Using human factors and ergonomics principles to prevent inpatient falls

Factors Associated with Acute Injurious Falls in Elderly Hospitalized Patients: A Multicenter Descriptive Study

BACKGROUND

The Centers for Medicare & Medicaid Services Hospital-Acquired Conditions (CMS-HAC) links Medicare payments to health care quality. Experiencing a serious disability or death associated with a fall in a health care facility based on diagnosis codes has been identified as an opportunity for improvement. Multiple factors contribute to an inpatient fall, including medications that affect cognition in older adults. The primary aim of this study was to investigate the effect of the commonly prescribed classes of medications on the CMS-HAC falls and trauma definition in US hospitals in a large inpatient database from 2019 to 2021.

METHODS

The authors analyzed data from 835 hospitals in the Vizient Clinical Data Base between January 1, 2019, and December 31, 2021, on patients ≥ 65 years of age with CMS-HAC patient falls and trauma codes. Using logistic regression and stepwise Poisson regression analysis, the authors identified demographic, clinical, and hospital-related variables associated with falls meeting the CMS-HAC definition. The top 20 prescribed drug classes in these patients were also identified.

RESULTS

Among 11,064,024 patient encounters, 5,978 met the CMS-HAC definition of a serious fall. Patients who experienced a serious fall were significantly more likely to be > 79 years of age (p < 0.001, odds ratio [OR] 1.30, 95% confidence interval [CI] 1.23-1.37), have a history of prior falls (p < 0.001, OR 2.30, 95% CI 2.11-2.50), have a code for dementia (p < 0.001, OR 1.50, 95% CI 1.40-1.60), and have higher anticholinergic cognitive burden (ACB) scores (p < 0.001, OR 1.14, 95% CI 1.13-1.14). Specific medication classes associated with CMS-HAC falls were first-generation antihistamines (p < 0.00, OR 1.21, 95% CI 1.09-1.35), second-generation antihistamines (p ≤ 0.001, OR 1.15, 95% CI 1.13-1.19), and atypical antipsychotics (p < 0.001, OR 1.18, CI 1.13-1.29).

CONCLUSION

Patients who experience a fall meeting the CMS-HAC fall definition are significantly more likely to have a prior history of falling, dementia, and a higher ACB score. Results from this study may inform future quality improvement work aimed at reducing injurious falls.

Nurses' Experience Implementing an Automated Video Monitoring System to Decrease the Risk of Patient Falls during a Global Pandemic

Healthcare is a complex sociotechnical system where information systems (IS) and information technology (IT) intersect to solve problems experienced by patients and providers alike. One example of IS/IT in hospitals is the Ocuvera automated video monitoring system (AVMS), which has been implemented in more than 30 hospitals. The purpose of this study was to evaluate nurses' attitudes toward AVMS implementation over time as they received the training program developed for this intervention. Consistent with the job demands-resources (JDR) model, we found that perceptions of AVMS usefulness increased over time and were positively associated with perceptions of social influence and behavioral control. These results were consistent with our finding that there was a significant decrease in the risk of unassisted falls from the bed from baseline to intervention. Leaders in hospital systems and healthcare organizations may want to consider implementing an AVMS as researchers continue to test, verify, and demonstrate the effectiveness of these interventions for improving patient well-being.

Improving Neurology Inpatient Fall Rate: Effect of a Collaborative Interdisciplinary Quality Improvement Initiative

Objective

To reduce unwitnessed inpatient falls on the neurology services floor at an academic medical center by 20% over 15 months.

Patients and Methods

A 9-item preintervention survey was administered to neurology nurses, resident physicians, and support staff. Based on survey data, interventions targeting fall prevention were implemented. Providers were educated during monthly in-person training sessions regarding the use of patient bed/chair alarms. Safety checklists were posted inside each patient's room reminding staff to ensure that bed/chair alarms were on, call lights and personal items were within reach, and patients' restroom needs were addressed. Preimplementation (January 1, 2020, to March 31, 2021) and postimplementation (April 1, 2021, to June 31, 2022) rates of falls in the neurology inpatient unit were recorded. Adult patients hospitalized in 4 other medical inpatient units not receiving the intervention served as a control group.

Results

Rates of falls, unwitnessed falls, and falls with injury all decreased after intervention in the neurology unit, with rates of unwitnessed falls decreasing by 44% (2.74 unwitnessed falls per 1000 patient-days before intervention to 1.53 unwitnessed falls per 1000 patient-days after intervention; P=.04). Preintervention survey data revealed a need for education and reminders on inpatient fall prevention best practices given a lack of knowledge on how to operate fall prevention devices, driving the implemented intervention. All staff reported significant improvement in operating patient bed/chair alarms after intervention (P<.001).

Conclusion

A collaborative, multidisciplinary approach focusing on provider fall prevention education and staff checklists is a potential technique to reduce neurology inpatient fall rates.