Lab managers need to manage supplies, balance workloads with staffing, carry out risk assessments and quality control. With the challenges imposed by the pandemic and the shift towards value-based reimbursement, lab administrators should pay more attention to data analytics lab integration. To maintain high performance and remain competitive as a lab service, managers need to address issues connected with daily management, such as:

  • Meeting all expected turnaround times
  • Monitoring the quality of lab processes and equipment
  • Providing adequate staffing during the pandemic
  • Detecting and reporting unnecessary tests
  • Maintaining a sufficient inventory of instruments, supplies, and reagents for molecular testing

Having access to electronic data can provide the means to handle these management tasks efficiently. However, spending time interpreting data manually can be counterproductive. That’s why labs need analytics solutions to automate daily management tasks for continuous improvement.

Here are three ways that data analytics can be used to improve lab performance.

1. Improve Staffing by Predicting Workload

Covid-19 has put a strain on lab finances, but the pandemic has also increased testing demands. As a result, lab employees are stressed, tired, and overworked and risk coronavirus infection.

Despite these challenges, lab administrators can make use of data analytics to boost staff productivity. The insight provided about future staffing requirements will allow the manager to determine staff needs with greater precision.

The number of technicians and attendants can be predicted by patient location, workstation, hours of the day, and days of the week.

2. Reduce Delays in TAT for COVID Testing

Data analytics enables lab managers to monitor testing patterns by observing TAT – turnaround time and the frequency of COVID testing by shift. Analytics can reveal the interruptions in processing that lead to TAT delays.

At a glance, it is possible to evaluate 24 hours of testing by shift. This allows you to easily predict and monitor TAT for large batches of COVID testing.

While smaller batches may be more desirable for reducing delays in TAT, the equipment set up for COVID is typically for high-volume testing and processing. That’s why analytics are needed to optimize large batch testing.

3. Boost Financial Performance through Improved Test Utilization

The healthcare industry has moved away from fee-for-service to value-based reimbursements. This has reduced the revenue of many clinical labs in the last few years.

Now that fixed reimbursements don’t adequately pay for increased clinical lab testing, there’s a need to improve test utilization to reduce care costs and boost patient outcomes.

Clinical lab analytics support improvements in lab test utilization. In most cases, when reports on test utilization show any unnecessary testing, it makes it easier for lab managers to identify the areas with potential for corrective action.

As soon as the lab administrators see the unnecessary tests occur, they can boost the utilization of employees’ time, reagents, and supplies.

Integrating data analytics into laboratory management provides actionable insights that can transform performance and boost profits.

Get Expert Advice on Data Analytics Lab Integration

Contact Lifepoint Informatics today at 877.522.8378 to book a free consultation. You can also talk to us through our contact page. We’re ready to hear from you and help you meet your data analytics needs.