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?
In most healthcare institutions, medical procedures are associated with orders or encounters. An order (or standing order) can be defined as rules, regulations, protocols, or procedures prepared by the professional staff of a hospital or clinic and used as guidelines in the preparation and carrying out of medical and surgical procedures. An encounter can be defined as a health care contact between the patient and the provider who is responsible for diagnosing and treating the patient.
It’s had to find good news in the report published by Protenus Breach Barometer. Their research says there were, on average, one significant protected health information breach per day during the month of January 2017. As a company that helps prevent criminal acquisition of data, I can say that I am not surprised. If you are sensitive to the issue, you’ll regularly see this kind of news.
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.
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.“
Critical results reporting or reporting lab results for priority patients from non-interfaced sources is no easy task. A delay in reporting can yield an unfortunate outcome for a patient whose condition is deteriorating. This is especially true for specialty departments that provide continued care for patients from far-flung locales, such as the transplant program. One transplant department receives thousands of these reports over a single patient's lifetime, and often hundreds of these documents for its patient population each day by fax.
The Centers for Medicare & Medicaid Services regulates laboratory testing performed on humans in the U.S. through the Clinical Laboratory Improvement Amendments (CLIA) to ensure quality laboratory testing. CLIA sets high standards for quality control, validation of data and tests, equipment calibration, proper training and certification of users and clear end result reporting that meets proper lab data requirements.
Tracking data in your transplant care software is a key component of QAPI programs, not only for CMS, but now also with UNOS debating the requirement of QAPI programs. One of the most challenging aspects of transplant program management is ensuring that your Quality Assessment and Process Improvement programs are measuring meaningful and actionable items that lead to program improvement.
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.
Healthcare Informatics recently published an article most of us can relate to—that if you want to remember something important, it helps to write it down. Information is only useful if available. According to the article, Research: Access to Docs’ Notes Increases Medication Aherence, researchers at Geisinger Health System found that patients who had access to their doctor’s notes demonstrated an improved adherence to a medication regimen. [medical record software and information accessibility
The Initial Evaluation
The evaluation process is really the lifeline of your program. If not done properly, your program will lack good candidates for transplant or will have insufficient patients to transplant. This is a critical topic! In our first blog of this series, we focused mainly on what happens when a new patient is referred to your program.
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.