The promise and pitfalls of eHealth


12.17.13 Thumbnail ElectronicRecordsOregon Health & Science University recently formed a partnership with Epic Systems Corp., one of the top makers of electronic medical record software. I talked about the future of “eHealth” with Dr. Aaron Cohen, an associate professor who directs commercial partnerships and collaboration for OHSU’s Informatics Discovery Lab.

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12.17.13 Blog ElectronicRecordsThe Obama administration has committed to spending $38 billion to push the development of electronic medical records, computerized decision support systems and related technologies. This massive investment in eHealth holds the promise of  improving quality, reducing medical errors, and saving money. Evidence to support such claims remains a little sparse, however, and some hospitals and health systems rushing to adopt eHealth solutions have actually worsened quality of care.

Aiming to speed the development of practical and effective eHealth solutions, Oregon Health & Science University recently formed a partnership with Epic Systems Corp., one of the top makers of electronic medical record software. OHSU’s Department of Medical Informatics & Clinical Epidemiology is the first academic center to sign such a deal with Epic.

I talked about the future of eHealth with Dr. Aaron Cohen, an associate professor who directs commercial partnerships and collaboration for OHSU’s Informatics Discovery Lab.

OB:  Can you tell me more about the terms of your deal with Epic Systems Corp.? What’s in it for OHSU and for Epic?

Cohen: Right now this isn’t really a financial exchange. This is a deal in which Epic supports us to use their system in ways it really hasn’t been used before. Education is one part. People really need hands-on training with real-world systems, but access to a large-scale commercial electronic health record has not been available before. The other side of this is training our researchers to use electronic health records for health system research. Epic is providing technical support and has enabled us to use Epic for informatics research and education by taking a broader view of the terms of our licensing agreement.

OB: Will any intellectual property come out of this, and who will hold the rights to it?

Cohen: I certainly hope that intellectual property will come out of this. We are building the infrastructure to allow us to do that kind of thing, to push Epic to its limit and come up with innovations. But the means of determining who owns what will be on an individual project basis.

OB: Sounds like you are aiming for some applications that are like nothing out there right now. Any particularly eye-opening examples?

Cohen: Yeah, I can think of several. One is, there is a lot of interest in expanding the electronic health record as a platform for doing both decision support, and resource and risk management. For example, if there was some special services that would benefit a particular patient before they are discharged you’d like a way to identify those patients in advance. Some of that identification could be done with advanced algorithms working off data that’s already in the electronic health record. I’m thinking of things like discharge planning services or frequent home health visits. One thing that could aid clinicians is some sort of risk modeling that could tell them how likely is this patient to not do well when they go home.

To actually get use out of  this, you need [the electronic health record] to be able to interact with the caregiver and the patient at the point of care. You can’t expect a physician to turn to the side, open up another computer window, and type in a bunch of information to query this expert system. It has to be integrated into the electronic health record so the information is immediately available when they need it and they don’t have to do anything extra to get it. The question is what kind of technological innovations are going to be necessary to do that. 

OB: How far are we from that vision? I’ve heard that the promise of decision-support software and predictive models has barely been tapped.

Cohen: It’s hard to give a year kind of estimate. We’ve really just gotten over the hump of deploying electronic health records, right? In the majority of large health systems the medical records are stored in electronic ways, so the data is available to be accessed and used. So now the next phase is getting additional value out of that data and providing that value to the patient and the care providers in a way that aligns with their work flow. The deeper value, the big data analytics value, we are only now able to start attacking some of those opportunities. 

We’re still learning the best ways of integrating these things together, the best ways of learning from data, the best ways of changing our work flows and processes to improve care, and how to measure those improvements. I can’t tell you how long it’s going to take [to realize the potential]. I will tell you though, the emergence of strong players in electronic health records, along with partnerships like what we are doing with Epic are the way we are going to learn these things and drive them forward. 

OB: Only at the end of 19th century did physicians begin to systematically record patient data. In the beginning, according to one historian of medical records, “Templates designed to organize and present these data in the medical record often sowed confusion instead. The result, today’s medical record, may not be what we intended.”  What unintended consequences are you worried about as we move into the era of electronic medical records?

Cohen: One of our faculty, Joan Ash, is an expert in this. I’m not the expert. There is a whole literature on unintended consequences of electronic medical records. I think there are a lot of lessons we’ve learned. One of the things that we still need to learn is how to better present the information that’s needed to the right person at the right time.

