Hiệu quả của y tế số trong tiến trình chấm dứt bệnh lao: Một nghiên cứu tổng quan
Nội dung chính của bài viết
Tóm tắt
Nghiên cứu hiệu quả của y tế số trong tiến trình chấm dứt bệnh lao, áp dụng thiết kế nghiên cứu tổng quan, sử dụng cơ sở dữ liệu Pubmed từ 1/2016 đến 7/2021. Nội dung tìm kiếm tập trung vào ba phần chính: bệnh lao, y tế số, và hiệu quả. Kết quả cho thấy 20 bài báo được lựa chọn vào phân tích. Các ứng dụng chủ yếu của y tế số bao gồm tin nhắn SMS (35%), quan sát trực tiếp qua video-VDOT (25%), hỗ trợ X-quang tự động (10%). Về hiệu quả của ứng dụng, 90% nghiên cứu cho thấy y tế số có hiệu quả trong các mục tiêu tăng tỷ lệ tuân thủ, điều trị thành công, quản lý dữ liệu, hỗ trợ chẩn đoán với độ nhạy-độ đặc hiệu chấp nhận được cùng giá thành thấp, chi phí hiệu quả. Tuy nhiên, một số nghiên cứu cho thấy tin nhắn SMS không có hiệu quả hỗ trợ tuân thủ điều trị (10%). Phần lớn nghiên cứu cho thấy kết quả tích cực trong quản lý và điều trị lao. Tuy nhiên, vẫn còn có sự không nhất quán trong một số ứng dụng, đặc biệt với tin nhắn SMS.
Chi tiết bài viết
Từ khóa
Y tế số, can thiệp y tế số, bệnh lao, hiệu quả, chi phí hiệu quả
Tài liệu tham khảo
1. Bahrainwala Lulua, Knoblauch Astrid M, et al Andriamiadanarivo Andry. Drones and digital adherence monitoring for community-based tuberculosis control in remote Madagascar: A cost-effectiveness analysis. PLoS One. 2020; 15(7): e0235572.
2. World Health Organization. Global Tuberculosis Report 2020. Geneva: World Health Organization, 2020.
3. Johnston James C, van der Kop Mia L, Smillie Kirsten et al. The effect of text messaging on latent tuberculosis treatment adherence: a randomised controlled trial. Eur Respir J. 2018; 51(2).
4. Fang Xue-Hui, Guan Shi-Yang, Tang Li et al. Effect of Short Message Service on Management of Pulmonary Tuberculosis Patients in Anhui Province, China: A Prospective, Randomized, Controlled Study. Med Sci Monit. 2017; 23:2465-2469.
5. World Health Organization. Classification of digital health interventions. Geneva: World Health Organization, 2018.
6. Moher David, Shamseer Larissa, Clarke Mike et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews. 2015; 4(1):1.
7. Falagas M E, Pitsouni E I, Malietzis G A et al. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 2008; 22(2): 338-342.
8. Alqahtani Sami, Kashkary Abdulhameed, Asiri Abdullah et al. Impact of mobile teams on tuberculosis treatment outcomes, Riyadh Region, Kingdom of Saudi Arabia, 2013-2015. J Epidemiol Glob Health. 2018; 7 Suppl 1(Suppl 1): S29-S33.
9. Beeler Asay Garrett R, Lam Chee Kin, Stewart Brock et al. Cost of Tuberculosis Therapy Directly Observed on Video for Health Departments and Patients in New York City; San Francisco, California; and Rhode Island (2017-2018). Am J Public Health. 2020; 110(11): 1696-1703.
10. Bionghi N, Daftary A, Maharaj B et al. Pilot evaluation of a second-generation electronic pill box for adherence to Bedaquiline and antiretroviral therapy in drug-resistant TB/HIV co-infected patients in KwaZulu-Natal, South Africa. BMC Infect Dis. 2018; 18(1): 171.
11. Chaintarli K, Jackson S, Cotter S et al. Evaluation and comparison of the National Tuberculosis (TB) Surveillance System in Ireland before and after the introduction of the Computerised Electronic Reporting System (CIDR). Epidemiol Infect. 2018; 146(14): 1756-1762.
