Moving Beyond Manual Data Entry


Vol. 25 • Issue 8 • Page 31

Automation

There’s a running joke in clinical labs that software and data management limitations are the reasons that lab managers have no trouble hitting their fitness-tracker goal of 10,000 steps each day. Diagnostic platforms come with proprietary software that doesn’t allow instruments to be connected to each other-or often to a central information system-keeping lab members hopping from one piece of equipment to the next to monitor test progress and results.

In the age of cloud computing and constant connectivity, outsiders might be surprised by the state of information systems in clinical labs. The molecular diagnostics community, though, is well aware of the inefficient state of data management faced by many teams even at the most advanced labs. Especially as they face budget challenges, clinical labs must make due with technologies that restrict their ability to meet market demands efficiently. There is hope, however, that technology improvements are coming soon to help lab teams overcome the data management hurdles they face today.

Challenges are evident from the start. While some labs process new orders through a lab information system (LIS), others still rely on manual data entry for this step. Either way, as most testing instruments do not connect seamlessly to the LIS, lab staff must make note of the new order, find the sample it pertains to and ensure that the right sample is run on the right instrument with the right assay. For labs processing dozens or hundreds of samples per day, it’s no wonder that occasionally a sample is run with the wrong test.

Once the test is ordered, there are many sample processing steps in which it’s all-too-easy to introduce errors. Commercial-scale labs often employ barcode-tracking systems to tell samples apart, but there’s still a lot of manual intervention-lab members picking up the sample at one station and dropping it off at another.

Monitoring test progress and reporting test results are other areas ripe for improvements. Lab managers often lament the state of systems that require someone to be physically present to check on assays. While diagnostic instruments usually include a computer to process the assays, these instruments do not typically connect easily to the LIS, so technicians are still required to walk up to that station to monitor the run. This presents an even bigger challenge for remote labs, where managers at another site can’t check on progress firsthand. Finally, reporting results back to ordering physicians usually requires manually entering data produced by a diagnostic instrument.

The seamless data transfer we experience in virtually all other areas of life, from getting text updates about a flight status to depositing checks through a smartphone app, has yet to penetrate the world of molecular diagnostic labs. There are several reasons that clinical labs have not yet been able to benefit from these advances in technology. First, there’s a misperception that the complex medical and privacy regulations governing clinical labs make it necessary to use established methods and to keep data out of any system that might be construed as cloud computing, even if it’s a locally based cloud. Another reason is simply lack of ðbandwidth. Testing out a new LIS tool requires a significant time investment from the IT group, unavoidable interruptions in the daily operations of the lab and lots of training for already overburdened lab members. Finally, even lab teams eager to embrace a better approach to data management can’t change what they’re offered by diagnostic and software companies, most of which is still focused on fragmented solutions that do not connect to each other.

The Right Tools for the Job

So, what needs to change? Solutions need to be developed that will help labs minimize manual entry and intervention and easily consolidate data for trending and reporting, while ultimately providing rapid and reliable results for the patient. As millennials join the workforce, mobile-ready and intuitive interfaces will become even more critical. Tools that empower lab managers to gain a full understanding of workflow while ðidentifying challenges and targeting error rates will need to enable labs to run more efficiently. We can get there!

There are already glimmers of hope that this situation will improve in the not-too-distant future. Luminex and other molecular diagnostic companies are working on new tools that will reduce the need for manual data entry and make it easier to track samples. The SYNCT software, for example, connects test instruments directly to the LIS so that everything from order entry to running the assay to reporting results back is handled through a single intuitive interface, which can also be viewed remotely to save time for lab managers and their teams.

Between these advances and efforts to effect change by large societies such as the Association for Molecular Pathology and the American College of Medical Genetics and Genomics, we could see significant innovation in the coming years that will benefit clinical lab teams and improve the quality of patient care through streamlined, enhanced data management systems.

Kevin Welling is senior product manager, ðLuminex Corporation.

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