COVID-19, Data architecture, Information system, Reportable diseases, Surveillance system

Shanbehzadeh, Mostafa; Kazemi-arpanahi, Hadi; Nopour, Raoof; Haghiri, Hamideh; Mobasheri, Fatemeh; Bazvand-Nezhad, Zeinab

doi:10.29252/sjimu.28.6.47

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Volume 28, Issue 6 (1-2021)

Journal of Ilam University of Medical Sciences 2021, 28(6): 47-61

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COVID-19, Data architecture, Information system, Reportable diseases, Surveillance system

Mostafa Shanbehzadeh¹

, Hadi Kazemi-arpanahi ^*

², Raoof Nopour³

, Hamideh Haghiri⁴

, Fatemeh Mobasheri⁵

, Zeinab Bazvand-Nezhad⁵

1- Dept of Health Information Technology, Faculty of Paramedical, Ilam University of Medical Sciences, Ilam, Iran
2- Dept of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran , hadi.kazemi67@gmail.com
3- Dept of Health Information Technology and Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
4- Dept of Health Information Technology and Management, Faculty of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
5- Dept of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran

Abstract: (2702 Views)

Introduction: Management and control of reportable diseases are challenging because these diseases include a large spectrum of infectious conditions that need accurate, precise, and timely reporting. To deal with this problem, an integrated surveillance system using the set of core data architecture principles is crucial to ensure the effective
management of data. Therefore, this study aimed to identify the core data architecture requirements for effective management of Coronavirus Disease 2019 (COVID-19), followed by designing a data architecture model.

Materials & Methods: This systematic review was conducted in 2020 through searching five databases, including PubMed, Web of Science, Science Direct, and Scopus M, as well as Google scholar search engine to identify metrics for COVID-19 data architecture designing. Moreover, the search formula definition, implication of inclusion and exclusion criteria, search filtering adjustment, and related study identification were performed in this study. Subsequently, the cases identifying the architecture data of the COVID-19 component were systematically extracted and categorized in suitable classes. Finally, the management system of the architecture model of the patient was visualized in this study.
Ethics code: IR.ABADANUMS.REC.1399.065

Findings: Out of 398 identified studies, 27 articles met the inclusion criteria. The obtained data were categorized into five classes, including organizations involved in data management (data producer, data users, and decision-makers), data sources, information requirements (11 information classes and 77 data elements), standards (semantic and syntactic), and control quality criteria of the data.

Discussions & Conclusions: Implementation of customized data architecture for COVID-19 can increase the potential of the health care systems to prevent the high prevalence of this disease and improve the quality of care through timely and effective health monitoring, accurate epidemiological investigations, clinical decision supports, and health-care policymaking.

Keywords: COVID-19, Data architecture, Information system, Reportable diseases, Surveillance system

Full-Text [PDF 1058 kb] (1105 Downloads)

Type of Study: Applicable | Subject: Health Information management
Received: 2020/05/19 | Accepted: 2020/09/19 | Published: 2021/02/28

References

1. Lazarus R, Klompas M, Campion FX, McNabb SJ, Hou X, Daniel J, et al. Electronic support for public health validated case finding and reporting for notifiable diseases using electronic medical data. J Am Med Info Asso2009;16:18-24. doi.10.2016/j.jbi.an24.07.009.

2. Gichoya J, Gamache RE, Vreeman DJ, Dixon BE, Finnell JT, Grannis S. An evaluation of the rates of repeat notifiable disease reporting and patient crossover using a health information exchange based automated electronic laboratory reporting system. Am Med Info Asso2012; 2:211-6. doi.10.1007/s12471-011-0234-x.

3. Li YK, Peng S, Li LQ, Wang Q, Ping W, Zhang N, et al. Clinical and transmission characteristics of covid-19 a retrospective study of 25 cases from a single thoracic surgery department. Curr Med Sci 2020:1-6. doi.10.102/hnftmj.20122.0071.

