Use Cases Overview

The absence of an authoritative source(s) of truth for provider data has resulted in a fragmented, often company-specific effort by healthcare enterprises to obtain, cleanse and maintain provider data. Accuracy rates for Provider Directories average approximately 50% across the industry. The latency in obtaining updated data from network providers can take up to six months or more. This is because internalizing that new data, reconciling it against master systems of record, detecting change and then propagating that change to all affected systems of record containing information about those updated providers, and creating batch updates that are pushed to or throughout the enterprise can be extremely difficult, assuming it can be done at all. Current industry costs to date to yield this 50% accuracy rate are approaching $3 billion annually. See how our interoperability solutions are solving the problems with Provider Data Management.

In 2016-2017, Apex built and delivered a Medication Reconciliation & Allergy Review (“MedRec”) clinical application to the Department of Veterans’ Affairs (“VA”). This MedRec application enabled the VA for the first time to federate, in near-real time, patient-specific data from different VA hospitals (including both medications and allergies) and to reconcile that data at the point of care. The MedRec application was integrated with another technology delivered by Apex to the VA, VistA.js, which was an enterprise microservices framework for federating and reconciling data (clinical or otherwise) across all 130+ instances of VistA, including write back to VistA, in support for clinic applications like MedRec and other Enterprise Shared Services.See how our technologies support clinical applications such as MedRec even when dealing with different health facilities operating different electronic health record platforms.

When one company acquires another, there is an urgent need to merge or otherwise integrate the acquired company’s IT into the new parent company’s enterprise stack. This problem can be so intractable for so many diverse reasons that a decision to leave them running independently is often inevitable. Various forms of bubble gum and band aids are then used to create the illusion of a unified enterprise data architecture, an illusion that is quickly dispelled by an audit. With Unify!, there is no need for band aid, bubble gum, or illusions, because the path to unification is built around a coherent concept of novelty detection and truth propagation that no other solution offers.