health care IT

Posted Comments on WSJ Article-“Can Data From Your Fitbit Transform Medicine?”

Posted comments on June 23rd WSJ Technology article addressing telemedicine – I follow this area and emphasized need to do more to develop telemedicine in the United States

We lag most developed countries in the telemedicine arena which reduces the quality of our healthcare system and increases costs

You can see the WSJ article and my comments at

http://online.wsj.com/articles/health-data-at-hand-with-trackers-1403561237?mod=djem10point

Here is a copy of comments I posted:

A winning formula- integrate telemedicine into patient’s EHRs. Mayo Clinic problems shows challenges. We are going in the wrong direction here. Three strategies to fully leverage telemedicine:1.Establish standards integrating remote monitoring devices with EHRs. The ACA ensures ‘meaningful use’ of EHRs. Well defined standards jumpstarts the remote health monitoring market moving from niche focus  2. Use analytics to emphasize benefits. Powerful analytics assess health issues and develop optimized treatment plans. For what is emerging, check out comments I posted on a healthsystemCIO.com site Posting HealthSystemsCIO.com. 3. Pro-actively address security concerns. “Tops down” national initiative emphasizing benefits- prenatal care, chronic conditions, improved outcomes particularly in rural areas with 25% of population but only 10% of physicians. Need to counter serious security concerns. e.g., April 26th guidelines from the Federation of State Medical Boards which can hamper growth.

Paul B. Silverman

 

 

 

 

 

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Good Analytics Article- “…Reaping Returns from Analytics”

Good insightful article in the October 18, 2013 issue of Information Management on analytics by Narendra Mulani who is Managing Director of Accenture Analytics. I posted comments sharing some additional perspectives and related opportunities I foresee. One clear message here- the analytics market is positioned for major growth and as I noted in my comment related to healthcare analytics, today we are only seeing the ‘tip of the iceberg’ in this sector.

Check out at http://tinyurl.com/nyrd8q2

Here is a copy of the comments I posted:

Excellent article. I am pleased to share some comments based on my experience in the analytics arena.

Analytics clearly provide powerful tools to optimize business processes and value chain functions. What is often overlooked is understanding the impact of external and industry factors critical to maximize performance and mitigate risk. Some studies, for example, show that external factors have a 45 percent impact on ROA. Ignore these, and your analytics may address only 55 percent of the critical performance and risk drivers.

How will global environmental policies impact your business; what is impact of changing healthcare regulations on new drug development and clinical trials; what new market opportunities are projected based on disruptive innovation in your business; how will privacy and transborder data restrictions impact your business today and tomorrow. These are external drivers which can create new markets and ‘destroy’ existing ones.

Addressing how the external environment impacts your business demands analytics addressing STEEP analysis, Porter’s Five Forces, Peer Group modeling, and similar diagnostics. And these are not static analyses- change is the only constant in today’s global environment, and having current data is critical. The winning formula- couple traditional external analysis tools, such as STEEP, with unstructured exogenous data analytics provides dynamic, real time insights on external market and business portfolio impact. Integrate these insights with internal data analytics to develop ‘actionable’ analytics. Today’s fiercely competitive global markets demands this analytics rigor.

One interesting statistic suggests 85 percent of today’s analytics solutions address CRM applications, improving the performance and operations dealing with customers and related supply chain activities. The remaining 15 percent are emerging exciting analytics directions that offer exciting opportunities.

For example, in the legal arena, Technology-Assisted Review or “TAR”, uses computer models, machine learning, and analytics to sort millions of documents identifying relevant and privileged documents to support litigation with dramatic cost savings. TAR technologies are rapidly evolving and the acceptance of TAR is now being tested in state and Federal courts.

Analytics will also play an expanded role in traditional corporate strategy management. Fortune 500 companies have thousands of business portfolios often managed using traditional analytics, e.g., hurdle rates, IRR, others. Understanding with precision how these individual portfolios align with the Company’s overall strategic plan, what are the overall projection risks, where are the corporate exposures based on both internal and external factors, are the exciting new directions being pursued by leading edge companies.

While analytics applications in healthcare are accelerating, we are at the tip of the iceberg. Using machine learning to optimize clinical care and reduce longitudinal costs for patient care; integrating healthcare claims data, EHR and genomic data to evaluate patient outlook for both clinical and insurance applications; tracking and analyzing medications and vital signs to assess drug efficacy and adverse effects for drug trial screening; are some of the many exciting new directions we see emerging that will redefine today’s healthcare system improving both quality and cost performance.

Senior management will be challenged to understand these new analytics applications to improve their global performance and mitigate risk. Even business schools must adapt- new analytics tools are reshaping our traditional approach to strategy development and competitive analysis.

