Tag Archives: Artificial Intelligence

Microsoft Healthcare is a new effort to push doctors to the cloud

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https://www.theverge.com/2018/6/27/17509096/microsoft-healthcare-cloud-systems

Microsoft has been working on health-related initiatives for years, but the company is now bringing its efforts together into a new Microsoft Healthcare team. This doesn’t mean you’ll be visiting a Microsoft Store anytime soon for human virus scans, instead it’s a bigger effort to create cloud-based patient profiles, push doctors to the cloud, and eventually have artificial intelligence analyzing data.

The software maker has hired two industry veterans to help out: Jim Weinstein and Joshua Mandel. Weinstein is the former CEO of the Dartmouth-Hitchcock Health system and joins Microsoft as the VP of Microsoft Healthcare, and will work with healthcare organizations to move systems to the cloud. Mandel joins as Microsoft Healthcare chief architect, after completing a nearly two-year stint at Google as an executive for the company’s Verily venture (formerly Google Life Sciences). Mandel will be working closely with the open standards community to create an open cloud architecture for all healthcare providers.

Microsoft’s new Healthcare team appears to be a more formalized approach to the company’s Healthcare NExT (New Experiences and Technologies) company-wide initiative that kicked off last year. NExT was designed to foster health industry partnerships and bring together Microsoft’s research, AI, and cloud teams to focus on healthcare.

Microsoft is trying to find ways to move healthcare data to the cloud securely and in a way that doesn’t break strict compliance requirements for confidentiality. The new Microsoft Healthcare team will be part of Microsoft’s broader AI and Research division. “At Microsoft, we’re confident that many aspects of the IT foundations for healthcare will move from on-premise doctors’ offices and clinics to live in the cloud,” explains Peter Lee, head of Microsoft Healthcare. “We are taking concrete steps with an initial ‘blueprint’ intended to standardize the process for the compliant, privacy-preserving movement of a patient’s personal health information to the cloud and the automated tracking of its exposure to machine learning and data science.”

Lee admits the company has its “work cut out for us,” and this certainly won’t be an easy task for Microsoft. There’s an ongoing race to bring more technology to healthcare and, in particular, artificial intelligence. IBM, Baidu Google, and Alibaba are all working on similar healthcare initiatives, but IBM has struggled with its own efforts. Some analysts predict that AI use in healthcare will grow over the next decade and potentially generate huge savings for the US healthcare economy. Microsoft is clearly part of the broader race to introduce cloud technology, IoT devices, and AI into healthcare, and this new team will be responsible for that. Microsoft now plans to share more about Microsoft Healthcare later this year.

 

Epic President says EHRs are not walled off, integrations are just hard

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Epic President says EHRs are not walled off, integrations are just hard

 

 

Tapping real-time analytics to create a digitally enabled organization

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http://www.healthcareitnews.com/news/tapping-real-time-analytics-create-digitally-enabled-organization?utm_source=facebook&utm_medium=social&utm_campaign=himss18_sponsor&utm_content=siemens

As a society, we can and are collecting data in many ways. The question is not how to get more data, but how to use it effectively?

By 2020, approximately 1.7 MB of new information will be created every second for every human being on the planet.1 That is an incredible amount of data!

Yet, of all the data the world is creating both personally and professionally, less than 0.5 percent of it is ever analyzed and used.2 Analyzing less than 0.5 percent leaves a lot of opportunity on the table.

Not just volume, connection and integration

Clearly, as a society, we can and are collecting data in many ways. The question is not how to get more data, but how to use it effectively? In healthcare, how do we capture greater knowledge from the right data at the right time for truly actionable insights?

Many healthcare organizations have started down the road to digital transformation by capturing more data from various service lines with different technologies and systems. However, that information is often captured and used within silos, which limits the impact. The true transformational change occurs when we put all of the data together – i.e., integrate the data, analyze and then share those insights across the organization.

Rapid analysis, insights and action

Better integrating and connecting data is, however, only one part of the equation. Insights from big data days, weeks, months or even years later limit our ability to make corrections and find opportunities for improvements. Speed to insights from the data is critical.

Technically, the data must be made available and analyzed in time to affect decisions. For example, near real time information is typically important for clinical care decisions. Once the data, analysis and insights have been generated, the individual making the decision needs to make that information part of the workflow and the decision-making process.

