A well-accepted truism in healthcare is that "good" patient data allows for "good" care. While defining high-quality care is complex, "good" patient data is accurate, timely, easily accessible, and relevant to the clinician's needs at the moment.
Getting "good” data to the point-of-care is challenging for several reasons. Patient medical records are fragmented across different systems, each of which are optimized to support billing and medical liability management versus care delivery. The patient data itself is a hodgepodge of structured EMR tables, medical claims, and free-text medical notes. At best they are organized by chronology. As such, clinicians must muddle through EMRs to understand the patient, self-identify critical insights that could impact care, and identify care improvement opportunities.