From Paper to Digital: Performance and Challenges of the Electronic Hepatitis B Surveillance System in Ninh Binh, Northern Vietnam (2017–2022)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Setting
2.3. Case Definition
- Immunoglobulin M antibody to hepatitis B core antigen (anti-HBc IgM)-positive;
- Hepatitis B surface antigen (HBsAg)-positive (or -negative in the window period).
- HbsAg-positive for more than 6 months, or HBsAg-positive and anti-HBc IgM-positive;
- There is evidence of progressive histopathological damage or cirrhosis without other causes.
2.4. Data Collection
2.5. Definitions of System Attributes
2.5.1. Simplicity
2.5.2. Timeliness
2.5.3. Data Quality
2.5.4. Acceptability
2.6. Data Analysis
3. Results
3.1. Epidemiology of Hepatitis B in Ninh Binh Province, 2017–2022
“To detect hepatitis B cases early in the community, our hospital launched a screening program in 2016. In 2018–2019, we increased screening activities in various communes, conducting them twice a month. From these efforts, we identified several suspected hepatitis B cases and referred them to our hospital for further diagnosis and treatment. After learning about the hepatitis B management program at the provincial hospital, patients registered immediately, as it saves considerable travel and treatment costs compared to going to central-level hospitals. In 2020–2021, due to the COVID-19 pandemic, we were unable to conduct community screenings, and patients rarely visited the hospital due to travel restrictions. As a result, the number of new hepatitis B cases reported to the eCDS decreased. Since 2022, we have been working to resume community screenings. This is the main reason the number of reported hepatitis B cases in 2019 was exceptionally high compared to other years”.(Interviewee 1)
3.2. Objectives of the Surveillance System
3.3. Simplicity
“Only the first patient visit should be reported to the surveillance system, not their follow-up visits. As nurses, we have various responsibilities, such as preparing health records and assisting doctors and patients, so we do not have much time for reporting. Every year, we manage about 4000 cases of hepatitis B, with many outpatients visiting our clinics monthly. Unlike other health conditions, hepatitis B is a special case, requiring us to prepare and store the medical records of all outpatients coming to our hospital”.(Interviewee 2)
3.4. Timeliness
“Almost all hepatitis B cases with positive diagnoses are reported the same day. In our department, all staff agree and follow the practice of reporting infectious disease cases to eCDS in the late afternoon each day”.(Interviewee 1)
“In the early stage of working with eCDS, system occurred quite frequently, which prevented us from updating hepatitis B cases in the software, leading to some cases being reported late. Recently, the system has been running more smoothly”.(Interviewee 2)
“During the peak of the COVID-19 pandemic, we were working hard to combat this disease, so we did not have time to report other cases to eCDS promptly”.(Interviewee 2)
3.5. Data Quality
3.5.1. Variables in the Reporting System
3.5.2. Data Consistency
“For hepatitis B, we only reported cases that had positive HBsAg test results provided by our laboratory or another hospital at central level” .(Interviewee 1)
3.5.3. Data Completeness
“Most patients did not know how they contracted HBV, so we had no data to report in the “Epidemiological history” field”.(Interviewee 2)
3.6. Acceptability
“Our previous reporting system for hepatitis B was paper-based. At that time, the Department of General Planning was responsible for aggregating data on all notifiable diseases managed by this hospital and submitting reports to the provincial CDC and Department of Health on a monthly, quarterly, and annually basis. Now, the Department of Communicable Disease oversees reporting case information through the new computer-based system, so we no longer need to prepare regular reports. We only enter case data once, and other health authorities at different levels can directly access this information via eCDS”.(Interviewee 3)
“With the old surveillance system, we only reported the number of infections and deaths. The new electronic reporting system provides more detailed data on each case. If we need patient information, we can simply look it up on eCDS—it is much faster and more convenient than the paper-based system. It also reduces data duplication, as the system warns us if we enter the same information from previously reported cases. This software generally helps both preventive and clinical units access data more quickly and easily”.(Interviewee 2)
“To optimize the design of a surveillance system, its objectives should be clearly communicated to all stakeholders. This way, everyone can understand the importance of this system and work towards providing the most accurate and timely data to eCDS. Currently, the objectives of this system are unclear to us, so we are unable to offer recommendations for its design and operation”.(Interviewee 1)
