Related Experiment Video
Updated: Jul 15, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
Published on: February 8, 2019
Innovative approaches to analysing aged care falls incident data: international classification for patient safety
Karla Seaman1, Isabelle Meulenbroeks1, Amy Nguyen1
1Australian Institute of Health Innovation, Macquarie University, Level 6 75 Talavera Road, North Ryde, New South Wales 2109, Australia.
Abstract:
Falls in residential aged care facilities (RACFs) are common and can have significant health consequences. Understanding how and why falls occur in RACFs is an essential step to design targeted fall prevention and intervention programmes; however, little is known about falls' mechanisms in RACFs. This study aims to use international incident classification systems and novel analysis techniques to describe factors that contribute to falls requiring hospitalization in RACFs. Retrospective data of falls assessed by nurses as requiring hospitalization from 429 residents in 22 Australian RACFs in 2019 were used. Data were reviewed using a modified version of the International Classification for Patient Safety (ICPS), which categorizes patient safety into incident types and contributing factors using a three-tiered structure. The ICPS codes were summarized using the descriptive statistics. The association between assigned ICPS codes were analysed using correspondence analysis. Six hundred and three falls assessed as requiring hospitalization were classified into 659 incident types, with the most common incident type being 'patient incidents' (injury sustained/adverse effect in the health care system) (603, 91.5%) at Level 1, 'falls' (601, 91.2%) at Level 2, and 'falls involving bedrooms' (214, 32.5%) at Level 3. The 603 falls had 1082 contributing factors, with the most common contributing factor being 'patient factors' (events affected by factors associated with the patient) (982, 90.8%) at Level 1, 'patient not elsewhere classified' (characteristics of the patient contributed to the incident not classified elsewhere) (571, 52.8%) at Level 2, and 'loss of balance' (361, 33.4%) at Level 3. In a correspondence analysis, three dimensions were responsible for 81.2% of the variation in falls incidents and environmental and organizational factors were important factors contributing to falls. The application of the ICPS demonstrated that personal factors (e.g. pre-existing physical and psychological health or impairment) were the most common contributing factors to falls assessed as requiring hospitalization, while the correspondence analysis highlighted the role of environmental and organizational factors. The results signal the need for more research into multifactorial falls prevention interventions in RACFs.
More Related Videos
11:21Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
06:52Assessment of Dependence in Activities of Daily Living Among Older Patients in an Acute Care Unit
Published on: September 30, 2020
Related Concept Videos
Documentation in Long-Term and Home Healthcare Setting
Long-Term Care Facilities
Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Nursing Clinical Information System
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
The Scientific Method in Nursing Process
When using research findings to change practice, one must understand the process used to guide a study. The scientific method is a systematic, step-by-step process that supports the data's validity, reliability, and generalizability. As a result, findings can be...
Cancer Survival Analysis