Leveraging existing lab data can improve laboratory performance and profitability
By Diane Janowiak
The beginning of 2018 ushered in new Medicare Part B price cuts for clinical laboratory and anatomic pathology testing, which the government expects will lower spending on lab tests by $400 million annually. These reductions in Medicare reimbursement rates come at the same time that rising copays are forcing many consumers to foot a greater portion of their bill for diagnostic testing, causing more patients to question the necessity of tests.
The convergence of reduced reimbursement rates and more-discriminating healthcare consumers is creating a difficult environment for clinical labs, many of which are already facing squeezed margins. Many hospitals are responding by questioning whether clinical diagnostic services should be considered a core asset, and some have chosen to outsource their clinical laboratory and diagnostic imaging services. In fact, the nation’s two largest lab services providers now work with about half of all US hospitals, and are positioning themselves with health systems to purchase hospital labs or to contract with hospitals to run their labs.1
In order to position a lab as a profit center rather than a cost center, clinical labs must make up lost revenue while also providing amazing customer service to both providers and patients. To accomplish all of these goals at once, lab managers must have insight into data that can help them make better decisions about which services are most profitable, and where to devote their time, while also automating as much as possible.
Traditionally, lab managers have made decisions about everything from staffing to quality initiatives based on such lagging indicators as workload volume, average time to resolve customer issues, and policy adherence. What’s more, pinpointing these indicators has been done manually by documenting incoming calls, gathering data, and searching through paper records—time-consuming processes that virtually guarantee the data will be obsolete before improvement initiatives commence.
A healthcare relationship management (HRM) system can help automate such manual processes, leveraging data already available in the lab to generate real-time insight that empowers managers to take immediate action (For more information, see “What is HRM?“).
There are three areas in the lab that are especially ripe to benefit from automation: optimized staffing, improved quality, and utilization management. By automating these three areas, clinical labs can better position themselves as revenue generators for the health system, and avoid the likelihood of having their operations outsourced.
Employee pay and benefits account for more than half of a laboratory’s direct costs.2 When looking for ways to cut costs, it’s no wonder that lab managers frequently opt to reduce staff as a quick fix. Unfortunately, staff reductions often lead to declining morale and service issues, which can have a negative impact on the lab’s bottom line. For all of these reasons, lab managers find themselves challenged to balance laboratory staffing and efficiency with expected service levels.
The better approach is for lab managers to fully understand their lab’s workflows, in order to identify precisely where changes need to be made. But getting a handle on all the information necessary to understand the workings of a laboratory can be difficult to do. In today’s labs, as a normal part of performing patient testing, staff already spend a great deal of time gathering data, receiving incoming calls, and searching through paper records. Trying to understand operational tasks at the same time is nearly impossible.
Even with a plethora of data systems—billing, case tracking, and laboratory information systems (LISs), to name a few—unifying a laboratory’s data in a way that can uncover trends and make workflows understandable is extremely difficult. Most of the data from such systems reside in their own data silos, making it hard to pull together a unified view of a lab’s operations.
HRM systems, however, unify all these data silos and make data ‘actionable.’ In other words, an HRM can provide a comprehensive view of lab data, revealing insights that could not be discovered by looking at just LIS or case tracking data, for example. Using an HRM system, labs can integrate both clinical and business data into a single system that reveals ways to streamline internal processes, and quickly uncovers where operational breakdowns are occurring.
When looking for ways to optimize staffing, lab managers can look to the HRM system to pinpoint the busiest times in the lab by tracking repeatable trends based on historical data, such as workload volume and turnaround times by the day of the week and hour of the day. A staffing director who automates a test volume dashboard in the HRM system, for example, may notice that volume is lightest on Mondays and heaviest on Thursdays. The director can then make staffing decisions based on this information. For outreach labs, the same types of data might make it possible to reduce courier services on low-volume days, thereby avoiding unnecessary pick-up visits (Figure 1).
In a similar example related to staffing, Cleveland Clinic Laboratories (CCL) now uses an HRM system to ensure that physicians are notified promptly about test results. In the past, CCL spread its critical and urgent lab testing across 10 separate campuses, making lab technicians at each location responsible for calling physicians to report test results. Since the same technicians were also responsible for performing tests, calls to physicians were often delayed, and CCL gradually found that the communication of test results had slowed. Using an HRM system, CCL centralized physician calls in one location and set up automated alerts that prioritized calls based on test urgency and how long results had been ready. Staffed with professional customer service reps, the new center significantly decreased notification time while increasing efficiency.
In order to remain in operation, labs that are certified under the Clinical Laboratory Improvement Amendments of 1988 (CLIA) are subject to ongoing quality inspections. Because of the importance of such inspections, it is not uncommon for a lab to delay any initiatives outside of its core testing processes prior to an inspection, so that it can generate reports on key performance indicators (KPIs).