12. Datta Bornali, Prakash Ashish Kumar, Ford David et al. Comparison of clinical and cost-effectiveness of two strategies using mobile digital x-ray to detect pulmonary tuberculosis in rural India. BMC Public Health. 2019; 19(1): 99.
13. Garfein R S, Liu L, Cuevas-Mota J et al. Evaluation of recorded video-observed therapy for anti-tuberculosis treatment. Int J Tuberc Lung Dis. 2020; 24(5): 520-525.
14. Ha Yoonhee P, Tesfalul Martha A, et al Littman-Quinn Ryan. Evaluation of a Mobile Health Approach to Tuberculosis Contact Tracing in Botswana. J Health Commun. 2016; 21(10): 1115-1121.
15. Jha Swati, Ismail Nazir, Clark David et al. Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis. PLoS One. 2016; 11(6): e0157554.
16. Kumboyono. Short message service as an alternative in the drug consumption evaluation of persons with tuberculosis in Malang, Indonesia. Jpn J Nurs Sci. 2017; 14(2): 112-116.
17. Lam C K, Fluegge K, et al Macaraig M. Cost savings associated with video directly observed therapy for treatment of tuberculosis. Int J Tuberc Lung Dis. 2019; 23(11): 1149-1154.
18. Meyer Amanda J, Babirye Diana, et al Armstrong-Hough Mari. Text Messages Sent to Household Tuberculosis Contacts in Kampala, Uganda: Process Evaluation. JMIR Mhealth Uhealth. 2018; 6(11): e10239.
19. Mohammed Shama, Glennerster Rachel, Khan Aamir J. Impact of a Daily SMS Medication Reminder System on Tuberculosis Treatment Outcomes: A Randomized Controlled Trial. PLoS One. 2016; 11(11): e0162944.
20. Nsengiyumva Ntwali Placide, Mappin-Kasirer Benjamin, Oxlade Olivia et al. Evaluating the potential costs and impact of digital health technologies for tuberculosis treatment support. Eur Respir J. 2018; 52(5).
21. Rahman Md Toufiq, Codlin Andrew J, et al Rahman Md Mahfuzur. An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients. Eur Respir J. 2017; 49(5).
22. Santra Sahadev, Garg Suneela, Basu Saurav et al. The effect of a mhealth intervention on anti-tuberculosis medication adherence in Delhi, India: A quasi-experimental study. Indian J Public Health. 2021; 65(1): 34-38.
23. Thomas Beena E, Kumar J Vignesh, Chiranjeevi M et al. Evaluation of the Accuracy of 99DOTS, a Novel Cellphone-based Strategy for Monitoring Adherence to Tuberculosis Medications: Comparison of DigitalAdherence Data With Urine Isoniazid Testing. Clin Infect Dis. 2020; 71(9): e513-e516.
24. Wang Ni, Guo Lei, Shewade Hemant Deepak et al. Effect of using electronic medication monitors on tuberculosis treatment outcomes in China: a longitudinal ecological study. Infect Dis Poverty. 2021; 10(1): 29.
25. World Health Organization & European Respiratory Society. Digital health for the end TB strategy: an agenda for action. Geneva: World Health Organization, 2015.
2. World Health Organization. Global Tuberculosis Report 2020. Geneva: World Health Organization, 2020.
3. Johnston James C, van der Kop Mia L, Smillie Kirsten et al. The effect of text messaging on latent tuberculosis treatment adherence: a randomised controlled trial. Eur Respir J. 2018; 51(2).
4. Fang Xue-Hui, Guan Shi-Yang, Tang Li et al. Effect of Short Message Service on Management of Pulmonary Tuberculosis Patients in Anhui Province, China: A Prospective, Randomized, Controlled Study. Med Sci Monit. 2017; 23:2465-2469.
5. World Health Organization. Classification of digital health interventions. Geneva: World Health Organization, 2018.
6. Moher David, Shamseer Larissa, Clarke Mike et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews. 2015; 4(1):1.
7. Falagas M E, Pitsouni E I, Malietzis G A et al. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 2008; 22(2): 338-342.
8. Alqahtani Sami, Kashkary Abdulhameed, Asiri Abdullah et al. Impact of mobile teams on tuberculosis treatment outcomes, Riyadh Region, Kingdom of Saudi Arabia, 2013-2015. J Epidemiol Glob Health. 2018; 7 Suppl 1(Suppl 1): S29-S33.
