Factors associated with the incidence of patient falls in hospitals:A scoping review

When a patient falls within a hospital setting,there is a significant increase in the risk of severe injury or health complications.Recognizing factors associated with such falls is crucial to mitigate their impact on patient safety.This review seeks to analyze the factors contributing to patient falls in hospitals.The main goal is to enhance our understanding of the reasons behind these falls,enabling hospitals to devise more effective prevention strategies.This study reviewed literature published from 2013 to 2022,using the Arksey and O’Malley methodology for a scoping review.The research literature was searched from seven databases,namely,PubMed,ScienceDirect,Wiley Library,Garuda,Global Index Medicus,Emerald Insight,and Google Scholar.The inclusion criteria comprised both qualitative and quantitative primary and secondary data studies centered on hospitalized patients.Out of the 893 studies analyzed,23 met the criteria and were included in this review.Although there is not an abundance of relevant literature,this review identified several factors associated with falls in hospitals.These encompass environmental,patient,staff,and medical factors.This study offers valuable insights for hospitals and medical personnel aiming to enhance fall prevention practices.Effective prevention efforts should prioritize early identification of patient risk factors,enhancement of the care environment,thorough training for care staff,and vigilant supervision of high-risk patients.By comprehending the factors that contribute to patient falls,hospitals can bolster patient safety and mitigate the adverse effects of falls within the health-care setting.

Analysis of the Clinical Interventions for Falls in Elderly Patients in the Community From 2002 To 2022:A Bibliometric Analysis

Objective:To analyze and provide a comprehensive overview of the knowledge structure and research hotspots of clinical interventions for falls in elderly patients in the community.Methods:The search for publications related to clinical interventions for falls in elderly patients in the community from 2002 to 2022 was conducted on the Web of Science Core Collection(WoSCC)database.VOSviewers,CiteSpace,and the R package“bibliometrix”were used to conduct this bibliometric analysis.Results:2091 articles from 70 countries,primarily the United States and Australia,were included.The number of publications related to clinical interventions for falls in elderly patients is increasing yearly.The main research institutions in this field were the University of Sydney,Harvard University,and the University of California.BioMed Central(BMC)Geriatrics was the most popular journal in this field and Journals of the American Geriatrics Society was the most co-cited journal.These publications came from 8984 authors among which author Lord SR had published the most papers and author Tinetti Me had the most co-citations.The main keywords in this research field were“balance,”“exercise,”and“risk factor.”Conclusion:This was the first bibliometric study that comprehensively summarized the research hot spots and development of clinical interventions for falls in elderly patients in the community.This paper aims to provide a reference for scholars and researchers in this particular field.

Effectiveness of Extended Care in Preventing Falls in Disabled Elderly and Its Impact on Quality of Life

Objective:To analyze the value of extended care interventions for disabled elderly in preventing falls and optimizing quality of life.Methods:A sample of 60 cases of disabled elderly in a tertiary hospital from May 2022 to May 2023 was selected and grouped by the random number table method.The observation group received extended care,while the control group adopted routine care.The differences in complication rate,fall rate,36-Item Short Form Health Survey(SF-36)score,health knowledge awareness score,and nursing satisfaction were compared.Results:The complication rate and fall rate of the disabled elderly in the observation group were lower than those in the control group,P<0.05;the SF-36 score,health knowledge score,and nursing satisfaction of the observation group were higher than those of the control group,P<0.05.Conclusion:Extended care for the disabled elderly can reduce the risk of falls and complications related to disability,as well as optimize their cognition and improve their quality of life,which is efficient and feasible.

Numerical and experimental study on the falling film flow characteristics with the effect of co-current gas flow in hydrogen liquefaction process

Liquid hydrogen storage and transportation is an effective method for large-scale transportation and utilization of hydrogen energy. Revealing the flow mechanism of cryogenic working fluid is the key to optimize heat exchanger structure and hydrogen liquefaction process(LH2). The methods of cryogenic visualization experiment, theoretical analysis and numerical simulation are conducted to study the falling film flow characteristics with the effect of co-current gas flow in LH2spiral wound heat exchanger.The results show that the flow rate of mixed refrigerant has a great influence on liquid film spreading process, falling film flow pattern and heat transfer performance. The liquid film of LH2mixed refrigerant with column flow pattern can not uniformly and completely cover the tube wall surface. As liquid flow rate increases, the falling film flow pattern evolves into sheet-column flow and sheet flow, and liquid film completely covers the surface of tube wall. With the increase of shear effect of gas-phase mixed refrigerant in the same direction, the liquid film gradually becomes unstable, and the flow pattern eventually evolves into a mist flow.