Clearly exciting times lie ahead for all players in the global analytics market

Paul B. Silverman is Executive Chairman of InferX Corporation, a predictive analytics company and also teaches at the R.H. Smith School of Business in the University of Maryland.

Paul B. Silverman

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THE ‘SUGGESTIVE’ VS. ‘PREDICTIVE’ ANALYTICS ISSUE

I posted comments on the HealthCIO.com site in response to article suggesting ‘suggestive’ rather than ‘predictive’ analytics (“PA”) provides real, demonstrable benefits and that, rather than PA,  should be today’s primary focus. My point is with the proper vision and commitments here, PA tools offer powerful, exciting new tools to improve health care, both from patient care and financial perspective, reducing claims fraud and improving processes.And these same tools are spawning exciting new ‘analytics-centric’ ventures which I see as a high potential new venture sector and is one of my focus areas.

You can visit the HealthCIO.com site to see the original article “A Suggestion About Predictive Analytics” at http://tinyurl.com/7nw6twd and also see a reply to my comments. Copy of my comments follows:

Paul says:

‘SUGGESTIVE’ AND ‘PREDICTIVE’ ANALYTICS WILL BOTH HELP IMPROVE HEALTH CARE
Thanks for sharing your insights. As a former CEO of a predictive analytics company, and currently leading a new ‘analytics-centric’ leading edge, personal health and wellness company, among other activities, I am pleased to also contribute my perspectives here.
I like your idea of contrasting Suggestive vs. Predictive Analytics- there is obvious proven benefit in using analytics to improve quality at the point of patient care.
With regard to predictive analytics, I am pleased to offer comments:
–Predictive analytics is often muddled in with other statistical tools as you say, it is often difficult to appreciate and understand just how powerful these tools are and what is their specific contribution
–Rather than saying there are two flavors of PA, “easy and hard”, I suggest a better approach is to say there are two PA target opportunity areas in health care (and also in other sectors):
— Using PA to analyze the “known unknowns” – all of the patient treatment enhancements you described fall into this category- addressing known issues and processes, using analytics to improve processes, quality of care, and doing this more efficiently and at lower cost.
—Using PA to analyze the “unknown unknowns” – this is the real and power of predictive analytics and I believe really offers high upside for all health care players, and patients as well
–Look at the magnitude of today’s health care issues. As one example, increasing complexity of medication regimens used by patients, coupled with a fragmented health care system involving multiple prescribers, has made the occurrence of serious drug-drug interactions more likely today than ever before. For example, one study suggests Preventable Adverse Drug Events injure 1.5 million people a year, costs the U.S. healthcare system $3.5 billion and resulting in an estimated 44,000 to 98,000 deaths every year. Some studies show even higher numbers.
–Our aging population exacerbates the above issues. Studies show 41 percent of seniors take
5 or more prescription medications, and more than half has 2 or more prescribing physicians. And 24 percent- about 1 out of 4 – seniors having 3 or more chronic conditions have not shared information with their health care providers during the last 12 months. No wonder medication errors among seniors on Medicare are estimated at almost $900 million.

–We can use the real power of PA to better understand the “unknown-unknown” drivers here that are impacting our health care system, and create powerful new tools, improved processes and do this more efficiently while improving patient care.

–The “unknown-unknown” data I would like to see addresses questions such as why do we have adverse drug events; what are the rules we should be looking at and changing to reduce these events save lives, and reduce health costs; what are the underlying drivers and patterns for adverse drug events- do these vary by geography, treatment modalities, user demographics, specific types of medical facilities, maybe how and where medical practitioners are trained. “Unknown-unknowns” may, for example, identify certain treatment modalities and drug regimens used by select groups of medical professionals which drive adverse drug events. Predictive analytics, an inductive rather than deductive process, offers a powerful tool to help us identify these and many other critical underlying health care drivers.

I agree there are many PA projects that today may seem academic, but I do see great possibilities to improve our health care system, using powerful new predictive analytics computing tools and platforms coupled with more traditional analytics (both suggestive and deductive ‘rule based’ analytics), to dramatically improve the quality of our health care system. These new analytics and tools will address clinical issues such as the growing problem of adverse drug events, as well as addressing Medicare and other health care claims fraud and errors.

We are making progress, but I still believe we can be doing much more to achieve significant improvement in our nation’s health care system and very clear to me predictive analytics and other tools, with the proper vision and commitments, will play a substantive role.

Paul Silverman, Managing Partner, Gemini Business Group, CEO  Sante Corporation, Adjunct Professor, R.H. Smith School of Business in the University of Maryland.

