Tag Archives: EHR

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.

Short link: http://wp.me/pyfFd-9E

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.

Short link: http://wp.me/pyfFd-9n

The Promise of EHRs for Pharmaceutical Companies

Today pharmaceutical companies conduct extensive research to obtain Food & Drug Administration (FDA) approval of a new medication. Typically this pre-approval research is structured in three phases: Phase I, a small (20-100) group of healthy volunteers to assess safety; Phase II, larger groups (20-300) to assess how well the drug works; and, Phase III, randomized controlled trials on large patient groups (300–3,000 or more ) to assess effectiveness vis-à-vis with the current ‘gold standard’ treatment.

Phase IV trials involve the safety surveillance of a drug after it receives permission to be sold. The safety surveillance is designed to detect any rare or long-term adverse effects over a much larger patient population and longer time period than is possible during the Phase I-III clinical trials.

There are opportunities to use data from Electronic Health Records (EHR) for Phases II and III, but the larger opportunity, and the one addressed here, is Phase IV, post approval surveillance.

Theoretically it should be possible to use the growing body of data in EHRs to track patients for whom a new medicine is prescribed. However, EHR adoption is still very limited; almost all reports show adoption rates less than 10%. More important, there are more than 200 vendors providing EHRs, all of which are built using limited standards for the information to be acquired, the coding for diagnosis and treatment, and for the exchange of information.

Historically, it has proven very difficult to exchange information among multiple systems within a single organization. The generally accepted solution is an enterprise resources program (ERP) which is complex, costly, and difficult to implement.

The collection and exchange of medical information is simpler in some ways and more difficult in others. The efforts of the Federal Government to develop and implement EHR standards will help but there is a great deal to do and the final definition and implementation of standards will take time—probably several years. Even with standards, there will be minor differences among systems developed independently by a large number of vendors that will limit the industry’s ability to exchange information and will raise questions about the quality of the data.

When a significant body of common data becomes available, pharmaceutical companies should be able to use that data to track a sample of patients using a new medication in “near real time,” perhaps within a week after a doctor sees a patient. This could provide four major benefits.

• First, regulatory agencies may give earlier approval subject to effective ongoing sampling and reporting of any adverse reactions—earlier to market.
• Second, any adverse reactions could be found early and evaluated to minimize damage to patients—minimize patient harm.
• Third, early warning could lead to examination of additional data from existing medical records of patients receiving the medication relatively quickly and at relatively low cost. This will further define the risk and whether or not there are patient, disease, or treatment conditions that create or reduce risk. It may be possible to eliminate a risk just by restricting use based on definable conditions—protection for both the patient and market value of the medication.
• Fourth, timely responses to an identified risk will make it difficult for plaintiff’s attorneys to successively demand punitive damages. Compensatory damages will be smaller and punitive damages will be smaller or non-existent—reduced legal costs.

There is enough information about current and near term EHR systems for pharmaceutical companies to develop strategies to use more and better data they will offer. The time to begin the development of those strategies is now.

Short link: http://wp.me/pyfFd-7L