| Learning Objective #1: Describe predictors of reduced ED visits in a low-income, uninsured population associated with a case management intervention | |||
| Learning Objective #2: Discuss strategies to support the translation of evidence-based research into an applied practice setting through staff involvement in research design |
Intervention: Nurses and social workers collaborated to assist high utilizers of ED services to find a primary care medical home and access community resources.
Methods: The voluntary, cross-sectional study sample included 459 low-income, uninsured adult residents of Sedgwick County, Kansas, enrolled between December 2001 through February 2004. Logistic regression was used to identify predictors of reduction in ED use among participants. Independent variables included age, gender, race, marital status, social support, education level, employment status and annual income. Case management process factors included number of days case was opened, number of contacts between client and team members, number of follow-up appointments, number and types of referrals. Dependent variable: Change in ED visits pre/post intervention.
Results: Nearly 85 percent (n=388) of program participants reduced their ED use (mean reduction 2.3 visits/client). Participant characteristics and process factors that were significant predictors of reduction in non-urgent ED visits included: female gender (OR 1.85, CI 1.00-3.48, p < 0.05), verified medical referrals (OR 0.63, CI 0.42-0.94, p < 0.05), number of ED visits before intervention (OR 1.22, CI 1.03-1.43, p < 0.05), client case was opened less than 63 days (OR 2.81, CI 1.03-7.70, p < 0.05), and client case opened from 64-123 days (OR 2.96, CI 1.14-7.64, p < 0.05).
Conclusions: Findings suggest those most responsive to the case management intervention may have less complex social needs or fewer health needs. In addition, more assertive case management may be required to reach those with more serious medical and social circumstances.
Implications: CCM is a potential solution for low-income, uninsured populations to navigate and access the fragmented, American health care delivery system.