Audacious Inquiry (Ai) is a health information technology and policy company that is making healthcare more connected. We facilitate the exchange of health information to deliver care coordination solutions. Our software is designed to be efficient and cost-effective, our nationally-recognized team-members provide tactful strategic consulting, and our services rethink how health information is shared, managed, leveraged, and protected.

SOFTWARE

FOR CONNECTED HEALTHCARE

EHR Connection & Data Quality

Extract, analyze, and transform data for enhanced useage

As our clients depend on connectivity and interoperability to meet evolving requirements, such as Stage 3 Meaningful Use, Alternative Payment Model reporting requirements, or improved coordination of care, they frequently tell us that they need multiple sources of data made available to them within their Electronic Health Record (EHR) System. Having the EHR as the central point for sharing information greatly increases the use of that information in care coordination and population health management.

Work with Ai To control interoperability standards to extract data from source systems, analyze and transform the data as necessary, and prepare it for loading into a repository accessed by end users or population health analytics.

How We Can Help You

Onboarding to Maximize Data Liquidity

Our experience with predominant EHRs allows our work to scale. We have developed a business process that allows for rapid connectivity across disparate clinical systems. Ai can leverage the data feeds for Quality reporting into our open source tool, CAliPHR, or to our care coordination suite, ENS® , and PROMPT®

Integrate with statewide registries

Health records (including quality reporting, immunization records, and more) can be routed by technology, not by people, to practice clinics, so they are timely, relevant, and scalable across large data sets.

Enhance data quality

In order for true value to be realized, data quality must accompany data connectivy. Ai can help define a data dictionary and then assess the quality of the connected data through the use of an instrument that analyzes batches of clinical documents for format and substantive content.