Issues of Inter-operability and Data Sharing
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Issues of Interoperability and Data Sharing
The CDC has developed myriad informatics applications in support of disease surveillance at the federal level. Information sharing among these applications enables public health personnel to better understand disease trends that may be difficult to interpret from the examination of a single system. However, a variety of legal, ethical, and practical issues arise as a result of this sharing of information. The potential for problems is magnified when information is available to and shared among multiple systems.
post an analysis of the obstacles that impact interoperability of the disease surveillance systems. Propose ways to improve/address the legal, ethical, and practical data-sharing obstacles. Evaluate how this impacts the future of local, state, national, and international systems/agencies sharing and use of information.
SAMPLE ANSWER
Data-sharing and interoperability obstacles
Department of Health and Human Services (HHS) estimates that 20% of medical errors are preventable and occur due to lack of immediate access to health education. The interoperability obstacles are bothersome especially in this technology era. In fact, banking industries and telecommunication industry interoperability have excelled substantially. One can transact from ant ATM with minimal interruption. Why is this not replicable in the health care sector? Despite the fact that 10 billion dollars have been allocated to facilitate the interoperability in health care industry, technical challenges on the same are insurmountable (King Et al, 2012). First, the data collected is inadequate due to the significant gaps in the disease surveillance systems, particularly in the developing countries. Additionally, most public health information is stored hard copy, and where electronic formats are use; they are often incompatible with the other advanced disease surveillance systems. Data format standards and metadata for health care including Data Documentation Initiative (DDI), the established International Classification of Diseases (ICD) and Metadata eXchange are insufficiently functional. This limits interoperability and secondary data usage. In fact, about 20% of deaths that occurred in certain countries between 1950 and 2010 were due to ill-fated use of the established ICD due to limited data sharing (CDC, 2012).
Another issue that holds back data sharing is the ownership and copyright issues. Institutions and agencies that collect data are liable for the person and the community privacy. This makes most of these agencies reluctant to carry out their tasks sufficiently as they feel like guardianship role has been bestowed on them. Additionally, government agencies such as Health Insurance Portability and Accountability Act (HIPAA) in US regulations on data acquisition using identifiers and the anonymous data makes it hard to use data collected in certain contexts. Some data are not released to anyone because they are perceived as sensitive and are only used for security purposes. Additionally, some stewards may be reluctant to share disease surveillance data because they fear that inexperienced individuals may abuse the information. In some cases, they may be reluctant because of socioeconomic impacts. For instance, the fears interoperability will reduce their relevancy or feasibility of the study. Other barriers include insufficient incentives and resources for data sharing and limited guidelines (Peter et al, 2012).
In cases of remaining relevant, the new approaches that protect the person or agency such as data perturbation should be established. This is a strategy which allows the researcher to provide key but limited information of their work while ensuring that their security is not breached. For instance, researchers can access restricted information through Research Data Center (RDC). For effective interoperability and data sharing, legal barriers that prevent data sharing must be annulled. The involved stakeholders should collaborate and debunk the existing miscommunications and misconceptions regarding the legal barriers (CDC, 2012). A standardized format should be established. This entails establishing a standard language, coding system, formatting and process involved in data sharing. This will ensure that disease surveillance systems are user friendly and data disseminated is adequate. Moreover, an efficient, secure disease surveillance system and the software program should be established for effective communication and exchange of information. If the obstacles are not eliminated, scientific discoveries will be reduced. The reduced understanding of individual study and pooling of data will negatively impact innovations. The accuracy and quality of research will reduce due to the limited sharing of data on critical issues such as effective treatment options and evidence based strategies (NCBI, 2013).
References
CDC (2012) Public health surveillance data: legal, policy, ethical, regulatory and practical issues. Supplements 61; 3, p30-34. Retrieved on January 26th 2015 from [http://www.cdc.gov/mmwr/preview/mmwrhtml/su6103a7.htm?s_cid=su6103a7_x]
King, G. Et al.(2012) Boundaries and e-health implementation in health and social care. BMC Medical informatics and decision making 12; 100, p1-12
NCBI (2013) Sharing Clinical research data: Workshop summary. Retrieved on January 26th 2015 from [http://www.ncbi.nlm.nih.gov/books/NBK137823/]
Peter, B. Et al. (2012). Mining electronic health records: towards better research applications and clinical care. Nature reviews 13; p395 -407
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