Challenge: Medicaid/Medicare/Tri-Care required computations of accurate KPIs and CQMs to provide more accurate data on quality of care and improve reimbursement.
The Problem: KPIs and CQMs for the practice are computed based on patient activity within the practice and do not include data on care and tests provided outside the practice. However, payers and the State compute these with different methodologies than the practices and payers. KPIs and CQMs are based on claims from all sources and these data are lagged by several months and do not reconcile with the data available directly to the practice.
The Data Aggregation Solution: Data used for computation of KPIs and CQMs is aggregated from CCDs provided by the provider. The number of data elements is easily scalable over time and enables actionable, predictive, data analytics which enable the computation of more accurate KPIs and CQMs. This data can be made near-real time, so it will be provided in time for the practice to take action, if appropriate and desired, to improve the KPIs and CQMs and thus improve both quality of care and reimbursement.