| Autor: |
Bertagnolli MM; Brigham and Women's Hospital, and the Alliance for Clinical Trials in Oncology, Boston, MA., Anderson B; MITRE Corporation, Bedford, MA., Norsworthy K; US Food and Drug Administration, Silver Spring, MD., Piantadosi S; Brigham and Women's Hospital, and the Alliance for Clinical Trials in Oncology, Boston, MA., Quina A; MITRE Corporation, Bedford, MA., Schilsky RL; American Society of Clinical Oncology, Alexandria, VA., Miller RS; American Society of Clinical Oncology, Alexandria, VA., Khozin S; US Food and Drug Administration, Silver Spring, MD. |
| Abstrakt: |
Wide adoption of electronic health records (EHRs) has raised the expectation that data obtained during routine clinical care, termed "real-world" data, will be accumulated across health care systems and analyzed on a large scale to produce improvements in patient outcomes and the use of health care resources. To facilitate a learning health system, EHRs must contain clinically meaningful structured data elements that can be readily exchanged, and the data must be of adequate quality to draw valid inferences. At the present time, the majority of EHR content is unstructured and locked into proprietary systems that pose significant challenges to conducting accurate analyses of many clinical outcomes. This article details the current state of data obtained at the point of care and describes the changes necessary to use the EHR to build a learning health system. |