9. Beeler Asay Garrett R, Lam Chee Kin, Stewart Brock et al. Cost of Tuberculosis Therapy Directly Observed on Video for Health Departments and Patients in New York City; San Francisco, California; and Rhode Island (2017-2018). Am J Public Health. 2020; 110(11): 1696-1703.
10. Bionghi N, Daftary A, Maharaj B et al. Pilot evaluation of a second-generation electronic pill box for adherence to Bedaquiline and antiretroviral therapy in drug-resistant TB/HIV co-infected patients in KwaZulu-Natal, South Africa. BMC Infect Dis. 2018; 18(1): 171.
11. Chaintarli K, Jackson S, Cotter S et al. Evaluation and comparison of the National Tuberculosis (TB) Surveillance System in Ireland before and after the introduction of the Computerised Electronic Reporting System (CIDR). Epidemiol Infect. 2018; 146(14): 1756-1762.
12. Datta Bornali, Prakash Ashish Kumar, Ford David et al. Comparison of clinical and cost-effectiveness of two strategies using mobile digital x-ray to detect pulmonary tuberculosis in rural India. BMC Public Health. 2019; 19(1): 99.
13. Garfein R S, Liu L, Cuevas-Mota J et al. Evaluation of recorded video-observed therapy for anti-tuberculosis treatment. Int J Tuberc Lung Dis. 2020; 24(5): 520-525.
14. Ha Yoonhee P, Tesfalul Martha A, et al Littman-Quinn Ryan. Evaluation of a Mobile Health Approach to Tuberculosis Contact Tracing in Botswana. J Health Commun. 2016; 21(10): 1115-1121.
15. Jha Swati, Ismail Nazir, Clark David et al. Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis. PLoS One. 2016; 11(6): e0157554.
16. Kumboyono. Short message service as an alternative in the drug consumption evaluation of persons with tuberculosis in Malang, Indonesia. Jpn J Nurs Sci. 2017; 14(2): 112-116.
17. Lam C K, Fluegge K, et al Macaraig M. Cost savings associated with video directly observed therapy for treatment of tuberculosis. Int J Tuberc Lung Dis. 2019; 23(11): 1149-1154.
18. Meyer Amanda J, Babirye Diana, et al Armstrong-Hough Mari. Text Messages Sent to Household Tuberculosis Contacts in Kampala, Uganda: Process Evaluation. JMIR Mhealth Uhealth. 2018; 6(11): e10239.
19. Mohammed Shama, Glennerster Rachel, Khan Aamir J. Impact of a Daily SMS Medication Reminder System on Tuberculosis Treatment Outcomes: A Randomized Controlled Trial. PLoS One. 2016; 11(11): e0162944.
20. Nsengiyumva Ntwali Placide, Mappin-Kasirer Benjamin, Oxlade Olivia et al. Evaluating the potential costs and impact of digital health technologies for tuberculosis treatment support. Eur Respir J. 2018; 52(5).
21. Rahman Md Toufiq, Codlin Andrew J, et al Rahman Md Mahfuzur. An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients. Eur Respir J. 2017; 49(5).
22. Santra Sahadev, Garg Suneela, Basu Saurav et al. The effect of a mhealth intervention on anti-tuberculosis medication adherence in Delhi, India: A quasi-experimental study. Indian J Public Health. 2021; 65(1): 34-38.
23. Thomas Beena E, Kumar J Vignesh, Chiranjeevi M et al. Evaluation of the Accuracy of 99DOTS, a Novel Cellphone-based Strategy for Monitoring Adherence to Tuberculosis Medications: Comparison of DigitalAdherence Data With Urine Isoniazid Testing. Clin Infect Dis. 2020; 71(9): e513-e516.
24. Wang Ni, Guo Lei, Shewade Hemant Deepak et al. Effect of using electronic medication monitors on tuberculosis treatment outcomes in China: a longitudinal ecological study. Infect Dis Poverty. 2021; 10(1): 29.
25. World Health Organization & European Respiratory Society. Digital health for the end TB strategy: an agenda for action. Geneva: World Health Organization, 2015.