Problem: Adult inpatients are at greater risk for falls causing injury, increased length of stay and additional costs. On an adult inpatient medical/surgical/telemetry unit at a community-based hospital, patient fall rates have increased from 5.2 falls per 1,000 patient days to an average fall rate of 6.2 falls per 1,000 patient days. The increase in falls has prompted concern for improvement in the fall prevention process for nursing staff. Purpose: To reduce fall rates an evidence-based fall communication algorithm was developed and implemented on the unit. The algorithm presented nurses with identified fall prevention items such as distraction techniques, communication guidance, and increased monitoring with tele-sitters. Methods: The algorithm was posted on the unit in the nursing stations, medication rooms, and portable computers for easy availability to nursing staff. Nursing staff voluntarily completed a survey using a QR code when they used the prompt on a specific patient. The survey asked if the prompt was effective in identifying a fall risk patient, fall prevention items, care planning for falls, or the need for tele sitter. The algorithm was used on an estimated 3% of patients. Results: There were no falls on patients with use of the algorithm. Survey results showed that 51.8% (n=44) of nursing staff reported the prompt helped identify fall risk patients, and 51.8% (n=44) reported that the prompt helped identify fall prevention tools. The overall fall rate increased to 7.6 falls per 1,000 patient days. Conclusions: The algorithm was not effective in reducing fall rates. Although no patients fell when identified as a fall risk with use of the algorithm, additional identifiers and prevention measures are needed to prevent falls.