Development of a Falls Registry: A Pilot Study

Berg, Gina M.; Carlson, Tara; Fairchild, Joanne; Edwards, Courtney; Sorell, Ryan

doi:10.1097/jtn.0000000000000295

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…In order to allow follow-up studies, more information is needed about the circumstances preceding falls, both to better understand the contributing risk factors and to develop specific and effective fall prevention strategies (Stevens et al, 2009). Thus, data regarding vehicle (rollator) and environmental factors should be included in the accident and injury registration (Berg et al, 2017;Carlsson & Lundälv, 2019). Injury severity and costs for falls would then be distinguishable for different environments (Berg et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Thus, data regarding vehicle (rollator) and environmental factors should be included in the accident and injury registration (Berg et al, 2017;Carlsson & Lundälv, 2019). Injury severity and costs for falls would then be distinguishable for different environments (Berg et al, 2017). Beside the lack of injury data, research into rollator users' experience of accidents and perceived risks in the traffic environment is also limited.…”

Section: Discussionmentioning

confidence: 99%

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Rollator related pedestrian single accidents and collision events in Sweden

Carlsson¹,

Lundälv²

2023

TSR

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Rollators (four-wheel walkers in USA; zimmer frames in UK) are commonly used as mobility aids for the elderly and people with a variety of disabilities. Pedestrian rollator users are a sub-group of Vulnerable Road Users (VRUs), although this group is rarely recognised in traffic safety contexts. The aim of this study is to extract and analyse rollator related pedestrian accident and injury data in Sweden. The results will provide valuable insight into the risks and obstacles rollator users are exposed to in the traffic environment and may in the long term contribute to improving the mobility of this group. The current study is based on data from 2,020 accidents involving 2,305 persons extracted from the Swedish Traffic Accident Data Acquisition (STRADA) database. For consistency reasons, a subset of data (N = 745) was analysed in order to investigate the development of accidents over a period of 10 years. Thereafter, each accident in the whole data set was registered as either single or collision. The results show that the number of rollator accidents in Sweden increased by approximately 80% during 2007–2016. Females dominate the injury statistics of single accidents, collisions, as well as fatal outcome, which may be due to exposure and/or differences in physical characteristics. Single accidents are much more common than collisions (n=1,668 and n=352, respectively) and the injury consequences are at least as serious. Data from the present study have revealed that the frequency of minor injuries (ISS 1–3) is 4.3 times, moderate (ISS 4–8) 6.0 times and serious injuries (ISS 9–15) 8.9 times higher in single accidents than in collisions. Fatal injuries are, however, more common in collision events (33 in comparison to 8). The vast majority of single accidents (99%) was due to falls. Many of the single accidents (29%) were caused by ground level differences (typically a curb) or due to surface conditions (19%). Collisions involved cars, trucks or buses in 91% of cases, occurring predominantly in car parks (31%) and on (zebra) crossings (30%). In 54% of cases the vehicles reversed into the rollator. Abbreviated Injury Scale (AIS) 3+ injuries were dominated by head (36%) and torso (33%) injuries in collision events, and hip fractures (71%) in single accidents. The present study shows that further research into rollator user related accidents, both single accidents and collision events, is required. In order to introduce appropriate measures, future work should follow up on accident and injury developments and further improve the quality of mobility aid related accident data in general. Improved stability and design, proper training programmes, effective maintenance services, development of a supporting infrastructure would contribute to increased safety for rollator users.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Rollator related pedestrian single accidents and collision events in Sweden

Carlsson¹,

Lundälv²

2023

TSR

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Epidemiologic features and intervention effect of fall injury among rural school-aged children in southwest China: a short-term cohort study

Shi

Wang

Nie

et al. 2018

International Journal of Injury Control and Safety Promotion

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Falls are the top one type in all unintentional injuries. In this study, we aim to explore the epidemiological characteristics of falls and assess the intervention effect. Our research had interviewed 2854 rural children in southwest China. Then, we used School-Family-Individual (SFI) comprehensive education model to conduct an intervention among 1506 children and follow up them for one year. The changes in injury knowledge and incidence rate before and after intervention were compared. We found the fall injury was 37.32% (178/477) and ranked top one in the total injuries. After intervention, the children's fall-injuries-related knowledge was significantly increased by 15.29 percent (P < 0.001). While falls incidence significantly decreased after- intervention (6.24% vs. 3.93%; P < 0.001). From the results we concluded that the falls rate was high and was the prior reason of all injuries. SFI intervention model can effectively reduce the incidence of the fall injury.

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Natural Language Processing Algorithms Outperform ICD Codes in the Development of Fall Injuries Registry

Taseh,

Sasanfar,

Chan

et al. 2024

Preprint

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Background: Standardized registries are commonly built using administrative codes assigned to patient encounters, such as the International Classification of Diseases (ICD) codes. However, fall patients are often coded using subsequent injury codes, such as hip fractures. This necessitates manual screening to ensure the accuracy of data registries. Herein, we aimed to automate the extraction of fall incidents and mechanisms using Natural Language Processing (NLP) and compare this approach with the ICD method. Methods: Clinical notes for patients with fall-induced hip fractures were retrospectively reviewed by medical experts. Fall incidences were detected, annotated, and classified among patients who had fall-induced hip fractures (case group). The control group included patients with hip fractures without any evidence of falls. NLP models were developed using the annotated notes of the study groups to fulfill two separate tasks: fall occurrence detection and fall mechanism classification. The performances of the models were compared using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-score, and area under the ROC curve (AUC-ROC). Results: A total of 1,769 clinical notes were included in the final analysis for the fall occurrence task, and 783 clinical notes were analyzed for the fall mechanism classification task. The highest F1 score using NLP for fall occurrence was 0.97 (specificity=0.96; sensitivity=0.97) and for fall mechanism classification was 0.61 (specificity=0.56; sensitivity=0.62). NLP could detect up to 98% of the fall occurrences and 65% of the fall mechanisms accurately compared to 26% and 12%, respectively, by ICD codes. Conclusion: Our findings showed promising performance with higher accuracy of NLP algorithms compared to the conventional method for detecting fall occurrence and mechanism in developing disease registries using clinical notes. Our approach can be introduced to other registries that are based on large data and are in need of accurate annotation and classification.

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Development of a Falls Registry: A Pilot Study

Cited by 4 publications

References 13 publications

Rollator related pedestrian single accidents and collision events in Sweden

Rollator related pedestrian single accidents and collision events in Sweden

Epidemiologic features and intervention effect of fall injury among rural school-aged children in southwest China: a short-term cohort study

Natural Language Processing Algorithms Outperform ICD Codes in the Development of Fall Injuries Registry

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