How do you introduce a class like Mindfulness to school children? You start where they are and make it meaningful to them. This is a link to such a story, a story that also provides a simple do-it-yourself app for your cell phone. An app I now use and you may want to too.

Why an app? Because texting is the “in” form of communication at the personal level for school kids. The app is a simple text message: .b

In England where the story started, a period at the end of sentence is often referred to as a full stop. The common focus of Mindfulness, particularly for the beginner is “breath.” Text .b and it is received as a reminder to: STOP! Breath, continue.

Simple message – simply delivered – simply profound.

A TED Talk: Mindfulness in Schools: Richard Burnett at TEDxWhitechapel
Published Feb 14, 2013 http://www.youtube.com/watch?v=6mlk6xD_xAQ


Apps & Comments

One of the virtues of the Internet is its ability to expand and respond to changing needs, interests and capabilities. A particularly good example occurs at the junction between electronic medical records (EMRs) and smart phones.

Several of my blogs have addressed the opportunities for patients to capture data and add it to their EMR and the challenges of making that information useful in the process of planning and managing the maintenance of good health and, as needed, treatment. Part of the challenge is to know what apps are available. “There’s an app for that” is now part of our language. But which one is the best one for your particular need?

There is a Wiki that will help: PHARMapps. It is structured by apps that deal with branded products and services and those that are unbranded, those for healthcare professionals and for patients, and by device operating systems. There are also classifications by topic. At this point there is no quick way to do a search by your choice of key word. Each app has an area for user comments–over time that may become the most valuable part of the Wiki.


FDA to Review Medical Smartphone Apps … the FDA is proposing a set of guidelines, outlining the types of apps that it plans to oversee. This won’t be all apps in the “Health” category, but will include those that, in the FDA’s words, “could present a risk to patients if the apps don’t work as intended.” 7/20/2011

iMeidicalApps Mobile medical apps review and comments by medical professionals

Digital Pharma: Big pharma’s iPhone apps: most recent update July 7, 2010

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EHR Tracking for Drugs and Devices

Cloud-based, integrated electronic health records (EHR or EMR) systems provide a new paradigm for the collection and use of data for long term research about drugs and devices after FDA approval—commonly referred to as Phase IV testing.

The new paradigm is particularly relevant for drugs and devices for chronic diseases and conditions because long term use may lead to adverse events that do not occur during the shorter term testing required prior to FDA approval. The significance of chronic conditions is indicated by the following statistics:

  • Chronic diseases cause 7 in 10 deaths each year in the United States.
  • About 133 million Americans, nearly 1 in 2 adults, live with at least one chronic illness.
  • More than 75% of health care costs are due to chronic conditions.

The primary differences between the EHR based paradigm and traditional Phase IV testing are listed here (Notes and comments are in italics.)

EHR description: Data is drawn from a database that provides for multiple uses of the data to maximize value.
Traditional Process: Data is collected for a single use—little or no cost sharing.

EHR description: A wide range of available data is identified and collected to provide flexibility during analysis.
Traditional Process: A narrow and focused range of data is collected to manage cost.

EHR description: Samples of existing data are used to validate test objectives and methods early in the research project.
Traditional Process: Prior similar studies and assumptions are used to validate objectives and methods.
Breakthrough drugs or devices may require significantly different objectives and/or methods than required in prior tests.

EHR description: Test subjects—people with the disease—and matching control subjects can be found in the database.
Traditional Process: Test subjects and matching control subjects must be found using a variety of means.
A computer can find test subjects in an existing database very quickly and at very low cost. Traditional processes for finding and recruiting test subjects are significantly more costly and time consuming.

EHR description: Data collection and analysis is conducted in accordance with HIPAA privacy requirements and patient participation is not required.
Traditional Process: Patients must be contacted and enrolled in the data collection process.
The initial data is available in the database day-one of the test to minimize start time and cost.

EHR description: Data collection is totally independent of and not biased by the research.
Traditional Process: Data collection may be suspect under some circumstances.
The process of contacting and enrolling patients may lead to changes in behavior such as greater care in taking drugs as prescribed and greater participation in follow-up visits. Independent data collection may provide a sample more closely aligned with actual patient behavior.

EHR description: Able to add new test and control subjects as needed including their history from the database.
Traditional Process: Ability to add new test and control subjects with past data is very limited.
If adverse events are concentrated in patients with a defined set of characteristics it may be necessary to expand the number of patients with those characteristics in both the test and control group to assure statistically reliable results and a sufficiently large sample to meet the HIPPA privacy rule.

EHR description: Additional historic data can be added from the existing database if preliminary analysis indicates it may be significant, e.g., prior use of similar drugs or a history of another ailment.
Traditional Process: Very difficult to obtain additional historic data from patient records late in study.
If adverse events are found in patients with defined prior conditions including prior use of similar drugs, exposure to other diseases, etc., the database can be searched to add subjects and findings related to that topic for further study and to assure statistical reliability.

