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There are many purposes for and types of health care data. In this discussion, you will summarize the purpose for and types of health care data, and discuss the emerging field of data analytics and Big Data as they are used in health care management. Include the following in your discussion post:

Explain the purpose of healthcare data and its relevance to patient outcomes and reimbursement.
Discuss the difference between:
Internal and external sources of data in healthcare
Qualitative and quantitative data in healthcare
Discuss data analytics and how it is being used in healthcare management and healthcare delivery.

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Sample Answer

Healthcare data is used for a variety of purposes, including:

  • Patient care: Healthcare data is used to provide better care to patients. This includes tracking patient health, identifying potential problems, and making informed decisions about treatment.
  • Research: Healthcare data is used to conduct research to improve our understanding of diseases and treatments. This research can lead to new treatments, prevention strategies, and ways to improve the quality of care.
  • Reimbursement: Healthcare data is used to determine reimbursement for services. This data is used to ensure that providers are reimbursed fairly for the services they provide.

There are two main types of healthcare data: internal and external.

  • Internal data:R Internal data is generated by healthcare organizations, such as electronic health records (EHs), claims data, and billing data. This data is typically stored in a centralized database and can be used to track patient care, identify trends, and make informed decisions about treatment.
  • External data: External data is generated by outside sources, such as insurance companies, government agencies, and research institutions. This data can be used to supplement internal data and provide a more complete picture of a patient’s health.

Full Answer Section

Healthcare data can also be classified as qualitative or quantitative.

  • Qualitative data: Qualitative data is descriptive and cannot be easily quantified. This data includes information such as patient symptoms, medical history, and social determinants of health.
  • Quantitative data: Quantitative data is numerical and can be easily measured. This data includes information such as lab results, vital signs, and medication dosages.

Data analytics is the process of collecting, cleaning, and analyzing data to extract insights. This can be used to improve patient care, identify trends, and make informed decisions about treatment.

Data analytics is being used in healthcare management in a number of ways, including:

  • Risk assessment: Data analytics can be used to assess patient risk for certain diseases or conditions. This information can be used to target interventions and improve patient outcomes.
  • Population health management: Data analytics can be used to track the health of a population and identify areas where interventions are needed. This information can be used to improve the overall health of a population.
  • Fraud detection: Data analytics can be used to detect fraud and abuse in healthcare. This information can be used to protect patients and ensure that healthcare dollars are used appropriately.

Data analytics is also being used in healthcare delivery to improve the quality of care. For example, data analytics can be used to:

  • Personalize treatment: Data analytics can be used to personalize treatment for patients based on their individual needs. This information can be used to improve patient outcomes and reduce the risk of adverse events.
  • Optimize care delivery: Data analytics can be used to optimize care delivery by identifying areas where inefficiencies exist. This information can be used to improve the efficiency of care delivery and reduce costs.

The field of data analytics in healthcare is rapidly evolving. As more data becomes available, data analytics will become even more powerful and will be used to improve patient care in even more ways.

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