Data analytics are getting increasingly more important as the healthcare industry is moving towards a more value-based care mission. In a recent article, experts pose the question, how will analytic tools evolve and what’s next? To answer this question, they weigh in on major industry shifts.
Googling the phrase “Clinical Data Capture” leads to an entire page of results dedicated to “Electronic Data Capture” for clinical trials. There is a vast number of articles and vendors that suggest they cover the existing challenges, technologies and innovations happening this area. But is this really true?
So, you're thinking of migrating to Epic's solid organ transplant module Phoenix? Or did you recently switch? The Phoenix product has come a long way since its initial release around 10 years ago. It is a great way to effectively manage your transplant population within the fully-integrated Epic suite of products. I helped to support the first 40 or so Phoenix go-lives during my Epic tenure and take great pride in the application.
Automating the extraction of all required information from faxes or other non-interfaced sources, ensures your patients’ safety and complete, compliant information in the EMR. Any solution you use should be matching patient and order level data, collecting physician demographic information, and capturing...
Recently while attending the AHIMA Conference last month in Baltimore I engaged in a number of conversations during the general sessions. As you may have guessed, many of the topics revolved around EMR integrations and data extraction. Being a conference for HIM professional’s, clinical documentation was also a major concern.
In the medical field, if you are an organization that receives incoming faxes of documents, you could have dozens of different categories. However, if you are part of the organization that manages lab results, the most important documents are those lab results, then everything else. In a world consumed by managing documents, proper classification and routing is critical to controlling these lab results. CAP Today outlined the need for lab documents control in their article, Bedeviled by Documents, Labs Seek Control.
If Google can make a self-driving car why can’t external labs be automatically integrated (driven) into clinical information systems?
Recently while visiting a National Cancer Institute customer that is also a designated Comprehensive Cancer Center we had a brief chuckle regarding cutting edge technology and healthcare. Our customer, a large academic medical center, had asked us to come and talk with other departments about expanding our clinical data extraction software to other departments. They currently use Extract to capture data from lengthy pathology reports and then import the information into their data analytics repository.
No, this isn’t an article about buying cars. Although it may sound like it, I'm actually talking about clinical extraction software. There are some striking parallels when comparing car purchases and data extraction software purchases.
Aside from the fact that modern cars are essentially computers on wheels—on average containing thirty computers and millions of lines of code—buying a car is similar to the purchasing process of choosing an extraction software in a more practical way.
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 recently spent three days driving across the northern Midwestern States and through a good part of Canada with a longtime friend as we headed to a once-in-a-lifetime wilderness adventure. As you might imagine our conversations spanning those 72 hours took as many twists and turns as did the roads we traveled. However, one saying my friend repeated several times stood out among many insightful remarks he’d made, “Your judgement is only as good as your information.“
Recently, Andy Slavitt, the CMS acting administrator, announced that CMS will likely end the Meaningful Use program this year.
Does that mean that the hopes of an internet-worked healthcare system that’s able to seamlessly share health information are completely dashed before interoperability truly got off the ground?