Another potential unintended consequence is caregivers relying too much on the technology. As opposed to the technology being an aid, it becomes more of a dependency. And so they figure, oh well, if the automated algorithm doesn’t  show me this data point there must not be that data there so I’m not going to look for it.  Which would be a mistake because in the end the responsibility always has to be with the clinician, the caregiver. 

OB: Experts in this field talk about the seductive power of data. “The problem of having too much information is now surpassing that of having too little,” according to the New England Journal of Medicine. How is that a problem, and what are some ways of handling the data deluge?

Cohen: There are two ways of looking at this. There is an individual clinician taking care of an individual patient and needing to have data that’s relevant to that encounter available and convenient and handy. Having too much data that is not pertinent, you can see how that would be a problem. The way EHRs are built right now, it’s like complete data overload. There is just so much data, and the screens are so complicated, and things can be in so many different places, that we really need to come up with different ways to visualize information, different ways to find information, and ways of integrating that information into the work flow of care providers. And that is something we are working on.

But from the other side, from a societal, medical knowledge point of view, I don’t think there is such thing as too much data. The more data you have, the more you can learn from it.  One of the things I’ve done my research on is ways of using computer systems to improve the systematic review process. Systematic reviews are ways of synthesizing a lot of studies into the current knowledge. A lot of those studies are based on randomized controlled trials, which are seen as the highest quality evidence in medicine.

The problem is, randomized controlled trials are very expensive. You can’t do enough randomized controlled trials to answer every question we have in medicine.  You can’t afford to do them all. And some questions you would like to address, you can’t do a randomized clinical trial because it is unethical. The way we can sort of combat that for situations where it’s not practical or ethical to do a randomized clinical trial is doing large retrospective and observational prospective studies on large amounts of pooled data from electronic health records. That’s another one of the great promises of the electronic health record. When this data is all digitized, we’ll be able to answer questions we wouldn’t otherwise be able to answer.


SIDEBAR: Nine unintended consequences of eHealth

Joan Ash, a medical informatics professor at Oregon Health & Science University, and her colleagues have identified nine types of harmful, unintended consequences that can arise when health systems implement computerized order entry. It’s an eye-opening catalog:

More/New Work Issues: Physicians find that CPOE adds to their workload by forcing them to enter required information, respond to alerts, deal with multiple passwords, and expend extra time.

Workflow Issues: Many unintended consequences result from mismatches between the clinical information system (CIS) and workflow and include workflow process issues, workflow and policy/procedure issues, workflow and human computer interaction issues, workflow and clinical personnel issues, and workflow and situation awareness issues.

Never Ending Demands: Because CPOE requires hardware technically advanced enough to support the clinical software, there is a continuous need for new hardware, more space in which to put this hardware, and more space on the screen to display information. In addition, maintenance of the knowledge base for decision support and training demands are ongoing.

Paper Persistence: It has long been hoped that CIS will reduce the amount of paper used to communicate and store information, but we found that this is not necessarily the case since it is useful as a temporary display interface.

Communication Issues: The CIS changes communication patterns among care providers and departments, creating an “illusion of communication,” meaning that people think that just because the information went into the computer the right person will see it and act on it appropriately.

Emotions: These systems cause intense emotions in users. Unfortunately, many of these emotions are negative and often result in reduced efficacy of system use, at least in the beginning.

New Kinds of Errors: CPOE tends to generate new kinds of errors such as juxtaposition errors, in which clinicians click on the adjacent patient name or medication from a list and inadvertently enter the wrong order.

Changes in the Power Structure: The presence of a system that enforces specific clinical practices through mandatory data entry fields changes the power structure of organizations. Often the power or autonomy of physicians is reduced, while the power of the nursing staff, information technology specialists, and administration is increased.

Overdependence on Technology: As hospitals become more dependent on these systems, system failures can wreak havoc when paper backup systems are not readily available.


Source: The Extent and Importance of Unintended Consequences Related to Computerized Provider Order Entry by Joan S. Ash, Dean F. Sittig, Eric G. Poon, Kenneth Guappone, Emily Campbell, and Richard H Dykstra; Journal of the American Medical Informatics Association (2007).

Joe Rojas-Burke blogs on science and health care for Oregon Business.10.04.13  Blog Health joerojas