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.
I chose the title for this blog a bit tongue in cheek. You see, there are numerous blog posts about how to “properly” redact PDF files. While all of those other blog posts correctly explain the challenges that makes redacting PDF files difficult and outline all of the steps that one must take to ensure private information is completely and irreversibly redacted, all of those blog posts fail to mention one critical idea that anyone tasked with the important job of redacting electronic documents should be aware of -- automation.