Regardless of the structure U.S. Health Care Reform takes, comprehensive changes in the way we deliver and finance health care are certain to result in unprecedented mandates for higher quality health care delivered with fiscal responsibility. Case managers must remain a relevant and integral force in creating and implementing processes that support these goals. Decreasing hospital length of stay (LOS) is a widely employed strategy used to reduce costs and identify inefficiencies. As such, health care administrators use clinical diagnosis and procedure codes to closely monitor and risk adjust LOS. Case managers have long recognized the profound impact of economic and psychosocial factors on protracted hospital stays without a reliable method of evaluating and tracking these factors.

The SBUMC Care Management (CM) Department convened a multidisciplinary team charged with developing a method of quantifying the discharge barriers that result in unnecessarily long hospital stays. Over a period of weeks, the team concurrently assessed patients hospitalized over ten days for clinical, financial, and social issues impacting LOS. Factors were divided into actual barriers and tracking categories. Implementation of the coding system was a dynamic process, resulting in revision and refinement to ultimately define forty-five discreet, mutually exclusive codes. Inter-rater reliability testing was used to ensure validity and consistency.

Every Monday, a list of patients with a LOS of 10 days or more, including demographic, clinical, and financial data, is created. Throughout the week, CM Leadership meets with the case manager and social worker teams to review the cases, identify action plans, and assign barrier code(s). Each Friday, a multidisciplinary Long-Stay Executive Committee reviews complex cases; and enlists administrative support as necessary.

Detailed analysis of discharge barriers is performed monthly, and results are shared with CM staff and organizational leadership. Consequently, both CM and administrative interventions are targeted, proactive and preventative. As a result, significant reductions in discharge delays have been achieved.

Future plans include data analysis using statistical modeling and design of a long-stay prediction model using barrier codes as independent predictor variables in addition to demographic and clinical data elements.