Big Data: Its Implications on Healthcare and Future Steps

Big Data: Its Implications on Healthcare and Future Steps

Shannon Wai Yi Yee, Carolina Gutierrez, Caroline Narae Park, Danny Lee, Scott Lee
Copyright: © 2020 |Pages: 18
DOI: 10.4018/978-1-7998-0047-7.ch005
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In the last three decades, big data has been applied to diverse fields, such as the government, international development, and education. It is only now that the US healthcare system has begun to explore its under-utilized data. Big data is not only referencing the quantity, but also the complexity, diversity, and relativity of the information. This information may be analyzed to reveal patterns, trends, and associations that may be applicable to the healthcare field. This information can be gathered through sources, such as EHRs, IRIS registry, and MIPS. Recognizing patterns would aid in predicting preventative measures for an increased holistic and personalized patient care. Although big data proves to have endless beneficial applications, it can bring into question the ownership of this information. Additionally, big data poses a risk for security breaches, and thus, precautionary measures will also be discussed. Ultimately, the emergence of big data creates an exhilarating frontier for healthcare with its unlimited possibilities.
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Data Collection Systems

In this section, different types of data collection are discussed beginning with a broad view provided by an EHRS that moves toward a specialty view provided by the IRIS Registry. The advantages and disadvantages of each big data collection process are discussed in detail.


Electronic Health Records Systems (EHRS) and Electronic Medical Records Systems (EMRS) are easily confused. EMRS comprise a clinical data repository, clinical decision support, controlled medical vocabulary, order entry, computerized provider order entry, pharmacy, and clinical documentation applications (Garets & Davis, 2006). EMRS, on the other hand, are intraorganizational systems used by healthcare professionals to document, monitor, and manage care of their patients. Ultimately, the data from EMRS are legal records of patient experiences at the care delivery organization (CDO) and are owned by the CDO. EHRS, are interorganizational systems and contain a subset of information from various CDOs that patients have utilized. For EHRS, the data generally is owned by the patient, which allows for greater access and the ability to supplement the information. EMRS are sources of data for EHRS, while EHRS allow sharing of medical information between patient, CDO, and stakeholders (Garets & Davis, 2006).

Key Terms in this Chapter

Human Immunodeficiency Virus (HIV): A virus that weakens a person's immune system by destroying important cells that fight disease and infection.

Medicare and Medicaid: National health insurance programs in the United States.

Intercommunication: Communication between different practices or organizations.

Computerized Tomography (CT) Scans: Combines a series of x-ray images taken from different angles around a patient’s body and uses computer processing to create cross-sectional images (slices) of the bones, blood vessels and soft tissues inside the body.

Structured Data: Information that can easily be stored or formatted by a machine

Intracommunication: Communication within a practice or organization.

Magnetic Resonance Imaging (MRI): A medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body in both health and disease.

Semi-Structured Data: Structured data that does not fully conform with the formal structure of data models associated with relational databases or other forms of data tables

Unstructured Data: Information that is not organized in any manner.

IT: Information technology; anything related to technology, such has hardware, software, professionals, etc.

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