Strength of Improvement Recommendations From Injurious Fall Investigations: A Retrospective Multi-Incident Analysis.

Abstract

The aim of this study was to examine the strength of improvement recommendations proposed after investigation of fall incidents in health care facilities that result in major injuries. This study was conducted using a retrospective multi-incident analysis design. The study setting was 4 tertiary teaching hospitals, 1 subacute rehabilitation facility, and a residential aged care facility in a metropolitan health district in New South Wales, Australia. Ninety-eight injurious fall incidents during a 2-year period (2015-2016) were investigated. Recommendations were grouped into 3 categories: strong (including environmental modifications, equipment, workflow or process redesign), medium (including changes in communication or documentation processes, staffing numbers and/or skill mix, education to address identified knowledge deficits), and weak (including alerts/warning/labels or expected practice without any associated policy or procedure). The majority of the incidents (34.7%; n = 34) occurred between 1300 and 1859 hours, 65.3% (n = 64) occurred in the patient's room, and 79.4% (n = 81) of the injuries were fractures. There were 224 recommendations made for 79 incidents, and 19 incidents did not have any recommendations. The average number of improvement recommendations proposed per incident investigation was 2.3 (SD, 2.1; range, 0-9). Nineteen (8.5%), 80 (35.7%), and 125 (55.8%) recommendations were classified as strong, medium, and weak, respectively. Half of the investigative teams included representatives from more than one professional group. There were a significantly greater number of medium recommendations made by multi-disciplinary teams compared with single-disciplinary teams (odds ratio, 1.83; 95% confidence interval, 1.05-3.21). There was no significant difference in the number of strong and weak recommendations made between the 2 teams. This study found that only 8.5% of recommendations were classified as strong. This suggests that a major challenge lies in formulating robust recommendations; hence, efforts should focus on enhancing the strength of improvement recommendations.