health insurance

Healthcare Monitoring – Fast Company Market Perspectives

Healthcare Monitoring – Fast Company -“Why We Don’t Talk About “Wearable Software”

Revolution is coming in the wearable healthcare monitoring arena as we move from devices to software/ ecosystems and new predictive analytics are fully embraced. Excellent Fast Company Labs article by Tina Amirtha summarizing directions. I see significant opportunity here not covered in the article  – why pharmas will play a key role, role of wearables in telemonitoring/Telehealth, tracking medication compliance,adverse drug reactions. And wearable healthcare monitoring coupled with analytics is spawning many exciting entrepreneurial ventures

Check out the Fast Company article at http://tinyurl.com/klzncnl. My comments shown are shortened due to space – here is a complete copy:

Tina- great article. As former CEO of a public predictive analytics company pleased to share comments. First, analytics is indeed the “Holy Grail” but my view is the real opportunity drivers here are not individuals but pharmas who have the incentive to establish and grow ongoing patient relationships. Healthcare monitoring/analytics is ideal strategy to help pharmas achieve this objective. Last time I looked the 3 to 4 major pharma chains represent about $200 billion or 75 percent of the market and about 24,000 locations- independent pharmas account for the rest of the locations and market. Secondly, health monitoring devices can make a substantive contribution to Telehealth/ telemedicine – I have done work in this area and telemonitoring proponents have not fully embraced these technologies- in my view and they are missing a real opportunity. We are seeing new entrepreneurial ventures addressing this market- my experience is creating sustainable business models addressing hardware, software, analytics dimensions is a real challenge for some of the reasons you noted.

Finally, in a late 2012 blog post “Buy Health Monitoring Devices Off The Clothing Rack      http://tinyurl.com/nhyp9uy 
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? Clothing may also be an external driver to grow this market

Bottom line here- the real opportunity, which translates into hard dollar cost savings and improved healthcare quality, is using wearables and the software ecosystem to track medication compliance, adverse drug reactions, drug efficacies, and similar data. My vision is coupling wearable healthcare monitors with predictive analytics will dramatically reshape today’s healthcare system- refocusing the emphasis of today ‘ s wearable discussion and educating industry players on the possibilities here are the challenges and next steps needed to make this happen

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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