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Good Talks and Real Health Care Reform

Bill Calhoun   |   July 17, 2012    2:18 PM ET

Many of us want to make a real difference in our world. So let's make a real difference in health care. Real health care reform is in our hands. It's between the patient and the doctor and the neighbor and family members. We are the key players.

We need the help of Congress and the State Legislatures to leverage corporate health providers to change from the business of illness to the business of wellness, from profit over people to helping people be well. But in our neighborhoods, you and I are the real difference makers until health care becomes accessible and affordable.

What does this look like?

Start with good talks. Engage in good talks within yourself and with family members and also good talks with the medical community. Consider two recent examples.

First, IBM made more money for its stockholders by dramatically cutting its health care costs. How? IBM made two simple moves: adding good talks between the medical staff and the patient and getting IBM workers to exercise more. The good talks between patient and staff happen in primary care offices. After the patient has 10 to 15 minutes with the doctor, the patient sits down with other office staff to talk over understandings of drugs, procedures and life style [exercise, relaxation, friendships]. Exercise is not only encouraged at home, but through access to facilities and time during the workday. IBM health care costs were reduced dramatically and the health of the employees improved significantly.

Second, Medicare can be a healthy financial tool if two factors are in place. One, Medicare fraud is significant and this fraud must be addressed by stronger government attention. Two, more good talks. A huge segment of Medicare costs come during an older person's last few months of life. If doctors would have the courage to have better listening talks with patients and patients' families about choices of procedures and drugs and simpler comfort options, my 40 years of pastoral experience is that the majority of patients choose the simpler path of less procedures and more quiet peace with family at the end of life. To choose this path, patients not only need good listening talks with the doctor, reviewing the options, but also time to think about it, to make their own choices. And as more patients choose the simpler comfort path, less expensive procedures and drugs are ordered and Medicare costs are reduced significantly.

Both of my aging parents had good reflective self-talks through which they chose, on their own, the route of fewer procedures and drugs. In both cases, the attending doctors were upset... either because they have pressure to recommend procedures or because they were trained to keep people alive, when both my folks desired to live with fewer procedures and less drug discomfort even if for a shorter time. In an ER one night as my mother finally won the battle with the doctor, she chuckled as she rightly said: "My contribution to reducing Medicare costs."

Many have said: 'take charge of your health.' Ask questions. Listen to your own insights. Listen to the guidance of the medical community. Do your own research. Be open to the right steps and the wellness that is right there. Scripture from our faith traditions have a major focus on lives turned around through healings. Among other healers, Elijah and Jesus look deeply into the life and spirit of the one before them. They see in the person to be healed the individual choice, faith, longing, to pursue wellness, to be well!

My deepest hope and prayer is that across our country there will be more good talks among the players [family members, friends, medical staff] and more individuals taking charge of their heath. The result will be a healthy nation and lower health care costs.

Is it Time for Healthcare to Engage Patients as Consumers?

Harry Reynolds   |   May 1, 2012    1:07 PM ET

What if your physician knew you as well as a personal shopper? Or how about if your health insurance provider could suggest the most advantageous plan the way your cell phone carrier recommends the latest family plan?

While the tongue depressor hasn't changed in years, new influences such as social media, the mobile revolution and higher expectations from consumers are forcing healthcare organizations to rethink the way they deal with patients.

We are entering the age of the empowered health consumer. Consider that 50 million consumers will enter the individual and exchange insurance market by 2017. Additionally, a 40 percent decline in group health care coverage is expected by 2017. Meanwhile, annual private healthcare spending will increase by $430 billion by 2015.

Consumers now have unprecedented access to information about medicine and health care. As a result they're becoming more demanding and better informed about the care they receive. Combine this new reality with the transition going on in healthcare and the industry will certainly face looking at patients and their health differently. Many organizations are even rethinking their business models.

This week during the World Health Care Congress in Washington, D.C., we're discussing this new reality and the need for healthcare to be more consumer focused. Together we'll explore what it will take to enable healthcare providers and insurance companies to connect and collaborate with patients better.

Taking a page from the retail industry playbook, can these types of organizations apply the retail mentality to better understand and influence consumer behavior through vast amounts of data? In all of this, analytics is key. Understanding the individual and providing a more personalized view of the patient will help organizations compete in a new era of healthcare transformation. This kind of insight can be used to keep patients healthier.