The digitally enabled organization

The organization needs to build trust in and adopt these new insights as tools to assist making the best decisions for each patient at the right place at the right time. This requires making the organization a digitally enabled organization.

The digitally enabled organization leverages experience, expertise and the best data-driven insights to make the right decisions, and operate most efficiently. The digitally enabled organization is agile and is enabled by the right insights at the right time. The digitally enabled organization drives the expansion of precision medicine, transforms the delivery of care and improves the patient experience.

Witness firsthand how digital agility and the digitally enabled organization can improve patient care and engagement. For example, organizations can create data-driven solutions to patient leakage challenges and rise to their operational opportunities. The result is optimal utilization and enhanced patient experience.3

Into the future

Achieving a digitally enabled organization lays a strong foundation to adopt new tools, ways of working and driving continuous improvement. This shift also allows the organization to incorporate predictive approaches and other advanced analytics that may include artificial intelligence. A layer of trust in insights creates a powerful data-driven culture that is transformative.

Machine learning is a big idea, but hospitals need business plans first

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http://www.healthcareitnews.com/news/machine-learning-big-idea-hospitals-need-business-plans-first

machine learning and AI in healthcare

Elizabeth Clements, business architect at Geisinger Health, will be hosting a session at HIMSS18 on March 7.

Don’t get lost in the complexity of large-scale use cases.

Machine learning has the potential to transform healthcare through new knowledge discovery and improved productivity, but many health systems do not have a business plan in place to support advanced analytics beyond research and development.

As health systems consider how best to leverage machine learning and artificial intelligence, it will require a shift in IT strategy to focus on not just data, but managing the model itself. This means, among other things, defining the value of machine learning and providing a framework for evaluation and application.

Health systems need to keep things simple when moving into machine learning, said Elizabeth Clements, business architect at Geisinger Health.

“When working with new technology and developing a service from scratch, it can be easy to get lost and slow progress down with the complexity of a large use-case,” Clements said. “If you keep your scope narrow and define near-term goals, you will find you are able to make more meaningful progress in a short amount of time.”

And healthcare professionals dealing with machine learning must themselves learn how to partner with the business.

“Understanding the current and future state use of the machine learning solution is critical,” Clements said. “If you don’t consciously determine how much you want or need human intervention with the model, it will make your solution much more difficult to implement and gain buy-in.”

Clements said a simple framework for thinking about machine learning in the context of the business is needed. That includes understanding its value and use-cases before embarking on this type of analytics advancement, as well as knowing the basic challenges and how to design a program that takes those into account.

“Machine learning is the next wave of advanced processing technology offering us new avenues for information discovery and productivity enhancement,” she said. “It has the potential to transform how we conduct business; however, it will require a shift in our IT strategy.”

It is not just about the data or the application, it is also about the model itself. IT leaders should consider how to complement their existing IT and data scientist teams with new skill sets and consider how machine learning can advance existing task execution, she added.

Clements will be speaking in the HIMSS18 session, “Managing Machine Learning: Insights and Strategy,” at 11:30 a.m. March 7 in the Venetian, Palazzo D.

The 5 drivers pointing toward the decentralization of healthcare

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http://www.healthcaredive.com/news/decentralization-health-care-health-2-0-keynote/506377/

Health 2.0 co-chairs Indu Subaiya and Matthew Holt said these factors pose big questions to healthcare companies, including “What is your job in the new healthcare ecosystem?”

The decentralization of healthcare may be a great talking point and the ultimate end with patients at the fulcrum of care delivery business practices, but first, many hurdles need to be overcome.

Health 2.0 co-chairs Indu Subaiya and Matthew Holt outlined the five factors driving the decentralization of healthcare during their keynote address at the conference this week. They posed two big questions to healthcare companies, including, “What is your job in the new healthcare ecosystem?”

