Resource:"Case Study 12: Implementing a Syndromic Surveillance System," Ch. 18 of Health Care Information Systems.
Readthe case study.
Write350 to 700 words that address the following issues as if you were the CIO of the State Public Health Agency:
- How will your agency ensure the quality of the data acquired from many hospitals throughout the state?
- What are the consequences of poor data quality in the syndromic surveillance system?
- How can management ensure that significant data trends are acted on without distraction from expected variations in the data?
And put the whole paper together with an intro and conclusion
How can management ensure that significant data trends are acted on without distraction from expected variations in the data?
As already stated, the Syndromic Surveillance System captures the changes and variations in the trends of the numerous diseases found in the general public. It is the State Public Health Agency's responsibility to react accordingly when significant changes in these trends occur. Therefore, the agency leaders are trained to handle every issue or concern equally, regardless of its significance. It is then up to the management to determine which among these changes or trend variations warrant more attention than the others. Furthermore, Guidelines and tools are in place to help them handle delicate situations such as these without causing any fear or panic in the general public. These protocols serves as their road map to ensure that overreaction as well as non-reaction does not occurs.
Wager, K.A, Lee, F.W., & Glaser, J.P. (2013). Health Care Information Systems: A Practical Approach for Health Care Management Third Edition.San Francisco, CA: Jossey-Bass
Ziemann, A., Rosenkötter, N., Riesgo, L. G., Fischer, M., Krämer, A., Lippert, F. K., & ... Krafft, T. (2015). Meeting the International Health Regulations (2005) surveillance core capacity requirements at the subnational level in Europe: the added value of syndromic surveillance. BMC Public Health, 15(1), 1-13. doi:10.1186/s12889-015-1421-2
How will your agency ensure the quality of the data acquired from many hospitals throughout the state?
Ensuring quality data required from many hospital in our state requires attention to certain details: for example Wang denotes one should have representational data quality program (1996). According to Wang, related formatting data concise and a brilliant representation couple with data interpretation lucid in understanding (1996). Interpret ability
Summary and Conclusions
Wang (1996) a framework, information systems professionals, yet better data understand and meet their data consumers' data quality needs. For example, data quality (DQ): intrinsic DQ with accuracy not subjective, trust worthiness, reliability, validity, and
In developing this framework, we conducted a two-stage survey and a two-phase sorting study. Te resulting framework has four data quality (DQ) categories: (I) intrinsic DQ consists of accuracy, objectivity, believability, and assessable (Wang, 1996).
Our programmers shall build one [system] application compatible to the state system and with the ability to merge or minimized a great deal of data in a short period of time. Keeping abreast to the things which accompany a great syndrome surveillance system, such as Wager (2013) notes: collect and analysis, prediagnostic and non clinical disease indicators, preexisting electronic dash searchable in the system. the system must link up with symptom to make predictions for public safety. Moreover, compliance to the state's system vital because of reimbursement, and other issues, too. Seamless input and output with excellent accuracy and transparency.
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5. Retrieved from http://search.proquest.com/docview/218911948?accountid=35812
Wager, K. A., Lee, F. W., & Glaser, J. P. (2013). Health care information systems: A practical approach for health care management(3rd ed.). San Francisco, CA: Jossey-Bass.
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