Perspectives on Care Coordination and Meaningful Use in the Emergency Department Setting

Although the emergency department (ED) has not been a focus for Meaningful Use (MU) efforts in Stage 1, the care coordination objectives for Stage 2 and proposed updates in Stage 3 have implications in the ED setting. More information about how these MU objectives affect the ED setting is needed. To learn more about MU in the ED, we conducted semi-structured interviews with a variety of stakeholders in the EDs of two academic medical centers. These interviews were designed to elicit information about the utility and feasibility of the objectives in the ED setting, electronic health record (EHR) changes needed to facilitate meeting the objectives, and ways to change them. The interviews were coded using NVivo. Perspectives were consistent within and across both EDs. Suggestions included a modified medication reconciliation process and the importance of automated notifications and care summary transmissions. Introduction The emergency department (ED) is designed for rapid, acute care with quality metrics that focus on minimizing patient waits and throughput time. To facilitate coordinated care, the ED must exchange relevant information with community caregivers who are caring for a given patient[1]. Such efforts as the patient-centered medical home reinforce this view. The proposed Stage 3 care coordination Meaningful Use (MU) objectives include these measures to facilitate care coordination: medication reconciliation, provision of targeted care summaries for transitions and after-visit consults and referrals, and notification of significant events. Because MU efforts have not traditionally focused on the ED, stakeholders must learn more about considerations with these objectives unique to the ED. Methods We conducted semi-structured in-person interviews of key stakeholders at two EDs at academic medical centers in North Carolina and Tennessee. Participants included physicians, nurses, case managers, pharmacists, and ED administrators. The results of the interviews were transcribed and coded using NVivo to identify themes. A sample of 10% of the interviews was double-coded to ensure consistency.