Big Data in HealthCare - Relevance and Challenges

Big Data in HealthCare - Relevance and Challenges

Analyzing the volume, assortment and speed of big data helps businesses understand existing trends and patterns, which in turn, promotes informed decisionmaking for greater productivity and revenue. In healthcare, the amount of data is increasing exponentially. The digitization of patient information (with electronic health records or EHR) has opened up immense scope for data analytics to improve the quality of services. With technological advancements, the healthcare sector is generating more information than ever before. Making sense out of it will help improve health outcomes and lower the costs of care.

Increasing Importance of Big Data in HealthCare Reasons for the increasing importance of big data in healthcare sector are:

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Increased communication between patients, providers and communities in social outlets

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Development of advanced technologies such as capturing devices, sensors, and mobile applications

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Genomic information collection has become cheaper

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Huge volume of medical knowledge/discoveries

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More incentives for professionals/hospitals to use EHR technology

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Traditional medical practice is moving from subjective decision making to evidence based decision making

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Physician decision-making is becoming increasingly based on the analysis of the big data. EHRs which provide demographics, medical history, data given by patient, and much more and have become a valuable source of information.

Providers can process and analyze this data to develop insights for reducing cost and improving treatment. For instance, by studying historical data, doctors can most likely predict the likelihood of a recovery or a return visit to the hospital. So the harnessing of the large volume of medical data available today has become crucial for effective treatment and care.

Data captured would include internal and external data. Internal data is that collected from within the healthcare system and external data refers to that collected from external sources such as the National Health Information Network (NHIN), Health Information Exchanges (HIE), and Health Information Organizations (HIO). All this information holds immense potential for research and the future delivery of healthcare. Combining both these types of data helps to establish baselines, draw correlations, and infer the nature of an illness.

Challenges of Using Big Data in HealthCare The major challenges of using big data in healthcare system are as follows:

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Capturing the patient’s behavioral data through sensors, social interactions and other communications

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Validating, processing and integrating all the patient data elements into a large data source to facilitate meaningful analysis

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The vast increase in the amount, diversity, and complexity of data will require new capabilities within the workforce

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Efficiently handling large volumes of medical imaging data and

extracting potentially useful information out of it

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Addressing concerns about privacy and security of data

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Understanding unstructured clinical notes in the right context

However, big data has the potential to transform health care and can significantly improve health outcomes. Building a data governance system can address the existing challenges and can ensure trust and document/data security to a great extent.

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