In-hospital Fall Research Articles

Falls and malnutrition are associated with in-hospital mortality in patients with cirrhosis.

Hospitalized patients with end-stage liver disease are at risk of malnutrition, reduced body function, and cognitive impairment due to HE. This combination may have an impact on in-hospital falls and mortality. The purpose of this study was to identify factors associated with the risk of falls and to analyze the consequences regarding in-hospital mortality. We performed a retrospective analysis of patients hospitalized with liver cirrhosis between 2017 and 2019 at the Department of Gastroenterology at the University Hospital Frankfurt. Clinical data, laboratory work, and follow-up data were analyzed. Factors associated with the risk of falls and in-hospital mortality were calculated using a mixed effect poisson regression model and competing risk time-to-event analyses. Falls occurred with an incidence of 4% (80/1985), including 44 injurious falls with an incidence rate of 0.00005/100 patient-days (95% CI: 0.00001-0.00022). In the multivariate analysis malnutrition (incidence risk ratio: 1.77, 95% CI: 1.04-3.04) and implanted TIPS (incidence risk ratio: 20.09, 95% CI: 10.1-40.1) were independently associated with the risk of falling. In a total of 21/80 (26.25%) hospitalizations, patients with a documented fall died during their hospital stay versus 160/1905 (8.4%) deaths in hospitalizations without in-hospital fall. Multivariable analysis revealed as significant clinical predictors for in-hospital mortality a Nutritional Risk Screening ≥2 (HR 1.79, 95% CI: 1.32-2.4), a falling incident during hospitalization (HR 3.50, 95% CI: 2.04-6.0), high MELD, and admission for infections. Malnutrition and TIPS are associated with falls in hospitalized patients with liver cirrhosis. The in-hospital mortality rate of patients with cirrhosis with falls is high. Specific attention and measures to ameliorate these risks are warranted.

Patient involvement in fall prevention in an acute care hospital: A survey study

ObjectivesInpatient falls are a major patient safety issue in acute care hospitals. Multifactorial in-hospital fall prevention programs have shown reductions in falls and related risks. One common element of successful programs is active patient involvement. This study objective was to explore patients’ and nurses’ experiences with a structured intervention to foster patient involvement. MethodsThis observational pre-post study was conducted between September 2020 and April 2021 in a university hospital neurological ward. The studied intervention consisted of a falls information leaflet, and a structured nurse-patient conversation about fall risk-reduction activities. Nurses were trained to deliver the intervention and supported throughout the study. Nurses’ and patients’ experiences regarding personal involvement, satisfaction, and confidence were surveyed and analyzed quantitatively and qualitatively. ResultsFifty-six patients recruited by ward nurses received the intervention. After receiving the intervention, patients reported high levels of satisfaction with the in-hospital fall prevention conversation. 21 nurses indicated that they would use the leaflet and communication aid. 21 nurses commented on intervention facilitators and barriers. More specific facilitators included their shared perception that “handing out the leaflet to patients was not problematic” and that the leaflet was seen as “applicable in many patient situations.”Their comments indicated two particularly prominent barriers to conducting the intervention in clinical practice: 1) “finding the time for the implementation in the daily clinical routine and workload” and 2) “environmental factors like a noisy and busy atmosphere on the ward.” ConclusionsThis study provides insights into a patient involvement intervention featuring a structured nurse-patient discussion about fall risks. The accompanying information leaflet and communication guide require adaptations to facilitate sustainable implementation into the hospital’s fall prevention program, but proved useful.

Risk Factors and Characteristics of In-Hospital Falls After Spine Surgery: A Retrospective, Single-Center Cohort Study in the Republic of Korea.

