Life In The Slower Lane

Here is the structured PICO analysis for the thirty-fourth article you uploaded:

✅ Full Title (verbatim and exact):

“Evaluation of the Predictive Accuracy of the interRAI Falls Clinical Assessment Protocol, Scott Fall Risk Screen, and a Supplementary Falls Risk Assessment Tool Used in Residential Long-Term Care: A Retrospective Cohort Study”Norman KJ, Hirdes JPCanadian Journal on Aging (2020); 39(4):521–532DOI: https://doi.org/10.1017/S0714980820000021

📄 Type of Article:

Retrospective cohort study

🔍 PICO Analysis:

Population:

• 1,553 residents of 18 residential long-term care (LTC) homes across Nova Scotia and New Brunswick, CanadaParticipants had interRAI LTCF or MDS 2.0 assessments between March 2015 and September 2016Average age: 82.1 years; 68.7% female27.2% experienced at least one fall within 90 days post-assessment 

Intervention:

Comparison of three fall risk assessment (FRA) tools:

1. interRAI Falls Clinical Assessment Protocol (CAP)

   • Categorises residents based on fall history (low/no = 0 falls, moderate = 1 fall, high = ≥2 falls)

2. Scott Fall Risk Screen (SFRS)

• Uses 11 risk factors, assigns weighted points; score ≥7 = high risk

Supplementary Fall Risk Tool (modified for Nova Scotia LTC policy)

• 14 equally weighted risk factors; score >10 = high riskThe interRAI CAP was the only tool integrated within standard LTCF assessment processes 

Comparator:

• The three tools were compared against each other for their ability to predict falls over the subsequent 90 daysNo external comparator group

Outcome:

1. Person-centred outcomes:

• Fall incidence in 90 days post-assessment

  • Of 1,553 residents, 422 fell, with 81 falling ≥3 timesinterRAI CAP high-risk residents had the highest actual fall rate: 75.4% fell in the follow-up periodSFRS and Supplementary FRA had lower discriminatory power, classifying more residents as high risk but with lower fall conversion rates 

2. Process outcomes:

• Accuracy metrics:

  • interRAI CAP: c-statistic = 0.673, sensitivity = 0.502, specificity = 0.834Supplementary FRA: c-statistic = 0.529, sensitivity = 0.943, specificity = 0.111SFRS: c-statistic = 0.609, sensitivity = 0.571, specificity = 0.615

  Augmenting interRAI CAP with chronic disease diagnoses (e.g. Parkinson’s, Alzheimer’s, COPD) increased accuracy to c = 0.749 

3. Health system outcomes:

• Tools with high sensitivity but low specificity (e.g. Supplementary FRA) may over-trigger interventions, increasing costs and workload without clear benefitinterRAI CAP offered more targeted identification, supporting better resource allocation and avoiding overuse of fall prevention resourcesAuthors argue that additional fall risk tools may not enhance predictive accuracy and could lead to unnecessary burden 

Summary Conclusion:

This retrospective cohort study evaluated three fall risk screening tools used in Canadian LTC facilities. The interRAI Falls CAP outperformed both the Scott Fall Risk Screen and a Supplementary FRA Tool, offering better specificity and overall predictive accuracy. A history of falls was the strongest predictor of future falls. Although all tools have limitations, the interRAI CAP—especially when adjusted for chronic disease covariates—showed the most promise for efficient and effective fall risk screening, reducing false positives and unnecessary intervention. The findings suggest that clinical judgement should complement standardised screening, particularly when fall history is absent.