A Narrative Review on the Conceptual and Methodological Advancements in Digital Disruption: A Way to Improved Quality of Services in Health Care
Abstract
Background: The adoption and successful implementation of digital health solutions heavily depend on digital health literacy, which is particularly critical in the current COVID-19 era. Low levels of digital health literacy are associated with poor preventative practices, the spread of inaccurate information, vaccine hesitancy, and reduced subjective well-being. Thus, the aim of this review was to highlight areas of current scholarly interest and identify any gaps in the literature regarding conceptual and methodological advancements in digital disruption.
Methods: The authors conducted a literature search using the databases Scopus, Embase, Web of Science, PubMed, and Google Scholar, focusing on papers released between 2003 and October 2023. The following keywords were used to conduct a thorough literature search: ((digital health OR digital disruption OR digital dental health)) AND (medical health OR telemedicine)), ((online doctor OR online consultation OR online health app)) AND (COVID-19 OR pandemic)). A total of 1,244 studies were screened, including duplicates and nonEnglish research. After applying inclusion and exclusion criteria, 72 articles were selected for the review.
Results: A total of 72 articles were included in this review. The studies discussed the potential reasons for disrupted access to healthcare, which is linked to avoidable hospital admissions. Delayed care due to disruptions can lead to disease progression, the exacerbation of existing conditions, and chronic ambulatory care-sensitive conditions. Digital health innovations were presented as solutions to enhance care, reduce clinical workload, and promote independent living.
Conclusions: In conclusion, this narrative review provides a comprehensive overview of the conceptual and methodological advancements in digital technology related to healthcare. It demonstrates the potential of digital technology to revolutionize both medical and dental education.
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9. Watt T, Sullivan R, Aggarwal A. Primary care and cancer: an analysis of the impact and inequalities of the COVID-19 pandemic on patient pathways. BMJ Open 2022;12(3):e059374.
10. McKinlay AR, Fancourt D, Burton A. A qualitative study about the mental health and wellbeing of older adults in the UK during the COVID-19 pandemic. BMC Geriatr 2021;21(1):439.
11. Wright FL, Cheema K, Goldacre R, Hall N, Herz N, Islam N, et al. Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries. Eur Heart J Qual Care Clin Outcomes 2023;9(4):377–88.
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13. Nakamura N, Koga T, Iseki H. A meta-analysis of remote patient monitoring for chronic heart failure patients. J Telemed Telecare 2014;20(1):11–7.
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23. Joda T, Yeung AWK, Hung K, Zitzmann NU, Bornstein MM. Disruptive Innovation in Dentistry: What It Is and What Could Be Next. J Dent Res 2021;100(5):448–53.
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25. McBee MP, Wilcox C. Blockchain Technology: Principles and Applications in Medical Imaging. J Digit Imaging 2020;33(3):726–34.
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30. Mohanty K, Subiksha S, Kirthika S, Sujal BH, Sokkanarayanan S, Bose P, et al. Opportunities of Adopting AI-Powered Robotics to Tackle COVID-19. In: 2021 International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE; 2021. page 703–8.
31. Brunelle F, Brunelle P. Artificial intelligence and medical imaging: Definition, state of the art and perspectives. [Bulletin Inst hist du temps présent]
32. Khatab Z, Yousef GM. Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics. Crit Rev Clin Lab Sci 2021;58(8):546–62.
33. Ljepava N. AI-Enabled Marketing Solutions in Marketing Decision Making: AI Application in Different Stages of Marketing Process. TEM Journal 2022;11(3):1308–15.
34. Burden K. Impact of disruptive technologies on sourcing and outsourcing transactions. Computer Law & Security Review 2018;34(4):886–9.
35. Garbuio M, Lin N. Artificial Intelligence as a Growth Engine for Health Care Startups: Emerging Business Models. Calif Manage Rev 2019;61(2):59–83.
36. Mesko B. Future Directions of Digital Health. In: Rivas H, Wac K, editors. Digital Health: Scaling Healthcare to the World. Cham: Springer International Publishing; 2018. page 339–63.
37. Mesko B. The role of artificial intelligence in precision medicine. Expert Review of Precision Medicine and Drug Development 2017;2(5):239–41.
