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Falls are the most frequently reported incidents among hospitalized patients in the United States with at least 4 falls per 1,000 patient days occurring annually. Falls are related to high rates of mortality and morbidity and high hospital costs. The purpose of this project was to evaluate a fall prevention quality initiative to reduce falls in an acute care facility by educating staff on an evidence-based fall prevention protocol. The project sought to explore whether implementation of an evidence-based fall prevention initiative in educating nurses would affect the nurses’ professional knowledge and the number of patient fall incidences in the cardiac care unit. The theoretical framework supporting this project was Neuman’s systems theory. The Iowa model was used to guide this evidence-based project. An educational session was implemented to increase nurses’ awareness of fall prevention practices. Two sets of data were collected: the pretest and posttest results, and the number of falls on the unit. A total of 21 unit nurses participated in the pretest; 18 (86.0%) completed the posttest. The mean score on the pretest was 81.62%; the mean score was 85.89% for the posttest with a mean difference of 4.27%. A paired sample t-test revealed no statistically significant differences in scores after education. This project has implications for social change by supporting patient safety, decreased hospital stays, and reduced health care expenses to patients and health care organizations.

Residents in nursing facilities are more prone to falls than those living in the community. Injuries resulting from falls impact residents, their families, and healthcare costs. The gap in nursing practice was the lack of a comprehensive fall-prevention program in a long-term care facility that had experienced high fall rates among residents. This project addressed whether an educational program using the American Medical Directors Association's clinical practice guideline and the Centers for Disease Control and Prevention's STEADI (Stopping Elderly Accidents, Deaths, & Injuries) toolkit for fall- prevention improved the self-efficacy of direct-care staff in preventing falls among residents in a long-term care facility. The practice-focused question focused on whether education on the use of an integrated multifactorial fall-prevention guideline would increase confidence of long-term care staff in reducing falls in long-term care residents. The evaluation used the 11-item Self-Efficacy for Preventing Falls-Nurse scale for 5 licensed nursing staff and the 8-item Self-Efficacy for Preventing Falls-Assistant scale for 21 nursing assistants. The positive change in self-efficacy scores of nurses and nursing assistants after the education program was greatest for face-to-face team communication regarding fall risk and individual resident prevention plans. The use of best-practice guidelines that improve fall risk-assessment and use of fall precautions to decrease the number of falls and falls with injury has the potential to bring about positive social change by improving the nursing care of nursing home residents, resulting in improved resident safety and quality of life.

Background: Fall injuries are a costly problem for society, with costs ranging up to 14 billion a year. In addition to economic loss accidental falls also creates human value losses and reduced quality of life for its victims. In order to prevent the occurrence of injury related to accidental falls healthcare providers utilize various scientifically developed risk assessment tools, one of them being Downton Fall Risk Index. Method: Empirical, quantitative cross-sectional study. Objective: The purpose of the extended essay was to describe the categories in Downton Fall Risk Index that have a bearing on patients' risk of falling while in hospital and in municipal care, and to illustrate how nurses can use the fall risk assessment tool. Results: Of the 708 participants a total of 73% had a high risk of falling according to Downton Fall Risk Index, of the patients being treated at a hospital 66% had high risk of falling and of the patients being treated in municipal care 87% had high risk of falling. Downton Fall Risk Index indicates that the medication was by far the largest category and included 576 patients (81%), followed by sensory impairment in 474 patients (67%). 335 patients (47%) had fallen previously. Discussion: Previous studies show that among patients being treated in hospitals, between 1.3 to 2.1% will fall. Downton Fall Risk Index indicates that 66% of the group of patients are at high risk of falling. This may be due to the fact that Downton Fall Risk Index focuses too much on medication. It is the nurse’s responsibility to coordinate work around the patient in order to minimize the risk of falling. For example, contact an occupational therapist or an ophthalmologist who can undertake specific actions to reduce patients' risk of falling. Nurses should also use appropriate risk assessment tools to identify risk factors in the patient and then use these to formulate a nursing diagnosis. Conclusion: Downton Fall Risk Index is too sensitive to be used on hospitalized patients, the instrument works better in patients being treated in municipal care. It is important that the nurse can use scientifically designed tool for ensuring good health care for the patient, tools such as the fall risk assessment tool. / Bakgrund: Fallskador är ett dyrt problem för samhället med kostnader som sträcker sig upp mot 14 miljarder kronor om året i Sverige. Förutom ekonomiska förluster skapar fall även humanvärdesförluster och försämrad livskvalitet för den drabbade. För att förhindra uppkomsten av fallskador används inom sjukvården olika vetenskapligt framtagna fallriskbedömningsinstrument, ett av dessa är Downton Fall Risk Index. Metod: Empirisk, kvantitativ tvärsnittsstudie. Syfte: Syftet med fördjupningsarbetet är att beskriva vilka kategorier i Downton Fall Risk Index som har betydelse för patienters fallrisk vid vistelse på sjukhus och vid kommunal vård, samt att belysa hur sjuksköterskan kan använda Fallriskbedömningsinstrument. Resultat: Av de 708 medverkande hade totalt 73% hög risk att falla enligt Downton Fall Risk Index, på sjukhus hade 66% av patienterna hög risk att falla och i kommunal vård hade 87% av patienterna hög risk att falla. Downton Fall Risk Index anger att medicinering var den klart största kategorin och inkluderade 576 av patienterna (81%), därefter kom sensorisk funktionsnedsättning med 474 patienter (67%). 335 patienter (47%) hade fallit tidigare. Diskussion: Tidigare studier visar att på sjukhus faller mellan 1,3-2,1% av patienterna. Downton Fall Risk Index anger att 66% av samma patientgrupp har hög risk för fall. Detta kan bero på att Downton Fall Risk Index fokuserar för mycket på medicinering. Det är sjuksköterskans uppgift att samordna arbetet runt patienten så att fallrisken minimeras. Till exempel ska sjuksköterskan kontakta arbetsterapeuter eller ögonläkare som kan utföra punktinsatser för att minska patientens fallrisk. Sjuksköterskan ska även använda fallriskbedömningsinstrument för att identifiera riskfaktorer hos patienten och sedan använda dessa för att utforma en omvårdnadsdiagnos. Slutsats: Downton Fall Risk Index är alldeles för känsligt för att kunna användas på patienter inneliggande på sjukhus, instrumentet fungerar bättre på patienter inneliggande i kommunal vård. Det är viktigt att sjuksköterskan kan använda vetenskapligt utformade verktyg för att säkerställa en god omvårdnad för patienten, verktyg såsom Fallriskbedömningsinstrument.