Holt and Subaiya shared their vision of where they see the industry going, mapping out the five drivers for the decentralization of healthcare:

  1. The new interoperability: With new standard protocols like FHIR and technology like blockchain, a new health IT paradigm could emerge where the monopoly of a user enterprise system (like an EHR platform) could disappear.
  2. Machine learning/artificial intelligence: Through the use of these tech tools, communication will change, leading to new form factors. The market has already seen the early spoils of this with products like Amazon’s Alexa and Google Home. Subaiya noted that, backed by the new interoperability, data transactions and services could become extensions of those new modalities.
  3. New entrants: One of the larger themes sprouting from 2017 is the looming question of, “What counts as a healthcare company now?” The short answer is all of them count. All of them are healthcare companies now. While that may be the cheeky answer, the fact, as Holt and Subaiya reminded the audience, is that many companies are looking into the digital health space. These new entrants are taking cues not from legacy healthcare companies but are bringing their own flavor, whether it’s offering customized nutrition plans or blending gym and healthcare business principles. What’s more, many of these companies are focused on consumer principles in an attempt to add a layer of stickiness to their core mission/product.
  4. Business model disruption: Early players in the space like Epic, Allscripts and Athenahealth have both seen changes in how they view their flagship products and all are prepping to adapt their offerings to a market that’s changed since they came to power. Largely, both consumers and clients want more functionality and capabilities to more easily interact with the products. The aforementioned new entrants are disrupting the business models for these legacy companies as well as changing the idea of what an entrant can be. Payer companies like Bright, Oscar and Clover, for example, are putting the customer at the center of their models and using technology not as an afterthought but as a core differentiator for operations.
  5. New environments: Healthcare and its care delivery services are increasingly being thought of outside of the four walls of traditional healthcare spaces. The prevailing innovative idea is to think of managing and preventing adverse health events by mixing and elevating a population’s environments. These new environments could express themselves in numerous ways such as rehabilitation parks. As Subaiya noted, health happens everywhere and these new environments could influence new players’ abilities to influence health.

The drivers that the presenters outlined point to a changing demographic where the patient is at the heart of care delivery services and wellness management while using new technology, a theme for which the conference is known for.

It’s a lot to take in, but Holt and Subaiya stated these new drivers require companies to ask of themselves “Who am I?”

For one, companies need to ask “What does value mean?” and, as Holt stated, not in the traditional venture capital way where a value proposition is another way to define why someone should give you money. Rather, what is the purpose and value a company is looking to add to the healthcare ecosystem, leading a company needing to answer “What is your new job in the new ecosystem?” Questions of who is the customer and what is the company’s job will be critical to navigate the healthcare business landscape going forward, especially since the environment is ripe for winners and losers in many facets of the industry.

While these thoughts are provocative about where the industry is heading, the business community of Silicon Valley and the policy makers in Washington, D.C., still need to recognize that those on the front lines of healthcare have a different perspective than a pie-in-the-sky take.

An article published in the new issue of Health Affairs found “hospitals’ use for patient care of data from outside providers was low, with only 18.7% of hospitals reporting that they ‘often’ used these data.”

“Our results reveal that hospitals’ progress toward interoperability is slow and that progress is focused on moving information between hospitals, not on ensuring usability of information in clinical decisions,” wrote the authors.

Thus, there may be a disconnect of current interoperability practices and where industry wants to go. The study plays on the tensions between end-users and health IT product makers, with both trying to navigate the end results to something usable and reliable.

Legacy EHR companies are looking to change. Epic is trying to incorporate more patient-sharing with Share Everywhere, for example. At Health 2.0, Allscripts CEO Paul Black stated the company is attempting to disrupt itself, or else others will come into the market and disrupt it for them. He added that Allscripts will soon be announcing different tools/offerings that seek to reimagine how a clinician interacts with a keyboard and how a patient interacts with an EHR.

Elsewhere at the conference, National Coordinator for Health IT Dr. Donald Rucker stated that new standards like FHIR and blockchain are still in an early stage of development. Technology changes in the healthcare space will largely be driven by consumers armed with apps that blend clinical data and lifestyle data. “That’s what the big drivers are and providers are sorting them out,” Rucker said.

The great technology dance between end-users, developers and policymakers continues on, but all seem to point to the need to keep the consumer at the forefront. Their businesses depend on it.

84% of Execs: Artificial Intelligence Will Transform Healthcare

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https://healthitanalytics.com/news/84-of-execs-artificial-intelligence-will-transform-healthcare?elqTrackId=c6140df4d8a94e82a5d7d8437ad150ef&elq=90c2d69c50ef46bd93f5e84b05759130&elqaid=2827&elqat=1&elqCampaignId=2613

Artificial intelligence in healthcare

Artificial intelligence has the potential to completely revolutionize the way healthcare systems interact with their patients.