38. Meskó B, Hetényi G, Győrffy Z. Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res 2018;18(1):545.
39. Michel AN, Hou L, Liu D. Stability of Dynamical Systems: On the Role of Monotonic and Non-Monotonic Lyapunov Functions. Springer; 2015.
40. Khatri S, Pandey DK, Penkar D, Ramani J. Impact of Artificial Intelligence on Human Resources. In: Data Management, Analytics and Innovation. Springer Singapore; 2020. page 365–76.
41. Prakash S, Balaji JN, Joshi A, Surapaneni KM. Ethical Conundrums in the Application of Artificial Intelligence (AI) in Healthcare-A Scoping Review of Reviews. J Pers Med [Internet] 2022;12(11). Available from: http://dx.doi.org/10.3390/jpm12111914
42. Păvăloaia VD, Necula SC. Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review. Electronics 2023;12(5):1102.
43. Morales-Narvaez E, Dincer C. Wearable Physical, Chemical and Biological Sensors: Fundamentals, Materials and Applications. Elsevier; 2022.
44. Pan L, Chortos A, Yu G, Wang Y, Isaacson S, Allen R, et al. An ultra-sensitive resistive pressure sensor based on hollow-sphere microstructure induced elasticity in conducting polymer film. Nat Commun 2014;5:3002.
45. Pang C, Lee GY, Kim TI, Kim SM, Kim HN, Ahn SH, et al. A flexible and highly sensitive strain-gauge sensor using reversible interlocking of nanofibres. Nat Mater 2012;11(9):795–801.
46. Siddiqui SA, Zhang Y, Lloret J, Song H, Obradovic Z. Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent Advancements and Future Prospects. IEEE Rev Biomed Eng 2018;11:21–35.
47. Lee MY, Lee HR, Park CH, Han SG, Oh JH. Organic Transistor-Based Chemical Sensors for Wearable Bioelectronics. Acc Chem Res 2018;51(11):2829–38.
48. Saha T, Del Caño R, Mahato K, De la Paz E, Chen C, Ding S, et al. Wearable Electrochemical Glucose Sensors in Diabetes Management: A Comprehensive Review. Chem Rev 2023;123(12):7854–89.
49. Koh A, Kang D, Xue Y, Lee S, Pielak RM, Kim J, et al. A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat. Sci Transl Med 2016;8(366):366ra165.
50. Ren H, Sun J. Electromagnetic Actuation and Sensing in Medical Robotics. Springer; 2017.
51. Igarashi T, Nishino K, Nayar SK. The Appearance of Human Skin: A Survey. Now Publishers Inc; 2007.
52. Webb RC, Bonifas AP, Behnaz A, Zhang Y, Yu KJ, Cheng H, et al. Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nat Mater 2013;12(10):938–44.
53. Giansanti D. Advancing Dermatological Care: A Comprehensive Narrative Review of Tele-Dermatology and mHealth for Bridging Gaps and Expanding Opportunities beyond the COVID-19 Pandemic. Healthcare (Basel) [Internet] 2023;11(13). Available from: http://dx.doi.org/10.3390/healthcare11131911
54. Luo S, Zhang X. High-quality 3D printing of ethylene vinyl acetate with direct pellet-based FDM for medical applications: Mechanical analysis, energy absorption and recovery evaluation. J Mech Behav Biomed Mater 2023;148:106231.
55. Rybicki FJ, Grant GT. 3D Printing in Medicine: A Practical Guide for Medical Professionals. Springer; 2017.
56. Wang C, Shi YF, Xie PJ, Wu JH. Accuracy of digital complete dentures: A systematic review of in vitro studies. J Prosthet Dent 2021;125(2):249–56.
57. Umer A, Abdella K, Tekle Y, Debebe A, Manyazewal T, Yuya M, et al. Community Engagement in the Fight Against COVID-19: Knowledge, Attitude, and Prevention Practices Among Dire Dawa Residents, Eastern Ethiopia. Front Public Health 2021;9:753867.
58. Ren Q, Wang Y, Zheng Q, Ye L, Zhou XD, Zhang LL. Survey of student attitudes towards digital simulation technologies at a dental school in China. Eur J Dent Educ 2017;21(3):180–6.
