Complex Cancer Datasets? No Longer a Problem.
View our webinar exploring how NLP-based AI addresses data challenges in healthcare
Learn how our AI supports customers in simplifying and improving registry reporting
Understand which of our E-Path solutions would best fit your institution
NLP-based AI for automated cancer datasets and registry reporting
Inspirata’s E-Path suite of cancer registry automation solutions is powered by an oncology-specific Natural Language Processing (NLP) based artificial intelligence fine-tuned for cancer reporting.
While complementing existing workflows, E-Path removes operator variability and far exceeds human performance in adjudicating reportable cases to help laboratories and cancer services rapidly arrive at more complete and accurate datasets.
Introducing the E-Path Suite
E-Path Reporter optimizes the cancer registry workflow by interpreting the text of diagnostic reports just as soon as they are produced, and then using local or jurisdiction-specific rules to identify reportable cancer cases.
E-Path Reporter is compatible with all AP-LIS/LIMS via HL7. Once it identifies a reportable case, it transmits the case directly to the cancer registry. The resulting end-to-end workflow takes mere seconds to complete and features greater accuracy and efficiency than manual approaches.
E-Path Reviewer surfaces coding data elements related to morphology, topography, laterality, grade, and pathologic (TNM) staging information. It builds on E-Path Reporter by providing additional scope for the laboratory to assure quality and/or triage cases before they are sent to the registry or other relevant stakeholders.
E-Path Plus provides significant time savings and improvements in the overall accuracy and consistency of how critical clinical data elements are surfaced and abstracted. This allows users, such as cancer registrars or cancer services teams, to better adjudicate cases and fulfill the requests they receive for clinical or research datasets related to population health, clinical studies, and registry reporting.
Benefits of E-Path
- Works with any AP-LIS/LIMS
- Ensures compliance with statutory reporting requirements
- Accelerates throughput by removing the need for pathologists to case identify
- Eliminates time spent in responding to registry requests for missing data
- Requires negligible ongoing input or support from laboratory or IT staff
- Reduces the risk of fines for non-conformance (UK)
Cancer Services & Registrars
- Reduces the risk of penalties for missing registry deadlines
- Improves the institutional confidence in the quality of cancer datasets
- Accelerates the review, coding, and verification of incoming pathology reports
- Eliminates the need for demographic data entry
- Reduces the amount of errors caused by missing data and human variation
- Enhances accuracy and completeness of reports
- Captures near real-time data to support ethically approved cancer research
- Improves data integrity, particularly demographic data for record linkage
- Enhances timeliness of registry data services to support research and evaluation
- Provides validation of stage at diagnosis submitted by hospitals
E-Path Suite Attributes
Automated review of pathology reports from LIMS
Auto-identification of reportable cancers and tumor classification
Seamless transfer of reportable cancer cases to local registry
Review portal for manual tumor coding
Automated coding and TNM extraction
Augmentation of patient view via auto-collation of parallel reports
300+ data elements for full oncology data extraction
E-Path report database repository and cancer case categorization
Output format customization and automated COSD/NAACCR mapping
E-Path in Action
National Cancer Institute (NCI)
14 Central Registries
E-Path is utilized at state registries across the US as part of the NCI Surveillance Epidemiology and End Results (SEER) program.
Cancer Council Victoria
Learn about Cancer Council Victoria’s implementation of E-Path across its large network of hospitals and laboratories.
Benchmark your performance in arriving at timely and accurate datasets for registry reporting.
When it comes to compiling your registry submissions:
- how much manual intervention is typically required?
- how many people are involved?
- how often is data missing or are reports delayed?
- have you received fines for falling short of conformance?
For a personalized report detailing your institution’s performance vis-a-vis your peers, take our survey today.
- 100+ institutions in the U.S., Canada and Australia utilize our automated cancer identification and reporting
- Established cancer reporting network and workflow within which we process 20M+ clinical reports per annum
- 99% accuracy in cancer case-finding as documented in NCI and other third party validation studies
- NLP and AI tools are developed and continuously updated by clinical cancer experts and validated by state and federal cancer registries worldwide
- Algorithms developed by oncology experts