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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Expanding EHRs to Include OTC Meds

My recent post about the Supreme Court’s decision in the case involving over-the-counter Zicam cold remedy got me thinking about over-the-counter (OTC) medication and personal health records (PHRs). PHRs are a logical next step in the evolving application of computer systems to capture, analyze and use healthcare information. In fact, many EHRs, including Practice Fusion, provide patients with PHRs. But, neither the EHRs nor the PHRs I have seen incorporate information about OTC medication and devices yet. How could that be done?

Some EHRs, including Practice Fusion provide two pieces to the puzzle: electronic transmission of prescriptions to my local pharmacy and an electronic file for my data: a PHR. My pharmacy provides two pieces: a frequent shopper card (FSC) and they upload prescription data to my PHR. The basic links and basic data provide a good starting point.

A workable system might look a lot like this: My doctor’s EHR company provides me with a personal health record. The EHR company and my pharmacy enter into an agreement to exchange data. I designate my PHR as the destination for my pharmacy’s transmissions.

Near the end of my next visit to my doctor sends two electronic prescriptions to my pharmacy; I pick them up. No change there, I can do that today. My pharmacist notes that one medication is for high blood pressure and recommends a blood pressure monitor that will transmit the results to my PHR. I pay for the prescriptions, monitor and a magazine using my FSC and credit card. The pharmacy uses the information associated with my FSC to send a confirmation of the purchase of my prescription including the last four numbers of each prescription (just in case I only picked up one of the two prescriptions). The pharmacy uses the same information from my FSC card and their inventory system to report that I purchased a blood pressure monitor that can transmit the readings. It does not mention the magazine. My personal health record forwards the information to my doctor’s EHR.

A month later, I refill my prescriptions and pick up an OTC medication. The pharmacy uses information from my FSC to send a confirmation to my doctor that I picked up my prescriptions. My doctor now knows I am continuing to take the medication. Her electronic health record can track my continued purchases or my failure to continue and recommend appropriate action. My pharmacy uses their FSC tracking system and inventory system to capture the information about the OTC medication and reports that to my PHR which forwards all of the information to my doctor’s EHR.

My doctor’s EHR checks the OTC meds for potential harmful interactions with my prescriptions and any other OTC meds I have reported. It also checks for any alerts such as evidence that Zicam caused people to lose their sense of smell. The EHR alerts my doctor and/or me if appropriate.
On my next visit my doctor sees that I now have a blood pressure monitor that can transmit data and suggests that I check my pressure weekly and send the information to my PHR. My doctors EHR will pick up the data and track any significant changes.
On the visit after that, my doctor is considering a change in my blood pressure medication but notes that there is a potentially harmful interaction with the OTC medication I bought. She now has information that will allow her to recommend I stop taking the OTC meds, she can select an alternative medication, she can ask me to check my blood pressure and send the data daily, or a number of other options. More and better health data gives my doctor and me more options.
So how do I keep my meds separate from my wife’s? My doctor’s EHR sets up a “family PHR.” My prescriptions with my name on them are reported to my PHR and everything else is reported to my family’s PHR. My wife or I or both of us move items from the family PHR to our own with a click of a mouse. My doctors EHR can send an alert to me if it finds a potentially harmful interaction with my medications and some on my family PHR. I can then unlink that med from my name (it was for my wife or one of the kids) or link it to my name so appropriate actions can be recommended to my doctor and/or me.
If I go to another doctor about an unrelated matter and he uses the same EHR I can give him direct access to my PHR. Alternatively, I can have records sent from my PHR to my new specialist and request appropriate records from him so I can update my PHR. If my new specialist uses the same EHR, I now have a medical team that always has current information about my conditions, prescriptions and OTC meds and available devices.
My doctors and I now have better information to provide healthcare at lower cost.
My pharmacy is now contributing information that gives me and my family a strong reason to give them all of our non-medical healthcare related business. Almost any FSC based system will have some capability to analyze purchases vis-à-vis individual card holders. The tabulation and transmission of the required data should be evolutionary, not revolutionary.
OTC manufacturers and distributors should find de-identified information about their products and any side-effects or unexpected benefits valuable. In the Zicam case the record showed that there was no loss of the sense of smell among the members of the company’s research group. Even a symptom with low frequency can be significant if the harm done to a few individuals is substantial, as it was in that case.
EHRs are still in the process of using the full capabilities of the Internet to gather, analyze and distribute data that will improve healthcare and reduce costs. This is just one of many near-term future opportunities.

