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.
What I know for Sure:
Discrete, trending data is the bread and butter of a specialty clinic.
Hunting and pecking through the media tab to track down information on a patient is infuriating! And not only for the doctors. For nurses. For abstractors. For the patient! Trending a post-transplant patient's drug levels alongside their medication doses, rejections, infections, transplant history, UNOS data, procedures, and relevant transplant-related scores is of paramount importance to a clinician and is very time sensitive. Getting all patient data into the EMR is the holy grail when it comes to specialty medicine.
Specialty clinics, especially transplant clinics, are mini-ACOs.
When you are treating an acute, chronic disease it is critical that everything about the patient is known regardless of where they are being treated on a daily basis. Luckily, we now live in a world of Care Everywhere, CCD documents, and reference labs…BUT, despite what everyone wants to believe, these things are not a panacea.
Paper is very much alive and well in the healthcare world.
Sometimes clinicians are "closet paper users," other times they just lay it out there. But don't make any mistake about it…they are using. In the transplant world, you may be familiar with the "wall chart." Also known as "the flowsheet" or "the flowchart." You know the one. The monstrous grid that is the holy grail for the transplant clinic, but is the disdain of the HIM team and the project team trying to migrate clinicians to the EMR. But there are good reasons for this chart and the other paper being used. Many hospitals have not implemented effective document management strategies that classify documents in useful ways. And many hospitals don't have the resources to support entering (and QAing) important data discretely as it comes in from external sources (or even internal sources such as the pathology lab).
Specialty clinics are crazy busy.
There were times during my tenure at Epic that I felt stressed. That I felt my days were busy. That I felt it was hard to create work/life balance. And then I'd go onsite and spend a week in a transplant department. Wow. My workday was like a walk in the park! The chaos that is the life of a person in a specialty clinic is very hard to explain or quantify. It seems there is not a moment to breathe. And this isn't just for the doctors and nurses. Even the folks doing data entry are getting calls, being pulled into other things, being tapped on the shoulder constantly. It is nearly impossible to give something 100% of your attention.
Extract's products can help.
I'm a passionate person. I don't back something I don't believe in and I don't work for companies whose product doesn't excite me. When I first encountered the Extract product I was very skeptical. Optical Character Recognition (OCR) with clinical data? Fuggettabout it! However, I've been able to peel back the curtain. The magic isn't in the OCR, it's in the rules, logic, and processing that Extract has fine-tuned while working with numerous healthcare organizations. I've seen it in action. I've seen the product improve with features that allow more reliable mapping to patients and existing orders. I've seen it process large documents and auto-classify subsections of that document and route them accordingly (think referral packets, transplant folks!). I've seen it work. I believe in the product and think it can improve data quality, care quality, data entry efficiency, EMR user happiness, and much more.
Extract's products aren't restricted to specialty clinics.
Yes, it is very easy to see the benefit of using the product to discretely enter lab results or split/file referral packets in a specialty clinic. But once you've seen it in action, it's very hard not to let your imagination run wild. Have an HIM department that is backlogged and needs some help classifying and discretely filing data? Have a natural speech recognition engine that needs some intelligent processing and filing after the output is generated? Have Care Everywhere but wish that you could get some more discrete data from it, such as labs? Still have paper DNR, release forms, or patient surveys coming in and want them to be discrete?
Have any other ideas?
We want to hear them! You can email me directly to discuss your ideas further.
About the Author: Rob Fea
He has spent 12 years partnering with IT teams and clinicians at major hospitals and clinics worldwide during his tenure on the technical services team at Epic. For the vast majority of his time at Epic, Rob supported Epic's Phoenix product, playing a major role in project kickoffs, installation, data conversions, ongoing support, and optimization. During his tenure at Epic, he watched the Phoenix customer base expand from 0 to 55 live and installing transplant organizations. It was a terrific experience and he loved every minute of it. It gave him expansive insight into the healthcare world, especially the solid organ transplant industry. Rob has spent countless hours on the floor in transplant departments observing multidisciplinary visits, committee review meetings, data entry, data trending, reporting, medication dosing, and more.
A consultant who supports analytics for population health and quality of care recently told me that frequently, they can only access 80% or less of the total data needed for these initiatives.
If that data is truly random and characteristic of the whole body of data, than acquiring 80% of it is pretty good, perhaps even great. But what if that 80% comes largely from one population sub-group. What if it represents patients who are local - city-dwellers who live nearby and come directly to your facility for lab work and other tests - while the missing 20% is a completely different population. Perhaps this 20% is defined differently by lifestyle, geography or other variables because that population cannot easily come to your facility?
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.
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.
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
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
Transplant Evaluation Process Part 3 in a 6 part blog series
Once the transplant evaluation visit has been completed, the required testing and other consults that were ordered or deemed necessary need to be completed. Frequently, this is the most time consuming segment of the evaluation process and where automation can be most useful.
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.
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.