Big Data has transformed the way patients, providers and payers manage, analyze and leverage data in healthcare. Healthcare Analytics brings together business intelligence and data visualization tools that provides real-time information to support decisions and deliver actionable insights.

Healthcare analytics have the potential to reduce costs of treatment, aid patient care efforts, improve medical procedures, streamline operations, predict epidemics outbreaks, avoid avertible diseases, manage health system donor engagement, analyze existing claims and improve the quality of life.

Real World Use Cases Big Data Analytics in Healthcare:

  1. Clinical Decision Support (CDS) – It analyzes medical data, providing health providers with real time guidance as they make prescriptive decisions. Propeller Healthn, a mobile health platform for managing chronic respiratory disease has started using inhalers with GPS-enabled trackers to identify asthma trends both on an individual level and looking at larger populations. This data is being used in conjunction with data from the CDC to develop better treatment plans.
  2. Claims, Clients and Premium Management – For Insurance Payers, healthcare analytics offers a granular process to track existing claims, clients, and premiums. With improved real-time measurements and historic visualizations, payers can adjust policies, manage open claims, and offer better prices for services.
  3. Personalized Treatment and Healthcare Outcomes – Healthcare Analytics in multifaceted healthcare marketplace assists the healthcare organizations treat their patients in a holistic manner, delivering personalized treatments and improving patient healthcare outcomes.
  4. Patients Predictions for an Improved Staffing – Health Systems are using historical admission data to analyze relevant patterns in admission rates. They are using machine learning to find the most accurate algorithms that predicted future admissions trends. This will resolve problem of having too many healthcare staff, causing unnecessary labor or too few healthcare staff, leading to poor customer service outcomes.
  5. Wearable and Smart Devices for patient engagement – Healthcare Analytics has becoming increasingly popular tool for patient engagement in form of wearable devices which keeps patient’s informed about their steps, their heart rates, sleeping habits, exercise, diet and other health alerts. A chronic insomnia and an elevated heart rate can signal a risk for future heart disease. Many payers and employers are promoting healthcare analytics and smart devices to promote healthy lifestyle.
  6. Management of Opioid Crisis – Data Scientists at Blue Cross Blue Shield have started working with analytics experts at Fuzzy Logix to tackle the Opioid emergency. Using years of insurance and pharmacy data, Fuzzy Logix analysts have been able to identify 742 risk factors to prevent Opioid Abuse in US.
  7. Informed Strategic Planning – Care mangers can analyze check-up results among people in different demographic groups and identify what factors discourage people from taking up treatment. University of Florida made use of Google Maps and free public health data to prepare heat maps targeted at multiple issues, such as population growth and chronic diseases leading to Informed Strategic Planning.
  8. Cancer Treatment – Medical researchers have started using large amounts of data on treatment plans and recovery rates of cancer patients to find trends and treatments that have the maximum rates of success in the real world. For example, researchers can examine tumor samples in biobanks that relate to patient treatment records. Using this data, researchers can understand things like how certain mutations and cancer proteins interact with diverse treatments and discover trends that will lead to better patient outcomes. This data can also lead to unexpected benefits, such as finding that Desipramine, which is an anti-depressant, could benefit cure certain types of lung cancer.
  9. Data-driven Decision Making – Healthcare Providers can make data-driven decisions within seconds and improve patient’s treatment. This is particularly useful in case of patients with complex medical histories, suffering from multiple conditions. New tools would also be able to predict, for example, who is at risk of diabetes, and thereby be advised to make use of additional screenings, manage weight and changes in life style. \
  10. Fraud Detection – Healthcare organizations have started using analytics to help prevent security threats by recognizing changes in network traffic, or any other behavior that replicates a cyber-attack. Healthcare Analytics can benefit in preventing fraud and inaccurate claims in a systemic, repeatable way. Analytics support streamlining the processing of insurance claims, enabling patients to receive better returns on their claims and providers get paid faster. Centers for Medicare and Medicaid Services, using analytics said they saved over $210.7 million in frauds in just a year.
  11. Chronic Disease Management through Telehealth– Providers use telemedicine to provide personalized treatment plans and prevent hospitalization or re-admissions. By keeping patients away from hospitals, telemedicine reduces costs and improves the quality of care. Patients can avoid waiting lines and providers evades wasting time for unnecessary consultations and paperwork. This allows providers to envisage acute medical events in advance and avert deterioration of patient’s conditions.
  12. Interpreting Medical imaging to automate the detection of abnormalities – Medical imaging is frequently used in routine, preventive screenings for cancers, such as breast cancer and colon cancer. In breast cancer, microcalcification in tissue can regularly be difficult to conclusively identify as either malignant or benign.  False positives could lead to unnecessary invasive testing or treatment, while missed malignancies could result in delayed diagnoses and worse outcomes. Analyzing and storing manually medical images such as X-Rays, CT Scans, MRIs is expensive both in terms of time and money, as radiologists need to examine each image individually, while hospitals need to store them for several years. Algorithms developed analyzing hundreds of thousands of images could identify specific patterns in the pixels and convert it into a number to help a physician with the diagnosis. Healthcare Analytics can reduce the false negative rate, patient risk, and medical legal risk for the radiologists.
  13. Donation Management – Hospitals and Health Systems are using Healthcare Analytics to track and plan donor engagement, retention, and previous contributions.
  14. Advancing the use of Immunotherapy – Immunotherapy is one of the most promising paths for treating cancer. Healthcare Analytics ability to produce highly complex datasets enables discovering new possibilities for targeting therapies to an individual’s unique genetic makeup.
  15. Reducing the risks of Antibiotic Resistance – Antibiotic resistance is a growing threat to populations around the world as overuse of these critical drugs nurtures the evolution of superbugs that no longer respond to treatments claiming thousands of patients lives every year. Healthcare Analytics improves accuracy and creates faster, more accurate alerts for healthcare providers.

Since 1989, Integrated Systems Management, Inc. (ISM) has provided software engineering and information technology solutions that help organizations solve a broad range of business challenges, capture unforeseen opportunities, and achieve impressive results. We are focused on providing Analytics, Artificial Intelligence (AI), Interoperability, Integrations and Customer Software Applications. ISM has extensive experience in FHIR (Fast Healthcare Interoperability Resources). With headquarters in Hawthorne, NY, we have created a 24-hour development and support platform that offers our clients faster turnaround and excellent quality, at very affordable rates. We have more than 200+ pool of skilled software professionals. We aggregate 500+ Years of healthcare domain development, maintenance and support experience.

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Source: Datapipe, Modern Healthcare