Retrospective analysis and nursing management of inpatient falls: Case series

Fall risk prediction ability in rehabilitation professionals: structural equation modeling using time pressure test data for Kiken-Yochi Training

Background

Falls occur frequently during rehabilitation for people with disabilities. Fall risk prediction ability (FRPA) is necessary to prevent falls and provide safe, high-quality programs. In Japan, Kiken Yochi Training (KYT) has been introduced to provide training to improve this ability. Time Pressure-KYT (TP-KYT) is an FRPA measurement specific to fall risks faced by rehabilitation professionals. However, it is unclear which FRPA factors are measured by the TP-KYT; as this score reflects clinical experience, a model can be hypothesized where differences between rehabilitation professionals (licensed) and students (not licensed) can be measured by this tool.

Aims

To identify the FRPA factors included in the TP-KYT and verify the FRPA factor model based the participants' license status.

Methods

A total of 402 participants, with 184 rehabilitation professionals (physical and occupational therapists) working in 12 medical facilities and three nursing homes, and 218 rehabilitation students (physical and occupational therapy students) from two schools participated in this study. Participant characteristics (age, gender, job role, and years of experience and education) and TP-KYT scores were collected. The 24 TP-KYT items were qualitatively analyzed using an inductive approach based on content, and FRPA factors were extracted. Next, the correction score (acquisition score/full score: 0-1) was calculated for each extracted factor, and an observation variable for the job role (rehabilitation professional = 1, rehabilitation student = 0) was set. To verify the FRPA factors associated with having or not having a rehabilitation professional license, FRPA as a latent variable and the correction score of factors as an observed variable were set, and structural equation modeling was performed by drawing a path from the job role to FRPA.

Results

The results of the qualitative analysis aggregated patient ability (PA), physical environment (PE), and human environment (HE) as factors. The standardized coefficients of the model for participants with or without a rehabilitation professional license and FRPA were 0.85 (p < 0.001) for FRPA from job role, 0.58 for PA, 0.64 for PE, and 0.46 for HE from FRPA to each factor (p < 0.001). The model showed a good fit, with root mean square error of approximation < 0.001, goodness of fit index (GFI) = 0.998, and adjusted GFI = 0.990.

Conclusion

Of the three factors, PA and PE were common components of clinical practice guidelines for fall risk assessment, while HE was a distinctive component. The model's goodness of fit, which comprised three FRPA factors based on whether participants did or did not have rehabilitation professional licenses, was good. The system suggested that rehabilitation professionals had a higher FRPA than students, comprising three factors. To provide safe and high-quality rehabilitation for patients, professional training to increase FRPA should incorporate the three factors into program content.

A stepped-wedge randomised controlled trial to assess efficacy and cost-effectiveness of a care-bundle to prevent falls in older hospitalised patients

BACKGROUND

Patient accidental falls in a hospital environment are a serious problem for patient safety, and for the additional costs due to associated medical interventions.

OBJECTIVE

The endpoints of this study were the assessment of the fall incidence in the hospital before and after the implementation of a multidisciplinary care-bundle, along with a cost-effectiveness evaluation.

DESIGN

A stepped-wedge trial was conducted between April 2015 and December 2016 in Bologna University Hospital.

METHODS

Incidence rates (IRs) of falls in both the control and intervention periods were calculated. A multilevel mixed-effects generalised linear model with logit link function, adjusted for age, sex, cluster cross-over timing and patients' clinical severity was used to estimate odds ratios (OR) of fall risk of patients of the intervention group respect to the controls.Intervention costs associated with the introduction of the care-bundle intervention were spread between patients per cluster-period-group of exposure. Incremental cost-effectiveness ratio was evaluated using total costs in the intervention and control groups.

RESULTS

IRs of falls in control and intervention periods were respectively 3.15 and 2.58 for 1,000 bed-days. After adjustment, the subjects receiving the intervention had a statistically significant reduced risk of falling with respect to those who did not (OR = 0.71, 95% confidence interval: 0.60-0.84). According to the cost-effectiveness analysis, the incremental cost per fall prevented was €873.92 considering all costs, and €1644.45 excluding costs related falls.

CONCLUSIONS

Care-bundle had a protective effect on patients, with a statistically significant reduction of the fall risk. This type of intervention appears cost-effective compared to routine practices.

Time-Varying Hazard of Patient Falls in Hospital: A Retrospective Case-Control Study

This study aims to evaluate the association between patient falls and relevant factors and to quantify their effect on fall risk. This is a retrospective case-control study using the secondary data collected from a tertiary general hospital. Study subjects were 450 patients who were admitted to the hospital between January 2016 and December 2020. The prevalence of falls was associated with the fall risk level by the Morse Fall Scale (MFS) and individual status at admission including history of admission, dizziness, sleep disorder, bowel dysfunction, and urinary incontinence. The odds ratios of patient falls were higher in the low-risk group by the MFS score (odds ratio (OR) = 2.61, p < 0.001) and the high-risk group (OR = 5.51, p < 0.001) compared to the no-risk group. The hazard ratio of patient falls was higher in the high-risk group by the MFS score (hazard ratio (HR) = 3.85, p < 0.001). The MFS had a significant explanatory power to predict fall risk. Sleep disorder and urinary incontinence were the significant factors influencing patient falls.