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The Initial [Estimated] Costs of Electronic Health Records Systems

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A Decade Look-Back Analysis

[By Richard Mata MD MIS]

Dr. MataStudies by the Organization for Economic Cooperation and Development (OECD) showed that healthcare spending in the U.S. accounted for 15.3% of GDP, which is more than six percentage points higher than the average of 8.9% in other OECD countries.  This translates into per capita health spending of $5,635 in the U.S. compared with median costs of $2,280 in other OECD countries.[1]

Suggestions as to the economic drivers of U.S. health spending include excessive service use, administrative complexity, population aging, threats of malpractice litigation, defensive medicine practices, and the lack of patient waiting lists.  In further comparisons with the OECD countries, it appears the U.S. overpays for physician visits, hospital stays, and pharmaceuticals.

In 2004

A 2004 OECD paper suggested that one way of improving performance would be to move towards EHR:

Health systems should invest in automated health-data systems, including electronic medical records and systems to automate medication orders in hospitals. Better systems for recording and tracking data on patients, health and health care are needed to make major improvements in the quality of care. [2]

In the U.S., possible savings from the adoption of EHR have been projected to reach $142 billion in physician office visits, and $371 billion in hospital costs over a 15-year period.  These projections have not been validated by the experience in other OECD countries where the adoption movement is ahead of U.S. efforts by anything from four to thirteen years.

Nevertheless, the U.S. began its quest to move towards EHR in 2004 as medical software companies began actively marketing their systems, although funding for this endeavor did not come through until 2006.

In spite of this effort, the U.S. has the lowest percentage of physician providers using any EHR compared to Germany, Canada, United Kingdom, and Australia.  The U. S. physicians’ low adoption rate involves fear of the loss of productivity, lack of financial incentives, and high startup costs of as high as $40,000 per physician EHR adoption.

When spending on IT implementation in the healthcare system is compared on an international level, the U.S. lags dramatically behind the major OECD countries.  The U.S. spends $0.43 per capita compared to a high of $193 in the U.K.  This difference is even more dramatic when compared with the German experience, where IT adoption in the healthcare system is almost universal.  In thirteen years, Germany has spent $1.88 billion.  Their annual per capita cost has been $1.63.  The U.S. has reached only 25% of that expenditure so far.

The greatest barrier to adoption of EHR in most OECD countries has been the need to simplify the health insurance contracts payment structures with standard nomenclatures that can be adapted to EHR.  The major OECD countries also report that there must be a national adoption of IT standards in the healthcare system as well as a national effort to focus on privacy and confidentiality standards.  This assures better coordination of implementation and provides better strategies for adoptions through public incentives and grants.

In the U.S., the five-year costs for a national IT healthcare network have been estimated to be as high as $103 billion in capital and $53 billion in interoperability.  Hospital costs for functionality were estimated to be $51 billion, skilled nursing facilities would bear $31 billion of costs, and physician offices would bear $18 billion of the costs. (Anderson, 2006)  EHR systems that have been implemented have been used mainly for administrative rather than clinical purposes.

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hospital bills

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In 2005

A 2005 study by Richard Hillestad and colleagues at RAND [3] estimates that implementation of a nationwide EHR network would take about 15 years and cost hospitals about $98 billion and physicians about $17 billion.  Over the 15-year period, the average annual cost to hospitals would be $6.5 billion and the average annual cost to physicians would be $1.1 billion (CQ HealthBeat [1], 9/14).

However, if 90% of providers adopted such a network, annual savings would total $81 billion, including $77 billion from improved efficiency and $4 billion from reduced medical errors, the RAND study found.  The study estimates that an EHR network would reduce adverse drug events in inpatient hospital settings by 200,000 annually and reduce such events in ambulatory settings by two million annually, saving $1 billion annually in hospitals and $3.5 billion in ambulatory settings.

For hospitals, about 60% of these savings would be from reduced adverse drug events in patients ages 65 and older, while 40% of savings to ambulatory practices from reduced medication errors would be in patients 65 and older (CQ HealthBeat [1], 9/14).

In addition, the study estimates that a national EHR network would save Medicare about $23 billion annually and save private insurers about $31 billion annually.  The study projects that the estimated total annual savings of $81 billion would double if providers followed all checkup reminders and other prompts from the system (AP/Las Vegas Sun, 9/14).  Currently, about 20% to 25% of hospitals and 15% to 20% of physician offices have EHR systems, according to the study (CQ HealthBeat [1], 9/14).

Assessment

What about today in 2015? How close have these estimates been?

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[1]    For details of the report, see http://www.oecd.org/dataoecd/29/52/36960035.pdf.

[2]   OECD, Towards High-Performing Health Systems, see http://www.oecd.org/document/26/0,2340,en_2649_37407_31734042_1_1_1_37407,00.htm.