EHR description: Off-label uses can be tracked through analysis of electronic medical records and prescriptions.
Traditional Process: Off-label uses are difficult to track based on paper records.
Off-label use can identify new marketing opportunities and a second parallel test can be conducted at relatively low cost to assure continued safety and effectiveness of both uses.

EHR description: If the drug or device has been on the market for some time historic and future data can be concatenated to expand the test horizon.
Traditional Process: It is difficult to find and map historic data to a current test.
Is a newly discovered side affect new or just newly discovered? Does a longer period of documented use show greater risk?

EHR description: The entire database can be used to assure the test and control groups are representative of all patients who are taking the drug or using the device.
Traditional Process: The study itself does not provide means to assure a representative sample over time.
The patient population may change over time; the test should change to assure that the entire patient population is adequately represented.

EHR description: Analysis can be conducted in near-real-time to minimize damage to patients that may occur between the time an adverse reaction is discovered and the time appropriate action is taken.
Traditional Process: Traditional analysis moves at the speed of paper which can delay appropriate actions to minimize damages.
Quicker response to adverse reactions reduces cost and provides an opportunity to demonstrate concern for patient well being to minimize punitive damages.

Cloud based, integrated electronic health records offer a new paradigm for tracking drugs and devices after FDA approval. This approach allows more testing to be done at lower cost. It supports faster analysis to minimize actual damages to patients and subsequent compensatory and punitive damages awarded to plaintiffs’ and their attorneys. Better healthcare at lower cost.

Originally published under this title on EHRbloggers, October 12, 2011

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Expanding the Scope of EHRs II

Morgenthaler Ventures, a premier venture capital firm, announced August 25, 2011, the 11 finalists of their nationwide contest to find the most promising health IT startups looking for seed and Series-A funding. The contest was organized by Morgenthaler Ventures with co-organizers Silicon Valley Bank, Health 2.0 and Practice Fusion.

There are 22 finalists, 21 of which probably (or potentially) could link to a patient’s EHR. My speculation for each product is indicated in italics. Speculation, not knowledge about specific products, based in part on my two recent posts: Expanding the Scope of EMRs and Devices, Applications and EHRs

These products provide more evidence that EHRs must be designed to interface with “data devices” and apps that go way beyond the scope of most traditional EHRs systems.

Seed-Stage Finalists:

Careticker is the world’s first platform that helps patients plan in advance for a hospital or outpatient procedure. (Miami, FL) probable link to EHR for information

EyeNetra is the most affordable mobile eye diagnostic ever developed, allowing anyone to take their own eye test, get a prescription for glasses, and connect to eye-care providers all on a mobile phone. (Cambridge, MA) add results to EHR for complete record

Skimble powers the mobile wellness movement with a cross-platform ecosystem of fun and dynamic coaching applications. Its latest title, Workout Trainer, ranks Top 10 in the free Healthcare & Fitness category on iPhone/iPad.  (San Francisco, CA) possible data capture for EHR

SurgiChart is a mobile, cloud-based, social-clinical network for surgeons to exchange relevant perioperative, case-centric information. (Nashville, TN) could include data from or links to EHR

Telethrive provides patients an instant connection to doctors for a medical consultation using any telephone or computer with complete audio and video conferencing.  (Los Angeles, CA) possible links to EHR for data and recording results

Viewics provides hospitals with cloud-based analytics and business intelligence solutions which enable them to drive enhanced operational, financial and clinical outcomes.  (San Francisco, CA) probable links to EHR for data

Series-A Finalists:

 AbilTo develops and delivers online mental health programs to managed care members and enterprise workforces that help reduce payor costs while improving overall health outcomes. (New York, NY) probable links to EHR for de-identified data

Axial Exchange moves healthcare organizations towards pay-for-performance, enabling providers to coordinate care and measure clinical quality across disparate settings. (Raleigh, NC) EHR as source of data about treatment and results

Empower Interactive‘s online services deliver proven psychotherapy methodologies via an e-learning platform to greatly improve the economics and accessibility of mental and behavioral health solutions. (San Francisco, CA) potential links to EHR for treatment planning and results

Jiff is the first HIPAA-compliant iPad platform for patient education in the medical industry –used by doctors, nurses, patients and more. (San Francisco, CA) could be driven by data in patient’s EHR

YourNurseIsOn.com employs bi-directional text, phone and email communications to help hospitals and agencies put “the right healthcare providers, in the right places, right now.” (New Haven, CT) no apparent link to an EHR, interesting that this was at the end of the list.

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EMRs Impact on Pharmaceutical Litigation

Electronic Health Records or Electronic Medical Records (EHRs/EMRs) are providing information that is impacting risks, risk management and litigation related to pharmaceuticals. I have posted several articles about the legal impact of EHRs at EHRbloggers.com This page provides links with comments about those posts.

My interest in these issues is based on my commitment to reducing costs and improving quality of healthcare. It is supported by my experience with litigation support consulting assignments. I am not an attorney and this material is not offered as legal advice. For legal advice, consult an attorney.

