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How Data Analytics Revolutionize The Healthcare Industry

Αrtificial intelligence tools, cloud computing platforms, machine learning models and blockchain networks will affect nearly all areas of healthcare.

No sector is expected to feel the impact of data analytics more than the ever-changing healthcare industry.

It is no chance that the global market for data analytics in healthcare was valued at $26 billion in 2019 and is expected to increase at an annual growth rate of 7.5% from 2020 to 2027, according to Grand View Research.

From cancer treatment to drug discovery and disease prevention, data analytics are expected to transform the provision of healthcare services.

The continuing geometric growth in the amount of data available and the application of advanced analytics techniques, such as artificial intelligence tools, cloud computing platforms, machine learning models and blockchain networks, will affect nearly all areas of healthcare. These include, inter alia :

  • early detection of disease

  • discovery of new drugs, automation of hospital administrative processes

  • personalization of patient care

  • more accurate calculation of health insurance rates

Here are 6 real-life applications of healthcare data analytics, according to Built In and HealthITAnalytics:

  1. researching cures for cancer

  2. conducting early disease detection

  3. improving patient documentation

  4. delivering telehealth services

  5. removing human bias for better outcomes

  6. managing financial error and risk

4 impactful benefits of data analytics in the healthcare industry

Maryville University summarizes the benefits of healthcare analytics in four categories :

  1. Analyzing clinical data to improve medical research. By gathering and analyzing clinical data from various sources, such as EHRs, electronic medical records, public health records and personal leath records, data analytics are applied to improve research efforts in many health-related areas.

  2. Using patient data to improve health outcomes. Through analyzing patient data, including blood sugar levels, blood test results, temperature, but also the patient's own wishes for care, healthcare providers can better identify at risk populations, lower readmission rates and reduce errors.

  3. Improving the quality and efficiency of healthcare. To achieve this, a combination of an organization-wide assessment of current conditions with the institution's goals is needed. The operational areas most likely to benefit from data analytics are emergency preparation, employee scheduling, administration, financial management, and compliance.

  4. Improving staffing through health business management analytics. Balancing the need to contain costs and improving efficiency in the provision of healthcare services with the growing shortage of well-qualified medical professionals is key to healthcare providers. According to data, labor cost account for about 60% of all hospital budgets, while the increasing demand for healthcare staff is expected to drive salaries higher in the future. Data analytics is applied to manage labor costs while simultaneously improving the quality of care patients receive. A worth-mentioning example is Hawaii Pacific Health (HPH), one of the largest healthcare systems in Hawaii, which was able to save $2.2 million over 16 months while maintaining high-quality outcomes by adopting a data-driven approach to labor management.

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