Falls after orthopaedic surgery can cause serious injuries, which lengthen hospital stays and increase medical expenses. This has prompted hospitals to implement various fall-prevention protocols. The aims of this study were to determine the incidence of in-hospital falls after spine surgery, to analyze the overall risk factors, to discern factors that have a major influence on falls, and to evaluate the effectiveness of the fall-prevention protocol that we implemented. This was a retrospective, single-center study including patients who underwent spine surgery from January 2011 to November 2021 at the National Health Insurance Service Ilsan Hospital (NHISIH) in Goyang, Republic of Korea. Reported falls among these patients were examined. Patient demographics; surgery type, date, and diagnosis; and fall date and time were evaluated. Overall, 5,317 spine surgeries were performed, and 128 in-hospital falls were reported (overall incidence: 2.31%). From the multivariable analyses, older age and American Society of Anesthesiologists (ASA) score were identified as independent risk factors for in-hospital patient falls (multivariable adjusted hazard ratio [aHR] for age 70 to 79 years, 1.021 [95% confidence interval (CI), 1.01 to 1.031]; for age ≥80 years, 1.035 [1.01 to 1.06]; and for ASA score of 3, 1.02 [1.01 to 1.031]). Similar results were seen in the subgroup who underwent primary surgery. Within 2 weeks following surgery, the highest frequency of falls occurred at 3 to 7 days postoperatively. The lowest fall rate was observed in the evening (6 to 10 p.m.). Morbidities, including rib, spine, and extremity fractures, were recorded for 14 patients, but none of these patients underwent operative treatment related to the fall. The NHISIH implemented a comprehensive nursing care service in May 2015 and a fall protocol in May 2017, but the annual incidence rate did not improve. The fall rate was higher after thoracolumbar surgeries (2.47%) than after cervical surgeries (1.20%). Moreover, a higher fall rate was observed in thoracolumbar cases with a greater number of fusion levels and revision spine surgeries. Patients with advanced age, more comorbidities, a greater number of fusion levels, and revision surgeries and who are female are more vulnerable to in-hospital falls after spine surgery. Novel strategies that target these risk factors are warranted. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Patient Safety Indicators During the Initial COVID-19 Pandemic Surge in the United States.

The COVID-19 pandemic presented a challenge to inpatient safety. It is unknown whether there were spillover effects due to COVID-19 into non-COVID-19 care and safety. We sought to evaluate the changes in inpatient Agency for Healthcare Research and Quality patient safety indicators (PSIs) in the United States before and during the first surge of the pandemic among patients admitted without COVID-19. We analyzed trends in PSIs from January 2019 to June 2020 in patients without COVID-19 using data from IBM MarketScan Commercial Database. We included members of employer-sponsored or Medicare supplemental health plans with inpatient, non-COVID-19 admissions. The primary outcomes were risk-adjusted composite and individual PSIs. We analyzed 1,869,430 patients admitted without COVID-19. Among patients without COVID-19, the composite PSI score was not significantly different when comparing the first surge (Q2 2020) to the prepandemic period (e.g., Q2 2020 score of 2.46 [95% confidence interval {CI}, 2.34-2.58] versus Q1 2020 score of 2.37 [95% CI, 2.27-2.46]; P = 0.22). Individual PSIs for these patients during Q2 2020 were also not significantly different, except in-hospital fall with hip fracture (e.g., Q2 2020 was 3.42 [95% CI, 3.34-3.49] versus Q4 2019 was 2.45 [95% CI, 2.40-2.50]; P = 0.01). The first surge of COVID-19 was not associated with worse inpatient safety for patients without COVID-19, highlighting the ability of the healthcare system to respond to the initial surge of the pandemic.

An inpatient fall risk assessment tool: Application of machine learning models on intrinsic and extrinsic risk factors

BackgroundThis study aimed to identify the most impactful set of intrinsic and extrinsic fall risk factors and develop a data-driven inpatient fall risk assessment tool (FRAT). MethodsThe dataset used for the study comprised in-hospital fall records from 2012 to 2017. Four machine learning (ML) algorithms, Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting (Gboost), and Deep Neural Network (DNN) were utilized to predict the inpatient fall risk level. To enhance the performance of the prediction models, two approaches were implemented, including (1) feature selection to identify the optimal feature set and (2) the development of three distinct shift-wise models. Furthermore, the optimal feature sets in the shift-wise models were extracted. ResultsAccording to the results, DNN outperformed other methods by reaching an accuracy, sensitivity, specificity, and AUC of 0.71, 0.8, 0.6, and 0.7, respectively, considering the full set of features. The performance of the models was further improved (by 3-5 %) by conducting a feature selection process for all models. Specifically, the DNN model achieved an accuracy of 0.74 while considering the optimal set of predictors. Moreover, the shift-wise RF models demonstrated higher accuracies (by 4-10 %) compared to the same model using a full feature set. ConclusionsThis study's outcome confirms ML models' compelling capability in developing an inpatient FRAT while considering intrinsic and extrinsic factors. The insight from such models could form a foundation to (1) monitor the inpatients’ fall risk, (2) identify the major factors involved in inpatient falls, and (3) create subject-specific self-care plans.

