CentraLink Data Management System
University of Michigan Hospital achieved:*†
- 97% increase in volume to 8 million tests per year
- 73% reduction in errors—just seven errors, or <0.001% per month
- 43% improvement in TAT
- 92% autoverification of results
Autoverification to customize reviews, automate tasks, and reduce errors
- Start quickly with rules wizard.
- Support special and/or complex circumstances.
- Apply review criteria consistently.
- Flag clinically significant changes.
- Use patient demographics in advanced diagnostic algorithms.
- Hold results linked to a QC failure for manual review.
Integrated QC for continuous, proactive monitoring
- View QC and patient results simultaneously.
- Find test results between two failed QC points in two clicks and easily locate samples.
- Monitor patient moving averages to identify and troubleshoot system errors.
- Upload real-time QC results to Bio-Rad UNITY program.
Workflow management using rules to automatically process orders
- Automate results.
- Apply autodilution cascades to save time and reagents.
- Define rules according to patient demographics.
- Implement advanced diagnostic algorithms to drive reflex testing, reruns, delta checks, instrument flags, and QC.
Real-time dashboard of up to 16 customized KPIs
- Highlight items in need of attention.
- Add visual cues to indicate severity.
- Prompt for immediate action.
- Customize to specific roles.
- Provide reassurance when operations are running smoothly.
Enhanced automation performance
CentraLink rules created to govern algorithm-driven testing, result-based workflows, and/or automated QC evaluations can do more than simply generate a flag which requires staff to intervene or initiate a next step. As part of an Aptio® Automation solution, the CentraLink system can drive automated next steps in sample management:
- Automated sample retrieval reduced add-on testing TAT from 6 to 2 hours at Australian Clinical Labs in Victoria, Australia.†
- TAT improved 61% for add-on tests at National Health Service Tayside in Dundee, U.K.†
- Reflex and add-on tests ordered via the HIS/LIS at North Memorial Health Care in Robbinsville, MN, are automatically retrieved from refrigerated storage and sent for analysis with no operator intervention†.
How it works:
CentraLink Data Management System integrates clinical data to automate lab workflow. When a QC failure occurs, the CentraLink system can automatically disable assay-specific testing on the instrument in question and immediately reroute samples to perform the required testing on another instrument on the Aptio Automation track. Likewise, when reflex testing is triggered or orders for add-on tests are received from the LIS, samples connected to the Aptio Automation track can be automatically retrieved and processed. Importantly, the ability to deeply integrate data from connected instruments and automation modules means that viability algorithms that include time of collection, time of centrifugation, storage time, etc., may be used to determine if the add-on tests will be clinically significant. If not, the middleware can alert the operator that a new sample draw may be required.
- Use with Aptio® Automation or VersaCell® X3 Solution.
- Reduce the number of manual steps from accession to test results.
- Algorithm-driven testing.
- Result- and QC-based workflows.
Education and customer support well beyond the initial installation
- On-site technical support and training is provided during implementation.
- Consulting services are available for customized solutions.
- Online education courses simplify ongoing staff training.
- One point of contact simplifies communication.
Learn more about these features
A variety of white papers, video tutorials, and customer case studies are available to help you better understand how powerful and easy to use the CentraLink Data Management System can be:
Autoverification and Rules
*Over 8 years without adding staff or instrumentation.
†The outcomes achieved by the Siemens Healthineers customers described here were achieved in each customer’s unique setting. Since there is no typical hospital, and many variables exist (e.g., hospital size, case mix, level of IT adoption), there can be no guarantee that others will achieve the same results.