More than 80 percent of healthcare executives polled by Accenture believe that artificial intelligence is on track to completely revolutionize healthcare, and a similar number believe that the advent of machine learning and digital healthcare is driving a significant restructuring of industry economics.

“AI is the new UI,” proclaims the report. “It’s a new world where artificial intelligence is moving beyond a back-end tool for the healthcare enterprise to the forefront of the consumer and clinician experience.”

“AI is taking on more sophisticated roles, with the potential to make every technology interface both simple and smart – setting a high bar for how future interactions work.”

The report envisions a healthcare environment where AI can take over the majority of processes currently overseen by humans.  Consumer relations and patient engagement are likely to be among the first tasks to undergo the shift.

Eighty-four percent of executives believe that AI will fundamentally alter how they gain information from patients and interact with consumers.  A similar number have prioritized the implementation of centralized platforms that take advantage of messaging bots and other services.

More than three-quarters believe that these decisions will make or break their ability to develop a competitive advantage over their peers in the near future.  Eighty-two percent agree that industry leadership will be defined by how well healthcare organizations architect comprehensive, seamless digital ecosystems that truly understand what motivates the choices of their patients.

“The new frontier of digital experience is technology specifically designed for individual human behavior,” the report asserts. “Healthcare leaders recognize that as technology shrinks the gap between effective human and machine cooperation, accounting for unique human behavior expands not only the quality of the experience, but also the effectiveness of technology solutions.”

 

Turning Healthcare Big Data into Actionable Clinical Intelligence

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http://healthitanalytics.com/features/turning-healthcare-big-data-into-actionable-clinical-intelligence?elqTrackId=4e2f8dd332d144279084da58c9623c84&elq=ff9dcb339dd14c5e807c6af05a723d2f&elqaid=2665&elqat=1&elqCampaignId=2463

How can healthcare organizations turn their big data assets into actionable clinical intelligence?

Healthcare organizations on the hunt for lower costs, better outcomes, and value-based care bonuses have invested heavily in hoarding as much big data as they can get their hands on.

From customer service call logs and clinical documentation to satisfaction surveys and patient-generated health data from the Internet of Things, providers of every size and specialty have fully accepted the notion that no scrap of information will go to waste in the era of machine learning, artificial intelligence, and semantic data lakes.

This may be true in the very near future. In just the past few years, the healthcare industry has made huge leaps forward in clinical decision support and predictive analytics.

The use cases for big data are proliferating rapidly as organizations move deeper into population health management and accountable care, and consumers are keeping pace with their growing demand for cost-effective services that leverage the convenience of their favorite apps and devices.

But despite the data-driven promises looming just over the horizon, the majority of healthcare organizations still have a great deal of work to do before they can turn their budding big data analytics competencies into truly actionable clinical intelligence.

A chronic lack of direction, exacerbated by deeply entrenched interoperability issues and a widespread inability to secure a qualified data science team, have left organizations in something of a slump.  A series of industry surveys from recent months point out significant staffing gaps, frustrating health data exchange roadblocks, and organizational planning deficiencies that are keeping providers from breaking through their data doldrums.

“The point of analytics is to help make better decisions on a timelier basis,” says Dr. Danyal Ibrahim, Chief Data and Analytics Officer at Saint Francis Care.  “But as we all know, there are so many times when our data ends up siloed. One component goes to the finance department, another to IT, and another to the quality improvement team.”

“So even though the data is supposed to be connected around a single patient’s story, ultimately it lands in different siloes all around the organization, and that can be a big barrier to using data to improve care.”

In order to develop a successful big data analytics initiative that can overcome every obstacle from data collection to point-of-care reporting, providers must not only understand where the challenges lie, but also what lies ahead once they overcome their issues.

What does it mean to achieve success with big data analytics, and how can healthcare providers reach their ultimate goal of extracting valuable insights from their rapidly expanding data stores?

Artificial Intelligence In Healthcare Will Make Decisions For Doctors

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https://techdigg.com/2017/03/25/artificial-intelligence-in-healthcare-will-make-decisions-for-doctors/

artificial intelligence

Artificial intelligence could soon make tough medical choices

Patients are often willing to put themselves in the hands of healthcare professionals when they need to see a doctor, and this includes accepting the technological devices that help physicians. But, artificial intelligence making vital decisions for doctors is another story.

