Hospitals provide care to several thousand patients hospitalized in various nursing units. This process involves admissions of patients entering the nursing units and discharges of patients leaving the nursing units. These admissions and discharges have been identified as hand-off points, and such transitional points have higher potential for errors. Furthermore, admissions and discharges also have several associated activities that need to be accomplished, thus causing an increase in the need for resources like nursing staff, etc., which impacts on efficiency. Hence, a better understanding of the trends and patterns in admissions and discharges is necessary to improve the safety and efficiency of healthcare processes. This healthcare-related forecasting case study uses admission and discharge data from more than 100 thousand patients from 38 nursing units like medicine, surgery, step-down, pediatric, etc., over a three-year period from October 2007 through October 2010 in a large academic health system in the United States. There are two primary goals for this study: (1) to perform pattern analysis on the admission and discharge data, for facility and workforce planning and determining shift structure purposes and (2) to perform forecasting for corrective allocation purposes. Similar methods can be used by other hospitals to improve safety and efficiency.