Monthly Archives: August 2011

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 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 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 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 which promises “millions of ratings comparing the real-world performance of treatments across 589 health conditions.” A third is 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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