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Electronic Medical Records and Securities Fraud?

Can a failure to disclose knowledge about a medication’s side-effects lead to a successful suit for securities fraud? In March 2011 the Supreme Court ruled that it can.

In this case, the medication was Zicam Cold Remedy, an over the counter product. The company received information from several sources that patients had suffered from anosmia (loss of the sense of smell) after using Zicam to treat their cold symptoms.

Shortly thereafter, two patients sued Matrixx in a products liability lawsuit based on Zicam-related anosmia.

“According to plaintiff/respondent investors, Matrixx reacted to these events with a series of public statements that were misleading and amounted to securities fraud.  These statements related in large part to the company’s financial prospects, including estimates that “revenues ‘would be up in excess of 50%'” as well as similar predictions regarding share earnings for investors.  Later, the company increased its rosy forecast to have revenues increasing by 80%.  The company acknowledged the products liability suits in required SEC filings (Form 10-Q) but did not disclose that such suits had already been filed.  In addition, the company responded to a Dow Jones Newswires story relating to reports of anosmia as a consequence of Zicam use (and the concomitant drop in share price by almost 12%) by releasing a statement that the company believed the allegations that Zicam use caused anosmia were “completely unfounded and misleading,” further stating that:

In no clinical trial of intranasal zinc gluconate gel products has there been a single report of lost or di­minished olfactory function (sense of smell).  …  In fact, in nei­ther study were there any reports of anosmia related to the use of this compound.  The overall incidence of adverse events associated with zinc gluconate was extremely low, with no statistically significant difference between the adverse event rates for the treated and placebo subsets.

The share price dropped even further when Good Morning America aired a segment highlighting research results relating Zicam use to anosmia and disclosing the existence of four product liability lawsuits.  “Matrixx persisted in its public statements that the link between Zicam use and anosmia was without merit, and filed documents (SEC Form 8-K) that it had convened a scientific panel that had concluded that there was “insufficient scientific evidence” that Zicam affected sense of smell in users.  These statements formed the basis of plaintiff/respondents’ complaint.”

Writing for a unanimous Court, Justice Sotomayor started with the language of the statute that … made it unlawful for “any person” to “make any untrue statement of a material fact or to omit to state a material fact necessary . . . to make the statements . . . not misleading.” … the materiality requirement can be satisfied “when there is “‘a substantial likelihood that the disclosure of the omitted fact would have been viewed by the reasonable investor as having significantly altered the “total mix” of information made available.”*

The availability of information from large, near-real-time databases like Practice Fusion’s** expands the “total mix of information … available.”  Does that create an obligation for pharmaceuticals – both prescription and over the counter – to make a reasonable effort to obtain that information and take appropriate action or risk claims of securities fraud in addition to compensatory and punitive damages for any harm done to patients? Does a securities firm that recommends a pharmaceutical company’s stock have an obligation to obtain and use that information? As often happens, the Zicam case raises more questions than it answers.

*Additional information at:

**70,000 users and 8 million patients:

Hal Amens is a senior management consultant specializing in process improvement. He is a Certified Consultant with Practice Fusion and a guest blogger. He is not an attorney and his comments are not to be interpreted as legal advice.


Prediction: Pharmaceutical Litigation

Pharmaceutical litigation is where huge lawsuits are common. I predict that this will change and the change will reduce the damage to the bodies and lives of patients, reduce the cost of healthcare, and speed up the process of moving new medications from the laboratory to patients. What will cause that change?

Historically, the pharmaceutical manufacturers have been responsible for the collection, analysis and distribution of data related to benefits and side effects of new medications. Data collection has been an extra cost of doing business. Like all costs, there is pressure to minimize these costs. If, and when, publicly available data including anecdotal evidence begins to point at a serious problem, the plaintiff’s bar also begins to develop data about risks and damage.

The cost of data collection using today’s methods imposes economic limits on the amount of data gathered by manufacturers. Cost control argues for the smallest amount of data that will likely be required, but how much is that? The smaller the data sample the less likely it is that a risk will be identified early in the life of a new medication. If a risk is limited to just some patients, a small total sample makes it unlikely that a risk to a sub-set will be identified, e.g., males over 70. If the total sample is statistically small, a sub-set will be even smaller and less reliable as an indicator of both the need for action and as a guide to appropriate action.

