Currently, promoting a safety culture, nurse staffing, and expanding nursing knowledge are the primary system factors emphasized for fall prevention in the nursing literature. Somewhat surprisingly, our findings suggest that these extrinsic system factors were not major causes for concern. The nurses perceived a favorable safety culture in the majority dimensions of the Hospital Survey on Patient Safety Culture and their nurse-to-patient staffing ratios were within the range reported in other studies.46
In contrast, our findings indicated that work processes and the physical environment presented the major limitations for fall prevention on this nursing unit. We also found from the NASA-TLX workload assessment, that the nurses perceived a high level of frustration related to fall prevention. Specifically, they perceived that they were exerting a great deal of time, attention, and effort to complete fall prevention tasks that required little mental demand.
Using the CWA approach that integrated findings from all of the data sources, we identified four constraints that appeared to be inhibiting the nurses' ability to prevent falls as well as nurse-developed workarounds for each constraint ().
Cognitive head-data constraint leads to written and mental chunking schemas
The nurses tracked and executed several tasks in parallel, some with numerous sub-tasks, by mentally noting their checklist. This notion, which we call ‘head-data’ here, has been described elsewhere.48
The paths toward completion were generally straightforward. However, the challenge was in remembering the list of tasks, the number of sub-tasks remaining, the temporal timeframe(s) remaining, and dealing with new entries into the list. The nurses viewed the activities related to fall prevention as imposing a high temporal demand, but low mental demand.
The nurses' workaround to this constraint was to develop written and mental chunking strategies. For example, several experienced RNs had developed schemas to permit them to retain relatively more information and to bypass limitations on short-term, working memory.49–51
Strategies used were visual reminders (eg, lists written on pocket cards) to outline planned tasks and patient assessment to be completed52
and means of chunking (eg, in their mind enumerating the overall tasks, ordering the list, and then trying to complete one block of sub-tasks before moving to another task).53
Given a lack of formal training in these strategies, some nurses appear to have greater skill in developing these schemas than others.
Workload constraint leads to the need for bed alarms
Throughout this study the nurses reported high levels of temporal demand, effort, and frustration in their workload. One component of workload is staffing. While the evidence base on nurse staffing does not call for standard nurse to patient ratios,55–57
the staffing ratios on the studies unit falls within the range mandated in the State of California (1 RN to 5 patients)58
and the range studied by healthcare analysts and economists for non-ICU staffing (1 RN to 4–8 patients) in other studies.46
Another component of workload in this analysis is how and where the nurse spends her time. The majority of nurse time on this unit was consumed providing indirect care or medications (67%), which positions nurses in the proximity of the nursing station, away from patient rooms. The task of monitoring for patient falls, however, is one in which the nurse must be in intimate proximity of the patient to predict, detect, and intervene an impending fall. Under a heavy workload with competing parallel demands and a large proportion of time away from the patient, the task of monitoring falls becomes increasingly difficult for the RN. An automation of the monitoring task may alleviate the perceived workload demands.
The nurses' workaround to the workload constraint was to use bed alarms, but these were employed inconsistently and their success varied. Bed alarms are an automated means to address constant monitoring, by notification of patient movement which offers an opportunity to intervene. The bed alarms used on this unit included a monitor with user interface, a speaker built into the bed rail, and a mat placed on the center of the bed, edge of the bed, or the floor. While ideal in theory, alarms used on this unit were either too sensitive or too insensitive. Alarms frequently provided feedback that was so sensitive that normal movement in bed triggered a response. Alarms also had problematic user interfaces whereby the operational modes were restrictive and involved sequences of typing that were difficult for a clinician to comprehend. Activated alarms were difficult to hear in the presence of competing tones (ie, with similar frequencies) and background noise. Similar findings associated with excess auditory stimulation in hospitals have been a problem documented by others.59
Given the difficulty that nurses faced in utilizing the alarms, it was not surprising that non-nurses (eg, therapists, family members)—on interacting with a patient—also struggled to reset them.
