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Developing technology can offset growing cost of healthcare

Technology such as machine learning and patient engagement platforms can lower the cost of healthcare and aid better population health management.

The rising cost of healthcare has been the focus of many political campaigns and part of the motivation for healthcare reform. Healthcare costs are increasing at an unsustainable rate, largely due to the number of patients that receive care for costly chronic diseases.  Treating patients with chronic diseases accounts for about 75% of the $2 trillion spent on medical care in the U.S. every year, according to the Centers for Disease Control and Prevention.

Federal and state initiatives, physicians, other healthcare entities and patients have all been part of the health IT transformation. The healthcare industry has shifted into the digital world, resulting in the adoption of EHRs, HIE and mHealth apps. These changes haven't lessened the desires of patients and providers to improve care outcomes and reduce the cost of healthcare. So, healthcare professionals are left wondering what technology and innovations can help the industry manage population health at a lower price tag.

Data analytics and machine learning are two outlets that providers can use to crunch population health data, providing them with significant insights in the following ways.

Early detection of disease outbreaks

Recent Ebola outbreaks brought the potentially fatal disease into the public eye. Media coverage contributed to the hysteria, but magnified the importance of early outbreak detection. A patient population can benefit from both a reduction in mortality rate and lower costs when a technology such as machine learning is used to analyze a disease in the early detection stage. The use of advanced analytics can provide the Centers for Disease Control and Prevention and other public health agencies with a head start in combatting the spread of illnesses. The Defense Advanced Research Projects Agency estimates"a two-day gain in detection time and public health response could reduce fatalities by a factor of six."

Machine learning is a field of data science in which data is processed through advanced algorithms and computing systems for the purpose of predictions and analytics. It has been used for financial modeling for years, and has begun to find its way into the healthcare arena.

Integrate behavioral health and acute care

Research has linked behavioral health to outcome improvements in patients with chronic diseases. As a result, there have been several initiatives to include mental health information as part of overall patient data and treatment plans. The ONC's interoperability roadmap details changes to medical record-keeping that would ensure all relevant health data is included in patient records. Within the technology space, Ginger.io has introduced a product that gathers patients' self-reported data and sensory data collected from their mobile devices and offers it to care providers as a warning system of behavioral or physical stress, or simply as another channel through which patients can be monitored.

Rise of technologies supporting health and wellness

Both the private and public sectors are eager to lower healthcare costs. Some providers face rising insurance premiums and possible financial penalties if they fail to satisfy key performance indicators.

Patients and providers want to avoid spending more on healthcare. This desire created an opportunity for new companies to create products that help patients get more involved in the long-term management of their health and any diseases they may have. Patient engagement platforms such as Welltok, Inc.'s CafeWell Concierge -- powered by IBM's Watson supercomputer -- track fitness and lifestyle data, and incentivize patients to hit personalized health goals.

Numerous factors affect population health, including policies, healthcare practices, research for cures and disease prevention. Big data, artificial intelligence, machine learning and advanced analytics are examples of technology that can be applied to improve population health. As the field of data science gains more popularity in healthcare, the industry will see a surge in the value of data, which will help reduce the long-term cost of healthcare.

About the author:
Reda Chouffani is vice president of development at Biz Technology Solutions Inc., which provides software design, development and deployment services for the healthcare industry. Let us know what you think about the story; email editor@searchhealthit.com or contact @SearchHealthIT on Twitter.

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This was last published in March 2015

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