The push by the federal government for healthcare providers to shift from paper records to electronic healthcare records (EHRs) has been seen as a potentially slow process. The common model assumes EHRs will be implemented first in hospitals and then spread to private practices because of two factors: first, the cost and complexity of the required computer systems, and second, the lack of the standards required to move meaningful data from system-to-system for consolidation and analysis.

The maturation of the Internet in terms of processing and security now means that data can be safely moved and stored. Cloud computing—remote data processing and storage—now allows service providers to grow new services rapidly without large up-front investments. The net result is a dramatic reduction in cost for the service provider and users, e.g. physicians. As an example, one company, Practice Fusion, provides a full function EHR to private practices totally free. Step one in the changes that are occurring is unexpected reductions in cost.

Hospitals generally have short term relationships with patients whereas private practices generally have longer term relationships. Private practices monitor more patients over longer periods of time than hospitals. Step two is a shift from hospitals first to private practices first for widespread implementation of EHRs which will provide better longitudinal data about the effectiveness and risks of new medications.

The original model for EHRs envisioned small libraries of patient data sitting on the hard drives in the offices of thousands of doctors. Solutions for the nightmares associated with moving and consolidating all of that data are still on the drawing boards. Rather than “stand-alone” systems, the Internet and cloud computing allow the use of a common set of databases and a single set of standards. As an example, Practice Fusion now has seven million patient records from 70,000 medical professionals in their database. That is nearly 10% of all of the doctors in the US and growing rapidly. The data from thousands of doctors is being monitored as it is received. The data is all in a common format and is available for analysis and reporting in near-real-time. Step three is the availability of large databases with one set of standards that dramatically reduce the time and cost required to convert data to useful information.

The data that was formerly collected by the manufacturers as an additional cost of doing business is now being collected as a routine part of patients’ visits to their healthcare providers. There is little or no extra cost to track a new medication. The data is being collected by nurses and doctors trained in diagnosis and documentation as a normal part of their medical practice. Step four is further lowering of costs; step five is better quality data.

The availability of more, better, and cheaper data at lower cost offers opportunities to reduce the risks associated with new medications and may allow regulatory agencies to approve new products with less research subject to close tracking and third party analysis of results. Lower cost of research and earlier to market could represent significant cost savings for new medications.

As a new medication enters the market feedback about its effectiveness and risks will begin to flow very shortly thereafter. Manufacturers who chose will be able to measure and document effectiveness and will also be able to identify risks. As the patient population using the medication grows, the sample being tracked will also grow. This means that that as risks become significantly large—however significance is determined—the data base will be growing to support both risk assessment and mitigation. Manufacturers, if they chose, will have new opportunities to minimize damage by providing additional information to the medical community and patients and to develop specific responses to specific problems. Timely action will reduce compensatory damages and responsible action will reduce punitive damages. Timely responsible action will reduce damage to the brand in the marketplace.

Manufacturers who chose not to participate in the analysis and application of this data will probably find that plaintiffs’ attorneys are using the data to find opportunities for litigation. The plaintiffs’ attorneys will probably argue that the reluctance of manufacturers to make effective use of the data justifies demands for increased punitive damages.

My prediction: more, better, faster, and cheaper data will speed up the process of moving new medications from the laboratory to patients, reduce the cost of healthcare, and reduce the damage to the bodies and lives of patients who have adverse reactions to new medications. Changes in the way that healthcare data is being collected, processed and stored will reduce both compensatory and punitive damages related to pharmaceutical litigation.

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EMRs as an Integral Part of Medical Research

The cost for collection and processing of data is a significant part of the budget for a typical medical research project. Use of data that is already being collected for other purposes provides opportunities to improve the quality of the available data, reduce the cost of obtaining it, and minimize the time required to get it to the analysts. Here’s where an EHR system can help.

As an example, a research project wants to track the use and effectiveness of a new medicine to manage a particular illness over a period of five years. Let’s call that illness Alpha. Today, research is pretty much limited to people already diagnosed with Alph unless the sample size is very large. With access to an EHR that has a large enough database, three types of patients can be tracked for the study.

