field, which is directly related to human life, is needed. Additionally, social policies and regulations regarding big data–related information and standards in dental healthcare are necessary.
Keywords: Big data, Dental healthcare, Dental technicians, Digital
Table 1 . General characteristics of subjects.
Characteristic | N (%) |
---|---|
Age (y) | |
20~29 | 5 (17.9) |
30~39 | 5 (17.9) |
40~49 | 13 (46.4) |
50~59 | 3 (10.7) |
≥60 | 2 (7.1) |
Job | |
Dentist | 1 (3.5) |
Dental technician | 18 (64.3) |
Professor | 5 (17.9) |
Postgraduate student | 4 (14.3) |
Career (y) | |
≤5 | 7 (25.0) |
6~10 | 3 (10.7) |
11~15 | 4 (14.3) |
16~20 | 8 (28.6) |
>21 | 6 (21.4) |
Total | 28 (100) |
Table 2 . Opinions on the outlook for the digital dental healthcare industry (N=28).
Characteristic | Division | Mean±SD | ||||
---|---|---|---|---|---|---|
Strongly disagree | Do not agree | Usually | Agreement | Very agree | ||
Mobile dental health | 1 (3.6) | 1 (3.6) | 3 (10.7) | 18 (64.3) | 5 (17.9) | 3.89±0.78 |
Tele healthcare | 1 (3.6) | 3 (10.7) | 4 (14.3) | 14 (50.0) | 6 (21.4) | 3.75±0.79 |
Dental health analytics | 1 (3.6) | 0 (0.0) | 4 (14.3) | 16 (57.1) | 6 (21.4) | 3.82±0.82 |
Digital dental health system | 1 (3.6) | 0 (0.0) | 4 (14.3) | 14 (50.0) | 9 (32.1) | 4.07±0.98 |
Utilization of big data in digital dental healthcare | 1 (3.6) | 0 (0.0) | 5 (17.9) | 11 (39.3) | 11 (39.3) | 4.10±0.95 |
Total | 3.97±0.86 |
Values are presented as number (%)..
Likert 5-point scale (minimum=1, maximum=5)..
SD: standard deviation..
Table 3 . Opinions on areas where big data can be utilized in digital dental healthcare (N=28).
Characteristic | Division | Mean±SD | ||||
---|---|---|---|---|---|---|
Very little | Little | Usually | Many | Very many | ||
Confirmation of the occurrence rate of palatal gingival sulcus in Koreans | 1 (3.6) | 2 (7.1) | 7 (25.0) | 16 (57.1) | 2 (7.1) | 3.57±0.88 |
Confirmation of dentition characteristics of Koreans | 1 (3.6) | 1 (3.6) | 4 (14.3) | 16 (57.1) | 6 (21.4) | 3.89±0.72 |
Analysis of age-specific trends in the occurrence of various oral diseases | 1 (3.6) | 0 (0.0) | 4 (14.3) | 16 (57.1) | 7 (25.0) | 4.00±0.98 |
Analysis of the relationship between periodontal disease and chronic disease | 1 (3.6) | 0 (0.0) | 6 (21.4) | 14 (50.5) | 7 (25.0) | 3.93±0.81 |
Analysis of differences in frequency of occurrence of oral diseases according to gender | 1 (3.6) | 0 (0.0) | 6 (21.4) | 15 (53.6) | 6 (21.4) | 3.89±0.78 |
Characteristic analysis of Korean tooth structure | 1 (3.6) | 0 (0.0) | 3 (10.7) | 19 (67.9) | 5 (17.9) | 3.96±0.81 |
Utilized for 3D digital product development through linkage with big data systems and industrial field manufacturing technology | 1 (3.6) | 0 (0.0) | 3 (10.7) | 15 (53.6) | 9 (32.1) | 4.11±0.67 |
Used to develop optimal equipment needed for occlusal diagnosis, adjustment, and treatment of Asian people’s unique natural teeth | 1 (3.6) | 0 (0.0) | 10 (35.7) | 13 (46.4) | 4 (14.3) | 3.68±0.76 |
Implementation of convergence certification development through living lab and utilization of rapid market entry system through connection with conformity certification | 1 (3.6) | 1 (3.6) | 11 (39.3) | 12 (42.9) | 3 (10.7) | 3.54±0.74 |
Analysis of period of use of dental prosthesis types | 1 (3.6) | 2 (7.1) | 7 (25.0) | 12 (42.9) | 6 (21.4) | 3.71±0.79 |
Dental prosthesis repair and management period analysis | 1 (3.6) | 2 (7.1) | 8 (28.6) | 10 (35.7) | 7 (25.0) | 3.71±0.77 |
Total | 3.82±0.78 |
Values are presented as number (%)..
Likert 5-point scale (minimum=1, maximum=5)..
3D: three-dimensional, SD: standard deviation..
Table 4 . Measures to increase the competitiveness of the domestic digital healthcare industry.
Characteristic | N (%) |
---|---|
R&D, clinical trials, establishment of infrastructure linked to business | 21 (12.9) |
Nurturing and attracting manpower | 21 (12.9) |
Improvement of related legal systems such as medical device licensing, etc. | 19 (11.7) |
Expansion of R&D research funds | 18 (11.0) |
Support for entering global markets | 18 (11.0) |
Medical information security and personal information protection | 16 (9.8) |
New workflow using digital health technology, establishment of R&R | 16 (9.8) |
Etc. | 14 (8.6) |
Improving patient safety and acceptance | 13 (8.0) |
Improvement of related legal systems such as health insurance fee application and registration process | 7 (4.3) |
Total | 28 (100) |
Multiple responses (total=163)..
R&D: research and development, R&R: role & responsibility..
Sun-Kyoung Lee
Journal of Technologic Dentistry 2024; 46(4): 182-188 https://doi.org/10.14347/jtd.2024.46.4.182Sun-Kyoung Lee
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Journal of Technologic Dentistry 2024; 46(4): 133-140 https://doi.org/10.14347/jtd.2024.46.4.133