In-hospital fall prediction using machine learning algorithms and the Morse fall scale in patients with acute stroke: a nested case-control study

BackgroundFalls are one of the most common accidents in medical institutions, which can threaten the safety of inpatients and negatively affect their prognosis. Herein, we developed a machine learning (ML) model for fall prediction in patients with acute stroke and compared its accuracy with that of the existing fall risk prediction tool, the Morse Fall Scale (MFS).MethodsThis is a retrospective nested case-control study. The initial sample size was 8462 admitted to a single cerebrovascular specialty hospital with acute stroke. A total of 156 fall events occurred, and each fall case was randomly matched with six control cases. Six ML algorithms were used, namely, regularized logistic regression, support vector machine, naïve Bayes (NB), k-nearest neighbors, random forest, and extreme-gradient boosting (XGB).ResultsWe included 156 in the fall group and 934 in the non-fall group. The mean ages of the fall and non-fall groups were 68.3 (± 12.2) and 65.3 (± 12.9) years old, respectively. The MFS total score was significantly higher in the fall group (54.3 ± 18.3) than in the non-fall group (37.7 ± 14.7). The area under the receiver operating curve (AUROC) of the MFS in predicting falls was 0.76 (0.73–0.79). XGB had the highest AUROC of 0.85 (0.78–0.92), and XGB and NB had the highest F1 score of 0.44.ConclusionsThe AUROC values of all of ML algorithms were similar to those of the MFS in predicting fall risk in patients with acute stroke, allowing for accurate and efficient fall screening.

Inpatient Falls and Orthopaedic Injuries in Elderly Patients: A Retrospective Cohort Analysis From a Falls Register.

Background Hospital inpatient falls have been a major area of concern in the healthcare setting. This poses a multifaceted challenge to healthcare systems, as elderly patients are at increased risk of harm and significant morbidity secondary to inpatient falls. In addition, hospital admission increases the risk of falls in acutely unwell elderly patients. There remains little consensus on best practices in reducing inpatient falls. With this, lies the risk to life or quality of life to this cohort of patients. Moreover, it is not evident whether orthopaedic injuries sustained by elderly patients in hospital and their management, including rehabilitation, has evolved with time. Methodology This was a retrospective cohort analysis of all inpatient falls over a three-year period in a single UK District General Hospital. A total of 101,183 acute admissions were analysed. All falls were identified and categorised into harm categories according to National Patient Safety Alerts. Patients sustaining moderate harm or more were assessed to determine injuries sustained, patient-associated factors, factors surrounding the fall, management incurred, length of stay, and financial burden incurred. Results A total of 101,183 admissions were analysed revealing a total of 2,453 in-patient falls. The rate of inpatient falls was 2.42%. Of these, 49 (1.98%) patients sustained moderate harm or more. Patient-related factors included age and comorbidities; 82% of patients were above the age of 75, and 78% of patients had three or more medical comorbidities. Fall-related factors leading to moderate harm or more included time of fall and ward. Most falls occurred out of hours (80%) and in acute medical wards (69%). The average length of stay following fall was 2.4 weeks per patient and a combined 110 weeks in the three-year period. In non-deceased patients, increased dependency and reduced mobility at discharge were noted. The total hospital annual financial burden due to moderate harm or more following an inpatient fall was approximately £123,490.00. Length of stay was the major contributor to this (£90,090.00 annually). Conclusions Inpatient falls remain a considerable patient safety issue, with orthopaedic injuries playing a central role in harm to patients following these falls. These also pose considerable service and financial costs to healthcare organisations. Further work is needed to identify best practices in in-hospital fall prevention and streamlining post-fall management and rehabilitation.

