Adherence to a multifactorial fall prevention program following paramedic care: Predictors and impact on falls and health service use. Results from an RCT a priori subgroup analysis

2017 ◽  
Vol 37 (1) ◽  
pp. 54-61 ◽  
Author(s):  
A Stefanie Mikolaizak ◽  
Stephen R Lord ◽  
Anne Tiedemann ◽  
Paul Simpson ◽  
Gideon Caplan ◽  
...  
Author(s):  
Serene S Paul ◽  
Qiang Li ◽  
Lara Harvey ◽  
Therese Carroll ◽  
Annabel Priddis ◽  
...  

IntroductionFalls in older adults are associated with increased healthcare costs. Falls may be prevented or minimised with multifactorial interventions including exercise and behavioural modification. Objectives and ApproachTo describe the reach of the scale-up of Stepping On, a fall prevention program targeting community-dwellers aged 65 years and older in NSW, Australia; and fall-related ambulance service use and fall-related hospitalisations after scale-up. Routinely-collected data on program reach, fall-related ambulance usage and fall-related hospital admissions in NSW residents aged ≥65 years between 2009 and 2015 were compared within Statistical Local Areas prior to and following implementation of Stepping On using multilevel models. ResultsFrom 2009 to 2014 the program was delivered in 1,077 sites to 10,096 people with an average (SD) age of 81.0 (7.2) years. Rates of fall-related ambulance use and hospital admissions per 100-person-years were 1-2 in people aged 66-74, 4-5 in people aged 75-84 and 12-13 in people aged ≥85. These rates increased over time (p<.001). Overall, the interaction between time and program delivery was not significant for fall-related ambulance use or hospital admissions. The time-related increase in fall-related ambulance usage in people aged 75-84 years may have been moderated by Stepping On (RR 0.97, 95% CI 0.93–1.00, p=.045). Conclusion / ImplicationsThere was no indication of either a reduced rate of fall-related ambulance use or hospital admissions across the entire sample. There was a suggestion of a reduction in ambulance call-outs for falls in people aged 75-84. The lack of a detectable impact on fall-related health service usage may be due to the use of routinely collected data not intended for research purposes or inability to remove those who would be ineligible for Stepping On from the data analyses. Increasing the program reach and targeting groups contributing most to health service utilisation may improve program outcomes.


2020 ◽  
Vol 11 (2) ◽  
pp. 98-107 ◽  
Author(s):  
Christina B. Gee ◽  
Gagan S. Khera ◽  
Alyssa T. Poblete ◽  
Barunie Kim ◽  
Syeda Y. Buchwach

2018 ◽  
Author(s):  
Srijesa Khasnabish ◽  
Zoe Burns ◽  
Madeline Couch ◽  
Mary Mullin ◽  
Randall Newmark ◽  
...  

BACKGROUND Data visualization experts have identified core principles to follow when creating visual displays of data that facilitate comprehension. Such principles can be applied to creating effective reports for clinicians that display compliance with quality improvement protocols. A basic tenet of implementation science is continuous monitoring and feedback. Applying best practices for data visualization to reports for clinicians can catalyze implementation and sustainment of new protocols. OBJECTIVE To apply best practices for data visualization to create reports that clinicians find clear and useful. METHODS First, we conducted a systematic literature review to identify best practices for data visualization. We applied these findings and feedback collected via a questionnaire to improve the Fall TIPS Monthly Report (FTMR), which shows compliance with an evidence-based fall prevention program, Fall TIPS (Tailoring Interventions for Patient Safety). This questionnaire was based on the requirements for effective data display suggested by expert Stephen Few. We then evaluated usability of the FTMR using a 15-item Health Information Technology Usability Evaluation Scale (Health-ITUES). Items were rated on a 5-point Likert scale from strongly disagree (1) to strongly agree (5). RESULTS The results of the systematic literature review emphasized that the ideal data display maximizes the information communicated while minimizing the cognitive efforts involved with data interpretation. Factors to consider include selecting the correct type of display (e.g. line vs bar graph) and creating simplistic reports. The qualitative and quantitative evaluations of the original and final FTMR revealed improved perceptions of the visual display of the reports and their usability. Themes that emerged from the staff interviews emphasized the value of simplified reports, meaningful data, and usefulness to clinicians. The mean (SD) rating on the Health-ITUES scale when evaluating the original FTMR was 3.86 (0.19) and increased to 4.29 (0.11) when evaluating the revised FTMR (Mann Whitney U Test, z=-12.25, P<0.001). CONCLUSIONS Best practices identified through a systematic review can be applied to create effective reports for clinician use. The lessons learned from evaluating FTMR perceptions and measuring usability can be applied to creating effective reports for clinician use in the context of other implementation science projects.


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