We are barreling through unprecedented change in the healthcare industry. Everything is changing with new competitors, new opportunities and new challenges. One thing is clear, better information just might enable better care.

A New Era of Computing: IBM Research Helps Doctors Choose Best Care Options for Individual Patients

Steve Hamm   |   March 29, 2012    2:34 PM ET

This is the latest in an occasional series of posts about A New Era of Computing. IBM envisions a monumental shift over the coming years: computing will be ubiquitous and machines will learn from their interactions with data and humans-essentially programming themselves. This quantum leap will be enabled by advances in artificial intelligence, data analytics, computing systems and nanotechnology. It will result in a smarter, better planet.

What if any doctor in the world had access to the expertise of the best doctors in the world when choosing among treatment options for an individual patient? That's the vision that's driving a small group of scientists at IBM Research - Haifa.

Their work is getting it's first real-world tryout with Fondazione IRCCS Istituto Nazionale dei Tumori, a public health institute in Milan, Italy, which specializes in the study and treatment of cancer. The IBM Research project, called Cli-G, for clinical genomics research, is a biomedical analytics system that uses machine learning, among other technologies, to provide physicians with treatment advice tailored for an individual. The Cli-G system combines a wide variety of data, including statistical records of the outcomes of particular treatments, clinical and genetic information about the particular patient and the expertise of top physicians. "We're incorporating the knowledge of experts-all the things the physician brings in from past experience," says Boaz Carmeli, the IBM researcher who leads the project.

Cli-G is a cousin to IBM Watson, the deep question-and-answer technology that beat two past-champions at the Jeopardy! TV quiz show and which is now being used in healthcare and financial services. Both are learning systems. While Watson focuses primarily on gathering unstructured textual information from published sources, Cli-G is aimed at gathering specific types of information. Carmeli and his colleagues have coined a term, Evicase, to describe the way they structure information. It's a combination of evidence-based medicine, which is statistical analysis of treatment outcomes, with case-based reasoning, which is knowledge gathered by studying the best practices of top physicians. Scientists in IBM Research are exploring how Cli-G and Watson could be used to compliment one another.

The project grew out of a long-term effort by IBM's Haifa scientists to develop a network that every party involved in healthcare delivery can tap into to share information. Cli-G adds sophisticated analytics to the network. The technology uses all of the information available to predict the most likely outcomes for a particular patient for various treatment options. Then, based on Evicase, it recommends what it considers to be the best treatment.

The Istituto plans on using Cli-G in two ways. In addition to the decision-support tool for its physicians, the organization will be able to get an aggregate view of patient care-enabling it to evaluate the performance of various departments or teams, and using this knowledge to make changes that could improve results. Already, the Haifa researchers have provided the Istituto with analysis of some of its clinical treatment data, which identifies situations where physicians deviated from standard treatment guidelines and tracks the outcomes.

This engagement is just the first of what the Haifa researchers hope will be several similar partnerships with healthcare organizations. They hope to branch out beyond cancer treatment to other important disease areas including HIV/AIDs and hypertension. "There's a tremendous amount of care data around the world, but it's not being used," says Carmeli. "Now we can use it and provide better care for patients. There are exciting possibilities."

We're still a long way from being able to provide a global expert system for physicians, but we're taking important first steps toward that goal.

Learning Machines: Watson Could Bring Cancer Expertise to the Masses

David Kerr   |   March 29, 2012    2:28 PM ET

Cancer is the second most common cause of death in the United States, and, according to the American Cancer Society, more than 1.6 million new cases are expected to be diagnosed this year. Discoveries in molecular biology and genetics in recent years have produced new insights into cancer biology, but these advances have also ratcheted up the complexity of diagnosing and treating each case.

The disease is one of the most important fields of medicine, yet it's devilishly complex and there's too much information for any single practitioner to keep up with.

A collaboration announced today between Memorial Sloan-Kettering Cancer Center in New York City and IBM could revolutionize how physicians in the United States and worldwide get access to world-class information about cancer.

Our two organizations are combining IBM Watson's natural language processing and machine learning capabilities with Memorial Sloan-Kettering's clinical knowledge and repository of cancer case histories. We aim to develop a decision support tool that can help physicians everywhere arrive at individualized cancer diagnostic and treatment recommendations for their patients based on the most complete and up-to-date information.

