Acute Kidney Injury and Big Data

The recognition of a standardized, consensus definition for acute kidney injury (AKI) has been an important milestone in critical care nephrology, which has facilitated innovation in prevention, quality of care, and outcomes research among the growing population of hospitalized patients susceptible to AKI. Concomitantly, there have been substantial advances in "big data" technologies in medicine, including electronic health records (EHR), data registries and repositories, and data management and analytic methodologies. EHRs are increasingly being adopted, clinical informatics is constantly being refined, and the field of EHR-enabled care improvement and research has grown exponentially. While these fields have matured independently, integrating the two has the potential to redefine and integrate AKI-related care and research. AKI is an ideal condition to exploit big data health care innovation for several reasons: AKI is common, increasingly encountered in hospitalized settings, imposes meaningful risk for adverse events and poor outcomes, has incremental cost implications, and has been plagued by suboptimal quality of care. In this concise review, we discuss the potential applications of big data technologies, particularly modern EHR platforms and health data repositories, to transform our capacity for AKI prediction, detection, and care quality.