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Building Robust Healthcare Information Systems With Data Science Techniques

The days of keeping patient records in paper files, with handwritten notes from healthcare providers, are well behind us. In recent years, there has been an explosion in the amount of health data that is electronically generated and collected. Health records, imaging, genomics, sensors, specialized electronic devices, patient portals and mobile health apps are now the norm.

Collecting data is the first step in utilizing it for healthcare benefits. The goal is to use data mining techniques, machine learning algorithms and big data to extract knowledge, interpret patterns and gain practical insights. According to Indeed, data science involves using “statistics, informatics and various methods of data analysis to collect information, process it and draw conclusions.”

Learning to manage technology and information in the healthcare field is the focus of the data science from Southeastern Oklahoma State University (Southeastern). This degree program gives graduates a working knowledge of the fundamentals of healthcare information management as well as an understanding of federal law and funding for tribal healthcare systems.

The Role of Data Science in Healthcare

The healthcare industry generates $2 trillion in data every year, and utilizing big data and analytics is essential to the success of healthcare companies. Zuci Systems notes that “as the amount of data being analyzed increases, so does the need for more powerful computing resources.” Medical imaging such as X-ray, MRI and CT scans are now being analyzed using deep learning technologies that make detecting anomalies and flaws much more reliable.

Other types of data science applications include genome sequencing and analysis, which helps to identify links between genetics and an individual’s health. Data science systems are also instrumental in drug discovery and design based on patient data insights. It’s also possible to use historical data to discover patterns and make predictions on the patient level and in population groups.

Disease monitoring and prevention are also reliant on accurate data collection and analysis. In several cases, AI has played a significant role in identifying diseases at early stages. Medical record management helps provide reliable data that can streamline the data management process and help prevent mistakes.

Wearable technology can now track heart rate, sleep patterns, blood glucose levels, stress levels and even brain activity. Machine learning algorithms can detect and track many common conditions, such as heart and respiratory diseases.

Types of Data Collected

Health information professionals encounter several types of data. The key data types include:

  • Structured data: Typically organized in an easily retrieved and analyzed format, such as tables and form fields
  • Unstructured data: Includes freeform text, which isn’t in tables or fields and contains images and other notes that require processing techniques to analyze
  • Clinical data: Relevant to a patient’s medical condition and treatment and includes test results, diagnoses, medications and other observations.
  • Administrative data: Consists of billing, scheduling and operational information
  • Electronic health records (EHRs): Electronic versions of patients’ medical records, such as clinical and administrative data
  • Research data: Includes data from clinical trials and epidemiological studies and helps inform policies and improve outcomes

Healthcare data is available from diverse sources, and since it is collected and stored in a variety of formats, it requires careful analysis to drive informed decision-making.

Healthcare Issues for Native Americans

Medical professionals working with Native Americans face unique opportunities. Having a thorough understanding of the organization and history of Native American peoples and tribes is essential to engaging with their healthcare needs.

The National Indian Health Board (NIHB) explains that the Federal government and Indian tribes have a unique legal relationship. The U.S. provides many services, including healthcare, to Indian people. The Indian Health Service (IHS) is an agency within the U.S. Department of Health and Human Services with the specific mission of delivering healthcare to American Indians and Alaskan Natives.

Current public health projects involving the NIHB include electronic case reporting to receive immediate data on reportable diseases and possible outbreaks. There are also current public health projects related to diabetes in Indian Country, environmental health, climate change and climate-ready tribes, and maternal and child health.

Becoming a Leader in Native American Healthcare Information Systems

Southeastern’s online M.S. in NAL – Healthcare Information Systems program provides an understanding of health information management and technology with a specialized focus on addressing the specific healthcare needs of Native American communities. Understanding the administrative intricacies and socio-cultural background of tribal nations prepares students to work with data science to improve healthcare delivery in Native American communities.

Learn more about Southeastern Oklahoma State University’s online Master of Science in Native American Leadership – Healthcare Information Systems program.

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