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My Original Post

In healthcare, big data is referred to as the magnitude of data that is connected to patient healthcare and physical well-being. Most of this data is derived from public sources, information collected and keyed in by the patients, stakeholders, and the medical practitioners. Some examples of these systems include genetic data bases, electronic health records (EHRs), patient portals, clinical data warehouses, claim data from clients, patient registries,research studies, public records, social media, financial transactions, and the Internet of Things(Hilbert, 2016). These sources were initially used as traditional methods of collecting clinical data before the advancement of data management programs. It is important to note that accessing this information may be a violation of privacy; hence the need to generate an algorithm that only collects information relevant to patient healthcare.

            EHRs are used in data collection and are important because they give basic information such as patient demographics, medical history, known medical conditions, allergies, medication, tests and results from radiology and laboratory consults and pathology reports, among others. Patient registries are vital in monitoring patient care within hospital institutions, and are often constrained to a specific facility. The importance of a patient portal is the access of patient information relevant in patient care and for secure communication with the healthcare team. Data collected from patient claims is important in making sure that cases such as claim fraud and are easily mitigated, and also for easier recovery of this data(Manogaran, Thota, Lopez, Vijayakumar, Abbas, &Sundarsekar, 2017). Data collected from research studies is crucial in managing treatments and specialized care relevant to patient care such as cancer clinical trials and disease management in the event of an epidemic. Such is possible through granular information such as patient profiles and demographic patterns. For example, genetic testing may be used to discover what foods react depending on the biological composition of saliva. Such a project could help in food administration in general, preventing food related allergies (Manogaran, Thota, Lopez, Vijayakumar, Abbas, &Sundarsekar, 2017).

            Public records are vital especially since they give information on marital status, births, deaths, and immigration status that also help in data security and management. Through information gathered during Census, medical providers are able to cross-reference the data received and deduce the number of citizens within their area based on age group, occupational status, and number of children, enabling hospitals to operate to best satisfy their clients(Groves, Kayyali, Knott, &Kuiken, 2016). Web searches and social media equally provide information that can alert healthcare providers on disease outbreaks and their trends, giving room to create a contingency plan.

References

Groves, P., Kayyali, B., Knott, D., &Kuiken, S. V. (2016). The'bigdata'revolution in healthcare: Accelerating value and innovation. Retrieved from http://hdl.handle.net/11146/465

Hilbert, M. (2016). Big data for development: A review of promises and challenges. Development Policy Review, 34(1), 135-174. Retrieved from https://doi.org/10.1111/dpr.12142

Manogaran, G., Thota, C., Lopez, D., Vijayakumar, V., Abbas, K. M., &Sundarsekar, R. (2017). Big data knowledge system in healthcare.In Internet of things and big data technologies for next generation healthcare (pp. 133-157).Springer, Cham. Retrieved from https://doi.org/10.1007/978-3-319-49736-5_7

Question

That is a good point, while patient data is not public information the census data is public information.  As you state this information may be able to determine where they may be more of a need for medical care in a particular area based on demographic information like age.   Do you see any other public information being used to assist medical professionals?