Using surveillance system evaluation to develop an influenza surveillance system for strengthened disease prevention and control at Bang Pahan Hospital, Phra Nakhon Si Ayutthaya Province
Article Sidebar
Main Article Content
Abstract
This study aimed to evaluate the performance of the influenza surveillance system at Bang Pahan Hospital and to develop an automated alert system using the Telegram application to enhance disease prevention and control. This developmental research applied an action research framework combined with a quasi-experimental before–after design. Data from the pre-development phase (June 1, 2021 – May 31, 2022) were compared with the post-development phase (June 1, 2024 – May 31, 2025). The intervention involved developing an automated alert system (Telegram Bot) integrated with the hospital information system (HOSxP) to identify suspected influenza cases based on surveillance case definitions. Quantitative surveillance attributes, including sensitivity, positive predictive value (PPV), and timeliness, were analyzed, along with qualitative attributes such as acceptability, simplicity, and stability. Statistical analyses were conducted using the chi-square test, Fisher’s exact test, and Mann–Whitney U test. After implementation, the surveillance system showed significant improvements. Sensitivity increased from 4.78% to 42.16% (p < 0.001), and the PPV increased from 23.81% to 91.21% (p < 0.001). The average reporting time significantly decreased from 3.76 days to 1.55 days (p < 0.001). Qualitative findings indicated improved staff acceptance of the system, with knowledge transfer, standard operating procedures, and operational coordination reaching 100% acceptance (p < 0.05). In conclusion, the automated alert system significantly improved influenza surveillance performance by increasing case detection, reducing reporting delays, and strengthening rapid response capacity. This digital surveillance model represents a practical and scalable approach for improving infectious disease surveillance systems in community hospitals.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Buckeridge DL. Outbreak detection through automated surveillance: a review of the determinants of detection. J Biomed Inform. 2007;40(4):370-9.
Epidemiology unit, Phra Nakhon Si Ayutthaya provincial public health office (TH). Summary of the epidemiological surveillance disease situation in Phra Nakhon Si Ayutthaya province, October 2022. Phra Nakhon Si Ayutthaya: Phra Nakhon Si Ayutthaya provincial public health office; 2022. p. 4-7. (in Thai)
Uyeki TM, Bernstein HH, Bradley JS, Englund JA, File TM Jr, Fry AM, et al. Clinical practice guidelines by the Infectious diseases Society of America: 2018 update on diagnosis, treatment, chemoprophylaxis, and institutional outbreak management of seasonal influenza. Clin Infect Dis. 2019;68(6):e1-47.
Mertz D, Kim TH, Johnstone J, Lam PP, Science M, Kuster SP, et al. Populations at risk for severe or complicated influenza illness: systematic review and meta-analysis. BMJ. 2013;347:f5061.
World Health Organization. Early detection, assessment and response to acute public health events: implementation of early warning and response with a focus on event-based surveillance. Geneva: WHO; 2014.
Centers for Disease Control and Prevention (US). Updated guidelines for evaluating public health surveillance systems: recommendations from the Guidelines Working Group. MMWR recomm rep. 2001;50(RR-13):1-35.
Chopkatanyu A, Saengsawang C, Thepparat T, Kaesaman S, Malae S. Evaluation of the influenza surveillance system in Narathiwat Province, 2019. Weekly epidemiological surveillance report. 2021;52(43):621-33. (in Thai)
Department of disease control, Ministry of public health (TH). Thailand case definitions. Nonthaburi: Department of disease control; 2020. (in Thai)
Division of epidemiology, Department of disease control, Ministry of public health (TH). Case definitions and guidelines for reporting dangerous communicable diseases and communicable diseases under surveillance in Thailand. Bangkok: Canna graphic; 2020. p. 72-4. (in Thai)
Drewe JA, Hoinville LJ, Cook AJ, Floyd T, Stärk KD. Evaluation of animal and public health surveillance systems: a systematic review. Epidemiol Infect. 2012;140(4):575-90.
Thacker SB, Berkelman RL. Public health surveillance in the United States. Epidemiol Rev. 1988;10:164-90.
Department of disease control, Ministry of public health (TH). Annual epidemiological surveillance report 2022. Nonthaburi: Department of disease control; 2023. (in Thai)
Department of disease control, Ministry of public health (TH). Guideline for disease surveillance and investigation (SRRT Manual). Nonthaburi: Bureau of epidemiology, Department of disease control; 2022. (in Thai)
Kemmis S, McTaggart R. The action research planner. 3rd ed. Victoria: Deakin University Press; 1988.
Centers for disease control and prevention (US). Overview of influenza surveillance in the United States. Atlanta: Centers for Disease Control and Prevention; 2022.
World Health Organization. Rapid influenza diagnostic tests (RIDTs): laboratory guidance. Geneva: World Health Organization; 2011.
World Health Organization. WHO global epidemiological surveillance standards for influenza. Geneva: World Health Organization; 2013.
Sudana O, Paramartha A, Wirdiani A, Rusjayanthi D. Design and implementation of Telegram Bot for integrated hospital Information system. Jurnal Sains dan Teknologi. 2022;11(1):165-174.