In-Hospital Fall Risk Prediction by Objective Measurement of Lower Extremity Function in a High-Risk Population

ObjectivesLimited data exist regarding association between physical performance and in-hospital falls. This study was performed to investigate the association between physical performance and in-hospital falls in a high-risk population. DesignRetrospective cohort study. Setting and ParticipantsThe study population consisted of 1200 consecutive patients with a median age of 74 years (50.8% men) admitted to a ward with high incidence rates of falls, primarily in the departments of geriatrics and neurology, in a university hospital between January 2019 and December 2021. MethodsShort Physical Performance Battery (SPPB) was measured after treatment in the acute phase. As the primary end point of the study, the incidence of in-hospital falls was examined prospectively based on data from mandatory standardized incident report forms and electronic patient records. ResultsSPPB assessment was performed at a median of 3 days after admission, and the study population had a median SPPB score of 3 points. Falls occurred in 101 patients (8.4%) over a median hospital stay of 15 days. SPPB score showed a significant inverse association with the incidence of in-hospital falls after adjusting for possible confounders (adjusted odds ratio for each 1-point decrease in SPPB: 1.19, 95% CI 1.10-1.28; P < .001), and an SPPB score ≤6 was significantly associated with increased risk of in-hospital falls. Inclusion of SPPB with previously identified risk factors significantly increased the area under the curve for in-hospital falls (0.683 vs. 0.740, P = .003). Conclusion and ImplicationsThis study demonstrated an inverse association of SPPB score with risk of in-hospital falls in a high-risk population and showed that SPPB assessment is useful for accurate risk stratification in a hospital setting.

Prediction of In-Hospital Falls Using NRS, PACD Score and FallRS: A Retrospective Cohort Study.

Harmful in-hospital falls with subsequent injuries often cause longer stays and subsequently higher costs. Early identification of fall risk may help in establishing preventive strategies. To assess the predictive ability of different clinical scores including the Post-acute care discharge (PACD) score and nutritional risk screening score (NRS), and to develop a new fall risk score (FallRS). A retrospective cohort study of medical in-patients of a Swiss tertiary care hospital from January 2016 to March 2022. We tested the ability of the PACD score, NRS and FallRS to predict a fall by using the area under curve (AUC). Adult patients with a length of stay of ≥ 2 days were eligible. We included 19,270 admissions (43% females; median age, 71) of which 528 admissions (2.74%) had at least one fall during the hospital stay. The AUC varied between 0.61 (95% confidence interval (CI), 0.55-0.66) for the NRS and 0.69 (95% CI, 0.64-0.75) for the PACD score. The combined FallRS score had a slightly better AUC of 0.70 (95% CI, 0.65-0.75) but was more laborious to compute than the two other scores. At a cutoff of 13 points, the FallRS had a specificity of 77% and a sensitivity of 49% in predicting falls. We found that the scores focusing on different aspects of clinical care predicted the risk of falls with fair accuracy. A reliable score with which to predict falls could help in establishing preventive strategies for reducing in-hospital falls. Whether or not the scores presented have better predictive ability than more specific fall scores do will need to be validated in a prospective study.

In-Hospital Newborn Falls and Near Miss Events: A Need to Report.

This study aimed to evaluate the clinical characteristics of the neonates who fell in the maternity ward and identify the incidence of near miss events during the immediate postpartum period. The study consisted of two steps. The retrospective part included the evaluation of admissions due to the in-hospital newborn fall for 6 years. The prospective part included the assessment of the near miss events (any probability of falling of the newborn; either cosleeping or an incident with a possible consequence of falling of the newborn) in the postpartum clinic (<72 hours after delivery) for a period of 4 weeks. The details of the events and clinical outcomes were recorded. A questionnaire about fatigue was administered to mothers who experienced near miss event. Seventeen in-hospital newborn falls were recorded: 1.8 to 2.4/10,000 live births. The median age of the neonates when the fall occurred was 22 (16-34) postnatal hours. Fourteen events (82%) occurred between 10 p.m. and 6 a.m. All neonates who experienced a fall were discharged without any known adverse outcomes. Twelve mothers (71%) had experienced a near miss event before. In the prospective arm of the study, 67 out of 804 mothers (8.3%) were found to experience a near miss event (44/1,000 days of postpartum hospitalization). Thirty-two events (49%) occurred in the first postpartum day. Fifty-two events (78%) occurred between 10 p.m. and 6 a.m. Fifty-eight mothers (86%) had no companion. Sixty-three percent of the mothers expressed intense fatigue after delivery. In-hospital newborn fall may occur in the postpartum period, and near miss events should warn clinicians for a probable fall event. The nighttime shift requires more attention regarding the prevention of both the fall and the near miss events. Immediate postpartum mothers are needed to be observed carefully. · In-hospital newborn falls occurred mainly during the night shift.. · Nearly two-third of the mothers whose newborn was fallen experienced a previous near miss event.. · Any near miss event in the hospital was detected in 8.3% of mothers..