Sometimes it can take months to pull reports together, and often IT resources are called in to help examine data and assemble usable reports and metrics. Even so, by the time the reports are put together, they are based on old data.
Rather than relying on manual processes to understand lagging KPIs, an HRM platform can automatically look at data in the system and send quality managers the real-time trend reports they need to plan for and pass regulatory inspections.
Automated reports can also deliver management efficiencies not possible with manual analysis of data. For example, lab managers can set up automated notifications when turnaround times are outside of the lab’s acceptable range, enabling lab directors to identify outliers by physician. Rather than being blindsided by a call from a concerned physician, the lab director can then contact the physician ahead of time to provide updated scheduling for the delayed reports. Directors can also set up automatic reports on volume trends by client, and can then investigate and address the reasons for declining test volume before an account is lost (Figure 2).
An HRM system also enables lab directors to capture items outside of a typical quality control drift, such as error corrections, instrument downtime, and temperature omissions. Automated reports based on such data can help lab directors provide additional training and instruction to maintain and improve performance quality.
For labs seeking to boost profitability, reducing operational waste is an essential first step. And there’s plenty of waste in clinical labs. In fact, one study showed that clinical waste accounted for about 14% of total healthcare spending in 2015.3
Utilization management is a means of reviewing a laboratory’s overutilized, underutilized, antiquated, or unreimbursed tests, and can be used to guide labs and their ordering physicians toward new ordering practices and reduced waste.
Utilization management is expected to become even more important as the use of genetic testing increases. Modern genetic tests are very expensive, but since they uncover an amazing amount of patient and genomic data, it’s easy for physicians to order such tests as a ‘catch all’ option.
Many labs know they should embrace utilization management, but the complexities involved in analyzing all the necessary data make it difficult to know where to start. In order to make constructive changes, labs must first know their reimbursed test volume, which physicians are ordering which tests, and the frequency of unreimbursed tests. With labs running hundreds of tests a day, however, it isn’t practical to gather all this information manually (Figure 3).
HRM systems can make accessing utilization data easy, and can present automated dashboards that contain actionable insight about which tests are not reimbursed, which tests are most profitable, and which tests are not medically necessary. Such insights enable lab managers to quickly identify physicians who are ordering incorrect or unnecessary tests, as well as their medical specialty. Lab directors can then use the HRM data and analyses to educate physicians about best testing practices, which will lead to a better patient experience.
Incyte Diagnostics, Spokane Valley, Wash, a clinical pathology lab, found that physicians were ordering unnecessary and antiquated tests that were not being reimbursed. Such practices were costing both the physicians and the lab a lot of money. Using automated alerts from its HRM system, the lab was easily able to identify areas of overutilization, and to educate physicians about how to improve their performance. In addition, since Incyte was able to document its training and education efforts, insurance providers retroactively authorized reimbursements and payments.
Laboratories are operating in a difficult environment, and it doesn’t appear that this is likely to change any time soon. New healthcare laws, dwindling reimbursements, and more-demanding patients will require lab managers to take a new look at how their facilities are operating.
Cutting costs, improving quality processes, and maximizing reimbursements are positive steps that lab managers can take to ensure the viability of their operations. To accomplish these goals, labs will need to look at how they can leverage their business and clinical data to gain insight into their operations, and take the guesswork out of decisionmaking.
Lab directors can start by pinpointing their most demanding challenges, and then researching how automation can help to resolve them.
For Mid America Clinical Laboratories, Indianapolis, the challenge was to determine which tests should be conducted in-lab and which should be outsourced to a reference lab. By using an HRM to combine test costs with reimbursement data, and to set up automatic reports, the lab was able to pinpoint which tests should be conducted in-house versus outsourced—and to make its determination based on volume data, not on feelings.
- Lee J. Outsourcing lab services can save money, but it’s not that simple [online]. Modern Healthcare. August 30, 2014. Available at: www.modernhealthcare.com/article/20140830/magazine/308309895. Accessed February 20, 2018.
- Jones BA, Darcy T, Souers RJ, Meier FA. Staffing benchmarks for clinical laboratories: a College of American Pathologists Q-Probes study of laboratory staffing at 98 institutions. Arch Pathol Lab Med. 2012;136(2):140–147; doi: 10.5858/arpa.2011-0206-cp.
- Sahni NR, Chigurupati A, Kocher B, Cutler DM. How the US can reduce waste in healthcare spending by $1 trillion [online]. Harv Bus Rev. October 15, 2015. Available at: https://hbr.org/2015/10/how-the-u-s-can-reduce-waste-in-health-care-spending-by-1-trillion. Accessed February 20, 2018.