The healthcare industry is undergoing an IT revolution of sorts, having recognized the transformational power of technology both in streamlining business processes and improving patient care. According to a study by BCC Research, the healthcare analytics market will reach an estimated $16.9 billion by 2020.

There are several reasons for this. On the operational front, Government regulations, the need for compliance as well as high cost of hospital equipment have made hospital management more complex. At the same time, there is a significant increase in the number of people seeking medical care thanks to aging populations, sedentary lifestyle induced diseases and general awareness about health.
But most importantly, there is also a clear understanding of the immense opportunities that analytics presents towards improving the quality of medical care through predictive analysis etc.
Predictive analytics to identify at-risk patients
One of our clients, a leading provider of in-center and at-home dialysis services in the U.S., was able to use analytics effectively to identify patients at high risk of readmissions; thereby reducing readmissions through appropriate intervention in high-risk cases.
The hospital had found that at least 20% of patients discharged had to be readmitted within 30 days due to complications. This was problematic because it increased patient care cost by 25-30%, not to mention greater patient dissatisfaction. To help counter the problem, we developed an analytics solution with three risk models – potential hospitalization, expiration and transfers to other facilities.  The solution enabled the hospital to assign a risk score to each patient and generate a pursuit list of high risk patients for appropriate intervention. It also helped identify key factors that caused high risks and helped client take necessary actions. Disease clustering techniques helped the hospital authorities understand how hospitalization, expiration and transfers fared, based on disease conditions. The solution has been able to predict readmission with 80% accuracy based on the three risk models, thereby helping the hospital reduce costs associated with readmissions and also reduce the related penalties.
The future of healthcare analytics is almost here
At Dartmouth-Hitchcock Health System in the Upper Connecticut River valley, Microsoft has teamed up with ecosystem partners to pilot an unprecedented solution called ImagineCare that is highly coordinated, intensely personalized and encompasses physical, mental and emotional health.
Built using Microsoft technology for machine learning, big data storage and processing as well as perceptual intelligence, it provides a cloud-based system in which nurses and health coaches track and respond to an individual’s health status in real time, irrespective of their location. Data from sensors and devices such as blood-pressure cuffs, pulse oximeter devices and activity trackers like Microsoft Band are transmitted via smartphone to the Azure cloud. From there, it’s pulled into a Cortana Analytics Suite dashboard at a “contact center” staffed 24/7 by registered nurses who have a singular view of each customer’s personalized care plan. When a person’s data exceeds a custom-prescribed threshold, an alert is sent to the nurse, who then reaches out to the customer via phone call, video chat or secure text — often before the person even knows there’s a problem.
What is absolutely mind blowing is the system’s ability to track mental and emotional health using the perceptual intelligence capabilities of the Cortana Analytics Suite. It monitors Twitter feeds and other social media to perform a sentiment analysis; it can also perform speech and tone analysis during interactions with ImagineCare nurses and it has a mobile app that invites timely mood check-ins.
And the number of patients enrolled goes up, machine learning provides an opportunity to continuously improve care plans based on a deep understanding of all the data generated, thereby improving care for all. If such a solution becomes mainstream, one can only imagine the massive impact on public health.