Implementation fidelity of a multifactorial in-hospital fall prevention program and its association with unit systems factors: a single center, cross-sectional study

BackgroundFalls are a common, costly global public health burden. In hospitals, multifactorial fall prevention programs have proved effective in reducing falls’ incidence; however, translating those programs accurately into daily clinical practice remains challenging. This study’s aim was to identify ward-level system factors associated with implementation fidelity to a multifactorial fall prevention program (StuPA) targeting hospitalized adult patients in an acute care setting.MethodsThis retrospective cross-sectional study used administrative data on 11,827 patients admitted between July and December 2019 to 19 acute care wards at the University Hospital Basel, Switzerland, as well as data on the StuPA implementation evaluation survey conducted in April 2019. Data were analysed using descriptive statistics, Pearson’s coefficients and linear regression modelling for variables of interest.ResultsThe patient sample had an average age of 68 years and a median length of stay of 8.4 (IQR: 2.1) days. The mean care dependency score was 35.4 points (ePA-AC scale: from 10 points (totally dependent) to 40 points (totally independent)); the mean number of transfers per patient -(e.g., change of room, admission, discharge) was 2.6 (range: 2.4– 2.8). Overall, 336 patients (2.8%) experienced at least one fall, resulting in a rate of 5.1 falls per 1’000 patient days. The median inter-ward StuPA implementation fidelity was 80.6% (range: 63.9–91.7%). We found the mean number of inpatient transfers during hospitalisation and the mean ward-level patient care dependency to be statistically significant predictors of StuPA implementation fidelity.ConclusionWards with higher care dependency and patient transfer levels showed higher implementation fidelity to the fall prevention program. Therefore, we assume that patients with the highest fall prevention needs received greater exposure to the program. For the StuPA fall prevention program, our results suggest a need for implementation strategies contextually adapted to the specific characteristics of the target wards and patients.

In-Hospital Newborn Falls and Suffocation Associated With Parental Drug-Related Fatigue.

In-Hospital Newborn Falls and Suffocation Associated With Parental Drug-Related Fatigue.

The Association between Delirium and In-Hospital Falls: A Cross-Sectional Analysis of a Delirium Screening Program.

A cross-sectional study using delirium screening and falls reports was used to measure the association between delirium and falls. All inpatient data from August, 2018, to January, 2020, at a large academic medical center were analyzed. A multivariable logistic regression of 29,655 hospital admissions was used to understand the association between in-hospital delirium and falls. Analysis revealed a delirium rate of 12.5% (n = 3,707) of all admissions and 286 (0.9%) admissions with falls; of the falls studied, 37.6% of these patients screened positive for delirium during their admission. Relative to those who screened negative for delirium, admissions that screened positive for delirium had a 2.81 increased odds of falling. Delirium and falls are related. This strong association should motivate health systems to look closely at both problems. Falls and delirium can both have immense impacts on the patient and the health system. The powerful association between them provides a window to reduce these additional patient harms. More specifically, a modern delirium screening tool should be used as part of routine risk assessment focused on reducing in-hospital falls.

External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients.

Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time. We used an Electronic Health Records (EHR) dataset with hospitalized patients (≥ 70), admitted for ≥ 24h between 2016 and 2021. Inpatient falls were extracted from structured and free-text data. We assessed the association between JHFRAT and falls using logistic regression. For test accuracy, we calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was measured by the AUC. For calibration, we plotted the predicted fall probability with the actual probability of falls. For time-related effects, we calculated the AUC per 6months (using data of patients admitted during the 6months' time interval) and plotted these different AUC values over time. Furthermore, we compared the model (JHFRAT and falls) with and without adjusting for seasonal influenza, COVID-19, spring, summer, fall or winter periods. Data included 17,263 admissions with at least 1 JHFRAT measurement, a median age of 76 and a percentage female of 47%. The in-hospital fall prevalence was 2.5%. JHFRAT [OR = 1.11 (1.03-1.20)] and its subcategories were significantly associated with falls. For medium/high risk of falls (JHFRAT > 5), sensitivity was 73%, specificity 51%, PPV 4% and NPV 99%. The overall AUC was 0.67, varying over time between 0.62 and 0.71 (for 6months' time intervals). Seasonal influenza did affect the association between JHFRAT and falls. COVID-19, spring, summer, fall or winter did not affect the association. Our results show an association between JHFRAT and falls, a low discrimination by JHFRAT for older inpatients and over-prediction in the calibration. Improvements in the fall-risk assessment are warranted to improve efficiency.

