Tag Archives: emr

Expanding EMRs: Prescribed Devices and OTC Smartphone Apps

The use and scope of electronic medical records (EMRs) is being changed by evolving technology and the way it is being used by doctors, patients and people who are sometimes referred to as the Quantified Self (QS). This latter category includes people who are using a growing number of devices to record data about their physical well being, data that can be harnessed for better healthcare and healthcare research.

Traditionally, healthcare has taken one of two paths:

  • Patient problem e.g., illness-> Data: treatment-> Solution
  • Solution e.g., new medication-> Data: who needs it-> Application

For people in the QS category, there is now a third option:

  • Data-> Problem or opportunity-> Solution

The first two paths are largely driven by a doctor and their patient. They lend themselves to the capabilities of traditional EMRs. The third presents new challenges and opportunities for Personal Health Records (PHRs) linked to EMRs.

  • The first challenge is the data is originated by a patient (or potential patient who may or may not have a primary care physician.) What do they do with the data? One option is to store it until needed, but patients typically don’t have the knowledge or experience to know when it would be useful or is needed.
  • The second challenge is the potential amount of data that will be collected relative to the limited amount of data involved in traditional EMRs.
  • The third challenge is finding useful information (needles) in haystacks of data. The ability to collect data does not carry with it the ability to analyze that data.
  • The fourth challenge is managing the interface between the regulated environment in which EMRs and PHRs operate and the unregulated environment of the quantified self.

With all those challenges, why bother?

One reason is that some of the devices being developed and tested by QS’ers have applications within the EMR environment. As an example, technology being developed by Green Goose includes sensors that can be applied to pill bottles and exercise equipment to record and transmit data about usage. Is the patient really taking their medication as prescribed? Are they really getting the exercise they claim? Useful questions in healthcare delivery and research.

Another is that this data is already being widely shared on the Internet where there is only limited ability to analyze it and apply it in traditional medicine. An example is PatientsLikeMe.com which has more than 100,000 people sharing information about major chronic disease, treatments and outcomes. This is self reported data that could be made more valuable by linking it to the patient’s clinical records. Another is CureTogether.com which promises “millions of ratings comparing the real-world performance of treatments across 589 health conditions.” A third is Asthmapolis.com which offers a device that attaches to inhalers and sends time and use to a database to assist individual users and support geographic risk analysis.

An article titled The Measured Life in Technology Review notes:

The Zeo, a sleep tracking device gives its users the option of making anonymized data available for research; the result is a database orders of magnitude larger than any other repository of information on sleep stages. The vast majority of our knowledge about sleep … comes from highly controlled studies, this type of database could help to redefine healthy sleep behavior. … The data base is obviously biased, given the fact that it is limited to people who bought the Zeo … But the sample is still probably at least as diverse as the population of the typical sleep study.

Such studies obviously lack the rigor of clinical trials, but they have their own advantages. Clinical trials usually impose stringent criteria, excluding people who have conditions or take medications other than the one being studied. But self-tracking studies often include such people, so their pool of participants may better reflect actual patient populations.

This is clearly not an either/or situation. Combinations of data from patient medical records + clinical studies + self reporting offer new ways to look at healthcare and related solutions. Ways that will almost certainly contribute to improvements in quality and reduction in costs of healthcare.

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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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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: More, Better and Quicker Data

Electronic medical records provide value at several levels. The most basic level is a specific doctor/patient relationship. Above that is care by a doctor team and a patient dealing with a complex medical issue such as cancer. Above that is a database derived from those records from multiple doctors and teams.

Large databases already exist. The Veterans Administration has one and so does Kaiser. Just three vendors—Meditech, McKesson, and Cerner—serve more than half of the acute care hospitals that have vendor systems. Practice Fusion is the dominant service in doctors’ offices with more than five million patient records.

We are already beginning to see more and better data quicker.

A large database—more data–has a number of advantages. First, you can look at issues that affect only a very small percent of the total population and still have enough cases to draw reasonable conclusions. Second, you can define “control groups” with very similar characteristics who are not affected by whatever you are studying so you can begin to look for potential causes.

Data collected by professionally trained doctors and nurses in the normal course of their medical practice using structured formats is more reliable and easier to analyze—better data–than most of today’s studies that rely on interviews and limited records. Practice-derived data will be adequate for some studies and will provide the starting point for others. One possibility is to use practice data to find patients of interest and then work with them and their doctors to obtain additional information. The Web site PatientsLikeMe.com has already demonstrated the willingness of people to share treatment and symptom information when they see value to themselves and others.

The processes of most of today’s research require a significant period of time between data collection and publication. Large databases support near real-time analysis of data and reporting—better data quicker. Two illustrations are provided by Practice Fusion’s response to the N1H1 flu using the guidelines published by the CDC and their posting of data on Microsoft’s Azure MarketPlace.

What can happen if we get better data quicker? Here is some of what we can expect:

  • Widespread use of standardized quantifiable measures of service, effectiveness and safety; healthcare is not totally quantifiable, but much of it is and the quantifiable part can provide guidance about what works best under what circumstances.
  • Identification of significant risks and steps to reduce them such as the risks associated with center line catheter infection.
  • New ways to identify, manage, and respond to the potential risks associated with new medications and new uses for existing medications.
  • Significant impacts on medical litigation including reductions in the actual harm done to patients with subsequent reductions in compensatory damages plus better standards of care and records to reduce, and in some cases eliminate, punitive damages.

More and better data quicker from EHRs will be one of the major medical breakthroughs in the next few years.

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$250 million for the social Web including healthcare

Pioneering venture capitalist John Doerr, lionized in Silicon Valley for leading investments in Netscape, Amazon and Google, helped build the consumer Internet. Now he’s making a huge bet on the next round of the Web. … Kleiner Perkins Caufield & Byers has established a $250-million fund called the “sFund” to back social entrepreneurs who connect people online no matter where they are. …

He described the fund as a “quarter-billion-dollar party,” but its intention is serious: not to create the next Facebook but to give advice and cash to the entrepreneurs building out the social Web. Some of the areas ripe for investment are healthcare, education, mobile computing and tablets. “The third great wave of the Internet is mobile and social together,” Doerr said. “It’s going to be tectonic.”  http://goo.gl/rsDO

Patientslikeme.com may be one example. Almost certainly, these new ventures will involve the collection and distribution of medical information from more people and about more topics. Our picture of both the maintenance of health and the treatment of sickness and injury will be impacted. Our ideas about the scope and role of electronic medical records will change as will the sources and applications of the data.

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EMRs: Increasing Complexity and Capabilities

Stadiums Utilize EHRs For Injured Fans

Electronic health records are coming to a sports arena near you. A hospital in New Jersey is providing emergency medical services at a stadium that hosts the local major league soccer team. If a person is hurt, they can go to the first aid station, where a team of doctors will treat them. When a person is transported to a hospital, doctors are able to treat them more quickly because they already have the patient’s medical record from the stadium and are notified of any medications that were already administered.”

Next step, an interface to transmit those records to the patient’s doctor if they do not need to be transported. The strategic objective, capture information that may be useful for medical purposes wherever and whenever it is generated and make it available wherever it is needed in essentially real-time.

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