59. Andreasen JO, Bakland LK, Flores MT, Andreasen FM, Andersson L. Traumatic Dental Injuries: A Manual. John Wiley & Sons; 2011.
60. Lucivero F, Prainsack B. The lifestylisation of healthcare? “Consumer genomics” and mobile health as technologies for healthy lifestyle. Appl Transl Genom 2015;4:44–9.
61. Mort M, Smith A. Beyond Information: Intimate Relations in Sociotechnical Practice. Sociology 2009;43(2):215–31.
62. Lupton D. Apps as Artefacts: Towards a Critical Perspective on Mobile Health and Medical Apps. Societies 2014;4(4):606–22.
63. Nicolini D. Practice Theory, Work, and Organization: An Introduction. OUP Oxford; 2013.
64. Leong T. Proceedings of the 26th Australian Computer-Human Interaction Conference on Designing Futures: The Future of Design. Association for Computing Machinery; 2014.
65. Duan Y, Luo J, Zhao L, Zhang X, Miao J, Moher D, et al. Reporting and data sharing level for COVID-19 vaccine trials: A cross-sectional study. EBioMedicine 2022;78:103962.
66. Chirico F, Teixeira da Silva JA. COVID-19 Health Policies: The Need for Transparent Data Sharing Between Scientists, Governments, and Policymakers. Oman Med J 2022;37(5):e418.
67. Cummins N, Schuller BW. Five Crucial Challenges in Digital Health. Front Digit Health 2020;2:536203.
68. Getachew E, Woldeamanuel Y, Manyazewal T. Capacity and Readiness Assessment of Healthcare Facilities for Digital Health Interventions Against Tuberculosis and HIV in Addis Ababa, Ethiopia. Front Digit Health 2022;4:821390.
69. Manyazewal T, Woldeamanuel Y, Blumberg HM, Fekadu A, Marconi VC. The fight to end tuberculosis must not be forgotten in the COVID-19 outbreak. Nat Med 2020;26(6):811–2.
70. Manyazewal T, Woldeamanuel Y, Fekadu A, Holland DP, Marconi VC. Effect of Digital Medication Event Reminder and Monitor-Observed Therapy vs Standard Directly Observed Therapy on Health-Related Quality of Life and Catastrophic Costs in Patients With Tuberculosis: A Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open 2022;5(9):e2230509.
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2. Getachew E, Adebeta T, Muzazu SGY, Charlie L, Said B, Tesfahunei HA, et al. Digital health in the era of COVID-19: Reshaping the next generation of healthcare. Front Public Health 2023;11:942703.
3. Sun T, He X, Song X, Shu L, Li Z. The Digital Twin in Medicine: A Key to the Future of Healthcare? Frontiers in Medicine [Internet] 2022;9. Available from: https://www.frontiersin.org/articles/10.3389/fmed.2022.907066
4. Budd J, Miller BS, Manning EM, Lampos V, Zhuang M, Edelstein M, et al. Digital technologies in the public-health response to COVID-19. Nat Med 2020;26(8):1183–92.
5. Neville P, van der Zande MM. Dentistry, e-health and digitalisation: A critical narrative review of the dental literature on digital technologies with insights from health and technology studies. Community Dent Health 2020;37(1):51–8.
6. Tay KIP, Wu JMY, Yew MSS, Thomson WM. The use of newer technologies by New Zealand dentists. N Z Dent J 2008;104(3):104–8.
7. Jain P, Gupta M. Digitization in Dentistry: Clinical Applications. Springer Nature; 2021.
8. Vandenberghe B. The digital patient - Imaging science in dentistry. J Dent 2018;74 Suppl 1:S21–6.
9. Watt T, Sullivan R, Aggarwal A. Primary care and cancer: an analysis of the impact and inequalities of the COVID-19 pandemic on patient pathways. BMJ Open 2022;12(3):e059374.
10. McKinlay AR, Fancourt D, Burton A. A qualitative study about the mental health and wellbeing of older adults in the UK during the COVID-19 pandemic. BMC Geriatr 2021;21(1):439.
11. Wright FL, Cheema K, Goldacre R, Hall N, Herz N, Islam N, et al. Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries. Eur Heart J Qual Care Clin Outcomes 2023;9(4):377–88.
