HealthyData Blog | Extract Systems

As we assist various programs around the country, one of the things we are asked is how does a program balance staffing constraints while accomplishing the many administrative and clerical tasks that are required and still deliver high quality patient care. Frequently when addressing staffing situations, what we find is that programs may have sufficient staff but everyone is doing so many other tasks that it detracts from their true function. Other times, we find that the program is simply understaffed for the volume or number of patients that they are caring for. While the scenarios seem to be different and one would think require different solutions, an assessment of staffing needs begins with an understanding of each role and what tasks that role is actually required to do (not just what we think they are doing). Once the tasks are defined, an understanding of the work flow processes and the current operational chains that each task requires is needed.

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The ultimate juggling act: clinical labs in a hospital setting are required to maintain the highest operational standards. They complete their own inpatient testing while managing the logistics of send-outs and the returning results from reference and specialty labs. No matter where it’s coming from, comprehensive data needs to get back to the ordering physician -  data required to make the best care decisions.

How do clinical labs provide quick and consistent information to providers if some of the data is interfaced and some of it is not? Interfaced clinical lab data travels smoothly throughout the organization to the ordering physician and other providers with permission to access it for the purposes of treating that patient. The data is secure and discrete, allowing providers to use it, graph it, analyze it and compare it to other data relative to that patient. But what if the data is stuck in a faxed document from an external lab? Information arriving this way loses those qualities and creates extra work to open it, find the valuable pieces of information, and consider its implications for that patient.

Tools are available to help clinical labs with the job of running their labs. Lab Information Systems and Analytical Tools enable them to enhance operational, clinical and financial outcomes. But what about the special issues caused by needing to manage your own data AND dealing with incoming results from send-outs?  An LIS or EHR gives you a repository for incoming information and facilitates the sharing of that information with providers, but what tools exist to help clinical labs get the information arriving from many sources into those systems?

A way to better serve the clinical staff is to convert external lab results into the same format (discrete, electronic) and input that information into the same systems as inpatient lab results. A solution for this problem lies in the workflow optimization and automated data capture provided by an Advanced Clinical Data Capture solution. Advanced data capture allows for faster, easier conversion and validation of incoming data into your LIS or EHR for immediate access by your clinical staff, the same way they would access it if the data came from inpatient sources.

 

 

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I was researching topics around data accuracy in healthcare the other day and came across this AHIMA article from 1997 (did we even have the internet back then? J). The article was focused on a growing demand for accurate coded data and as I read the article, I felt that AHIMA was ahead of its time and like I was in a time warp. They were stating the importance of data accuracy and consistent coding to speak about how “these data are used to assess resource utilization and outcomes throughout the delivery system and to develop plans for the provision of more efficient and effective patient care.”  They go on to speak about the “analysis of outcomes has become a major focus because of the relationship between better outcomes, improved efficiency, and lower healthcare costs. Improving the quality of care and managing diseases in such a way that expensive complications can be avoided reduces healthcare costs.” Sound familiar to anyone?

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Interoperability, yes, but with truly accurate data
A mid-Atlantic hospital’s transplant program recently went live with Epic Phoenix to better track pre and post-transplant patients. Prior to the Epic implementation, all patient data was maintained manually on paper flowsheets.

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One of the many advances that have been achieved in transplantation care today is the ability of patients to return to their community physicians after a period of time for most of their long term care. While the ability to receive care closer to home has obvious advantages for transplant patients, it can pose challenges for the transplant centers that are responsible for the outcomes as well as for the community physicians who may not be as familiar with transplant specific issues. With the never ending demands on both transplant centers as well as their community partners, an effective way of managing the data flow between the centers and referral sources is imperative. This includes timely communication and recognition of laboratory and imaging studies. Manual transmission and review of these documents can be time consuming, costly and fraught with error, particularly if the paper does not reach the appropriate destination.

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Let’s imagine that you like the features of your transplant database and your hospital is transitioning your department away from your comfortable and dependable software, into an enterprise application. You’ve likely heard this transition makes sense and will provide costs savings for the entire organization, but you might be wondering if the cost savings will benefit your department. There are obvious economies of scale with an enterprise solution, but you can’t help but wonder if this will create new problems for you. Having access to clinical data within the continuum of care is wonderful, but it hasn’t eliminated the need for a fax machine.

Even as the largest healthcare systems implement enterprise electronic health records, interfaces and interoperability are still issues that must routinely be pondered. For example, the third largest public healthcare system in the nation is still using fax machines to share clinical results with their 1,600 physicians. ( Read More

One of the universal issues we face when asked to help a program that has below standard outcomes, is how that program handles workflow and data management challenges. A big part of managing a transplant program is collecting and managing all the information needed to make good decisions. For instance, regardless of the type of transplant, one common factor that determines who receives the Gift of Life, and when, is the Waitlist. Management of this seemingly simple list can become a daunting task when one considers the complexities of not only transplantation itself, but also of the information management required to determine appropriate candidates to place on the waitlist and ultimately carry out that transplant.

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As I wrote recently, the Certified Tumor Registrar shortage is currently being exacerbated by the Commission on Cancer’s CTR Standard 5.1. I’m not saying the standard is not a worthy step to ensure that the abstraction of patient records to local registries and the NCDB is accurate - just that it clips the available pool of in-house or outsourced personnel to keep up with the load.

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You've just installed a new electronic health record and a dedicated module for transplant.
Now you discover your long term medical secretary, who is capable of typing 90 wpm, is planning to retire. What do you do? High turnover in any service line is a problem, but when you have a constant flow of paper in an environment that requires up-to-the-moment patient data, it is only a matter of time until patient safety becomes your primary sense of urgency. What are your options? 

Have you experienced this before? Your long term employee leaves and now you need to hire two people to handle the workload.

You hate to see them go after investing so much effort to train them on your specialized service line, but it's not uncommon for your workflow to be impacted by life decisions; employees move, retire, get sick.

Healthcare media continues to report that numbers of patient encounters are steadily rising due to the Affordable Care Act, especially in large urban areas. The problem will persist while your new hire(s) get up-to-speed. Your appreciation for that former employee will skyrocket when you realize how much the speed and accuracy of data entry fluctuates from one employee to the next.

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A pressing issue in transplantation today is appropriate organ allocation and ensuring that the sickest patients and those who would benefit the most are afforded the gift of life. In order to be listed, all patients require certain specific data points in order to be successfully entered into the national database and deemed active on the waitlist. For some patients, such as those awaiting a lung or liver transplant, organ allocation is driven by scoring systems (the LAS and MELD score respectively) that are a reflection of disease severity.

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