4. Masouri N, Ebadifard AF. A comparative study on surveillance system of notifiable infectious diseases in the selected countries proposed model for Iran. J Ghazvin Uni Med SCI 2006; 10:1-6. doi.10.26719/2016.22.11.794.

5. Adekoya N, Roberts H. Comparison of provisional with final notifiable disease case counts national notifiable diseases surveillance system 2009. MMWR Morb Mortal Wkly Rep 2013;62:747. doi.10.1016/j.ijmedinf.2010.04.007

6. Revere D, Hills RH, Dixon BE, Gibson PJ, Grannis SJ. Notifiable condition reporting practices: implications for public health agency participation in a health information exchange. BMC Publ Health2017;17:247. doi.10.1016/j.pmr.2019.09.005.

7. Doyle TJ, Ma H, Groseclose SL, Hopkins RS. Phskb a knowledgebase to support notifiable disease surveillance. BMC Med Info Dec Mak 2005;5:27. doi.10.1177/1062860618787056.

8. Persson L, Bartlett M. Notifiable Diseases Database system review and development strategy. New South Wales Publ Health Bul2004;15:10-2. doi.10.1016/b978-0-12-815370-3.00013-x. doi: 10.1109/iacc.2016.31.

9. Bagherian H, Farahbakhsh M, Rabiei R, Moghaddasi H, Asadi F. National communicable disease surveillance system a review on information and organizational structures in developed countries. Acta Info Med 2017;25:271. doi.10.1007/s10096-019-03501-6.

10. Vogt RL, Spittle R, Cronquist A, Patnaik JL. Evaluation of the timeliness and completeness of a Web based notifiable disease reporting system by a local health department. J Publ Health Manage Pract 2006;12:540-4. doi.10.1007/s10096-019-03501-6.

11. Klompas M, Lazarus R, Daniel J, Haney GA, Campion FX, Kruskal BA. Electronic medical record support for public health automated detection and reporting of statutory notifiable diseases to public health authorities. Adv Dis Surv 2007;3:1-5. doi.10.1016/j.ijmedinf.2012.06.004.

12. Hu H, Yao N, Qiu Y. Comparing rapid scoring systems in mortality prediction of critically ill patients with novel coronavirus disease. Acad Em Med 2020;27:461-8. doi. [DOI:10.1016/j.pbiomolbio.2011.07.001.]

13. Krause G, Altmann D, Faensen D, Porten K, Benzler J, Pfoch T, et al. Survnet electronic surveillance system for infectious disease outbreaks Germany. Em Inf Dis 2007;13:1548. doi. 10.1016/j.ijmedinf.2012.07.003.

14. Schumacher J, Diercke M, Salmon M, Czogiel I, Schumacher D, Claus H, et al. Timeliness in the German surveillance system for infectious diseases amendment of the infection protection act in 2013 decreased local reporting time to 1 day. PloS One2017;12: 187037. doi.10.1136/qshc.2007.025247.

15. Rolfhamre P, Jansson A, Arneborn M, Ekdahl K. Sminet-2 description of an internet-based surveillance system for communicable diseases in Sweden. Euro Surve Bul Europeen Dis. 2006;11:103-7. doi.10.2991/iconhomecs-17.2018.1.

16. Chandrasekar K, Mahesan S, Bath P. Notifiable disease surveillance in Sri Lanka and the United Kingdom: a comparative study. Sri Lanka J Biomed Info 2013;4:32-7. doi.10.1016/j.jacep.2018.11.013.

17. Herbert S, Leong G, Hewitt K, Cassell J. Do genitourinary physicians report notifiable diseases? A survey in South East England. Int J STD AIDS 2015;26:173-80. doi.10.4103/rcm.rcm_34_17.