I credit leaders at Memorial Sloan-Kettering for envisioning a way to have a huge impact on cancer treatment worldwide. Patricia Skarulis, the organization's chief information officer, first approached us last April, shortly after she watched the Watson computer defeat two past grand-champions on the Jeopardy! TV quiz show. She said MSK had collected more than a decade's worth of digitized information about cancer-including treatments and outcomes for all of their patients-which could be mined for insights and made widely available.

She thought Watson could help. We decided to work together to try to make that happen. And, today, we believe the goal is attainable.

Since Watson's television victory last year, IBM has been on a path to improving the technology. We're making it possible for people to engage Watson in ongoing dialogues aimed at surfacing the most useful insights. After receiving an initial query, Watson will be able to ask for additional information to help it understand more precisely what the human wants to know. Also, people will be able to view the logic and evidence upon which Watson makes a recommendation.

Memorial Sloan-Kettering's oncologists will assist in developing IBM Watson to use a patient's medical information combined with a vast array of medical information-including an extensive library of medical literature, diagnosis and treatment guidelines, a database of MSK cancer cases and the institution's knowledge management system. Watson will learn from its encounters with clinicians. It will also get smarter as it amasses more information and correlates treatments with outcomes.

Our two organizations will spend most of this year loading Watson with information. This data will be used to train a version of Watson created specifically for this task. Then, starting late this year and continuing in 2013, we'll run a pilot program focused on the diagnosis and treatment of a handful of cancers, including lung, prostate and breast cancer.

Memorial Sloan-Kettering is one of the most accomplished cancer treatment centers in the world. But, when you do the math, you see that only a small percentage of cancer patients are able to receive care at MSK and other world-renown institutions.

The vast majority of patients are treated by physicians who don't have access to the more advanced knowledge that MSK oncologists possess. If MSK and IBM succeed at developing an effective decision-support tool, physicians anywhere could potentially have access to the knowledge of some of the field's top experts-and more cancer patients could get better care no matter where they live in the world.

Can you think of other fields where IBM Watson could help bring specialized expertise to the masses?

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Here's a link to a post about the hookup between IBM and WellPoint, the giant health benefits company, which is complimentary to the MSK relationship.


Smarter Healthcare: Let's Pay Doctors to Keep People Healthy

Dr. Paul Grundy   |   February 21, 2012    7:47 AM ET

As a medical doctor, I'm concerned about many aspects of the changes taking place in heath care.

But I'm also excited, because we have the opportunity to make health care a lot better. It's a chance to change to a system of keeping individuals healthy, rather than performing procedures for payment. We can improve individuals' health by creating a smarter health care system that uses comprehensive information technology.

Things need to improve. U.S. health care spending has risen sharply, adding up to nearly $2.6 trillion in 2010, which is 10 times more than we spent in1980 and more than 50% higher than any other country. The costs threaten to make the U.S. uncompetitive.

And all that spending isn't buying great results. The Commonwealth Fund's third national health care scorecard last year found that the U.S. ranks last out of 16 developed countries when it comes to deaths that could have been prevented by effective medical care.

One reason is that the U.S. is behind in information technology systems for health care, according to the Commonwealth Fund's research. Even though the U.S. is the world's leader in computer systems and software, our huge health care system lacks sophisticated electronic systems.

The nation's health care system has had difficulty in developing seamless interaction among computer systems because of multiple physicians, hospital systems, government and private insurers. Rivalries among payers and suspicions by care-givers sometimes discourage open sharing.

The situation needs to get better. And we're talking about how to do so at the Healthcare and Information Management Systems Society Conference Conference, which is holding its annual meeting in Las Vegas now through Feb. 24.

The push to adopt electronic medical records by 2015 could bring big improvements. When a comprehensive record is accessible to any doctor who sees a patient, the result should be fewer unnecessary tests and fewer cases of prescribing medicine that could dangerously interact with a patient's existing prescriptions.

The creation of regional health information exchanges will also allow better sharing of clinical health information. After all, 90 percent of healthcare is delivered locally.

