At Animas Data Solutions (now Curatus) we believe strongly that it is critical to measure performance and results to achieve the best outcome. For this reason, ProviderLenz is designed to constantly score our client data with our proprietary Accuracy Confidence Level (ACL) methodology. This ensures that any deficiencies in data are highlighted so they can be monitored and improved upon.
The ACL algorithm which is built into Curatus’ ProviderLenz platform computes a myriad of data elements including source reliability, corroboration, quality, source authority, applicability, and recency of the data and applies an ACL to each provider (or group) for all of the areas that health plans use provider data ensuring a constant actionable understanding of provider data accuracy.
If you are a health plan and would like to receive a free Accuracy Confidence Level Analysis of your data or to learn more about ProviderLenz Accuracy Confidence Level Scoring or other Curatus technology, reach out to us using the form below today.