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One of the many promises of EHRs is that, in fairly short order, they’re going to make an ever-growing amount of data available in the quest for better population health management.
But how realistic is that promise?
As this academic sees it, “there is sometimes unbridled enthusiasm that the data captured in clinical systems, perhaps combined with research data such as gene sequencing, will effortlessly provide us knowledge of what works in healthcare and how new treatments can be developed. . . . I honestly share in this enthusiasm, but I also realize that it needs to be tempered, or at least given a dose of reality. In particular, we must remember that our great data analytics and algorithms will only get us so far. If we have poor underlying data, the analyses may end up misleading us. We must be careful for problems of data incompleteness and incorrectness.”
From there he goes on to cite a number of reasons for poor data capture. “Probably the main one,” he says, “is that those who enter data, i.e., physicians and other clinicians, are usually doing so for reasons other than data analysis.”
Adding to the list, he says, “I also know of many clinicians whose enthusiasm for entering correct and complete data is tempered by their view of the entry of it as a data black hole. That is, they enter data in but never derive out its benefits. . . . (A) common complaint I hear from clinicians is that data capture priorities are more driven by the hospital or clinic trying to maximize their reimbursement than to aid clinicians in providing better patient care.”
And then there’s data entry logistics, which in our experience is the most common lament among providers. As he puts it, “Another challenge for clinicians is the time required for electronic data entry. There is no question that the 20th century means of clinical documentation, mostly consisting of scribbling illegible notes on paper, was much easier and faster than typing and/or clicking.”
So what can be done about it? Well, he’s got some suggestions, at least in broad terms. But we’re pondering, and hearing your thoughts, on the overall timeline. In other words, mountains of data have been promised, and in many respects that promise is already coming true. But, to his point, there’s a difference between having lots of data and having lots of useful data.
So how long will it be before we can seriously say the data being captured and stored in new EHRs is actually leading, on a broad scale, to new opportunities for patient care?
Jeff Rowe blogs regularly at EHRWatch.com.