User Satisfaction With EHRs

Was just talking about EHR usability with a colleague.  From the ACP:

“Dissatisfaction is increasing regardless of practice type or EHR system,” said Michael S. Barr, MD, MBA, FACP, who leads ACP's Medical Practice, Professionalism & Quality division. “These findings highlight the need for the Meaningful Use program and EHR manufacturers to focus on improving EHR features and usability to help reduce inefficient work flows, improve error rates and patient care, and for practices to recognize the importance of ongoing training at all stages of EHR adoption.”

The findings are from 4,279 responses to multiple surveys developed and analyzed by ACP and AmericanEHR Partners between March 2010 and December 2012. Of the clinicians who responded to the surveys, 71 percent were in practices of 10 physicians or less and 82 percent of respondents intend to participate in Meaningful Use incentive programs, up from 65 percent in 2010.

More.

EHR Data for Medical Research

A nice writeup in the New York Times about mining EHR data to further medical knowledge.

The upside:

The use of electronic records also may help scientists avoid sidestep [sic] the rising costs of medical research. “In the past, you had to set up incredibly expensive and time-consuming clinical trials to test a hypothesis,” said Nicholas Tatonetti, assistant professor of biomedical informatics at Columbia. “Now we can look at data already collected in electronic medical records and begin to tease out information.”

Recent work by Dr. Altman and Dr. Tatonetti, published in 2011, offers a compelling case study. As a graduate student at Stanford, Dr. Tatonetti devised an algorithm to look for pairs of drugs that, taken together, cause a side effect not associated with either drug alone. One pairing popped up when he used his new software to search the Food and Drug Administration’s database of adverse drug reports: Paxil, a widely used antidepressant, and Pravastatin, a cholesterol-lowering drug.

Neither was known to raise blood sugar, but Dr. Tatonetti’s results suggested they might when taken together.

The downside:

But the challenges posed by this sort of research are significant. The information entered into a medical record may be wrong, and diagnostic codes are notoriously unreliable, according to Dr. Tatonetti, partly because they are also used for billing. And doctors don’t think like researchers.

“If a patient gets well after treatment, a physician may not feel the need to follow up with a lab test because it doesn’t have any clinical usefulness,” Dr. Altman said. “But that’s exactly the kind of data a researcher looks for.”

Perhaps the most pressing issue is patient privacy. Electronic health records must be “de-identified” before they can be used for research. That requires more than simply removing a name. Any information that might identify the patient must be excised. At the same time, researchers have to be able to tell when they’re looking at records from the same patient, which may be stored in several databases.

“One patient may be in as many as 20 different databases,” said Dr. William S. Dalton, founding director of the Personalized Medicine Institute at Moffitt Cancer Center, which is currently tracking more than 90,000 patients at 18 different sites around the country. Moffitt combines information from the electronic medical record with data from X-rays and other imaging studies, tumor tissue cultures and even genetic profiles.

“There’s an immense amount of information and different databases, all using different data dictionaries,” Dr. Dalton said. “And they don’t all agree.”

More...

[via coworkers]

Data in EHRs

The comparative effectiveness piece in the Jan MLA News is worth a read.  In particular:

As electronic health record systems begin to provide rich data sources for conducting CER [comparative effectiveness research] and the body of effectiveness research evidence grows, it is likely that evidence derived from CER will substantially supplement or even replace traditional RCTs as the main source of evidence for EBM guidelines and clinical decision support.

EHRs are (or will be) great sources of data and it seems reasonable to expect that data to become the centrepiece of new evidence.  

EHR Alerts, Evidence, and Usability

The IOM's lengthy report on HIT and patient safety provides a nice overview of the evidence regarding clinical decision support (CDS) components of HIT systems (on pp 2-9 to 2-11).  The report discusses the relatively strong evidence for medication alerts and the somewhat lacking evidence for other types of CDS, and more importantly the underlying key to success:

When implementing an alert system, success depends on how alerts impact workflow (Bates et al., 2003). If implemented correctly, alerts can improve patient safety. Alerts have been demonstrated to lower the rate of inappropriate medication prescriptions to select vulnerable populations, such as the elderly (Raebel et al., 2007). Flag alerts — reminders of patient diagnosis or conditions to clinicians who access patient EHRs — have been demonstrated to improve longterm treatment and increase the likelihood of achieving treatment goals (Agostini et al., 2007; Whitley et al., 2006). A retrospective analysis examining a diagnostic alarm system showed that the alarm system could detect and alert clinicians of critical events during anesthesia administration as effectively as anesthesiologists (Gohil et al., 2007).

Simply having an alert in the system doesn't ensure better care.  The same can probably be said of infobuttons and all other CDS features.  To work well, they need to be a seamless part of the clinical workflow.  This is, I think, important for us to keep in mind when we're engaged in conversations about integrating resources and evidence into EHRs.  Integration is important, but we want to make sure the evidence is integrated in a convenient and usable way.  

Using EMR Data to Create New Evidence

Considering the types and amount of data that can be collected and stored in EMRs, the use of such a system to create new evidence seems like a logical step in the progression of EMRs.  In this brief writeup in the NEJM, clinicians used EMR data to inform their clinical decision:  

Our case is but one example of a situation in which the existing literature is insufficient to guide the clinical care of a patient. But it illustrates a novel process that is likely to become much more standard with the widespread adoption of EMRs and more sophisticated informatics tools. Although many other groups have highlighted the secondary use of EMR data for clinical research, we have now seen how the same approach can be used to guide real-time clinical decisions.... We look forward to a future in which health information systems help physicians learn from every patient at every visit and close the feedback loop for clinical decision making in real time.

Give it a decade or two and no doubt Siri will be added in to synthesize data and spout out recommendations.  

[via Evidence-Based Health]