History of Falls and Bedriddenness Ranks are Useful Predictive Factors for in-Hospital Falls: A Single-Center Retrospective Observational Study Using the Saga Fall Risk Model.

In our former study, we had validated the previously developed predictive model for in-hospital falls (Saga fall risk model) using eight simple factors (age, sex, emergency admission, department of admission, use of hypnotic medications, history of falls, independence of eating, and Bedriddenness ranks [BRs]), proving its high reliability. We found that only admission to the neurosurgery department, history of falls, and BRs had significant relationships with falls. In the present study, we aimed to clarify whether each of these three items had a significant relationship with falls in a different group of patients. This was a single-center based, retrospective study in an acute care hospital in a rural city of Japan. We enrolled all inpatients aged 20 years or older admitted from April 2015 to March 2018. We randomly selected patients to fulfill the required sample size. We performed multivariable logistic regression analysis using forced entry on the association between falls and each of the eight items in the Saga fall risk model 2. A total of 2932 patients were randomly selected, of whom 95 (3.2%) fell. The median age was 79 years, and 49.9% were men. Multivariable analysis showed that female sex (odds ratio [OR] 0.6, 95% confidence interval [CI] 0.39-0.93, p = 0.022), having a history of falls (OR 1.9, 95% CI 1.16-2.99, p = 0.010), requiring help with eating (OR 1.9, 95% CI 1.12-3.35, p = 0.019), BR of A (OR 6.6, 95% CI 2.82-15.30, p < 0.001), BR of B (OR 7.5, 95% CI 2.95-19.06, p < 0.001), and BR of C (OR 4.1, 95% CI 1.53-11.04, p = 0.005) were significantly associated with falls. History of falls and BRs were independently associated with in-hospital falls.

Een cardiocerebraal stollingsdilemma bij een oudere patiënte

A cardio-cerebral coagulation dilemma A 77-year-old patient with permanent atrial fibrillation and mechanical heart valves on a treatment with fenprocoumon developed a subdural hematoma after an in-hospital fall. The initially successful burr-hole trepanation was followed by an expanding contralateral subdural hematoma with midline shift 36 hours later. Because of the prior cognitive and functional decline with recurrent falls and an irreconcilable dilemma between the need for thrombo-embolic prevention with adequate anticoagulation and the need for neuroprotection with normal clotting times, the prognosis was considered to be poor. A multidisciplinary decision was made offering the best supportive care without further neurosurgical treatment.

Automatic Patient Fall Outcome Extraction Using Narrative Incident Reports.

Patient outcome is one of the key information categories in incident reporting. Being able to extract meaningful patient fall outcomes would allow better analysis of the consequences and possible mitigating actions for in-hospital fall incidents. This study aims to automate the extraction of patient outcomes from narrative fall incident reports by decomposing this into three classification subtasks: injured or not, injury types, and the number of injuries. Implementing an existing incident report classification (IRC) framework, the experimental results demonstrated that oversampling and structured features were effective to achieve better overall performances across all three subtasks. The study further validated the application of an IRC framework to deal with imbalanced classification problems found in fall patient outcome classification and advanced the science of automatic patient outcomes extraction.

Patient-level and organizational-level factors influencing in-hospital falls.