EHR Technology Driving Drug Safety

March 4, 201
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? …

As a new medication enters the market feedback about its effectiveness and risks will begin to flow very shortly thereafter [in EHRs.] 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.

EHRs Meet Pharma’s Need for Better Risk Management

May 26, 2011
Pharmaceutical product liability lawsuits are notoriously large and represent a major threat to the commercial success of new medications for years after they are introduced. There are new tools available to manage and reduce those risks. … Actual damages provide the basis for lawsuits but punitive damages are often a large part of the final settlement. Early indicators of potential damages offer opportunities to demonstrate concern for patient safety and thereby reduce or avoid punitive damages. … “We didn’t know about the risk,” is no longer a defense, if it ever was one.

EHRs Meet Pharma’s Need for Post-Approval Research

May 23, 2011
Historically, the identification of members of sub-groups and acquisition of additional information has been prohibitively expensive. Rapidly evolving, fully networked, cloud based EMR systems such as Practice Fusion are now being used to collect this data as part of the physician’s normal practice. Data collection, the most costly part of the research process, is now essentially free.

Using data captured by an EHR vendor avoids any real or implied relationship between the doctor who captures it and the pharmaceutical company that uses it. This lends credibility to the outcome by eliminating any appearance of undue influence by the pharmaceutical company on the conduct or outcome of the research.

Personal Health Records Make Care Safer and Cheaper,

April 21, 2011
OTC manufacturers and distributors should find de-identified information about their products and any side-effects or unexpected benefits valuable. … 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.

Electronic Health Records and Securities Fraud

April 12, 2011
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. … The availability of information from electronic health records with large, near-real-time databases like Practice Fusion’s expands the “total mix of information… available.”

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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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EHRs Support FDA Accelerated Approval

There are provisions for accelerated approval by the Federal Drug Administration (FDA) of new drugs for patients with serious illnesses. As an example, Genentech’s Avastin for metastatic breast cancer received accelerated approval on February 22, 2008. On June 29, 2011, the FDA’s Oncologic Drugs Advisory Committee recommended 6 to 0 that the approval be withdrawn. As of this posting, the FDA has not announced a decision.

The approval was based on standard research for this type of medicine and showed sufficient benefit that accelerated approval was granted. Subsequent similar studies raised questions about effectiveness and risks that led to the recommendation for withdrawal.

Standard research methods have been tested and generally provide the required information for FDA action. However, samples are small—the largest sample in this series of tests was fewer than 800. Most of the critical measures are in the low single digit percentages which mean that errors induced by small sample size can be significant.

Recent advances in electronic healthcare records (EHRs) are creating a new parallel path to provide much larger samples to assist in the assessment of traditional research. What ERHs lack in precision, they make up in breadth in both the research target group and control groups. This greater breadth allows for analysis of factors that may contribute to adverse events or produce higher rates of effectiveness among sub-groups in the target population.

There are, according to material presented at the hearings, 45,000 patients diagnosed with HER2-negative matasticised breast cancer every year. All of these patients have healthcares records although most of them are probably not yet in electronic format. Reasonable projections based on recent history and the continued efforts by the US government to encourage the use of electronic records suggest that EHR sample sizes for a population of this size could be well over 1,000 records in the immediate future and in the foreseeable future significantly greater.

Research based on EHRs is relatively inexpensive compared to traditional research because the cost of data collection has already been covered. There are additional advantages as outlined in EHRs Meet Pharma’s Need for Longitudinal Research. I am not suggesting replacing traditional research with EHR based research, but rather, doing both in parallel. A model of such a testing program might look like this:

During Drug Development: Use EHR based research to assist in defining the scope and nature of the potential market for a new drug as soon as there is high probability that a request for FDA accelerated approval will be made. Begin to build a control group that includes all potential variables including current and prior medications used for the target disease. Maximize the size of the control group to minimize sampling error there. Include relevant findings from this analysis as part of the request for accelerated approval and agree to continue the research after approval with the addition of patients for whom the product is prescribed.

At Launch: Begin tracking weekly for market research to gain insights about who is prescribing it and for which patients. Also track any adverse events to manage risk.

Three To Six Months Out: Reduce the frequency of reports to monthly or quarterly depending on market research needs and medical research requirements. Look for clusters of adverse results and clusters of effectiveness. Expand the control group with sub-groups to maintain sampling validity as smaller clusters are explored in depth. Explore options to reduce adverse effects including notices. Explore opportunities to focus marketing aimed at other clusters to improve overall performance in terms of satisfying FDA requirements and improving market penetration.

Map the EHR results to those from traditional research to build credibility for the smaller sample sizes of the traditional research or to explain any differences and their significance for FDA review and approval.

After FDA Approval: Continue the EHR research to manage risks associated with adverse events, continue to develop the market, and find new opportunities for new or improved products.

The rapid evolution and implementation of Web based, fully networked, database driven EHRs like Practice Fusion are creating a new set of tools to facilitate accelerated release and post-release research leading to final approval.


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