Monthly Archives: June 2011

Cloud Based EMRs: Better Post-FDA-Approval Research

A recently closed longitudinal study of a medication to boost “good” HDL cholesterol concluded: “… that the HDL-boosting drug niacin failed to cut the risk for heart attacks and strokes.” The study was designed to track patients for 4 to 6 years but was terminated 18 months early based on the results to that point. The cost: $52.7 million or $15,500 per person for the 3,400 study participants. Fully networked, cloud based, electronic medical records (EMR) appear to offer a better solution.

The topic of this post is research about medications that have received FDA approval and are being prescribed for general use. The subject of a research study could be a new medication being tracked for purposes of risk management among patients who were not fully represented in the limited sample used to obtain FDA approval. It could also be an established medication where adverse events are suggesting that more needs to be learned or where there is reason to believe it is not significantly effective to justify continued sale. In this case, it was a matter of both effectiveness and risk.

The key to a better solution is the evolution of fully networked, cloud based EHRs that create a database that is large enough to provide meaningful statistics about specific occurrences. As an example, Practice Fusion now hosts electronic records created by 90,000 medical providers in a single database that has more than 12 million patient records and is growing. The data is being collected as part of physicians’ normal practice—the electronic version of historically hand written notes.

There are operational advantages:

• Data collection is conducted to serve the day-to-day needs of the physician and their staff so they have established procedures and a vested interest in quality.
• The use of the data is totally independent of its collection so there is no bias in the data collection process or the data; neither the doctor nor the patients are even aware of how the data may be used: a totally blind process.
• Separation of data collection and use remove any presumption of undue influence by the sponsor of the study.
• Data is uploaded by physicians daily so it can be made available in near real-time for use at checkpoints in the study.
• If an area of particular interest is discovered, e.g., women over 60 who are more than 20 pounds overweight, additional participants with those characteristics can be identified and added to provide a larger, more reliable sample of that group.
• The study can provide information about risks and effectiveness, increased levels of HDL, and continued use, i.e., prescription renewal.
• In many cases, patient history related to their disease including prior medications is available and information will be available about patients who stop taking the medication or change to a different medication.
• The same database can be used to create a control group of patients that are not taking the medication and have essentially the same medical conditions and demographics as those who are; if a member of the control group begins taking the medication they can be moved to the study group and replaced in the control group—there is no need to deny patients the opportunity to take the medication just to protect the integrity of the data.

The largest benefit is that there is no marginal cost for data collection. The data is already being collected. There are, of course, charges for extraction of the specific data required for the study, for HIPAA compliant de-identification of the data, and for the use of the data. The study costs cited in the introduction, $15,500 per participant, include costs in addition to data collection, but data collection is a major part of that cost and could be dramatically reduced through the use of fully networked, cloud based, electronic health records.

Better data for the reasons noted above at lower cost translate to better healthcare at lower cost.

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Medical Records Are Just One Form of Healthcare Information.

In just a few years medicine has taken major steps to move from paper records in individual doctor’s offices to electronic medical records that can be shared with patients and their other physicians. The primary point of coordination of care among a patient’s physicians is moving from the patient—I saw Dr. Adams last month and he told me…—to the patient and her team of physicians who share the same records. The good news is each physician now has more information; the bad news is they have no additional time to analyze it. That is the tip of the iceberg.

At the same time, the marketplace has seen the value of health related information and is rapidly creating new ways to collect that information. Sources as diverse at private individuals working on smart phone apps to corporate giants like Ford Motor, Intel and General Electric are creating new ways to capture more and more health related information. Most of this will be routine but some of the haystacks will have needles of data critical to a healthy future for some patients or even life savings requirements.

Physicians can choose what medical information to collect depending on each patient’s specific circumstances; they can decide what is relevant and influence the volume of physician generated medical information. Patients will make the decisions about the information to be collected from many of the marketplace solutions: Here are my vital signs taken during my bicycle ride last week when the temperature was 89 to 95 degrees and I climbed 1321 feet and averaged 13.2 miles per hour. Here is the data from my Ford car last month and the statistics Intel/GE captured with regard to when I took my medication and how I answered the phone. How good is the data? Are there any needles of critical data?

We are rapidly moving from inadequate amounts of data to overwhelming amounts.

Prior solutions are the source of almost all significant problems. There is a problem on the horizon and now is the time to explore ways to manage the growing amount of data being generated and shared within the medical community and the marketplace. The people who are harnessing computers to capture medical data may be the logical ones to develop ways to capture, assess, integrate and analyze the growing amounts of data or the solution may be out in the marketplace. Stay tuned.

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