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Number of Patients (n = 5066) | Percentage (%) |
---|---|---|
Age (Median, IQR) | 46 (34–58) | |
Age group | ||
<18 | 28 | 0.6% |
18–29 | 733 | 14.5% |
30–39 | 1138 | 22.5% |
40–49 | 1035 | 20.4% |
50–59 | 1024 | 20.2% |
≥60 | 1108 | 21.9% |
Sex | ||
Male | 3050 | 60.2% |
Female | 2016 | 39.8% |
Occupation | ||
Farmer | 2586 | 51% |
Blue-collar worker | 645 | 12.7% |
Retiree | 498 | 9.8% |
White-collar worker | 407 | 8% |
Student | 93 | 1.8% |
Armed forces | 59 | 1.2% |
Other | 778 | 15.4% |
Vaccination status | ||
Unvaccinated | 3445 | 68% |
Unknown | 1621 | 32% |
Reporting unit | ||
Ninh Binh PGH | 4908 | 96.9% |
Others | 158 | 3.1% |
Variables | 2017 n (%) | 2018 n (%) | 2019 n (%) | 2020 n (%) | 2021 n (%) | 2022 n (%) | Total n (%) |
---|---|---|---|---|---|---|---|
Diagnostic classification | |||||||
Laboratory-confirmed | 871 (99.7%) | 884 (98.4%) | 2573 (99.7%) | 268 (75.3%) | 279 (79%) | 2 (40%) | 4877 (96.3%) |
Suspected | 2 (0.2%) | 10 (1.1%) | 4 (0.2%) | 87 (24.4%) | 73 (20.7%) | 3 (60%) | 179 (3.5%) |
Clinical | 1 (0.1%%) | 4 (0.5%) | 3 (0.1%) | 1 (0.3%) | 1 (0.3%) | 0 | 10 (0.2%) |
Testing results | |||||||
Positive | 862 (98.6%) | 810 (90.2%) | 2356 (91.3%) | 319 (89.6%) | 293 (83%) | 4 (80%) | 4644 (91.7%) |
Negative | 0 | 1 (0.1%) | 0 | 0 | 1 (0.3%) | 0 | 2 (0%) |
Result pending | 11 (1.3%) | 87 (9.7%) | 223 (8.6%) | 15 (4.2%) | 35 (9.9%) | 1 (20%) | 372 (7.3%) |
No test | 1 (0.1%) | 0 | 1 (0%) | 22 (6.2%) | 24 (6.8%) | 0 | 48 (1%) |
Type of test | |||||||
Rapid test | 846 (96.8%) | 865 (96.3%) | 2566 (99.5%) | 309 (86.8%) | 239 (67.7%) | 4 (80%) | 4829 (95.3%) |
Mac-Elisa | 19 (2.2%) | 31 (3.5%) | 8 (0.3%) | 18 (5.1%) | 67 (19%) | 1 (20%) | 144 (2.8%) |
PCR | 6 (0.7%) | 0 | 4 (0.2%) | 1 (0.3%) | 2 (0.6%) | 0 | 13 (0.3%) |
HbsAg | 1 (0.1%) | 0 | 1 (0%) | 2 (0.6%) | 1 (0.3%) | 0 | 5 (0.1%) |
HBV DNA | 0 | 2 (0.2%) | 0 | 1 (0.3%) | 0 | 0 | 3 (0.1%) |
Blood count | 1 (0.1%) | 0 | 0 | 0 | 0 | 0 | 1 (0%) |
Unknown | 0 | 0 | 0 | 3 (0.8%) | 20 (5.7%) | 0 | 23 (0.5%) |
No test | 1 (0.1%) | 0 | 1 (0%) | 22 (6.2%) | 24 (6.8%) | 0 | 48 (1%) |
Variable | 2017 n (%) | 2018 n (%) | 2019 n (%) | 2020 n (%) | 2021 n (%) | 2022 n (%) | Total n (%) |
---|---|---|---|---|---|---|---|
Vaccination status | 642 (73.5%) | 517 (57.6%) | 1625 (63%) | 304 (85.4%) | 352 (99.8%) | 5 (100%) | 3445 (68%) |
Date of onset | 412 (47.1%) | 300 (33.4%) | 806 (31.2%) | 336 (94.4%) | 346 (98%) | 4 (80%) | 2204 (43.5%) |
Epidemiological history | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Date of sampling | 856 (98.1%) | 880 (98%) | 2552 (99%) | 333 (99.7%) | 329 (100%) | 5 (100%) | 4955 (98.7%) |
Date of testing result | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Current situation (treatment results for inpatient) | 66 (84.6%) | 119 (86.2%) | 192 (86.9%) | 28 (20.9%) | 0 | 0 | 405 (63.5%) |
Date of hospital discharge/referral/death (among inpatients) | 65 (83.3%) | 117 (84.8%) | 188 (85.1%) | 88 (65.7%) | 34 (51.5%) | 0 | 492 (77.1%) |
Characteristics | Previous Paper-Based System | eCDS |
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Format |
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Responsible department |
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Frequency |
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Reporting data |
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Accessibility |
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Nguyen, H.T.; Pham, T.Q.; Hoang, D.M.; Tran, Q.D.; Chu, G.T.; Nguyen, T.T.; Le, N.H.; Nguyen, H.T.; Nguyen, K.C.; Vogt, F. From Paper to Digital: Performance and Challenges of the Electronic Hepatitis B Surveillance System in Ninh Binh, Northern Vietnam (2017–2022). Trop. Med. Infect. Dis. 2024, 9, 299. https://doi.org/10.3390/tropicalmed9120299
Nguyen HT, Pham TQ, Hoang DM, Tran QD, Chu GT, Nguyen TT, Le NH, Nguyen HT, Nguyen KC, Vogt F. From Paper to Digital: Performance and Challenges of the Electronic Hepatitis B Surveillance System in Ninh Binh, Northern Vietnam (2017–2022). Tropical Medicine and Infectious Disease. 2024; 9(12):299. https://doi.org/10.3390/tropicalmed9120299
Chicago/Turabian StyleNguyen, Hien T., Thai Q. Pham, Duc M. Hoang, Quang D. Tran, Giang T. Chu, Thuong T. Nguyen, Nam H. Le, Huyen T. Nguyen, Khanh C. Nguyen, and Florian Vogt. 2024. "From Paper to Digital: Performance and Challenges of the Electronic Hepatitis B Surveillance System in Ninh Binh, Northern Vietnam (2017–2022)" Tropical Medicine and Infectious Disease 9, no. 12: 299. https://doi.org/10.3390/tropicalmed9120299
APA StyleNguyen, H. T., Pham, T. Q., Hoang, D. M., Tran, Q. D., Chu, G. T., Nguyen, T. T., Le, N. H., Nguyen, H. T., Nguyen, K. C., & Vogt, F. (2024). From Paper to Digital: Performance and Challenges of the Electronic Hepatitis B Surveillance System in Ninh Binh, Northern Vietnam (2017–2022). Tropical Medicine and Infectious Disease, 9(12), 299. https://doi.org/10.3390/tropicalmed9120299