Accountable Care

CiDrep for Accountable Care

CiDrep Cloud-based Informatics platform – offers ACOs precisely the tools they need to collect and analyze key quality and cost data to recognize patters from the highest levels (e.g., hospital-wide) to the lowest levels (physician or patient). CiDrep’s solutions can be rapidly implemented and configured to integrate data from disparate sources, harmonize that data with leading cloud platform and use powerful data-visualization and pattern recognition tools to identify trends in real-time. Recognizing patterns in claims, cost, and quality data is one of the key drivers that will enable ACOs to make timely adjustments that lead to improved cost and quality outcomes.

Healthcare reform – and trends in value-based medicine are pushing payers and providers to find new technology solutions that provide insight into the clinical practices that affect cost and quality.  Enabling truly accountable care and effective population health management requires that payers and providers have a real-time capability to aggregate and analyze claims, cost, and clinical data from many disparate sources. While some of this data is in electronic health record (EHR) systems, accountable care requires that payers and providers harmonize the claims, cost, and clinical data from many different sources and provide robust, real-time analysis and pattern-recognition tools.

Clinical registries – are widely acknowledged as the solution for effective aggregation and analysis of clinical outcomes data, but ACOs and other integrated delivery systems have struggled to find clinical or patient registry software that is robust enough to meet their data management needs.  EHR systems and electronic data warehouses (EDWs) promise the ability to gather and analyze this data, but their brittle architecture makes it difficult to aggregate and analyze cost and quality data since this exercise requires specialized database administrators and software engineers to create new reports or modify data collection tools.