Assessment of Falls among the Elderly in the Emergency Department of the Idrissa Pouye General Hospital in Dakar, Senegal: A Cohort of 100 Cases

Background: Falls in the elderly are a global public health problem with serious medical and socio-economic consequences, especially in low and middle-income countries. The aim of this study was to describe the characteristics of falls among the elderly in trauma units in Senegal. Materials and Methods: This was a descriptive, prospective study from April 20, 2022 to October 30, 2022 among people aged at least 60 and admitted to the surgical emergency department of Idrissa Pouye Hospital in Dakar following a fall. Socio-demographic, clinical, therapeutic and evolutionary characteristics were collected and analyzed using Sphinx Plus 2 and Excel 2019 for Windows software. Results: Out of 730 elderly people seen during this period, 100 met the criteria, representing a prevalence of 13.69%. The average consultation time was 3.25 +/? 4 days. The average age was 73 +/? 8.43 years, with women predominating (74%). Medical expenses were mainly covered by the family (73%). Most falls occurred during the day (68%), at home (82%), especially in the bedroom (30%), with stumbling (32%) as the main mechanism. The majority of patients (86%) spent less than 30 minutes on the floor. Predisposing factors were dominated by visual disorders (56%) and precipitating factors were mainly environmental (62%). Geriatric syndromes were dominated by frailty (22%). Complications were dominated by fractures (86%), and almost half (47%) had lost their autonomy for post-fall Activities Daily Living (ADL). Prescription medication was almost systematic (98%), dominated by analgesics (98%). Surgery was indicated in 58% of patients. The average waiting time for surgery was 25.36 +/? 19 days. A death rate of 1% was recorded in the emergency department. Conclusion: Falls in the elderly are a frequent occurrence in traumatological emergencies, with etiological factors that are often multiple and interrelated, leading to significant morbidity. Raising awareness among people at risk and setting up an orthogeriatric service would help prevent falls and optimize care in the short and long term.

Dense Spatial-Temporal Graph Convolutional Network Based on Lightweight OpenPose for Detecting Falls

Fall behavior is closely related to high mortality in the elderly,so fall detection becomes an important and urgent research area.However,the existing fall detection methods are difficult to be applied in daily life due to a large amount of calculation and poor detection accuracy.To solve the above problems,this paper proposes a dense spatial-temporal graph convolutional network based on lightweight OpenPose.Lightweight OpenPose uses MobileNet as a feature extraction network,and the prediction layer uses bottleneck-asymmetric structure,thus reducing the amount of the network.The bottleneck-asymmetrical structure compresses the number of input channels of feature maps by 1×1 convolution and replaces the 7×7 convolution structure with the asymmetric structure of 1×7 convolution,7×1 convolution,and 7×7 convolution in parallel.The spatial-temporal graph convolutional network divides the multi-layer convolution into dense blocks,and the convolutional layers in each dense block are connected,thus improving the feature transitivity,enhancing the network’s ability to extract features,thus improving the detection accuracy.Two representative datasets,Multiple Cameras Fall dataset(MCF),and Nanyang Technological University Red Green Blue+Depth Action Recognition dataset(NTU RGB+D),are selected for our experiments,among which NTU RGB+D has two evaluation benchmarks.The results show that the proposed model is superior to the current fall detection models.The accuracy of this network on the MCF dataset is 96.3%,and the accuracies on the two evaluation benchmarks of the NTU RGB+D dataset are 85.6%and 93.5%,respectively.

