The leading voices in healthcare are talking about the next big thing on the horizon. That would be CHR (Comprehensive Health Record). But what about the unfinished business that still exists for healthcare records? How do you incorporate the data from incoming external documents that bog down clinics and hospitals? This data comes from faxes, paper, and scanning workflows.
Patients feel that they aren’t getting quality care from their physicians. They are being incorrectly diagnosed because they simply aren’t getting more than 15-minutes with their physicians. Their questions aren’t being answered, but instead being directed towards nurses. Patients are feeling more and more like Dorothy from the Wizard of Oz, on a journey to the Emerald City to find the Wizard and ask the for help.
Many of you know the fairly tale tilted, "Goldilocks and the Three Bears." Upon entering the home of the Three Bears, Goldilocks sits in their chairs, eats their porridge, and falls asleep in their beds. Upon sampling each of the Bear's chairs, porridge, and beds she exclaims that one is too much, the other is not enough, but the last option is just right. What does this fairy tale have to do with Healthcare data and performing one's job, you may ask?
Once again I had the pleasure of attending the 24th Annual UNOS Transplant Management Forum for my 4th time earlier this year. As always, it was a flurry of learning, knowledge-sharing, networking, and well-deserved awards for leaders in the industry.
It was as apparent this time as it was every time before, that the transplant community is a close-knit group who all struggle with similar things regardless of their geographical location. These struggles span across many areas, including financial, staffing, regulatory requirements, lack of organs, information technology, reporting, managing the constant deluge of paper, and many more. While I can't claim that Extract can help with all of these, there are two specific struggles that we excel at fixing: extracting discrete results from faxed external lab results and intelligently splitting, classifying, and filing large documents (such as referral packets) into patients' charts.
Despite massive adoption of electronic medical records over the past several years, the promise of easy and nearly effortless chart abstraction from electronic medical records enabled by an interconnected web of interoperable EMRs sharing standardized data has yet to be fully realized. You need to look no further than the media tab to see the evidence that we have yet to arrive at this Utopian future.
Do you frequently find yourself searching for and routing documents, whether paper or electronic, to colleagues, care team members or departments that need them? Or, worse do you find yourself waiting for documents to be routed to you? In our work, helping hospitals to automate clinical data abstraction, we're struck by the hours of time lost each day to inefficient workflows involving "loose" records that we often find ourselves helping our customers extract data from.
An ounce of prevention is worth a pound of cure. Or, reduce medical errors through better documentation. Which one of these expressions do we tend to remember? In healthcare we hear quite a bit of talk these days on reducing medical errors. Of course this is with good reason. When getting data into the EMR, errors such as inaccurate or delayed results, can negatively impact patient health and lead to extended hospital stays, unnecessary treatment or worse. As a matter of fact, many healthcare organizations are now striving to eliminate mistakes and streamline efficiency by adopting principles such as Six Sigma and other business practices which are designed to continuously evaluate and improve best practices.
Health data challenges are a part of any healthcare organization. Frustration is a natural consequence. This is also a common topic in most healthcare press lately. It often feels like depending on which way the wind is blowing, the consensus is that EMR adoption by clinicians is either improving or getting worse. A recent KLAS report indicates adoption is improving across the globe. The decision to move to an enterprise EMR for most organizations often includes as a factor the goal of reducing the total number of applications supported. Initiatives to improve adoption then becomes a challenge if your department's prized application is removed for something "less than robust". Along with pain and frustration, keeping your clinicians happy is also a challenge
In our last post in this series, we talked about the challenges of getting ready for the selection committee meeting. As a transplant coordinator, the selection committee meeting is your opportunity to advocate for your patient that you have been nurturing from the initial evaluation until this upcoming meeting. Now that your patient has completed the pre-transplant evaluation which I covered in the first post in this series, the decision of whether or not to add them to the waiting list must be made.
In my previous post, the fourth in a series of seven blog posts that discuss some of the misconceptions about lab interfaces and intelligent clinical data extraction software, I addressed the belief that if a hospital has an in-house laboratory, all test results will be integrated with the patient record in the EMR.
In a recent Health Informatics Journal article reporting of “true integration” of electronic laboratory results, it was mentioned that transcription errors remain a bottleneck with comprehensive electronic health records. This shouldn’t come as a surprise to those who encounter paper labs every day in their daily workflow. For most hospitals, a significant number of records are interfaced. But if you are working with paper daily, you might think it debatable that manual data entry is insignificant.
As with every study, the article laid out the limitations of this particular study, which focused on blood pressure only, before getting into the detailed results of their work. The seven limitations they named were quite typical, including possible duplicate data and possible non-reporting of improved patients, but the limitation that seemed most unnecessary and raised my blood pressure indeed was, “Sixth, incentive program CQM reporting was based only on the data available in the EHR system of the health care provider. If a patient transitioned to another provider, such as a specialist, the original EHR might not have subsequent, possibly improved, blood pressure values recorded.”
Recently there was a new report that got the attention of my colleagues here at Extract Systems. The headline was “Urgent Change Needed to Improve Diagnosis in Health Care or Diagnostic Errors Will Likely Worsen.” According to this report issued by the Institute of Medicine of the National Academies of Sciences, Engineering and Medicine, most people will experience at least one diagnostic error – or inaccurate or delayed diagnosis – in their lifetime.