Patients must also become part of the information stream. There are plenty of easy-to-use, low-priced monitors for blood sugar and blood pressure. Connecting patients' information to computer systems could provide much more detailed information about chronic conditions.

If doctors were paid for keeping patients healthy rather than for office visits, they would have more incentive to encourage remote monitoring. They might find it cost-effective to e-mail with their patients.

New technology that can interpret the content and context of human language and analyze massive amounts of data will help. IBM Watson was developed as a sophisticated question and answer system to compete on Jeopardy! But now, IBM Watson is at work in healthcare.

The nation's largest health insurance company, WellPoint, is working with oncology experts at Cedars-Sinai in Los Angeles on a pilot. The system could even help doctors determine which treatment methods are covered by a patient's insurance plan.

As we change the health system, I hope that we won't lose the great things about American medicine. We as a nation lead in medical research. Many patients in the U.S. have deep relationships with skilled, caring physicians. We don't want to lose the best things about health care in the U.S. But being smarter about securely sharing health information could make health care more effective in its primary mission. It will make people healthier.

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To learn more on transformative healthcare, click here.

New Health Care: Putting More Intelligence in Your Doctor's Hands

Dr. Martin Kohn   |   November 1, 2011    2:49 PM ET

Health care is long due for transformation. Although treatments may not change dramatically, the way physicians make decisions will. While technology has changed the way we do everything -- from buying groceries to booking travel -- health care remains stubbornly resistant to change.

Medicine has moved into the 21st century, but many aspects of health care have not. Doctors still often write prescriptions by hand, which has vast potential for errors. Most medical records are still on paper and difficult to access. The processes by which medical claims are filed and paid are woefully archaic.

At the same time, the rapidly increasing volume of medical data makes it almost impossible for doctors to keep up with current knowledge. (Conventional wisdom is that the amount of medical knowledge doubles every five years.) Medical journals, clinical decision support systems and the Internet are helpful support systems, but they have their limits. The information in a doctor's notes about an individual patient, for example, is not readily accessible. Nor can any piece of relevant research be accessed at a moment's notice since online content isn't organized for efficient extraction. Technology has already dramatically changed medicine but much more can be done. Taking a smarter approach to healthcare requires something new.

IBM's Watson, the computer system that competed on "Jeopardy!" earlier this year, stands to dramatically change the way clinicians get information. It can absorb millions of pages of text from thousands of different sources -- including patient interviews, lab reports, university research, newspapers, medical journals, transcripts of calls and consultations, etc. -- and it can make sense of the information. It understands puns and colloquialisms and is not stumped by spelling errors or incorrect grammar. By reviewing many information sources, analyzing as many as 200 million pages of content in three seconds, it can offer prioritized suggestions to doctors and nurses to help them make more knowledgeable decisions.

While this technology could never replace a doctor, it could serve as an invaluable tool for doctors to use. It not only retains millions of pages of information, it has the ability to analyze a conversation with a patient and note critical pieces of information -- such as drug interactions or family histories -- and ask for additional information that might have been overlooked. This could help reduce misdiagnoses and delayed diagnosis which today account for an estimated 15 to 20 percent of medical errors.

If it sounds like some futuristic technology that will never make it past the "interesting idea" stage, at least one health insurer already plans to put Watson to practical use. WellPoint Inc. forged a long-term deal with IBM to deploy the system -- as early as next year -- to support doctors and nurses. By helping reduce erroneous diagnoses and recommending the most effective treatment options, the insurer expects to help keep its members healthier.

This is a win-win-win situation for patients, insurers and medical professionals. Medical errors resulting in injuries are estimated to cost between $17 billion and $29 billion annually. In many cases, the financial cost is trivial; by one account, at least 44,000 Americans die every year as a result of a medical error. Watson isn't a cure-all -- it can't solve the health care crisis, nor can it prevent people from getting sick, but it can help doctors manage information overload, thereby allowing them to more effectively treat patients.

For more information on transformative healthcare, click here.

The Next Era of Computing: Learning Systems

Dario Gil, PhD   |   October 20, 2011    4:19 PM ET

When IBM's Watson defeated two past champions on TV's Jeopardy! game show last February, it awoke many people to the awesome power of computing. Watson demonstrates that computers are at last becoming learning systems-capable of consuming vast amounts of information about the world, learning from it and drawing conclusions that can help humans make better decisions.