Ambulance Records as an Information Source to Document and Prevent Fall Injuries in Sweden

In Sweden, there has been only limited documentation for injuries requiring ambulance responses. The main objective of this study is, through the use of historic data, to assess the suitability of ambulance records to describe circumstances with fall injuries. Methods: The injury events data around patients were sourced from the ambulance data register. Descriptive statistics were used to describe injured patients based on age group, type of injury, place of injury, injury mechanism and consequence of an injury event. Two-group comparison was performed with Pearson’s chi-squared. Predictors of transport to hospital were identified using logistic regression analyses. Result: Ambulance provides unique data on all injury events, with direct implications for translational research, public policy and clinical practice (safety promotion). In 2002 ambulance attended 3964 injured people which represents 14% of ambulance attended workload in Värmland county, Sweden. The most common trauma location was the traffic area followed by residential area and nursing home. These three injury sites account for 2320 cases (61.6%). The most common cause of injury was falls (63.9%) followed by contact with another person (26.5%). Contact with another person is the most common site of injury in the traffic area (79.5%), and men aged 25-66 years are overrepresented. Conclusion: Logistic regression found that, age-group and place code were significant predictor for being attended by ambulance. Traffic, home and nursing homes were over-represented injury environments (61.6%) that require special attention. Most injury cases occur in the home and nursing homes among people over 67 years of age. Surprisingly, most of the injury events in the traffic environment are about hitting another person. Paramedics can provide rich and valuable data on injury events. Registration of such data is entirely possible and desirable, and can be used in preventive work.

Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining.Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations.As a result,a reliable roof fall prediction model is essential to tackle such challenges.Different parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research issue.The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls.Data acquired for 37 mines is limited due to several restrictions,which increased the likelihood of incompleteness.Fuzzy logic is a technique for coping with ambiguity,incompleteness,and uncertainty.Therefore,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters.The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

A Novel Fall Detection Framework Using Skip-DSCGAN Based on Inertial Sensor Data

With the widespread use of Internet of Things(IoT)technology in daily life and the considerable safety risks of falls for elderly individuals,research on IoT-based fall detection systems has gainedmuch attention.This paper proposes an IoT-based spatiotemporal data processing framework based on a depthwise separable convolution generative adversarial network using skip-connection(Skip-DSCGAN)for fall detection.The method uses spatiotemporal data from accelerometers and gyroscopes in inertial sensors as input data.A semisupervised learning approach is adopted to train the model using only activities of daily living(ADL)data,which can avoid data imbalance problems.Furthermore,a quantile-based approach is employed to determine the fall threshold,which makes the fall detection frameworkmore robust.This proposed fall detection framework is evaluated against four other generative adversarial network(GAN)models with superior anomaly detection performance using two fall public datasets(SisFall&MobiAct).The test results show that the proposed method achieves better results,reaching 96.93% and 92.75% accuracy on the above two test datasets,respectively.At the same time,the proposed method also achieves satisfactory results in terms ofmodel size and inference delay time,making it suitable for deployment on wearable devices with limited resources.In addition,this paper also compares GAN-based semisupervised learning methods with supervised learning methods commonly used in fall detection.It clarifies the advantages of GAN-based semisupervised learning methods in fall detection.

A Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller Model Combined with an Improved Particle Swarm Optimization Method for Fall Detection

In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.

Falls Lake水库内溶解物输运模拟

溶解物在水库内的输运过程受人为因素影响较大。为研究水库内物质输运的过程和机制,以美国北卡罗来纳州的Falls Lake水库为研究对象,运用EFDC三维数值模型对物质在水库内的输运过程进行模拟研究,分析示踪物平均年龄和滞留时间的分布以及变化。结果显示:理想状态下,流量决定溶解物的输运过程;实际情况中,除流量外,水库的即时蓄水量是影响输运过程的另一个重要因素;水库结构和径流分布是导致示踪物在各区域局地滞留时间存在差异的主要因素。

Prevalence and Related Factors of Falls among the Elderly in an Urban Community of Beijing

