Insight-Driven Data to Real Outcomes with Healthcare Analytics

From Insight-Driven Data to Real Outcomes with Healthcare Analytics

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Healthcare companies worldwide are constantly challenged to improve outcomes, reduce costs, do more with less, and at the same time reserve time to care for their patients. Yet, the industry is paved with outdated technologies and old-fashioned strategies that no longer work in the digital era. Developing Healthcare Analytics competency among IT, HR, operation, and even marketing departments, can help organizations put big data to good use and develop actionable insights.

At a global level, healthcare Analytics is experiencing a fundamental shift from a volume-based to a value-added business model. With modern consumers wanting quality services fast and providers feeling constantly pressured to deliver better outcomes, the key to success mainly relates to one thing: advanced technology with insights-driven data at its core.

The medical and healthcare analytics market is projected to exceed $31 billion by 2022, witnessing a CAGR increase of over 27% in the period mentioned. The dynamics of healthcare are changing due to impactful factors such as breakthroughs in medicine, efficient medication for severe illnesses and infectious diseases, advanced medical equipment, and more.

How can healthcare analytics aid organizations reach the best outcomes? Read on to find out more.

Dealing with the data revolution in healthcare

Big data is now used in almost all industries around the world, starting from weather forecasting to consumer marketing. It shouldn’t come as a surprise that it has become fundamental in healthcare, too. Amid a data revolution, according to AHIMA, the industry could benefit tremendously from automating operations and streamlining processes with advanced technologies based on AI, NLP, machine learning, and more.

A study performed by the McKinsey Global Institute mentioned that business intelligence and big data applications could save organizations up to $450 billion/year in the US alone. BI-enable software is smart enough to identify underused services from the most profitable ones, therefore enabling a hospital, for example, to change its strategy so as to bring added value when caring for patients.

Bringing down barriers to analytics adoption

Most barriers linked to analytics adoption in healthcare are organizational. There are still companies that don’t believe in sharing information, not to mention that lack of understanding about the way data is used and analyzed dominates even the most experienced healthcare facilities. Lack of skill among employees is yet another barrier that can only be taken down if the business model is shifted to a digital-oriented strategy. Integration is fundamental but training among the staff is just as important.

IBM’s supercomputer Watson is a great example of analytics done right. Watson’s ability to analyze the context and meaning of the human language, as well as process outstanding amounts of data has helped Mayo Clinic successfully complete its clinical trial matching project, advance cancer treatment, and research, as well as improve patient health outcomes. Another example is Dekalb Medical which leveraged IBM’s CareDiscovery solution to reduce patient complications by 58%, save an average of 55 lives per year, and ultimately help the company save over $12 million.

Driving action to deliver value

Unless health organizations act upon the opportunities provided by advanced analytics, value cannot be delivered. The key to a good outcome is to make new insights act as a catalyst for upper management to take action. Integrating small, action-based analytics into fundamental business processes is a great start. Move up the digital transformation ladder with proper training for your company’s personnel, and little by little improvements will be made visible.

Last but not least, it pays to learn best practices from those rocking healthcare analytics, such as Impedimed, a global healthcare company that partnered with tech startup Redox to streamline the interoperability of its device with multiple EHR vendors”.

Bottom line is, that healthcare analytics are here to stay. In fact, according to the 2018 Health Trends Report done by Stanford Medicine, AI-based technologies could help reduce healthcare costs by $150 billion by 2026. Needless to say, although every company has its own goals for using tech stacks like big data or predictive analytics, at the end of the day one principle applies to all: doing whatever is needed to save lives.