Healthcare providers deal with a lot of data. This data is often stored across a variety of legacy systems that don't communicate with one another that well. Not only do data discrepancies eat up medics' time (think:
nine hours per week), but they also influence the quality of care. You know it better than anyone: drawing a complete picture of what a patient has and is experiencing health-wise is the first step toward correct diagnosing and effective treatment.
To fend off healthcare data disparities, medical organizations have long been turning to
data management and
data analytics providers. The aim? Bring siloed data together into single, consolidated storage — a healthcare data warehouse — and use it to draw insights.
This blog post covers vital aspects of adopting a data warehouse in healthcare, zooming in on its technical characteristics, highlighting the value a centralized data storage can drive for medical organizations, and providing a high-level data warehouse implementation roadmap.