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Due to the large number of falls that occur in hospital settings, inpatient fall prevention is a topic of great interest to patients and health care providers. The use of electronic decision support that tailors fall prevention strategy to patient-specific risk factors, known as Fall T.I.P.S (Tailoring Interventions for Patient Safety), has proven to be an effective approach for decreasing hospital falls. A paper version of the Fall T.I.P.S toolkit was developed primarily for hospitals that do not have the resources to implement the electronic solution; however, more work is needed to optimize the effectiveness of the paper version of this tool. We examined the use of human factors techniques in the redesign of the existing paper fall prevention tool with the goal of increasing ease of use and decreasing inpatient falls. The inclusion of patients and clinical staff in the redesign of the existing tool was done to increase adoption of the tool and fall prevention best practices. The redesigned paper Fall T.I.P.S toolkit showcased a built in clinical decision support system and increased ease of use over the existing version. [ABSTRACT FROM AUTHOR]

The Human Factors Analysis and Classification System (HFACS) is a framework for classifying and analyzing human factors associated with accidents and incidents. The purpose of the present study was to examine the inter- and intra-rater reliability of the HFACS data classification process. Methods A total 125 safety professionals from a variety of industries were recruited from a series of two-day HFACS training workshops. Participants classified 95 real-world causal factors (five causal factors for each of the 19 HFACS categories) extracted from a variety of industrial accidents. Inter-rater reliability of the HFACS coding process was evaluated by comparing performance across participants immediately following training and intra-rater reliability was evaluated by having the same participants repeat the coding process following a two-week delay. Results Krippendorff’s Alpha was used to evaluate the reliability of the coding process across the various HFACS levels and categories. Results revealed the HFACS taxonomy to be reliable in terms of inter- and intra-rater reliability, with the latter producing slightly higher Alpha values. Conclusion Results support the inter- and intra-rater reliability of the HFACS framework but also reveal additional opportunities for improving HFACS training and implementation. [ABSTRACT FROM AUTHOR]