Inadequate written data and verbal communication lead to informal querying of previous nurse
As a result of inadequate written data (lack of capability in the MIS and paper chart) and verbal communication (between RNs and NAs), the fall risk status of a patient was often communicated only via RN verbal report at shift change, and not consistently done. This lack of structure in the verbal report introduces the possibility for additional human error, in this case inconsistent reporting of fall risk status. We found there to be inconsistency between the MIS data and the nursing care plan that had been compiled from the paper chart, shift change information, and patient assessment. Fall risk status and other pertinent patient information in the MIS were rarely updated. The MIS does not have a field or prompt to complete falls data, and therefore was not conducive to falls tracking. Nurses can enter a general comment, but this information is not readily displayed to the subsequent nurses. The paper chart was the source of more reliable data, but it was not always read at the beginning of the shift, as the nurse would first receive shift report and begin to meet with patients. Therefore, typically only those nurses who had worked the previous day, who were assigned the same patient, could rapidly and readily appreciate the patient's level of risk for falls and be able to select appropriate fall prevention interventions. In most incidences, however, nurses only had consistent patient assignments for two consecutive days.
A second issue surrounds the lack of formal, verbal communication between RNs and NAs and between RNs and the patient/family. While RNs implement fall prevention protocols, the NAs conduct the routine monitoring that ensures their effectiveness. There was an overwhelming consensus in the focus group that the RN–NA partnership was vital to preventing falls, but a lack of communication hindered its effectiveness. The observation data (shadowing and time motion) also showed that in contrast to RNs, the NAs were not involved in the formal exchange of information between RNs at hand-off or with a prior NA. As they were not informed of patient fall risk or RN fall prevention interventions, they relied instead on visual cues (eg, bracelets, slippers, stickers) to determine fall risk.
The nurses' workaround to decipher patient fall risk was to rely on informal querying of the previous care nurse about fall status. This reliance was evident in the TMS, where 24% of time was spent in communication either between nurses at shift change (9%) or with unit staff (15%). Conversely, only 9% of time was spent interacting with the MIS. It is possible than an inadequate understanding of or lack of confidence in the current MIS may have led to its underutilization. It is also important to note that informal querying contributes to human error; formalized documentation systems would better inform fall risk while decreasing the time spent obtaining a patient's status.
Limitations in the physical environment constraint lead to informal surveillance
The physical layout of the unit removed nurses from physical proximity to their patients and did not permit direct patient visibility. It is quite difficult for a nurse to prevent a fall when positioned far from the patient–while at the nursing station, for example, to mix medication, access equipment, or update documentation. In this study, it was found that nurses spent only 33% of time in the patient rooms, divided among four to five patients. There were no means of formal surveillance to deal with this constraint. In particular, from the location of the nursing station () there was a direct viewing angle into only 3 of 17 patient rooms.
The nurses' workaround was to add informal video and audio surveillance to improve patient visibility. Many nurses sought to monitor patients by using closed-circuit video (or relying on video assistants to watch the monitors) to patient rooms. However, most cases where an impending fall might be detected would be caught essentially by chance when a nurse happened to be in position near the camera. Also, video cameras were used only in those rooms (five in total, apart from the three with direct visual angles) where epileptic patients were assigned. Other nurses relied on reports from the unit clerk, the person to whom patients in all rooms could call over the audio intercom. In one observed case, a nurse was able to use this means to talk a patient back into bed, but this likely is a rare occurrence. In the focus group, several nurses reported that more surveillance was necessary via sitters and/or cameras.
While increased audio and video surveillance of patients may alert nurses to an impending fall, the knowledge often occurs too late to prevent it. Patients at risk for falling benefit from having people nearby who can quickly respond to an impending fall. Some redesign strategies to overcome this constraint include relocating nurses' indirect care tasks to be in close physical proximity to the patients' bedside and to allow more space for patient family members to stay overnight.61