The EHR can be used to find 1,000 patients who have the disease. They can be given the new medicine and tracked over the next five years using data from their EHR that is being collected as a routine part of visits to their doctor. Extra blood tests or other procedures may be required with a new medication. Reminders to the doctor can be included in the EHR and the results will then be tracked like any other data. The extra cost of obtaining and delivering the data will be relatively low.

A sub-project can be designed to get some of these patients to participate in additional research such as development of family histories of Alpha, or genetic testing. Recruiting patients for additional test through their doctors will be less costly than most of today’s means of obtaining this type of data.

The EHR can be used to find 1,000 patients who have Alpha, are demographically very similar to the first set of patients and are not part of the test of the medication. Data from their EHRs can be used to provide a baseline against which to assess changes among the patients who are taking the medicine. Again, the extra cost of obtaining and delivering the routine data will be relatively low.

The EHR can also be used to find newly diagnosed cases of Alpha over the course of the five years of the study. Newly diagnosed patients of the doctors with patients already in the study can be given the medicine and then tracked to see how effective it is if administered early. Newly diagnosed patients of doctors who are not in the study (and presumably are not aware of the medicine) can be  found and tracked to provide a dynamic baseline for early use of the medicine. There would be no extra cost to obtain the data; it is already in patient EHRs. The cost of a wider search of the database to find these cases could be noteworthy but significantly less than any other way to build a baseline of newly diagnosed patients.

There is one other piece to a complete solution and that is access to a large enough number of electronic health records to find a limited number of cases. There are a number of organizations including the VA, Kaiser, and vendors of hospital systems that have large databases. There are also physician office systems like Practice Fusion that are database driven and can quickly draw information from millions of patient records today over a much more diverse demographic (location, age, and socioeconomic status).

A research project based on EHRs will have data collected by nurses and doctors who are trained to collect health related data to assure quality. Data can be delivered to the research team in a matter of days; the interim and final research results will be available for use substantially faster than is possible with most of today’s data collection methods. When an EHR is an integral part of the research project the result is better data at lower cost faster.

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EMRs as Part of Larger Networks

Electronic medical records provide an alternative to paper based records. They are also a source of information that can be used as part of other processes to address a wide range of healthcare issues. Here’s one example:

Congress has passed a bill requiring food processors to implement systems to track cases of food that may be related to outbreaks of food-borne illness.

An estimated 76 million people contract food-borne illnesses in the U.S. each year, with 325,000 hospitalizations and 5,000 deaths, according to the Centers for Disease Control and Prevention in Atlanta. Those illnesses cost the U.S. economy $152 billion a year in health care and related expenses. Rapid identification of the source of these illnesses and their removal from the market is critical.

Under the required tracking system, farmers would scan individual cases of produce, keeping records of where they are shipped. If a recall is ordered by the FDA, the records would be quickly disseminated to trace the current location of the recalled produce.

Once specific cases have been identified as carrying a food-borne illness, the new system will allow those cases to be removed from the market; however this is only part of a complete system. How can the illness be linked to specific cases of food? Here’s where an EMR system can help.

Most EMR systems provide for reporting of food-borne illnesses. By adding a few additional elements of information, the search for the source can be narrowed very quickly. When a doctor enters a diagnosis of food-borne illness, the system can ask for the type of food that is suspect, i.e., eggs, fish, spinach, etc., and the name of the market where the suspected food was purchased. The EMR can track doctors’ reports and when a target number of similar reports is reached an analysis can be launched. A single answer will not be helpful, but if the answers from several cases list the same food and the same market or chain, that provides a place to start. Appropriate information can be forwarded to a public agency.

Samples can be acquired, tests run, and the investigation focused on just a few likely sources. Once a case of food carrying an illness is found, the food processors’ system can be used to find all of the cases from a specific producer and they can be remove from the market.

There is one other piece to the complete solution and that is rapid access to a large enough number of records to find what may be an isolated set of incidents. There are a number of organizations including the VA, Kaiser, and vendors of hospital systems that have large databases and could report to public health agencies or the FDA. There are also physician office systems like Practice Fusion that are database driven and can quickly draw information from more than five million patient records today.

The tracking process from identification of a problem to a solution would look like this:

A Food Illness Tracking Process

This provides an illustration of the way an EMR can also be linked to other tracking systems to identify and facilitate the search for health issues such as some common types of sports injuries or automobile accident injuries. EMRs are clearly more than just systems to replace doctors’ paper records.

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