12. Girman CJ, Ritchey ME. Pragmatic Randomized Clinical Trials: Using Primary Data Collection and Electronic Health Records. Academic Press; 2021.
13. Nakamura N, Koga T, Iseki H. A meta-analysis of remote patient monitoring for chronic heart failure patients. J Telemed Telecare 2014;20(1):11–7.
14. World Health Organization. Global Diffusion of EHealth: Making Universal Health Coverage Achievable: Report of the Third Global Survey on EHealth. World Health Organization; 2017.
15. Gurbeta L, Badnjevic A, Maksimovic M, Omanovic-Miklicanin E, Sejdic E. A telehealth system for automated diagnosis of asthma and chronical obstructive pulmonary disease. J Am Med Inform Assoc 2018;25(9):1213–7.
16. Malmgren Fänge A, Carlsson G, Chiatti C, Lethin C. Using sensor-based technology for safety and independence - the experiences of people with dementia and their families. Scand J Caring Sci 2020;34(3):648–57.
17. Asthana S, Jones R, Sheaff R. Why does the NHS struggle to adopt eHealth innovations? A review of macro, meso and micro factors. BMC Health Serv Res 2019;19(1):984.
18. Robertson R, Wenzel L, analyst) JT (data, Charles A. Understanding NHS Financial Pressures: How are They Affecting Patient Care? King’s Fund; 2017.
19. Milligan LO, Tikly L. English as a Medium of Instruction in Postcolonial Contexts: Issues of Quality, Equity and Social Justice. Routledge; 2018.
20. Manickam P, Mariappan SA, Murugesan SM, Hansda S, Kaushik A, Shinde R, et al. Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare. Biosensors [Internet] 2022;12(8). Available from: http://dx.doi.org/10.3390/bios12080562
21. Rapanyane MB, Sethole FR. The rise of artificial intelligence and robots in the 4th Industrial Revolution: implications for future South African job creation. Contemporary Social Science 2020;15(4):489–501.
22. Kelly JT, Collins PF, McCamley J, Ball L, Roberts S, Campbell KL. Digital disruption of dietetics: are we ready? J Hum Nutr Diet 2021;34(1):134–46.
23. Joda T, Yeung AWK, Hung K, Zitzmann NU, Bornstein MM. Disruptive Innovation in Dentistry: What It Is and What Could Be Next. J Dent Res 2021;100(5):448–53.
24. Ahmad P, Alam MK, Aldajani A, Alahmari A, Alanazi A, Stoddart M, et al. Dental Robotics: A Disruptive Technology. Sensors [Internet] 2021;21(10). Available from: http://dx.doi.org/10.3390/s21103308
25. McBee MP, Wilcox C. Blockchain Technology: Principles and Applications in Medical Imaging. J Digit Imaging 2020;33(3):726–34.
26. Wirries A, Geiger F, Oberkircher L, Jabari S. An Evolution Gaining Momentum—The Growing Role of Artificial Intelligence in the Diagnosis and Treatment of Spinal Diseases. Diagnostics 2022;12(4):836.
27. Maliha G, Gerke S, Cohen IG, Parikh RB. Balancing Safety and Innovation. Milbank Q 2021;99(3):629–47.
28. Jabarulla MY, Lee HN. A Blockchain and Artificial Intelligence-Based, Patient-Centric Healthcare System for Combating the COVID-19 Pandemic: Opportunities and Applications. Healthcare (Basel) [Internet] 2021;9(8). Available from: http://dx.doi.org/10.3390/healthcare9081019
29. Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, et al. Explainable AI for Healthcare 5.0: Opportunities and Challenges. IEEE Access 2022;10:84486–517.
30. Mohanty K, Subiksha S, Kirthika S, Sujal BH, Sokkanarayanan S, Bose P, et al. Opportunities of Adopting AI-Powered Robotics to Tackle COVID-19. In: 2021 International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE; 2021. page 703–8.
31. Brunelle F, Brunelle P. Artificial intelligence and medical imaging: Definition, state of the art and perspectives. [Bulletin Inst hist du temps présent]
32. Khatab Z, Yousef GM. Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics. Crit Rev Clin Lab Sci 2021;58(8):546–62.
