Fall Prevention Algorithm Reduces Falls Among Hematology/Oncology Patients

Factors such as frailty and cognitive decline contribute to fall risk in the elderly.
Factors such as frailty and cognitive decline contribute to fall risk in the elderly.
A quality improvement project sought to reduce falls and falls with injury among inpatient hematology/oncology patients.

Using a standby assist algorithm can help nurses better individualize fall prevention strategies for hematology/oncology patients, who are at increased risk for falls due to side effects of their treatment, according to a presentation at the 48th Annual Oncology Nursing Society (ONS) Congress.

A team of nurses reviewed inpatient falls with injury on a 30-bed hematology/oncology/bone marrow transplant unit. A review of data revealed that many inpatient falls — 64 of 127 falls — occurred when patients were moving to the bathroom without assistance. These falls occurred despite the use of the Morse Fall Scale and standard fall precautions.

They initiated on a quality improvement project to decrease the rates of falls, including falls with injury, for patients on the inpatient hematology/oncology unit. They implemented a nurse-developed risk factor algorithm designed to evaluate a patient’s fall risk. The risk factor algorithm included specific oncology risk factors that were not captured by the Morse Fall Scale. The algorithm included 2 sets of criteria.

Criteria in the “red” category were the following:

  • Low hematocrit (≤21) and/or low platelets (<10)
  • Orthostasis, hypotension (change by 20 mm Hg)
  • Confused mental state

Criteria in the “yellow” category were the following:

  • Fever (temperature ≥100.4)
  • Diarrhea, vomiting, diuretics
  • Reported dizziness or prior falls during this hospital stay

A patient who achieved 1 of the red criteria or 2 or more of the yellow criteria would receive a stand-by assist.

The implementation involved the nurses assessing their patients’ risk of falling based on the stand-by assist algorithm at change of shift, which occurred at 7 am and 7 pm. If the algorithm flagged a patient as needing help with ambulation, the nurses were to notify them of their ambulation needs and risk factors and also put appropriate signs outside their room.

Although the authors reported the study was still ongoing, they noted a 50% reduction in falls with injury on the 30-bed unit, compared to the previous year. A key component of the program’s success was a daily safety huddle that involved patient care assistants and unit coordinators, as well as the patients’ perceptions of their risk factors for falling.

The authors concluded that the algorithm was useful in reducing falls and falls with injury in this patient population, which could improve patient outcomes and reduce readmission costs and length of stay.

Reference

Miller D, Toomey E. Decreasing rates of inpatient falls with injury: implementing an individualizable fall prevention algorithm for hematology/oncology patients. Oral presentation at: 48th Annual ONS Congress; April 26-30, 2023; San Antonio, TX.