After the keynote, attendees can learn about real-world examples of digital transformation in the healthcare and government track case study sessions. We’re thrilled that our partner KenSci will be sharing how it’s helping providers use machine learning to improve health outcomes and reduce costs as part of the healthcare track.

KenSci customer Fullerton Health used advanced analytics and machine learning to immediately identify over a million dollars in fraudulent and questionable claims as Tom Lawry wrote recently. It also helped an employer reduce the costs of managing the health of an employee population with chronic conditions by 60 percent. Next up, Fullerton Health plans to apply machine learning to improve its evidence-based medicine initiative and help clinicians predict the next best step for a patient.

In its session at the Japan CityNext Forum, KenSci will share how providers can identify population health risks, improve care outcomes, and streamline patient flow through the hospital with its Clinical Analytics solution. Usually providers only have the time and tools to look at a limited number of variables about a patient to determine a diagnosis and treatment. But machine learning can sift through oceans of data to bring valuable insights to the surface. With the right machine learning solution, providers can not only get a closer look at each patient’s history, they can foresee future risks and get suggestions on how to provide the most effective care.

Helping physicians prioritize time and make better-informed decisions is exactly what the KenSci Clinical Analytics solution is designed to do. The solution, built on trusted Microsoft Cloud technology, is the world’s first vertically integrated machine learning platform for healthcare. It delivers risk predictions to providers in the context of their daily workflow, using machine learning models that mine millions of records from public and customer data sets—like claims, EHR, ADT, financial, and patient-generated data. These insights can help clinicians base decisions on dynamic analysis that gets more precise every day.

Empower your care teams with machine learning—starting now

The KenSci Clinical Analytics solution takes advantage of more than 180 pre-built machine learning models, delivering a substantial return on investment in just 12 weeks. Plus, it integrates easily with existing EMR systems—so care managers and care providers aren’t slowed down by having to learn and use a separate interface.

If you’ll be at the Japan CityNext Forum, attend the healthcare track case study session #3 to learn more. You can also read about the solution in this blog by David Turcotte, Global Industry Director, Public Sector, Microsoft.

And you can try the solution today on Microsoft AppSource.

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1. Improve independence via remote care
2. Keep the elderly connected to their families with technologies like Skype, email, and social media
3. Involve the elderly in their community to help them feel involved and active
4. Productivity of the healthcare system to help healthcare professionals spend more time on patient-facing activities

These four priorities can be met by creating policies that allow technologies like the cloud, data sharing, sensors, and predictive analytics. Data sharing between healthcare workers, pharmacists, and the patients enables integrated and personalized healthcare. Predictive analytics can help identify accidents or health concerns before they occur. Cloud empowers all of the technologies to work, will help create an efficient work flow, and improve productivity.

2026 may feel far away, but with incremental changes starting now, we can vastly improve healthcare for the elderly.

The post The world in 2026: how should we care for the elderly? appeared first on Microsoft Industry Blogs.

In early September, our Microsoft Health Asia team attended and presented at Hospital Management Asia in Yangon, Myanmar. While I was there, I had the privilege of meeting many brilliant and forward-thinking people. One of the mornings of the conference, Dr. Andrew Winnington—whom I’d met the previous day and who is the brainchild behind XY Leap, an exciting health IT startup—took a swab of saliva and cells from the inside of my mouth. He put it in a vial, labeled it, and said, “In three weeks’ time, I’ll send you an analysis report that will show you what XY Leap does.”

And sure enough, three weeks later, I receive an incredibly comprehensive report predicting how my body will likely respond to various medications, exercises, and foods given my genetic profile. It predicts my genetic risk of diseases such as Type 2 Diabetes and heart disease and how I can best prevent these chronic conditions. It provides information about how I would typically respond to surgery or injury and the best recovery methods for my genetic makeup. Plus, much more.

The XY Leap analytic platform brought together my genetic data with thousands of medical research papers to derive the predictive insight provided in the report. What’s more, the report is constantly updated as new research comes out. It’s stored online and only I have the ability to access it at this point.

Nothing is absolute, of course. But the report basically tells me that research has shown that other people with similar gene markers have had this level of disease risk, or responded to certain pharmaceuticals, exercises, diets, injuries, and so on, in these ways.

Now that we have the capability to do this type of analysis, what does it mean for the future of healthcare?

Incorporating genetic predictive insight into their decision-making process can help clinicians provide personalized treatment and guidance for their patients. For example, they can use such insight to help them prescribe the most effective medication for a patient’s genetic profile. They can also use it to avoid prescribing a medication to people more likely to suffer from an adverse reaction to it based on their genetic markers as discussed in this recent article in The Atlantic.

As the field of genomics analytics evolves and clinicians become increasingly confident about using it as part of their decision-making processes, how can the right insight be surfaced at the right time for health professionals? In other words, how could this type of genetic guidance for personalized medicine be part of the standard clinical process and built into the clinical applications that health professionals use?  How could it be tied together with the patient information that clinicians capture? And how do we make sure that we can simultaneously gather and combine all this personalized information, while protecting patients’ privacy?

As science and technology progress, we’ll need to answer these questions and so many more. But it’s an incredibly exciting future that holds the promise of empowering doctors and patients alike with personalized, predictive insight that could lead to better clinical outcomes, healthier lifestyles, fewer chronic conditions, and reduced medical and drug complications.

Please let us know if you have any questions or feedback via email, Facebook, or Twitter.

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That’s what makes events like the Healthcare Innovation Solution Day Series so valuable. This series of one-day regional conferences brings together organizations like Microsoft and healthcare IT stakeholders to talk about health innovation and strategies. This fall, Microsoft participated in Healthcare Innovation Solution Day events in Taipei, Hong Kong, New Delhi, Jakarta, Bangkok, Manila, and Kuala Lumpur. Each conference was filled with discussion about amazing new innovations that will transform healthcare in Asia in the years to come.

Here are the three key trends that were a key focus at all the conferences:

• It’s All About the Cloud
  The rapid rise of cloud computing platforms such as Microsoft Azure continues for many healthcare organizations. It’s easy to see why: it’s often been too expensive for healthcare providers to acquire new technology. This is particularly true in many emerging markets, where organizations are challenged to find affordable solutions. By moving to the cloud, providers can move from an economic model where they’re spending a lot upfront to a much more cost-effective and flexible consumption-based model where they get to pay for what they need rather than what might be.
• Mobility Is On the Rise
  Like many other industries, healthcare is seeing the value of using mobile solutions. At the conferences, I heard a lot of excitement around mobility, and about how using pen and paper at the front line of patient care is coming under fire from providers who want to do things differently. For a growing number of healthcare organizations, touch-based technologies like Microsoft Surface are quickly changing the dynamic to one of speed and efficiency.
• Providers Want More from Their Data
  It’s becoming more and more important for healthcare organizations to derive insights from their data in more intelligent ways. The needs are going to be different depending on whether an organization is in a developed or developing economy, but the goals are very much the same: using data analytics and business intelligence technologies like Microsoft Power BI to make better business decisions.

Getting from where we are today to where we need to be will demand a strong focus and commitment from governments to drive technology investment from the right places. But as I saw at the regional conferences in Asia, there is some real technology innovation momentum going on right now in healthcare, and a great cast of passionate people and participants who believe in the change that can be mustered. I can’t wait for next year’s conferences to discover how much bigger that momentum has grown.

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