AI is already playing a significant role in healthcare. The healthcare organization, MedyMatch says it is, “creating a new category of AI-driven diagnostic tools” and “leveraging the richness of 3D imaging, the breadth of patient-specific data, and other relevant data… to deliver precise clinical decision support directly to the physician.”

MedyMatch recently announced a major collaboration with IBM Watson Health. The aim is for artificial intelligence applications to work alongside doctors in emergency rooms and other acute care settings.

AI can use deep learning to help physicians by highlighting regions of interest that could “indicate the potential presence of cerebral bleeds in suspected head trauma and strokes.”

Better decisions from better information

So what would AI decision making in a hospital setting look like?

“Clinical Decision Support (CDS) is where the greatest opportunity exists to make an impact,” MedyMatch CFO Michael Rosenberg told TechDigg.

While it’s well known that better decision making comes from having better information, it’s also well known that healthcare professionals are constantly short of time, making it difficult to process a lot of information.

“CDS in its classical sense has been about decision trees, if this then do that… when it comes to AI, we take it to a whole other level,” Rosenberg said.

“When looking at decision support, we aren’t looking at a set of rules, but a set of considerations highlighted for the physician, whether they be statistical data looking at similar patients across a population or highlighting regions of interest.”

This also has a positive financial impact, because: “better decisions lead to better outcomes, and better outcomes mean the reduction of costly errors, which means cost savings for the healthcare system from the Provider, Patient, and Payer.”

Speaking on the relationship between artificial intelligence and doctors, and the stage that relationship is now at, Rosenberg said:

“I think we are seeing the very early stages of an evolution where the definition of a doctor changes. AI will never replace the physician, at least not in our lifetime. The physician will always be the ultimate decision maker, however that decision will be influenced by recommendations that an AI platform recommends.”

“We think of AI as a capability that can be used to enhance the work of a physician… the final diagnosis will always be the responsibility of the doctor, but it will rapidly increase the number of physicians that can perform at an expert level.”

Can we be sure artificial intelligence decisions are safe?

There are many areas of life where people are both excited and cautious about the role that AI can play. Healthcare is perhaps the number one area where the public needs to know it can trust the technology.

“The great thing in healthcare is the regulator,” Rosenberg said. “The FDA is looking out for the patient, and close collaboration between the healthcare industry and the AI provider will result in the best quality for the marketplace.”

Even the best doctors get tired and short of time, and artificial intelligence could be on hand to do the work they simply can’t do themselves.

Frost and Sullivan’s 9 healthcare predictions for 2017

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http://www.healthcarefinancenews.com/slideshow/frost-and-sullivans-9-healthcare-predictions-2017?p=0

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Uncertainty. Opportunity. It’ll all be there for healthcare in 2017, PwC says

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http://www.healthcaredive.com/news/uncertainty-opportunity-itll-all-be-there-for-healthcare-in-2017-pwc-sa/432384/

You reap what you sow. The idea is the push behind countless movie plots and rock songs but it’s also a central theme to PricewaterhouseCooper’s (PwC) Health Research Institute’s (HRI) new report on healthcare trends to watch out for in 2017. The seeds for next year were planted in 2007, according to the new report.

There will be certain uncertainty over the fate of the Affordable Care Act next year. However, many of the trends that should be on top-of-mind for hospital administrators next year will relate to value-based care, Trine Tsouderos, PwC’s Health Research Institute director, told Healthcare Dive. “If you think about the political changes as the waves on the surface of the ocean, there’s a very strong current underneath that is the shift to value-based care,” she said. “We do not see that changing. We see the shift continuing industry-wide despite any changes in Washington, DC.”

For example, only 90 or so retail clinics were in operation and about one in 10 consumers have been to one in 2016. Today, more than 3,000 such clinics have been propped up across the U.S. with one in three consumers having visited one. This drift highlights the continued move to more convenience in healthcare access as well as price transparency for patients.

Sticking with the nautical theme, Tsouderos likened the healthcare industry to a battleship in explaining why ideas from 10 years ago are now coming to fruition. It takes a long time to change the course of such a large and complex ship. “You can’t turn [the industry] on a dime,” she said.

What emerging trends administrators should know for 2017

https://www.pwc.com/us/en/health-industries/top-health-industry-issues.html