33. Ljepava N. AI-Enabled Marketing Solutions in Marketing Decision Making: AI Application in Different Stages of Marketing Process. TEM Journal 2022;11(3):1308–15.
34. Burden K. Impact of disruptive technologies on sourcing and outsourcing transactions. Computer Law & Security Review 2018;34(4):886–9.
35. Garbuio M, Lin N. Artificial Intelligence as a Growth Engine for Health Care Startups: Emerging Business Models. Calif Manage Rev 2019;61(2):59–83.
36. Mesko B. Future Directions of Digital Health. In: Rivas H, Wac K, editors. Digital Health: Scaling Healthcare to the World. Cham: Springer International Publishing; 2018. page 339–63.
37. Mesko B. The role of artificial intelligence in precision medicine. Expert Review of Precision Medicine and Drug Development 2017;2(5):239–41.
38. Meskó B, Hetényi G, Győrffy Z. Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res 2018;18(1):545.
39. Michel AN, Hou L, Liu D. Stability of Dynamical Systems: On the Role of Monotonic and Non-Monotonic Lyapunov Functions. Springer; 2015.
40. Khatri S, Pandey DK, Penkar D, Ramani J. Impact of Artificial Intelligence on Human Resources. In: Data Management, Analytics and Innovation. Springer Singapore; 2020. page 365–76.
41. Prakash S, Balaji JN, Joshi A, Surapaneni KM. Ethical Conundrums in the Application of Artificial Intelligence (AI) in Healthcare-A Scoping Review of Reviews. J Pers Med [Internet] 2022;12(11). Available from: http://dx.doi.org/10.3390/jpm12111914
42. Păvăloaia VD, Necula SC. Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review. Electronics 2023;12(5):1102.
43. Morales-Narvaez E, Dincer C. Wearable Physical, Chemical and Biological Sensors: Fundamentals, Materials and Applications. Elsevier; 2022.
44. Pan L, Chortos A, Yu G, Wang Y, Isaacson S, Allen R, et al. An ultra-sensitive resistive pressure sensor based on hollow-sphere microstructure induced elasticity in conducting polymer film. Nat Commun 2014;5:3002.
45. Pang C, Lee GY, Kim TI, Kim SM, Kim HN, Ahn SH, et al. A flexible and highly sensitive strain-gauge sensor using reversible interlocking of nanofibres. Nat Mater 2012;11(9):795–801.
46. Siddiqui SA, Zhang Y, Lloret J, Song H, Obradovic Z. Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent Advancements and Future Prospects. IEEE Rev Biomed Eng 2018;11:21–35.
47. Lee MY, Lee HR, Park CH, Han SG, Oh JH. Organic Transistor-Based Chemical Sensors for Wearable Bioelectronics. Acc Chem Res 2018;51(11):2829–38.
48. Saha T, Del Caño R, Mahato K, De la Paz E, Chen C, Ding S, et al. Wearable Electrochemical Glucose Sensors in Diabetes Management: A Comprehensive Review. Chem Rev 2023;123(12):7854–89.
49. Koh A, Kang D, Xue Y, Lee S, Pielak RM, Kim J, et al. A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat. Sci Transl Med 2016;8(366):366ra165.
50. Ren H, Sun J. Electromagnetic Actuation and Sensing in Medical Robotics. Springer; 2017.
51. Igarashi T, Nishino K, Nayar SK. The Appearance of Human Skin: A Survey. Now Publishers Inc; 2007.
52. Webb RC, Bonifas AP, Behnaz A, Zhang Y, Yu KJ, Cheng H, et al. Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nat Mater 2013;12(10):938–44.
53. Giansanti D. Advancing Dermatological Care: A Comprehensive Narrative Review of Tele-Dermatology and mHealth for Bridging Gaps and Expanding Opportunities beyond the COVID-19 Pandemic. Healthcare (Basel) [Internet] 2023;11(13). Available from: http://dx.doi.org/10.3390/healthcare11131911
54. Luo S, Zhang X. High-quality 3D printing of ethylene vinyl acetate with direct pellet-based FDM for medical applications: Mechanical analysis, energy absorption and recovery evaluation. J Mech Behav Biomed Mater 2023;148:106231.