18. Vlieg WL, Fanoy EB, Asten L, Liu X, Yang J, Pilot E, et al. Comparing national infectious disease surveillance systems: China and the Netherlands. BMC Pub Health 2017;17:415. doi. 10.1093/europace/eut149.

19. Zhang L, Wilson DP. Trends in notifiable infectious diseases in China implications for surveillance and population health policy. PLos One2012;7:31076. doi.10.4102/sajr.v20i2.1048

20. Zhang X, Hou F, Li X, Zhou L, Liu Y, Zhang T. Study of surveillance data for class B notifiable disease in China from 2005 -14. Int J Inf Dis2016;48:7-13. doi.10.1016/j.chest.2017.05.040.

21. Wang L, Wang Y, Yang G, Ma J, Wang L, Qi X. China information system for disease control and prevention. HIT Brief Book 2013:101-8. doi.10.1016/s0140-6736(12)61463-9

22. Hsieh YH, Kuo MJ, Hsieh TC, Lee HC. Underreporting and underestimation of gonorrhea cases in the Taiwan National Gonorrhea Notifiable Disease System in the Tainan region evaluation by a pilot physicia based sentinel surveillance on Neisseria gonorrhoeae infection. Int J Inf Dis 2009;13:413-9. doi.10.1016/j.jbi.2014.03.011.

23. Yoo HS, Park O, Park HK, Lee EG, Jeong EK, Lee JK, et al. Timeliness of national notifiable diseases surveillance system in Korea a cross sectional study. BMC Publ Health 2009;9:93.

24. Tan HF, Chang CK, Tseng HF, Lin W. Evaluation of the national notifiable disease surveillance system in Taiwan an example of varicella reporting. Vaccine 2007;25:2630-3. doi.10.1016/j.pbiomolbio.

25. Benson FG, Levin J, Rispel LC. Health care providers compliance with the notifiable diseases surveillance system in South Africa. PloS One 2018;13: 195194. doi.10.4103/jehp.jehp_2_19.

26. Girdlerbrown B. Evaluation of the notifiable diseases surveillance system in South Africa. Int J Inf Dis 2017;59:139-40. doi.10.1016/j.hrthm.2019.05.002.

27. Benson F, Musekiwa A, Blumberg L, Rispel L. Survey of the perceptions of key stakeholders on the attributes of the South African Notifiable diseases surveillance system. BMC Publ Health2016;16:1120. doi.10.1016/j.ijmedinf.

28. Miller M, Deeble M, Roche P, Spencer J. Evaluation of Australias national notifiable disease surveillance system. Commun Dis Int Quarter Rep 2004;28:311. doi.10.1016/j.jbi.2018.07.009. doi.10.1089/tmj.2012.0071.

29. Azar F, Masoori N, Meidani Z, Paul L. Proposal for a modernized Iranian notifiable infectious diseases surveillance system: comparison with USA and Australia. Eastern Med Health J2010;16: doi. 10.1007/s12553-014-0085-8.

30. NNDSS ARWG. Australia's notifiable disease status 2014 annual report of the national notifiable diseases surveillance system. Commun Dis Intel quarter Repo2016;40: 48. doi.10.1007/s12553-014-0085-8.

31. Yadaw AS, Li Yc, Bose S, Iyengar R, Bunyavanich S, Pandey G. Clinical features of COVID-19 mortality development and validation of a clinical prediction model. Lancet Digital Health2020;2: 516-25. doi. 10.5335/rbca.v11i2.8651.

32. Jones NF, Calder L. eNotification adapting ereferral for public health notifiable disease reporting in new zealand. Healthcare Info Res2012;18:225-30. doi. 10.0000-0002-5578-758X.

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Shanbehzadeh M, Kazemi-arpanahi H, Nopour R, Haghiri H, Mobasheri F, Bazvand-Nezhad Z. COVID-19, Data architecture, Information system, Reportable diseases, Surveillance system. J. Ilam Uni. Med. Sci. 2021; 28 (6) :47-61
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