At IBM Research, we believe that learning systems will shape the future of information science and the IT industry, and that Watson represents a very significant step on that journey.
But every innovator needs a target to aim for, so, after the Jeopardy! challenge, we're searching for the next "grand challenge" to will drive the next advances in Information Technology. To help shape our thinking, we're engaging in a conversation about the future of computing with scientists and business leaders at an IBM Research Colloquium on Friday at the lab in Yorktown Heights, N.Y. The questions we're asking are straightforward: What should the next grand challenge be? How should we design it? How should we pursue it?

We want to throw a wider net, as well. The Jeopardy! contest inspired a team of IBM and university researchers to create a system that could beat the best Jeopardy! champions. What "grand challenge" would you choose? Hopefully, the colloquium and follow-up conversations will help us set an audacious goal.


The colloquium is part of an IBM centennial program designed to convene thought leaders - including leading scientists, academics, leaders of industries, public policy makers and IBM clients -- for a series of talks and panel discussions on transformational technologies and their potential impact on the world. In addition to addressing learning systems, there will be guest lectures at the colloquium about emerging, disruptive technologies that will change the computing landscape and help enable learning systems in the future -- biologically inspired nanosystems, exascale-level processing and the analysis of massive quantities of data from multiple sources.

The decision to focus on learning systems for this particular lab event emerged out of a year-long project that was connected to the IBM centennial. The leaders of IBM Research asked a group of us to look out decades into the future and identify the most important trend in computing that we believe will be a major focus of interest over that long time span. After much deliberating, we chose learning systems.

We picked this topic, in part, because of our belief that for all that computing does for us today, it doesn't yet do nearly enough. We need new systems that can become our partners in expanding the horizon of human cognition to help us navigate the increasing complexity of our globally interconnected world. Until now, most electronic computers have been based on the "calculating" paradigm. Our expanding technology frontiers are providing us with the opportunity to build a new class of systems that can learn from both structured and unstructured data, find important correlations, create hypotheses for these correlations, and suggest and measure actions to enable better outcomes for users. Systems with these capabilities will transform our view of computers from "calculators" to "machines that learn", a shift that will radically alter our expectations of what computing is and the nature of problems it should help us solve. These systems will impact virtually every sector of the economy, enabling applications and services that will range from preventing fraud and providing better security, to helping launch new products, to improving medical diagnosis.

Achieving this level of performance will require advances (and sometimes breakthroughs) in learning algorithms and architectures, expanded data input and output modalities (e.g. the ability to process text, graphs, images, video, sound, and other sensory information) and novel device technologies that will exploit the latest semiconductor and nanotechnology advances (as an example, researchers at IBM are actively working on employing phase-change-memory crossbar arrays to mimic neuronal synapses, paving the way for a new class of biologically inspired neuromorphic computation).

We believe that there will be three phases in the learning systems revolution.
The first phase will be driven by "static" learning systems. The Watson system that was built to play Jeopardy! is a good illustration of a state-of-the-art "static" learning system. The term "static" is connected to the fact that researchers had to feed information to Watson, teach it how to play the Jeopardy! game and tweak the programming when they spotted flaws in Watson's game play.

In a second phase, which we call "dynamic," the systems will constantly mine information on their own from multiple domains via multiple sources, including text, video and audio. They'll engage in deeper reasoning, taking advantage the ability to performer higher levels of semantic abstraction to better understand how pieces of information relate to one another.
The third phase would involve "autonomous" learning systems. In this phase, the systems would achieve understanding of natural language, image, voice, emotion, and other sensory information; be able to self-formulate hypotheses and generate questions across arbitrary domains; and utilize the selection of multiple algorithms to learn autonomously.

At IBM, we believe that exponential growth in our industry has been achieved by a combination of continual improvement and disruptive innovation. Today, it's time for a huge disruption-learning systems. What are your ideas? What grand challenge should we choose?

Perspective on Healthcare

Jarrod Dicker   |   September 13, 2011    1:45 PM ET

Medical records, texts, journals and research documents are all written in natural language -- a language that computers traditionally struggle to understand. The ability to deliver a single, precise answer from these documents could go a long way in transforming the healthcare industry. Watson, the IBM computing system designed to play Jeopardy!, could deliver such a solution.