55. Rybicki FJ, Grant GT. 3D Printing in Medicine: A Practical Guide for Medical Professionals. Springer; 2017.
56. Wang C, Shi YF, Xie PJ, Wu JH. Accuracy of digital complete dentures: A systematic review of in vitro studies. J Prosthet Dent 2021;125(2):249–56.
57. Umer A, Abdella K, Tekle Y, Debebe A, Manyazewal T, Yuya M, et al. Community Engagement in the Fight Against COVID-19: Knowledge, Attitude, and Prevention Practices Among Dire Dawa Residents, Eastern Ethiopia. Front Public Health 2021;9:753867.
58. Ren Q, Wang Y, Zheng Q, Ye L, Zhou XD, Zhang LL. Survey of student attitudes towards digital simulation technologies at a dental school in China. Eur J Dent Educ 2017;21(3):180–6.
59. Andreasen JO, Bakland LK, Flores MT, Andreasen FM, Andersson L. Traumatic Dental Injuries: A Manual. John Wiley & Sons; 2011.
60. Lucivero F, Prainsack B. The lifestylisation of healthcare? “Consumer genomics” and mobile health as technologies for healthy lifestyle. Appl Transl Genom 2015;4:44–9.
61. Mort M, Smith A. Beyond Information: Intimate Relations in Sociotechnical Practice. Sociology 2009;43(2):215–31.
62. Lupton D. Apps as Artefacts: Towards a Critical Perspective on Mobile Health and Medical Apps. Societies 2014;4(4):606–22.
63. Nicolini D. Practice Theory, Work, and Organization: An Introduction. OUP Oxford; 2013.
64. Leong T. Proceedings of the 26th Australian Computer-Human Interaction Conference on Designing Futures: The Future of Design. Association for Computing Machinery; 2014.
65. Duan Y, Luo J, Zhao L, Zhang X, Miao J, Moher D, et al. Reporting and data sharing level for COVID-19 vaccine trials: A cross-sectional study. EBioMedicine 2022;78:103962.
66. Chirico F, Teixeira da Silva JA. COVID-19 Health Policies: The Need for Transparent Data Sharing Between Scientists, Governments, and Policymakers. Oman Med J 2022;37(5):e418.
67. Cummins N, Schuller BW. Five Crucial Challenges in Digital Health. Front Digit Health 2020;2:536203.
68. Getachew E, Woldeamanuel Y, Manyazewal T. Capacity and Readiness Assessment of Healthcare Facilities for Digital Health Interventions Against Tuberculosis and HIV in Addis Ababa, Ethiopia. Front Digit Health 2022;4:821390.
69. Manyazewal T, Woldeamanuel Y, Blumberg HM, Fekadu A, Marconi VC. The fight to end tuberculosis must not be forgotten in the COVID-19 outbreak. Nat Med 2020;26(6):811–2.
70. Manyazewal T, Woldeamanuel Y, Fekadu A, Holland DP, Marconi VC. Effect of Digital Medication Event Reminder and Monitor-Observed Therapy vs Standard Directly Observed Therapy on Health-Related Quality of Life and Catastrophic Costs in Patients With Tuberculosis: A Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open 2022;5(9):e2230509.
71. Manyazewal T, Woldeamanuel Y, Getinet T, Hoover A, Bobosha K, Fuad O, et al. Patient-reported usability and satisfaction with electronic medication event reminder and monitor device for tuberculosis: a multicentre, randomised controlled trial. EClinicalMedicine 2023;56:101820.
72. Marzo RR, Su TT, Ismail R, Htay MNN, Essar MY, Chauhan S, et al. Digital health literacy for COVID-19 vaccination and intention to be immunized: A cross sectional multi-country study among the general adult population. Front Public Health 2022;10:998234.
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| Files | ||
| Issue | Vol 8 No 4 (2024) | |
| Section | Review Article | |
| DOI | https://doi.org/10.18502/htaa.v8i4.16987 | |
| Keywords | ||
| Digital Disruption Telemedicine COVID-19 Digital health. | ||
| Rights and permissions | |
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Kanade D, Kale S, Reddy M, Mathur A. A Narrative Review on the Conceptual and Methodological Advancements in Digital Disruption: A Way to Improved Quality of Services in Health Care. Health Tech Ass Act. 2024;8(4).