 

v. is what we need to focus on to improve health care

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Understanding ‘Unknown- Unknown’ Information Drivers Addresses ‘Sea of Data’ Issues and Creates Opportunities

Understanding The ‘Unknown- Unknown’ Information Drivers Addresses ‘Sea of Data’ Issues and Creates Opportunities

I posted comments on Fast Company article discussing ‘Sea of Data’ issues Fast Company Article “Avoiding Short-Term Thinking In A World of Big Data”   http://tinyurl.com/7gaepbl

I shared my vision that predictive analytics is ‘raising the bar’ in how we manage the ‘sea of data’,  and offered comments on new directions I see in manufacturing and health care. Here is a copy of my comments posted on the Fast Company site:

The article makes the point that “…in a sea of data, how can we make sure that we’re not just reacting to the information in front of our face, but rather analyzing every possible input.”

One solution to the problem, not mentioned in the article, is the need to develop new analytics to identify key drivers which create the data ‘outcomes’. Predictive analytics enable us to identify these ‘unknown-unknown’ drivers that can only be found by analyzing data, looking for relationships and new rules that emerge developed by analyzing the data. Contrast this to today’s ‘deductive’ approach using expert opinion and well-defined rules.

This ‘data-driven’ analysis to create new rules is an inductive (rather than deductive ‘expert opinion’ based approach) and from my perspective holds great promise to radically change current business processes, improve productivity and improve our quality of life.

This may sound bold, but as the former CEO of an early stage predictive analytics company and also looking at new opportunities in analytics, I see exciting potential here.

Some possibilities:

Look at manufacturing. If a “supplier’s supplier” has a problem, supply chain management ensures quick notification, before it impacts the assembly line. Predictive analytics engines ‘raise the bar’ here by analyzing historical performance and risk data, often real time, defining future risk and performance drivers, and enabling management to optimize performance and mitigate risk.

Going beyond traditional data mining, these new predictive analytics tools analyze industry reports, government filings, trade press, and other sources to assess supplier “health,” pending regulations, and other “unstructured” data sources. Seamlessly integrating with other data, we can use these to more accurately gauge supplier and production line risk and improve performance.Driving new rules,  providing real time early warning signs that impact future supplier and business performance are the new management tools to harness ‘the sea of data’.

Look at health care, my primary focus, where PA techniques hold great promise to help our current health care system. Consider the benefits of these new capabilities which are only a small sample of what lies ahead here:

•    Tracking  Medical Diagnoses, Treatments, Medications, Outcomes, Costs,Reimbursements, and Relationships

ICD or International Classification of Disease Codes , classifies diseases on health records.CPT or Current Procedural Terminology codes developed by the AMA describe services provided by medical practitioners. Medicare employs a similar system, using ‘HCPCS’. Tracking and examining relationships among these metrics, looking at patient data, identifying processes, and key cost and patient health drivers, you can develop ‘best practices’ to improve the health
care process.

•    Identifying Adverse Drug Analyses – assessing underlying drivers to more effectively identify “at risk” patients

•    Optimizing clinical trials (candidate selection and monitoring) – predicting higher risk clinical trial candidates and assessing the key risk drivers

•    Developing directional indicators to predict the underlying drivers for treatment of chronic disease to understand how medication protocols impact treatment plans and patient outcomes

The new predictive analytic-based tools now emerging in all sectors are helping companies cope with the sea of data problem, and  “raising the bar” in how leading firms optimize business performance in today’s  dynamic global markets.

Paul B. Silverman

Author: Worm on a Chopstick : Understanding Today’s Entrepreneurial Age: Directions, Strategies, Management Perspectives http://paulbsilverman.com/books/

Email:      paul@paulbsilverman.com
blogs:       http://paulbsilverman.com/blog/
Linked in:  Paul Silverman
Twitter:     globalbizmentor

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Buy Health Monitoring Devices Off The Clothing Rack?

In my recent  book, I talked about how technology is reshaping traditional markets and strategies. Given new directions in integrating health care monitors into clothing, I suggested we may be buying health care monitors in Lands End, and discussed how this will impact traditional retailer strategies. Sales staff questions may move from “What size and color jacket would you like to see?” to “Can I show you our blood pressure-only monitoring jacket or our top of the line full featured model tracking glucose, oxygenation and includes a USB port?”

And what about health care coverage. Expect to see some interesting issues emerge here- are you buying a jacket or a medical device; where do you draw the line?

The recently announced MisFit Wearables, with an investment by John Sculley MisFit Wearables Health Care Startup , I expect is moving in this direction joining other players and more are coming. The proliferation of sensor data from a wide range of devices (some you wear as clothes, some you attach to your body, some are like  band-aids, you use and dispose), and the need to track, securely manage, share, analyze and communicate  this data is spawning a new sector.

What is really exciting is moving from collection of basic vital sign data and using advanced analytics to analyze vital sign data, understand the real time impact of medications (both pharmaceuticals and nutraceuticals) and empower users and clinicians with new tools that can, I believe make a real contribution to improve our personal health and wellness, a market sector I am pursuing with a talented team. Lots of exciting developments here. Stay tuned.

 

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