Part 1 of our new series, Spotlight on Analytics
Q: What are some of the challenges the healthcare industry is facing today?
A: Population management initiatives, service bundling programs, payor and provider consolidation, expanding regulatory oversite, an aging population, and expanding quality initiatives – all are increasing value in the U.S. healthcare industry, stretching resources, but also reducing competition.
At the same time, increased healthcare coverage has increased the number of paying customers in the industry. The growing focus on risk promises to change care planning for patients with diverse health profiles, but requires new ways of looking at patient care.
In addition, the increased availability of basic health monitoring data to individuals is helping people manage their health, but incentives for lifestyle change are still evolving. Telehealth is becoming an important healthcare/population health management tool that will likely to continue to disrupt existing on-site clinic and hospital models.
And finally (unfortunately): The growth in options for physically passive content consumption will continue to lead people down a sedentary path toward obesity and cardiovascular complications.
Q: Where do you see big data analytics fitting into the healthcare industry?
A: Increasingly, as more detailed consumer data becomes more accessible to healthcare organizations, they will be better positioned to identify health risks, manage chronic conditions, and tailor care offerings to match patient health profiles. They will also be able to better target marketing and healthcare service offerings to specific populations.
On the new treatments front, genetic factor analysis is becoming faster, easier, and cheaper. The next decade will see us looking at genetic data to better understand and predict health outcomes and guide diagnostic and treatment options.
Genomic analysis and cancer-risk profiling are a growing big-data topic, with genomic data for an individual patient taking big storage.
Natural language processing (NLP) is another big-data area that we can expect to start to impact the way we communicate and get things done. Most large vendors are using natural language processing technologies to respond to simple support and service requests. NLP is also being used to understand sentiment in a wide range of categories, often driven off of Twitter feeds. Expect NLP tools to come to your EMR or health records and analyze health risks.
This concludes Part 1 of Spotlight on Analytics, an ongoing series of blog posts. Stay tuned for Part 2!