Healthcare Evolution — Some Big Changes for Analytics and Insights

The world of healthcare data, analytics, and intelligence moves quickly. Technological innovation, patient demands, regulatory environments, and changing medical and insurance needs require that healthcare businesses adapt or fail. This need for transformation is driving thinking in the space and was at the heart of discussions around healthcare at the annual HIMSS Big Data and Healthcare Analytics Forum.

Here are some of the topics that were discussed, together with our take on how this will create innovation throughout the healthcare data and medical information space.

Clinical Intelligence and a Holistic Approach to Healthcare Data
If we want to evolve the quality of care and deliver truly next-generation patient outcomes, we need to go beyond simply capturing and reacting to specific patient and medical information. One of the main tools that can assist in evolving how we treat people is “clinical intelligence.” This is a toolset that can gather together, cleanse, analyze, and correlate medical data across multiple people, population groups, regions, conditions, and more.

Mining this data will reveal surprising insight into wellness, diseases, common causes, and the steps that medical providers, patients, families, insurers and more can take to enhance patient outcomes. It’s bringing the well-established discipline of “business intelligence” out of the boardroom and into the consulting room, giving patients and doctors the right insight to make better decisions.

Enhancing Patient Care by Looking Beyond Reactive, Individual Patient Needs
The strong drive toward value-based care is only going to get more powerful as patients focus on outcomes and a better quality of life, rather than providers trying to give as many tests and procedures as possible.

One way to deliver greater value is through proactive health management — using data and insights to suggest changes individuals can make to maintain a healthy lifestyle and enhance their own wellness. This comes about both through understanding an individual’s medical history but also tying that into further medical information for greater context. For example, family history, genetic makeup, or conditions that affect individuals of a similar population group, lifestyle, or other common factors.

This move towards proactive health management doesn’t just apply at an individual level. It can also be predictive of larger health issues within a population and help medical providers prevent these problems from occurring, and dealing with them effectively if they do.

Discovering Trends and Correlations in Healthcare Data
Access to large healthcare datasets, coupled with the proper level of granularity, will allow researchers and analysts to make insightful predictions on regional or population-wide health changes. This will help health providers deal with long-term shifts in diseases, conditions, and wellness. Coupled with proper policy, this can lead to much better preventative care and enhanced patient outcomes.

Taking Advantage of Precision Medicine and Real-Time Analytics
Medicine and effective treatments are becoming more personalized. From bespoke drug combinations to individual diagnostics, healthcare providers are moving towards treating the patient rather than the condition. This type of precision medicine will become more powerful as real-time analytics allows for immediate insight into how effective a treatment is, not just for that patient, but for others who have extremely similar characteristics.

This is an exciting time in the healthcare field. As we think of new ways to use medical information, the opportunity to gain real insight on healthcare data protection that leads to better patient outcomes is becoming a reality.

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