5 Simple Steps to Optimizing Test-Ordering Patterns in Oncology
Last month, we introduced a small pilot study, led by Lâle White, analyzing the test-ordering patterns of oncologists. A banner example of LabacoEconomics in action, Lâle’s study is yielding eye-opening results that are changing the way oncologists and pathologists practice—and helping to redefine the value of the lab.
This month, we’ll detail specific steps you can take to initiate a similar study in your lab or institution.
For a brief look at Lâle White’s study and the results it’s achieved so far, read “Three stories of how labs can redefine the economics of oncology.”
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immediate and enduring value
Why undertake such a study in your lab? Mainly because a swift, smart analysis of test-ordering patterns can confer both immediate and downstream benefits to help your lab increase quality and reduce spending in the larger continuum of care.
Take a look at some of the positive differences a well-executed test-ordering pattern study might make.
BIG RESULTS - Quickly
Initiating a study like this may seem like a long, drawn-out task. However, an effective pilot study can show positive results in a relatively short period of time.
Refining test-ordering in five simple steps
You can implement a test-ordering pattern study in your lab or institution, simply by navigating through the five phases of Lâle White’s pilot.
Make sure you choose a software company that does more than just review lab orders—they should have experience providing an ordering package.
You also want to select software and content-management partners that are as up-to-date as possible. Watch out for companies using standards like NCCN (National Comprehensive Cancer Network) and ASCO (American Society of Clinical Oncology)—they may be “behind-the-times.”
To initiate a study like this, you’ll first have to team up with the right partners:
provides a package designed to optimize test-ordering
Content-management and semantics analytics partners:
analyze billing data, diagnostic data, and EMRs
Finding optimal partners may require some effort—but it’s a critical step. (Note: XIFIN Software is a company that can offer help in this area.)
You’ll want to review the types of genetic and molecular tests that have been ordered for specific patient conditions. When Lâle’s team did this (looking back at six months of data), they quickly uncovered suboptimal test-ordering ripe for improvement.
Pursue this information in your own institution, choosing a time frame appropriate to your situation. Share your findings with oncologists and pathologists. You may be surprised at their level of interest and how receptive they are to taking action to optimize test-ordering.
Once you’ve gained their buy-in, it’s time to get oncologists and pathologists comfortable with the new ordering software. The proper software is a powerful tool that can sift vast troves of data in real time to show what types of therapies are being selected in similar cases—and which ones are successful. The data allow oncologists and pathologists to make better decisions based on more information than they’ve ever had access to before.
Lâle White, CEO, Xifin Software
Now it’s time to put the system into action. Oncologists should begin ordering tests using the software. As they do, the software will return a prioritized list of tests in as little as 10–15 seconds for the oncologist to consider.
As new test orders accrue, your content management and semantics analytics partners will analyze the new ordering patterns relative to the prior six months (or whatever time frame you’ve chosen). In no time, you may begin seeing results similar to those from Lâle’s study.
With positive results, you will be in a position to approach your C-suite and gain their approval to pursue outcomes data. Do so, and then begin the ongoing process of collecting patient data to build a registry.
Lâle White, CEO, Xifin Software
This is where the rubber really meets the road. An analysis of the registry can reveal real-world improvements in patient outcomes, traced back to diagnostic and therapy decisions made using the new system. This is invaluable, as it demonstrates you are practicing laboratory medicine and positively impacting the area that matters most in the emerging healthcare landscape: patient outcomes.
That’s LabacoEconomics in action.
“The value in optimizing test-ordering patterns extends far beyond oncology,” according to Lâle White. Indeed, any costly area of disease management stands to benefit from this type of analysis: diabetes, cardiovascular disease—you name it. This is especially true when genetic testing is involved, because of the need to educate physicians quickly in this new area and because it impacts smaller portions of the population. Huge clinical trials taking multiple years to generate actionable data are not feasible, nor desirable.
Seek out appropriate opportunities to improve test-ordering in your lab. And consider implementing a study similar to Lâle’s, for its potential to educate physicians, elevate your lab’s status as a leader, and enhance patient outcomes.”
“I think diagnostics—lab diagnostics specifically—provides the shortest-term ability to change the way healthcare is practiced in the easiest manner, because everything else requires so much more data analysis. And this is actually one of those things that can impact your facility almost immediately. That’s what our pilot showed.”