There are a variety of efforts going on regarding nurse to patient staffing ratios. Learn what’s happening with some of these and the sides people are taking.
Do you ever find yourself asking "how could we still be processing so much paper and faxes in the year 2017?" Sometimes, it can feel like there are mountains of paper that need to be climbed and processed with no summit in sight. There are EMR's, Care Everywhere, FHIR, HIE's, reference lab interfaces, and hundreds of other ways to exchange information electronically. But here we are…still seeing hundreds or even thousands of actual faxes per day in clinics and HIM departments.
I can guarantee that anybody reading this blog uses machine learning dozens of times each day without even realizing it. When you perform a web, search using Google or Bing, for instance, the search engine works so well because their software has figured out how to predict searches and rank pages for you.
A few weeks ago, my colleague started the discussion on signs that you need a more automated way to get valuable information out of a document, 4 Signs You Need an Advanced OCR Solution. People turn to OCR to convert text from a fax, scanned document, or PDF into raw text that can be used more readily. Companies like ours put an intelligent layer over that OCR process and automate the extraction, pre-validation and structuring of that data so that it becomes even more useful more quickly and in a more automated 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.“
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.
There’s no question that users rely on the EMR In Basket for day-to-day workflow management. The “In Basket” or “Inbox,” depending on what EMR you’re using, provides a centralized location to receive notifications and important patient information, such as admission and discharge notifications, new lab results, refill requests, patient calls, appointment reminders, patient portal communication and much more.
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.
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?