Objective To understand the prevalence, consequences and risk factors of falls among urban community-dwelling elderly in Beijing. Methods A cross-sectional study was conducted in Longtan Community, Beijing. A total of 1512 individuals aged 60 years or over were selected by stratified cluster sampling. Data regarding the frequency of falls in the previous year, as well as circumstances, consequence and related factors of falls were collected from the elderly through face-to-face interviews with questionnaires in their home. Results The prevalence of falls was 18.0% on the average among 1512 participants, higher in women （20.1%） than in men （14.9%） （P=0.006）, and increased with age （Х^2 for trend=10.37, P=0.001）. The total rate of falls-induced injuries among the fallers was 37.7%. Falls usually resulted in soft-tissues bruises （58.7%）, fear of repeated episodes of falls （58.8%）, loss of independence and confidence in movement （35.7%） and even in hip fracture. In addition to the burden of medical care, falls also generated a big economic burden. Occurrence of falls was significantly associated with both intrinsic and extrinsic factors. The related factors of falls in the elderly included age≥60-70 years, femininity, less physical activities, fear of future falls, living alone, severely impaired vision, health problem-impacted activities of daily living, chronic diseases （diabetes, hypertension, postural hypotension, stroke sequela, cataract, arthritis, dementia and depression）, medications （psychoactive, anti-diabetic）, gait imbalance, high bed and faintly-lighted stairway. Conclusion The prevalence of falls among urban community-dwelling elderly in Beijing is closely associated with significant associated with intrinsic and extrinsic factors. Efforts to prevent falls in the elderly should be made at community level.

Falls from height： A retrospective analysis

BACKGROUND: Emergency services manage trauma patients frequently and falls from height comprise the main cause of emergency service admissions. In this study, we aimed to analyse the demographic characteristics of falls from height and their relationship to the mortality.METHODS: A total of 460 patients, who admitted to the Emergency Department of Inonu University between November 2011 and November 2014 with a history of fall from height, were examined retrospectively. Demographic parameters, fall characteristics and their effect to mortality were evaluated statistically. RESULTS: The study comprised of 292(63.5%) men and 168(36.5%) women patients. The mean age of all patients was 27±24.99 years. Twenty-six(5.6%) patients died and the majority of them were in ≥62 years old group. The highest percentage of falls was at 0–5 years age group(28.3%). People fell mainly from 1.1–4 metres(m) level(46.1%). The causes of falls were ordered as unintentional(92.2%), workplace(8.1%) and suicidal(1.7%). Skin and soft tissue injuries(37.4%) were the main traumatic lesions. CONCLUSION: Age, fall height, fall place, linear skull fracture, subarachnoidal hemorrhage, cervical fracture, thoracic vertebra fracture and trauma scores had statistically significant effect on mortality. The casualties died because of subarachnoid hemorrhage mostly.

Incidence and Associated Factors for Single and Recurrent Falls among the Elderly in an Urban Community of Beijing

Objective To investigate the incidence of falls and recurrent falls, and explore associated factors for single and recurrent falls among urban community-dwelling elderly in Beijing. Methods A cross-sectional study was conducted in 472 elderly in the Longtan community of Dongcheng district, Beijing in 2009. Data regarding the incidence of fall and recurrent falls in the previous year, as well as associated factors were collected from the elderly through face-to-face interviews. Results The incidence of falls and recurrent falls was 17.8% and 6.1%, respectively, and it increased with age （X^2for trend=21.06, 19.20, P=0.001, 0.002）. Binary logistic stepwise regression analysis showed that age （OR=2.20）, living alone （OR=4.67） and gait disturbance （OR=1.27） were risk factors, while housing with elevators （OR=0.35）, appropriate width/height of stair steps （0R=0.78）, sufficient lighting for stairway （OR=0.45） and regular exercise （OR=0.12） could lower the risk for single fall; factors such as low monthly family income （OR=1.39）, poor vision （OR=1.83）, low physical ability （OR=4.47）, abnormal static balance （OR=2.48）, and fear of falls（OR=2.23） were risk factors, while appropriate width/height of stair steps （OR=0.49） and easiness of access to daily supplies （OR=0.41） were protective factors for recurrent falls. Conclusion The incidence of falls in commun and their related injuries have been associated ty-dwelling elderly people in Beijing is common, and falls with both intrinsic and extrinsic factors.

