Introduction
Background: Patient falls in a hospital setting are considered serious, never events and vary according to unit specialty [1]. Around 2% of in patients will fall during their hospital stay [2], reflecting a number of different reasons and risks [3]. The National Database of Nursing Quality Indicators (NDNQI) collects data on multiple nursing events from over 2000 hospitals, categorizing specific nursing quality events for benchmarking (Press Ganey, nd) [4]. This allows for evaluation of nursing and hospital performance on events and issues of importance to patient safely and care. More often than not (76.6%) patients who fell were assessed for risk of falling [1]. Assessment of the sensitivity of the falls risk assessment tools, as well as their specificity for the type of clinical unit is important [3].
Psychiatric specific challenges: Intentional fall events, or those instances where a patient descends to the floor on purpose, are seen more frequently in psychiatric units than medical units [5]. NDNQI defined intentional fall events in an expansion of a review of defining falls, actually excluding intentional fall events out of the fall’s category of reporting. The amount of research that has occurred regarding inpatient safety on psychiatric units is limited, despite the fact that 26% of Americans have a diagnosable mental illness [6]. Sometimes, in a psychiatric unit, physical areas can be identified as increased risk factors. Five areas were defined using risk levels from 1-5, with 5 being the highest risk area. These areas were 5b) seclusion areas with patients who are experiencing aggressive behaviors, 5a) admitting areas where patients are not yet aware of the rules and boundaries and are new to interactions with staff, 4) Patients bedrooms and bathrooms, 3) activity rooms and group lounge rooms (IE TV rooms), 2) corridors and other areas where patients are easily being observed by staff, and 1) nurses stations and other staff only areas [7]. Hunt and Sine (2009) identified the architectural design as a factor in understanding patient and staff safety issues, supporting the need for designing psychiatric units with patient and staff safety in mind. The three factors identified by Hunt and Sine (2009) for falls in psychiatric units are flooring material, presence of grab bars and adequate lighting in halls and bedrooms. The study conducted by Hunt and Sine evaluated falls, among 6 other elements, over a 7-year period. Their study identified level four as having the most number of falls (390) and level 3 also at high risk (135). The total number of falls reported on the unit made up for 44% (n=582) of the seven larger categories of safety issues.
Wong and Pang assessed two fall risk assessment tools, The Morse Falls Scale (MFS)and The Wilson Sims Fall Risk Assessment Tool (WSFRAT), with psychogeriatric in patients. The pilot program was a part of the development of a fall’s prevention program. Their program identified time of day (nights), toileting, advanced age, dementia and gender (female) as increasing the risk factor for falls. Their conclusion was that the WSFRAT was a better indicator of risk for falls in their psychiatric units [8].
The current study examines and compares three fall risk assessment tools, The Morse Falls Scale (MFS) The Wilson Sims Fall Risk Assessment Tool (WSFRAT) and the Edmonson Psychiatric Falls Risk Assessment tool (EPFRAT) on an inpatient psychiatric unit. The aim of this study was to determine which assessment tool best identified risk for falling and provided nursing with information for patient fall prevention and management.
Method
Design: Randomized, comparative archived chart review.
Sample: The sample of charts were randomly drawn from hospital ID numbers of previous in-patients from the psychiatric ward. Three nurse researchers each randomly retrieved five archived charts.
Setting: A psychiatric dedicated, in-patient unit in a suburban medical center in New Jersey.
Procedure: Three nursing researchers were trained in chart review to identify the criteria for each of the fall’s assessment tools. Patient account numbers representing patients who had been discharged in the preceding year were randomly chosen. Each nurse evaluated five to seven charts. This provided a double-blind method concealing the identity of the patients. All charts were independently reviewed using each of the criteria from the three tools.
Each chart was reviewed to identify the variables established and measured by each of the three measurement tools. The criteria were cross listed to determine where the assessment tools shared criteria and where they differed. The final scores were compared across the three tools to identify where there was agreement between the surveys, with a focus on identifying those at highest risk for falls. Risk factors were tallied according to the scales and compared for consistency in results indicating level of patient fall risk. Total scores were compared across each patient. Twenty-four variables were identified across the three scales with an additional two variables identified by nurses for inclusion in any future scale.
Results
The final number of charts reviewed were 14. One chart was removed as the evaluation sheet was incorrectly completed on two scales. Scales were compared to see what variables were included in each of the scales. Twenty-four variables were identified between the three scales: Age, gender, mental status, cognition, physical status, elimination, impairments, gait/balance, history of falls, diagnosis, secondary diagnosis, ambulatory aids, IV therapy, nutrition, sleep disturbances, medication (general), mood stabilizers, benzo, diuretics, narcotics, sedative hypnotic, atypical antipsychotic, detox protocol and an area for clinical nursing judgment. . Table one reflects how age and gender are recorded on the three scales and the percentage of patients whose score identified those patients at risk for falls secondary to age or gender. Age as a fall risk was only considered in the Wilson Sims (WSFRAT) and Edmonson Scales (EPFRAT) scales, and gender only on the Wilson Sims (Table 1).
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