Essay Example: The Obstacles that Affect Interoperability of the Disease Surveillance Systems

Milwaukee is the largest city in the state of Wisconsin, United States. One of the local surveillance systems utilized in Milwaukee, and the whole of Wisconsin, is the Wisconsin Electronic Disease Surveillance System (WEDSS). The WEDSS a secure, Internet-based system developed with the aim of facilitating reporting, investigation, and surveillance of communicable diseases (Wisconsin Department of Health Services, 2014). The WEDSS was developed for use by public healthcare professionals, clinics, clinical laboratories, infection control practitioners, and other individuals tasked with disease reporting. Like other surveillance systems, the WEDSS faces obstacles that impact the interoperability of the disease surveillance systems. For health surveillance systems to be effective in disease surveillance, it is vital that semantic interoperability is achieved. According to Dixon, Siegel, Oemig, and Grannis (2013), semantic interoperability is the capacity of one information system to import data or information from another computer without the prior need to seek approval.

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Dixon et al. (2013) have reported that Wisconsin and Indiana are both characterized by high use of advanced health information systems with most of the laboratories and hospitals utilizing systems which claim to have high interoperability. However, Dixon et al. (2013) noted that very limited electronic laboratory reporting messages come from real-world systems with interoperability of codes for identification of tests and clinical findings. To ensure effective use of electronic laboratory reporting messages, Wisconsin and Indiana health departments use software and individual workarounds for translation of incoming data into standardized concepts that can be used by their surveillance systems. This approach is ineffective in ensuring interoperability of Wisconsin's and Indiana surveillance systems.

It has also been noted that one of the obstacles affecting interoperability of disease surveillance systems is the need to balance between the public interest in the gathering of health or disease data and the privacy rights of the affected individuals (Labilles et al., 2014). Theoretically, proper utilization of disease surveillance system is indispensable in public health. However, the legal implications that are associated with the 4th Amendment prohibition against unreasonable searches and seizures. The 4th amendment protects against unlawful access on personal health records. Consequently, this the 4th Amendment can hinder the health surveillance system from receiving disease data on time and sharing with other surveillance systems.

Kostkova (2018) also noted that even though information technology systems have enhanced public health early detection of diseases and outbreaks, implementing these systems in real-world surveillance by CDC and other organizations tasked with disease surveillance has always felt short. Specifically, the first ethical challenge that has hindered interoperability of surveillance systems is sharing data across many early warning tools to aid the assessment of risks and calibrating of predictive models. Kostkova (2018) also noted that another challenge affecting surveillance system is related to a clear definition of the legal frameworks for public health information sharing with the aim of unlocking the potential of population-level datasets for research with no adverse effect on citizens privacy.

Ways of Addressing the Legal, Ethical, And Practical Data-Sharing Obstacles

One of the approaches that can be utilized in addressing the legal, ethical, and practical challenges associated with data sharing between or among health surveillance systems is ensuring that there is strict adherence to the Health Insurance Portability and Accountability Act's Privacy (HIPAA) by all the surveillance systems. According to CDC (2018a), HIPAA is a federal law that regulates privacy and the sharing of particular types of data. To ensure that there is compliance with HIPAA Security Rule, it is essential for disease surveillance systems to provide that all electronic protected health information is confidential and meet all the established integrity criteria (CDC, 2018b). Also, the surveillance systems are required to have in place mechanisms for detecting and safeguarding against expected threats to the security of the patients' data. Another requirement that should be met by the surveillance systems as outlined by the CDC (2018b) is the need for protection against any expected impermissible uses or disclosures of patients' healthcare information. Lastly, to ensure that there are no legal challenges in utilizing patients' information for public health surveillance, all the workers tasked with surveillance need to be compliant with HIPAA.

The ethical challenge that characterizes the sharing of private health information can be resolved by ensuring that all public surveillance systems incorporate full transparency about the use of such data. This can be attained if the public is actively engaged in surveillance and made aware of the benefits and risk of the same (Kostkova, 2018). This also helps in building trust with the public (Edelstein, Lee, Herten-Crabb, Heymann, & Harper, 2018).

Impacts on The Future of Sharing and Use of Public Health Information

It is expected that adherence to ethical and legal guidelines in disease surveillance will increase the rate and willingness of different surveillance systems to share public health information. Consequently, it is predicted that there will be an increased sharing of information between and among local, state, national, and international systems or agencies. Therefore, there is a high likelihood that disease surveillance will be improved and any new disease or outbreak will be easily detected (Gasner, Fuld, Drobnik, & Varma, 2014).

References

Edelstein, M., Lee, L. M., Herten-Crabb, A., Heymann, D. L., & Harper, D. R. (2018). Strengthening global public health surveillance through data and benefit sharing. Emerging Infectious Diseases, 24(7), 1324-1330. https://doi.org/10.3201/eid2407.151830

Gasner, M. R., Fuld, J., Drobnik, A., & Varma, J. K. (2014). Legal and policy barriers to sharing data between public health programs in New York city: a case study. American Journal of Public Health, 104(6), 993-997. https://doi.org/10.2105/AJPH.2013.301775

CDC. (2018). Health information & privacy. Retrieved from https://www.cdc.gov/phlp/publications/topic/healthinformationprivacy.html

CDC. (2018). Health insurance portability and accountability act of 1996 (HIPAA). Retrieved from https://www.cdc.gov/phlp/publications/topic/hipaa.html

Kostkova, P. (2018). Disease surveillance data sharing for public health: the next ethical frontiers. Life Sciences, Society and Policy, 14(1). https://doi.org/10.1186/s40504-018-0078-x

Labilles, U., DMD, & PhD. (2014, May 14). A challenge to public health surveillance interoperability and clinical research. Retrieved February 4, 2019, from https://onenationsecho.com/2014/05/13/a-challenge-to-public-health-surveillance-interoperability-and-clinical-research/

Sinn, H.-P., & Kreipe, H. (2013). A brief overview of the who classification of breast tumors, 4th edition, focusing on issues and updates from the 3rd edition. Breast Care, 8(2), 149-154. https://doi.org/10.1159/000350774

Wisconsin Department of Health Services. (2014). Wisconsin electronic disease surveillance system (WEDSS). Retrieved from https://www.dhs.wisconsin.gov/wiphin/wedss.htm