Reducing costly falls after total knee arthroplasty

AIM To investigate whether adductor canal nerve block(ACB) reduces patient falls when compared to femoral nerve block(FNB) after total knee arthroplasty(TKA). METHODS We conducted an institutional review of all-cause falls after TKA from January 2013 to August 2016 using a quality improvement database. Our inclusion criteria were patients with diagnosis of primary knee osteoarthritis who underwent primary unilateral TKA with either a FNB or an ACB and sustained a fall during their hospitalization. We excluded patients who had revision TKA and extensor mechanism reconstruction. We also excluded patients with a history of post-traumatic arthritis, prior history of lower extremity fracture, history of neurological disease, or cerebrovascular disease. RESULTS A total of 834 patients had TKA with femoral nerve block and knee immobilizer(FNB + KI). Of those patients, 11(1.3%) experienced a fall during their hospital stay. In contrast, 791 patients had TKA with ACB. Of those patients, only one(0.13%) patient fall was recorded within this group. We used the Fisher's exact test to compare the differences between the two groups. The difference between the two groups achieves statistical significance(P = 0.006). We also found that 11 out of the 12 patients that fell had a right TKA procedure while one patient had a left TKA procedure. Nine out of twelve patients that fell were female, while only three patients were male.CONCLUSION Given the reduction in the number of falls with ACB, it is recommended that ACB be considered the preferred analgesia for patients undergoing a TKA procedure.

Psychological risk factors associated with falls among elderly people in Baghdad city, Iraq

Background: Ageing of the population is one of the most important demographic facts that come to the foreground in the 21st century. Objective: To assess the relationship between psychological factors (depression, loneliness, using anti anxiety medication, fear from falls and internal displacement of the population) and falls among elderly people in Baghdad city, Iraq. Methods: A matched 1:1 community based case-control study involving 716 elderly respondents, recruited randomly from six Non Governmental Organization (NGO) in different areas of Baghdad. Interviews to each respondent were done accordingly. Geriatric depression scale (GDS) was used to assess the depression among the elderly people. Results: The minimum age for cases and controls was 60 years old while the maximum age for cases was 87 and for controls was 85 years old. The female was predominant than male, 53.6% to 46.4% respectively. The relation between depression, fear from fall, using anti anxiety medication, internal displacement and falls was statistically significant

Handgrip strength and falls in community-dwelling Egyptian seniors

Purpose: To establish a relationship between falls and handgrip strength (GS) in communitydwelling senior citizens in Egypt. Subjects: Crosssectional study enrolling 132 subjects, all ≥60 years old. Materials and Methods: History of falls in the past year and their number as well as GS measurement in both hands using Baseline? pneumatic squeeze handheld dynamometer. Results: There is a highly significant difference between the GS of fallers and non-fallers in both hands (P = 0.000). There is a highly significant negative correlation between the mean GS and the number of falls (P = 0.003). There is a highly significant positive correlation between GS of the right hand with the number of falls (R = 0.226, P = 0.009), as for the correlation with the left GS it was a weaker positive correlation (R = 0.209, P = 0.16). Conclusion: Seniors with history of falls have a lower GS in both dominant and nondominant hands and it is directly related to the number of falls. GS is decreased in senior fallers even if within the normal range.

Establishing the Reliability and Validity of Health in Motion^©Automated Falls Screening Tool

Introduction: Blue Marble Health Company has created a digital fall risk screening tool (Health in Motion&#169;) that can be used by means of self-report (touch/mouse) or by means of motion capture (Microsoft Kinect Sensor). Health in Motion&#169;consists of automated versions of the Fall Risk Question-naire, 30-Second Chair Stand Test, and the One Leg Stance Test. Methods: We compared the three methods (self-report, sensor, and clinical standard measurement) using stopwatch and observation in 15 community-dwelling older adults, aged 63 - 80 years old. Each version was completed three times each in random order, for a total of nine trials. Results: Health in Motion&#169;falls screening tool accessible via self-report and sensor is a valid and reliable automated at-home self-assessment for falls risk. Conclusion: Results support the use of Health in Motion&#169;falls screening tools as viable alternatives to standard falls risk assessments for use by older adults at home.

Predictors of Falls Efficacy Scale responses among nursing home residents in China

Objectives:The objective of this study was to examine the falls efficacy of older adults in nursing homes and the related predictors of falling.Methods:A sample of 317 older adults was recruited from 18 nursing homes in the Fujian province of China.The Modified Falls Efficacy Scale(MFES)and Kessler Psychological Distress Scale(K10)were employed to collect data.Results:The falls efficacy of older adults was moderate(7.80±1.17).The falls efficacy questionnaire item“Get dressed and undressed”scored the highest(9.12±1.440),while“Crossing roads”scored the lowest(5.77±3.371).Multiple regression analysis demonstrated that mental health status,degree of self-care,age and gender were each predictors of the falls efficacy of older adults.Conclusions:Falls efficacy enhancing programs for nursing home residents should take mental health status,degree of self-care,age and gender into account.