[3]   See http://www.rand.org/health/feature/2006/060414_shekelle.html.  The report is also discussed in some detail in Neergaard, AP/Las Vegas Sun, 9/14/05.  See http://www.ihealthbeat.org/index.cfm?Action=dspItem&itemID=114707.

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Population Health Management Integration

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Efficient Market Hypothesis – or Not?

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Contradicting the Hypothesis

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***

Not everyone believes in the efficient market.  Numerous researchers over the previous decades have found stock market anomalies that indicate a contradiction with the hypothesis.  The search for anomalies is effectively the hunt for market patterns that can be utilized to outperform passive strategies.

white swan

[White Swan of the EMH]

Such stock market anomalies that have been proven to go against the findings of the EMH theory include:

  1. Low Price to Book Effect
  2. January Effect
  3. The Size Effect
  4. Insider Transaction Effect
  5. The Value Line Effect

The Anomalies

All the above anomalies have been proven over time to outperform the market.  For example, the first anomaly listed above is the Low Price to Book Effect.  The first and most discussed study on the performance of low price to book value stocks was by Dr. Eugene Fama and Dr. Kenneth R. French.  The study covered the time period from 1963-1990 and included nearly all the stocks on the NYSE, AMEX and NASDAQ. The stocks were divided into ten subgroups by book/market and were re-ranked annually.

In the study, Fama and French found that the lowest book/market stocks outperformed the highest book/market stocks by a substantial margin (21.4 percent vs. 8 percent).  Remarkably, as they examined each upward decile, performance for that decile was below that of the higher book value decile.  Fama and French also ordered the deciles by beta (measure of systematic risk) and found that the stocks with the lowest book value also had the lowest risk.

What is Value?

Today, most researchers now deem that “value” represents a hazard feature that investors are compensated for over time.  The theory being that value stocks trading at very low price book ratios are inherently risky, thus investors are simply compensated with higher returns in exchange for taking the risk of investing in these value stocks.

The Fama and French research has been confirmed through several additional studies.  In a Forbes Magazine 5/6/96 column titled “Ben Graham was right–again,” author David Dreman published his data from the largest 1500 stocks on Compustat for the 25 years ending 1994. He found that the lowest 20 percent of price/book stocks appreciably outperformed the market.

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Ex-Cathedra black swan

[Ex-Cathedra or Black Swan Event]

Assessment

One item a medical professional should be aware of is the strong paradox of the efficient market theory.   If each investor believes the stock market were efficient, then all investors would give up analyzing and forecasting.  All investors would then accept passive management and invest in index funds.

But, if this were to happen, the market would no longer be efficient because no one would be scrutinizing the markets.  In actuality, the efficient market hypothesis actually depends on active investors attempting to outperform the market through diligent research

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The Author

Timothy J. McIntosh is Chief Investment Officer and founder of SIPCO.  As chairman of the firm’s investment committee, he oversees all aspects of major client accounts and serves as lead portfolio manager for the firm’s equity and bond portfolios. Mr. McIntosh was a Professor of Finance at Eckerd College from 1998 to 2008. He is the author of The Bear Market Survival Guide and the The Sector Strategist.  He is featured in publications like the Wall Street Journal, New York Times, USA Today, Investment Advisor, Fortune, MD News, Tampa Doctor’s Life, and The St. Petersburg Times.  He has been recognized as a Five Star Wealth Manager in Texas Monthly magazine; and continuously named as Medical Economics’ “Best Financial Advisors for Physicians since 2004.  And, he is a contributor to SeekingAlpha.com., a premier website of investment opinion. Mr. McIntosh earned a Bachelor of Science Degree in Economics from Florida State University; Master of Business Administration (M.B.A) degree from the University of Sarasota; Master of Public Health Degree (M.P.H) from the University of South Florida and is a CERTIFIED FINANCIAL PLANNER® practitioner. His previous experience includes employment with Blue Cross/Blue Shield of Florida, Enterprise Leasing Company, and the United States Army Military Intelligence.

Conclusion

So, what about the “January Effect for 2015“?

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Leveraging connected car technology to provide piece of mind for car owners and effective marketing for Dealers

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DEM blueWhat it is

Driven Analytics uses connected car technology to better target car owners on behalf of dealerships, all the while reducing the anxiety associated with routine car maintenance for drivers.

How it works

Using advanced algorithms and a data transmission device installed on new cars by the dealership, Driven Analytics provides a marketing platform that allows dealers to advertise maintenance services to their customers exactly when they need them.

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Sale Disposition

Once a vehicle is sold, Driven Analytics monitors the vehicle’s systems and provides the car owner with actionable maintenance information via a smartphone app, text or email.

Customer Retention

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