In-hospital fall is one key safety issue in a healthcare setting. Although healthcare providers apply several strategies for preventing falls, falls still occur in hospitals. The aim of this study was to investigate patient-level and organizational-level factors influencing in-hospital falls. A multicentre retrospective observational study. This study used the national healthcare database and supplemented with organizational data obtained through a survey. Data extraction and survey were conducted between July and August 2020. A mixed-effect logistic regression model was used to analyse factors influencing in in-hospital falls. A total of 43,286 patients admitted in 86 hospitals were included in this study. Fall rate was 0.85 per 1000 days. Length of stay was significantly longer for fall patients than for no-fall patients. Patient-level factors (including age, mobility impairment and surgery) and organizational-level factors (including nurse staffing and proportion of new nurses) were significant factors influencing in-hospital falls. Since in-hospital falls increase economic burden to patients, we should consider various fall prevention strategies to reduce falls. For a strategy to be applied stably to patients, organizational factors must be supported. Proactive fall management in acute settings is essential to ensure patient safety. Considering that the number of patients with fall risk is increasing due to ageing, organizational factors should be supported to provide quality nursing care for fall risk patients. Therefore, nurse leaders should primarily ensure an appropriate level of nurse staffing. They also need to make efforts to strengthen clinical competency of nurses.

Fall determinants in hospitalised older patients: a nested case control design - incidence, extrinsic and intrinsic risk in Malaysia

BackgroundThe older person is at greater risk of falls due to multiple intrinsic and extrinsic factors. This is compounded when the elderly is admitted to hospitals, as they are acutely ill and placed in an unfamiliar environment. Delirium and polypharmacy further complicate these problems. As falls reflect quality of care with potential for grave outcomes, this study aimed to identify the extent and risk of falls in public hospitals.MethodsWe conducted a nested case control study in 12 public hospitals in Malaysia. In the cohort section, we screened all inpatients 60 years of age and above daily until discharge, or the end of the study period. Daily, we identified those who fell, inclusive of near falls, in the preceding 24 h. Our enumerators interviewed patients on experience of fall, and supplemented data from the nurses and caregivers. For each case, ten controls were chosen.ResultsThe incidence of falls/near falls was 1.0 per 1000 patient days (95% CI: 0.9, 1.1). Intrinsic risk factors found to be significant included patients who were not from a nursing home or not cared for by a domestic helper prior to admission, had prior history of indoor fall either in home or hospital, had four or more clinical diagnoses or exited from the bed on the weak side. Significant extrinsic factors were the absence of transfer bar in toilet, call bells, light switches or walking aids that were not within reach, as well as not having a walking aid. Non-sturdy chair was associated with lesser falls than when sturdy chairs with armrests were present.ConclusionQuerying patients for falls produced better results than incident reporting. Several intrinsic factors such as history of indoor or in-hospital fall, having four or more clinical diagnoses or exiting from weaker side and residence history may help to identify those at higher risk. Addressing significant extrinsic factors such as transfer bars and the identification of switches may help in reducing falls risk in hospitals.Trial registrationThis study was registered in National Medical Research Register of Malaysia (NMRR-07-772-1044; date 26/05/2008) with Ethics Approval from Medical Research and Ethics Committee (MREC: MRG-07-LOI-HSR-1).

Anticholinergic Drug Use on Admission and the Risk of In-Hospital Falls in Older Hospitalized Patients.

PurposeIn-hospital falls, especially among older patients, are a major and underestimated problem. Several studies have suggested a possible association between anticholinergic drug use and falls, but the results are inconclusive and studies focusing on in-hospital falls are scarce. The aim of the present study was to investigate whether anticholinergic drug exposure on admission is associated with in-hospital falls.Patients and MethodsThis retrospective chart review study was conducted in the Erasmus MC University Medical Center, Rotterdam, the Netherlands. Patients aged 65 years and older, who were acutely admitted to the geriatric ward between 2012 and 2015, were included. Anticholinergic drug exposure was determined with the Anticholinergic Risk Scale (ARS), the Anticholinergic Cognitive Burden scale (ACB) and the list of Chew. Logistic regression was used to investigate the possible association between anticholinergic drug exposure and in-hospital falls. Analyses were adjusted for age, sex, fall history, fall as reason for admission, number of drugs on admission, use of a mobility aid and delirium.ResultsA total of 905 patients were included, of which 94 patients experienced one or more in-hospital falls. Each additional anticholinergic drug in use, according to the ARS, was associated with an increased odd of experiencing a fall (OR = 1.49, 95% CI: 1.06–2.10). Other measures, ie anticholinergic drug use (yes/no) and different categories of anticholinergic drug burden, measured with the ARS, ACB and list of Chew, were all not associated with in-hospital falls.ConclusionAnticholinergic drug exposure on admission is possibly not a main risk factor for in-hospital falls among older patients.