By far the biggest injury risk faced by people with late onset dementia is a serious fall. Commercial fall detectors are available which automatically alert a call centre or carer if they detect a fall. They use accelerometers to look for the kinematics of a fall but this method is unreliable and the frequent false alarms must be cancelled by the wearer. This is inappropriate for someone with dementia. This thesis examines how a wrist-worn fall detector better suited to someone with dementia might be built. It reviews what other sensors could be used alongside accelerometers, and whether looking for the physiological effects of falling might be beneficial. It concludes that the pulse provides a source of data and describes three empirical trials to examine whether the body pose can be determined from the pulse waveform. A small convenience sample proved the viability of the concept, followed by a larger study to investigate it further, and finally a trial in people of the same age group as late onset dementia sufferers. Producing a technically better device is not sufficient, as it must also be usable by the people it is intended for. The thesis describes two qualitative studies which use carers to define, and then evaluate, a conceptual fall detector suitable for people with moderate or severe dementia which fits underneath a wrist watch. The thesis argues that wearable fall detectors should utilise physiological data to complement kinematic data. It demonstrates the practicality of a novel technique for determining body position using the pulse waveform, and finally concludes that it would be possible to build the conceptual fall detector utilising this technique.

Falls are the second leading cause of accidental or unintentional injury deaths worldwide. Many factors contribute to an increased risk of falling, such as age, disease state, and medication use. The purpose of the current investigation was to compare an electronic medical record (EMR) fall risk calculator, the theoretical Timed Up and Go (T-TUG), which utilizes gender, age, BMI, and prescription and OTC drug counts as variables, to other established performance- and paper-based assessments of fall risk. The National Social Life, Health, and Aging Project (NSHAP) Database was used to develop the T-TUG. Data was analyzed from participants in Wave 1 of the Irish Longitudinal Study on Ageing (TILDA) to validate the T-TUG. Performance-based assessments included mean grip force for both dominant and nondominant hands, Timed Up and Go (TUG), and a paper-based assessment titled the Steadiness Index. The latter is a series of 3 questions assessing steadiness when walking, standing, or getting up from a chair. Those participants of the TILDA cohort passing the inclusion criteria were divided into those who reported a fall in the previous year (N=1159) and those reporting no falls (N=4746). Two group comparisons were analyzed by Mann-Whitney U Test (p<0.05) and a Receiver Operator Characteristics (ROC) curve analysis was used to detect separation of fall and non-fall groups. For the Mann-Whitney U test the fall and no fall groups were statistically different for the T-TUG (p<0.001), TUG (p<0.001), dominant and nondominant grip forces (p<0.001), and the steadiness index (p< 0.001). In the fall group, the grip forces were weaker, T-TUG and TUG time longer, and the steadiness index scores lower. For the grip force assessments and steadiness index, lower scores are more likely to be associated with a higher fall risk. In the T-TUG and TUG, longer times are more likely to be associated with a higher fall risk. In the ROC curve analyses, the T-TUG (0.567, p<0.001) demonstrated similar outcomes compared to dominant (AUC=547, p<0.09) and non-dominant (AUC=0.550, p<0.01) grip forces, and the TUG (AUC=0.558, p<0.001). The steadiness index ROC analysis was slightly better than the T-TUG (AUC=0.579, p<0.001). Sensitivity (52-58%) and specificity (50-57%) ranges were equivalent for all performance-based assessments, whereas for the Steadiness Index, the sensitivity (40%) was lower than the specificity (75%). The EMR fall-risk calculator (T-TUG) is a valid triage tool to estimate fall risk in older community dwellers. The EMR calculator has the potential for real-time assessment of patients using current data compared to other performance- and paper-based assessments, which would allow the healthcare team to spend more time with higher fall risk patients.

