Low Acuity Emergency Department Visits: Comparing Demographics and Patient Profiles for an Accountable Care Organization

Frequent non-urgent emergency department (ED) visits have escalated despite legislation to enact routine affordable care for all Americans. It is already known that ED overcrowding often limits hospital functional capacity and can affect patient outcomes. Much of the ED crowding is due to unnecessary visits from patients who could have been evaluated in the primary care setting by their physician. The lower acuity patients often will wait longer for care depending on department census. Emergency departments domestic and international continue to investigate non-urgent emergency department visits seeking to understand the dynamics of this patient population. A large Midwestern Accountable Care Organization (ACO) has mimicked national trends with escalating non-urgent visits during weekdays when clinics are open. Policymakers concentrate on rising ED utilization as a direct reflection of community health and is regarded as a potential avoidable source of health care dollars. Our participating ACO has enrolled in a new care delivery model and payment structure of care through Centers for Medicare and Medicaid (CMS) that concentrates on aggressive patient care coordination. This model will be evaluated according to its ability to deliver better care to individuals, care coordination, better health for populations, and lower growth in expenditures.

Purpose:  The purpose of my study was to characerize the non-urgent ED patients who have a physician assignment within the ACO and those who do not. Patients evaluated were treated and released from the ED during clinic hours Monday through Friday 8-4:30. Patient profiles provided an initial step into demand strategies of this group of patients and how to mitigate unnecessary visits.

Methods:  My study was a twelve-month, retrospective review utilizing a descriptive comparative design. Information was collected from one inner city Level II trauma center. Yearly census iaverages 50-55,000 patients a year. Frequency and percentages of patient demographics including, gender, race, age, insurance status, and Zip Code were collected. Emergency Severity Index (ESI), marital status and discharge diagnoses were obtained to add richness to the data and further characterize the patient. A Chi-square analysis compared differences between the two variables, ACO vs. no ACO with a significance level set at 0.05.

Results: in process

Conclusion: in process