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Evaluating Electronic Disease Surveillance Systems


The growing interest and significant investment in electronic surveillance systems have fueled the demand for techniques that evaluate their effectiveness accurately. This paper will analyze issues associated with evaluating electronic disease surveillance systems. Besides, it will explain how one would address the interests of multiple constituencies. Moreover, the paper will consider the implications for evaluating surveillance systems.

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Analysis of the Issues Affecting The Evaluation Of Electronic Disease Surveillance Systems

There exists a challenge in the standardizing criteria for evaluating the success of electronic disease surveillance systems. This is because there are different aspects connected with evaluating such systems, for example, some offer usability testing and socio-technical analysis, whereas the rest propose quality of care and user and patient satisfaction in determining the accuracy of success of such systems (Strom, 2004). Therefore, this has raised questions about the effectiveness of the use of electronic surveillance systems in all health sectors within the country. For example, electronic disease surveillance systems face challenges in interoperability. This is because their use creates challenges in achieving the desired effect as most of them are utilized in the monitoring and evaluation of different diseases, hence are considered to be stand-alone systems (Sosin & DeThomasis, 2004). Therefore there are scarcely anyways how these systems can be used in the health care sector these systems work on their own without sharing information with other relevant areas. Moreover, the use of electronic surveillance systems poses challenges to the states which use it in the health care system because only a few resort to developing integrated modules. The cost of developing the systems is high and negative impacts associated with the evaluation of the systems are amongst the barriers that prevent other states from developing integrated modules. Likewise, the modules used in electronic surveillance systems are always ineffective because they are not harmonized (Sosin & DeThomasis, 2004). Lack of harmony in the modules leads to errors in the reporting of different diseases because messages uploaded to different individual surveillance modules are not recorded accurately.

What is more, electronic surveillance systems also face issues in data sharing which results in reduced user satisfaction. This is because the system works independently, hence making the process of sharing information amongst different servers a challenge. Moreover, it does not adequately elaborate on the type of information to be shared and the parties responsible for sharing the information on the question (Lombardo & Buckeridge, 2007).

Addressing the Interest of Multiple Constituencies in Electronic Surveillance Systems

To address the interest of multiple constituencies in electronic surveillance systems, it is mandatory to address the issue of surveillance design. The process involves building explicit trade-offs on the type of information to be included in the systems and the user needs that are targeted. In addition, time and data issues should be adequately addressed when scheming the explicit observation trade-offs.

To protect the accuracy of the data provided by electronic surveillance systems in the interest of multiple constituencies, sample size thresholds should be used for reporting cases to guarantee individual patient data (Psaty, Furberg, Ray., & Weiss, 2004). Moreover, the general strategy used in ensuring that the interest of multiple constituencies is met should take into consideration and balance the expected challenges of using the system in question (Strom, 2004).

Implications for Evaluating Surveillance Systems

According to the sources used for the paper, evaluating surveillance systems is imperative because it enables individuals involved in the evaluation process to achieve efficiencies. The process of the assessment allows a change of workflow and process, and the result is a better and more efficient surveillance system (Braun et al., 2002). Evaluation of the surveillance systems also promotes the growing focus on quality and performance. The result of this is that an effective platform that assists in infection prevention is created; hence diversification is achieved in the healthcare IT requirements (Bernheim & Melnick, 2008).

To facilitate an efficient review of useful data used for health care purposes, the evaluation of an electronic surveillance system is necessary as it enables the process found in the system to work in accordance or harmony with other processes (Heffernan et al., 2004).This assists in meeting the existing need for the challenges which are present in the health care system, for example, increased data demand collection, analysis, and reporting. The result of this is an improved trajectory for transparency of healthcare-associated infection (Buehler, Berkelman, Hartley, & Peters, 2003).

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In conclusion, the evaluation of electronic disease surveillance systems is necessary for the identification of emerging diseases that affects the society today. Moreover, the evaluation process of systems provides action plans that might be used in combating the diseases. To effectively use the electronic disease surveillance systems, it is important to consider issues arising from their evaluation and develop a roadmap for the best future use of the systems.


Bernheim, R., & Melnick, A. (2008). Principled Leadership in Public Health. Journal of Public Health Management and Practice, 14 (4), 358-366.

Braun, K. V. N., Pettygrove, S., Daniels, J., Miller, L., Nicholas, J., Baio, J., & Rice, C.(2002). Evaluation of a methodology for a collaborative multiple source surveillance network for autism spectrum disorders—Autism and developmental disabilities monitoring the network. Web.

Buehler, J. W., Berkelman, R. L., Hartley, D. M., & Peters, C. J. (2003). Syndromic surveillance and bioterrorism-related epidemics. Emerging Infectious Diseases, 9(10), 1197-1204.

Heffernan, R., Mostashari, F., Das, D., Karpati, A., Kulldorf, M., & Weiss, D. (2004). Syndromic surveillance in public health practice, New York City. Emerging Infectious Diseases, 10(5), 858-864.

Lombardo, J. S., & Buckeridge, D. L. (2007). Disease surveillance: A public health informatics approach (Eds.). Hoboken, NJ: Wiley-Interscience.

Psaty, B. M., Furberg, C. D., Ray, W. A., & Weiss, N. S. (2004). Authors’ reply to Bayer’s response to ‘Potential for conflict of interest in the evaluation of suspected adverse drug reactions: Use of cerivastatin and risk of rhabdomyolysis. Journal of the American Medical Association, 292(21), 2658-2659.

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Sosin, D. M., & DeThomasis, J. (2004). Evaluation challenges for syndromic surveillance: Making incremental progress. Morbidity and Mortality Weekly Report, 53 (1), 125-129.

Strom, B. L. (2004). Potential for conflict of interest in the evaluation of suspected adverse drug reactions: A counterpoint. Journal of the American Medical Association, 292 (21), 2643- 2646.

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