Falls among hospitalized elderly patients are a safety concern for health care organizations and the patients they serve, but falls can be prevented through the team effort of nurses and other health care professions to promote safety within the organization. The project site was experiencing an increase in the number of patients falls and identified the need for staff education related to assessment and intervention to prevent patient falls in the elderly population. Thus, the practice-focused question for this project was whether an educational program on evidence-based fall prevention strategies using the American Medical Directors Association clinical guidelines would improve staff nurse ability to assess fall risk and apply intervention strategies for elderly patients in an acute care setting compared to standard practice. Lewin's change theory was used as the theoretical foundation for this project. A total of 29 cardiac unit staff nurses who participated in the educational program were provided information on recognizing risk factors for falls, conducting an accurate fall risk assessment using the Morse Fall Scale, and developing individualized care plan for managing fall risk. The Agency for Healthcare Research and Quality 2E Fall Knowledge Test was used in a pre- and posttest design to assess the efficacy of the educational program. The results showed a statistically significant increase (p < 0.001) in staff members' knowledge in recognizing, assessing, and managing falls. This project can improve nurse's knowledge with evidence-based recommendations in practice, which promotes positive social change through improved staff competency that may result in decreased patient falls and adverse patient outcomes.

Injuries associated with fall accidents pose a significant health problem to society, both in terms of human suffering and economic losses. Existing fall intervention approaches are facing various limitations. This dissertation presented an effort to advance indirect type of injury prevention approach. The overall objective was to develop a new fall event detection algorithm and a new integrative ambulatory measurement (IAM) framework which could further improve the fall detection algorithm's performance in detecting slip-induced backward falls. This type of fall was chosen because slipping contributes to a major portion of fall-related injuries. The new fall detection algorithm was designed to utilize trunk angular kinematics information as measured by Inertial Measurement Units (IMU). Two empirical studies were conducted to demonstrate the utility of the new detection algorithm and the IAM framework in fall event detection. The first study involved a biomechanical analysis of trunk motion features during common Activities of Daily Living (ADLs) and slip-induced falls using an optical motion analysis system. The second study involved collecting laboratory data of common ADLs and slip-induced falls using ambulatory sensors, and evaluating the performance of the new algorithm in fall event detection. Results from the current study indicated that the backward falls were characterized by the unique, simultaneous occurrence of an extremely high trunk extension angular velocity and a slight trunk extension angle. The quadratic form of the two-dimensional discrimination function showed a close-to-ideal overall detection performance (AUC of ROCa = 0.9952). The sensitivity, specificity, and the average response time associated with the specific configuration of the new algorithm were found to be 100%, 95.65%, and 255ms, respectively. The individual calibration significantly improved the response time by 2.4% (6ms). Therefore, it was concluded that slip-induced backward fall was clearly distinguishable from ADLs in the trunk angular phase plot. The new algorithm utilizing a gyroscope and orientation sensor was able to detect backward falls prior to the impact, with a high level of sensitivity and specificity. In addition, individual calibration provided by the IAM framework was able to further enhance the fall detection performance. / Ph. D.

Yes / Inpatient falls are the most common safety incident reported by hospitals worldwide. Traditionally, responses have been guided by categorising patients' levels of fall risk, but multifactorial approaches are now recommended. These target individual, modifiable fall risk factors, requiring clear communication between multidisciplinary team members. Spoken communication is an important channel, but little is known about its form in this context. We aim to address this by exploring spoken communication between hospital staff about fall prevention and how this supports multifactorial fall prevention practice. Data were collected through semistructured qualitative interviews with 50 staff and ethnographic observations of fall prevention practices (251.25 hours) on orthopaedic and older person wards in four English hospitals. Findings were analysed using a framework approach. We observed staff engaging in 'multifactorial talk' to address patients' modifiable risk factors, especially during multidisciplinary meetings which were patient focused rather than risk type focused. Such communication coexisted with 'categorisation talk', which focused on patients' levels of fall risk and allocating nursing supervision to 'high risk' patients. Staff negotiated tensions between these different approaches through frequent 'hybrid talk', where, as well as categorising risks, they also discussed how to modify them. To support hospitals in implementing multifactorial, multidisciplinary fall prevention, we recommend: (1) focusing on patients' individual risk factors and actions to address them (a 'why?' rather than a 'who' approach); (2) where not possible to avoid 'high risk' categorisations, employing 'hybrid' communication which emphasises actions to modify individual risk factors, as well as risk level; (3) challenging assumptions about generic interventions to identify what individual patients need; and (4) timing meetings to enable staff from different disciplines to participate. / This research was funded by the National Institute for Health and Care Research Health Services and Delivery Research Programme (project number HSDR NIHR129488).

Thesis (M.B.A.)--Boston University