HealthyData Blog | Extract Systems

Every patient has a history. Getting those histories moved from other systems and sources is an important consideration when implementing a new EHR. Whether your healthcare organization is deploying a new EHR, replacing one or implementing a new module in an existing EHR, your ability to capture data into the fields of the new EHR/module will define how fast you can use that history to make better care decisions.

Besides, can you imagine your new EHR/module being empty? I think not. Therefore, those deploying new systems invest in data conversion tactics that move as much information into the right spots to make the new system useful. Planning recommendations and checklists for that process are well documented on healthit.gov and many EHR and 3^rd party conversion vendors’ websites.

Your plan: you define the data that will be converted and migrated, including patient demographics, lab results, radiology results, medications, immunization records, allergy lists, ECG and vitals, and other clinical and business documentation.

If data is already structured and can be easily mapped to the new system, then the migration is typically simple. But what if it is not? What if data from the old system needs to be parsed differently for the new system? What if some important data is still stuck on paper or in other unstructured formats?

While many organizations have begun to deploy advanced clinical data capture for day-forward needs, it's equally if not more valuable in converting unstructured or re-mapping structured data to a new system. The advantages of an advanced clinical data capture system include its ability to read unstructured clinical data and find the vital information that is needed for discrete fields of an EHR or specialty database based on the defined criteria set by the organization that has deployed it. Applying the same principles for data conversions speeds up the conversion process, plus the built-in validation and Quality Assurance functionality helps ensure the data is 100% correct. The ultimate goal: A new system with the right historical information so that the right quality of care decisions can be made.

Document management associations and consulting organizations have published a mountain of studies addressing the inefficiencies of manually keying data from unstructured documents to electronic databases. Most acknowledge that manual data entry is error prone, labor intensive and slows the workflow process. Yet, particularly in healthcare, it’s stunning how many organizations still rely on this practice day to day to populate demographic and lab results data into EHRs and other clinical decision support systems.

Beware as I sound off about a sensitive topic, but doesn’t it feel like access to outpatient data and lab results is more difficult than ever? The problem remains: a significant portion of relevant patient information is not being presented to the care team promptly in a format that will provide the most benefit. There is a world of difference for time savings and quality of care between having discrete information in the Electronic Health Record compared to having to search for pages of data or documents. The difference is having data immediately available for overviews, reports and trending. Having patience and a good attitude will go a long way while waiting for structured and usable data.

Enterprise applications are driving change in most every hospital, and transplant programs are no exception. I’ve spoken to many nurse coordinators, and I often hear they are coping with change; many are adopting new systems in progress, or will be soon.  I get to speak to a variety of healthcare personnel as part of my job and it seems that the only constant these days, is change.  Changes in software, changes in workflow, changes in management, and merging of institutions are common.  Sometimes change is for the better of the organization but is it always welcome for the service line or more importantly, the transplant team working with patients.

Are you someone who likes change? 

Effective January 1, 2015, all abstraction of medical records for cancer cases at Commission on Cancer (CoC) accredited facilities must be performed by cancer registrars who have achieved the Certified Tumor Registrar (CTR) credential.

Population health management’s success is based on many factors that fundamentally rely on data. To start, you will need data to segment higher risk patients and rising risk patients from the others. Once segmented, you may also need additional data on those specific patients to continue to assess their risk levels or consider other attributes that contribute to those risks. This data typically originates from the EHR, laboratory, e-prescribing, specialist reports, and claims data.

So, how complete is your data?
We can all agree that the more “complete” data that you have about a patient, the better chance you can use analytics to assess, manage and even prevent common population health issues.  

How can you actually get more complete data?
One existing and easily accessible source of “missing” data for any patient is clinical information that is stuck in paper or electronic documents. Although this data is “accessible” to providers as a scanned document, it does not play a role in supplying population health databases or in running analytics on the data to assess if a patient is at risk. If blood tests or consultative notes from specialists are not getting into the EHR as discrete clinical data, then your population health risk assessments cannot be accomplished easily and reliably.

Mining your existing paper and electronic documents and extracting all pertinent clinical data from them is the easiest, most cost-effective way to begin to fill the gap of missing data. You already have the data, you just need to get it into your systems!

In doing so, it is also important to create workflows that automate this process, not burden clinical staff with data entry, and ensure high accuracy and quality assurance of the data being extracted and entered. By essentially “converting” all document/paper-based information into discrete clinical data, you are on your way to better patient prioritization and better preventative care.

Got data gaps? We'd love to show you some health data management tools to get your unruly, unstructured data in line!

When considering how you get vital clinical data that arrives via “paper” (mail, fax, etc.) into the hands of providers quickly, people often say, “oh, we have scanning.” But what does that really mean?
 
Generally, “we have scanning” falls into 2 areas:

If you're like me, you see your physician regularly for your annual exam. When you reach a certain age, man or woman, one needs to consider routine screenings for cancer. I reached a milestone age for one of those routine screenings this year.  You know, the one where you stay home so you can be prepared for a quick run to bathroom. Don't worry, I won’t go into details, but I’m grateful to say that I’m good for another 10 years. The one thing that amazed me during my outpatient visit, other than the kindness from the nursing staff, was now much paper remains in an ambulatory/outpatient setting. 

Ensuring the Safety and Effectiveness of Laboratory Data in Electronic Health Record Systems

Resource: Paper from CDC’s Lab Program Division
The CDC’s Division of Laboratory Programs recently published a paper: The Essential Role of Laboratory Professionals: Ensuring the Safety and Effectiveness of Laboratory Data in Electronic Health Record Systems. This paper offers excellent cautions, guidelines and advice for both lab professionals and IT staff who work on LIS or EHRs.

Emphasis on three topics

• Engagement: lab professionals have expertise; don’t be afraid to share yours!
• Data Integrity and Usability: lab professionals can guide and maintain data integrity. It’s your data; don’t let it be compromised.
• Innovation: lab professionals are in a unique position to partner with stakeholders to stimulate innovation. Your voice and experience are valued!

The paper is chockfull of studies and resources you can call upon when discussing these topics with your team and colleagues outside your lab. Patient stories bring abstract concepts to life. You’ll find ideas for engaging, a list of opportunities for you and colleagues to be proactive rather than reactive, and strategies you can employ for innovation.
 
It’s about you!
Your knowledge and experience give you a unique viewpoint when it comes to ensuring patient safety. Raise your hand, share your expertise, and use materials such as this paper to help guide that process.
 
You and your colleagues may also be interested in materials from ONC, such as Safety Assurance Factors for EHR Resilience (SAFER) guides. These guides help to assess patient safety risks in lab test orders and results reporting functions within provider EHRs or other health information systems.
 
In future postings of our Healthcare blog, we’ll investigate and share strategies you can employ to ensure your lab leads the way in data integrity and patient safety.

Does your transplant team have all the info they need?

I often read that every detail matters when caring for patients. The evaluation process is complex and peri-transplant treatment decisions leave little room for error. But what happens when physicians don’t have all the information in the transplant information systems? Care decisions may need to be made despite some patient data missing in the database. Or at the very least, decisions are delayed while waiting for additional information.

We all know transplant care involves dozens of professionals. And the average multi-organ transplant program incorporates hundreds of test panels and thousands of individual test components. The average cost of transplantation is well into the six figures. With so much at stake, critical patient information - including external lab results - must be accessible for decision support.