 Sample sizes for the study were determined for call light usage rates, patient satisfaction scores, and fall rates. Current process averages for sample size calculations were obtained as follows: 1 fall rates from existing fall rate reports 2 patient satisfaction from Avatar surveys, and 3 call bell usage from preliminary Hill Rom system data. For all sample size calculations, α0.05 and β0.10 were used. Based on these calculations, the study baseline data for patient satisfaction will be calculated using Avatar patient satisfaction data from the six-month period prior to study initiation. The baseline data for falls will be collected from existing fall rate reports using the six months of data prior to study initiation. Data for these variables will continue to be collected for 6 months after the implementation of nursing rounds. For call bell usage rates the data for 2 weeks prior to rounding implementation will be collected as baseline data. Data will be collected for 4 weeks following the implementation of nursing rounds. Data for average patient age, length of stay, and severity of illness for both units will be obtained from Transition Systems, Inc. TSI, a financial data base is a type of Decision Support System. In order to get the information on a patients age a query will be made of TSI. It will then print up average ages of a particular unit within a specified time. Measures of central tendency and spread will be calculated for these variables to compare both units. Chi-square tests, rank sum tests, and tests of means will be used to compare baseline and post-intervention demographic characteristics and reasons for call light usage on both units. Rate ratios comparing post- to pre-intervention fall rates and call rates will be calculated on both. For both fall rates and call rates, significance tests will be conducted to determine whether the rate ratios differ between the two units. The change in the proportion of patients who indicated they were satisfied with their care in each unit before and after the intervention will also be calculated and compared. The data will be analyzed using SAS9. No data involving individual patient identifiers will be presented with the analysis. Findings from this study will potentially be used to change nursing practice at Crouse Hospital. 