Category Archives: Opinion

Opinion of the author

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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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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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.

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Electronic Tower of Babel II

“Friday, July 30, 2010: When the Veterans Affairs and Defense departments began testing health information sharing for their joint virtual lifetime electronic record (VLER) project, they could not initially exchange patient data successfully using the very standards specified by the Office of the National Coordinator for health record formatting. …

“Dr. Doug Fridsma, acting director of ONC’s standards and interoperability office, used the experience of VA and DOD as an example of the trickiness of getting standards right so healthcare providers can exchange health information properly. C32 is among the requirements of ONC’s recent final rule on standards and certification of electronic health records (EHRs).” Government Health IT http://govhealthit.com/newsitem.aspx?nid=74346

Two agencies of the Federal Government encounter the electronic Tower of Babel. Can 200+ vendors who are focused on individual healthcare providers with little or no financial incentive to deal with the networking of data beyond insurance do it better?

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EMRs: An Electronic Tower of Babel?

When you mix 200+ EMR vendors with $19 billion dollars of federal funding and send them out to chase 700,000 doctors and 5,000 hospitals what do you get? We are about to find out.

Years ago the commercial world learned that it is almost impossible to network and share date between computer systems sponsored by siloed organizations within a single company: marketing, production, distribution, HR, etc. The solution was enterprise systems (ERPs) from a limited number of vendors that cost millions and take years to fully implement.

Now we are looking to independent medical providers to acquire systems from a very large number of vendors driven by pressure to implement quickly with only limited standardization of some data and expecting to reap the full benefits of networked data.

It sounds more like a recipe for an electronic Tower of Babel than a solution for the 21st century. Am I missing something?

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EMR Risk & Opportunities Map

Medical information is rapidly moving from paper records to electronic formats and new sources of information are being added. The electronic formats provide opportunities to capture, store, share and use information in new ways. These new ways create risks and opportunities.

Most of the elements identified and discussed here have been identified and discussed by others. What is new, is a broader view of more elements at the same time and their interdependencies.

It is these interdependencies that pose risks and create opportunities.

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THE MAP

Cathedral & Bazaar Revisited: Healthcare Information

One of the problems we face when we talk about electronic medical records, personal health records, etc. arises because we think and talk about them as systems. A recent post on LinkedIn says:

What was apparent from the first 23 comments is that opinions and perspectives are all over the place. It’s not clear folks are all of one mind with respect to WHO constitutes the users, WHAT constitutes an EHR, what constitutes usability, and/or HOW one should be assessing usability. Many look at usability only from, ultimately, the safety perspective (decreasing medical errors), but how about efficiency, including impact on overall workflow? User acceptance/satisfaction? What are the appropriate usability measures by which to evaluate EHRs?

These are systems related questions. Systems lend themselves to being defined, developed, deployed and used. That is not the case with healthcare information. The information requirements of healthcare providers, patients, and the supporting infrastructure are evolving rapidly as we learn what works and what doesn’t. Supporting technologies – iPhone and iPad to name just two – are evolving and enabling new cost effective services to be provided. The economics of health care are changing because the current medical business model doesn’t fit any economic model that makes sense and the economics of health care are what will provide much of the funding for information solutions. The problems and opportunities of health care information don’t lend themselves to the discipline required for traditional systems.

In 1997 Eric S. Raymond published an essay called The Cathedral and the Bazaar that described the traditional system development process as centrally managed and built to last like a cathedral as contrast to a bazaar that is constantly being modified by its users to meet their evolving needs—in his essay: Linux. The article was sold and is now copyrighted and available only for a fee.[1]

Eric now points to In Praise of Evolvable Systems by Clay Shirky which points in the same direction. I think Shirky’s definition of Evolvable Systems provides and apt description of what is required to realize the benefits promised by improvements in health information:

THREE RULES FOR EVOLVABLE SYSTEMS

Evolvable systems — those that proceed not under the sole direction of one centralized design authority but by being adapted and extended in a thousand small ways in a thousand places at once — have three main characteristics that are germane to their eventual victories over strong, centrally designed protocols.

  Only solutions that produce partial results when partially implemented can succeed. The network is littered with ideas that would have worked had everybody adopted them. Evolvable systems begin partially working right away and then grow, rather than needing to be perfected and frozen. …

  What is, is wrong. Because evolvable systems have always been adapted to earlier conditions and are always being further adapted to present conditions, they are always behind the times. No evolving protocol is ever perfectly in sync with the challenges it faces.

  Finally, Orgel’s Rule, named for the evolutionary biologist Leslie Orgel — Evolution is cleverer than you are. …  it is easy to point out what is wrong with any evolvable system at any point in its life. … However, the ability to understand what is missing at any given moment does not mean that one person or a small central group can design a better system in the long haul.

Evolution is messy, brilliant ideas don’t work, money is wasted, efforts are duplicated, but the Internet has shown that the process is capable linking growing requirements with expanding capabilities to produce solutions to problems we don’t even know we have. The Internet is a better model than traditional, cathedral like systems for what we are dealing with when we talk about converting and sharing medical information in an electronic format.

It’s dinosaurs vs. mammals, and the mammals win every time. … Infrastructure built on evolvable protocols will always be partially incomplete, partially wrong and ultimately better designed than its competition.

There will be some large systems to deal with complex environments. Small systems to deal with special needs. “Apps” to deal with general needs, and forms we haven’t imagined to deal with opportunities undreamed of. We need to recognize that lack of clarity and structure is just part of the process. We need to learn to live with it and occasionally laugh at it, curse it, and celebrate it


[1] Eric S. Raymond (1999). The Cathedral & the Bazaar. O’Reilly. ISBN 1-56592-724-9.

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