Project Title

Comparing EMR Fall Risk Calculation to Performance-based Assessments

Authors' Affiliations

Regan Bell, Department of Pharmaceutical Sciences, College of Pharmacy, East Tennessee State University, Johnson City, TN. Nomathamsanqa Mgutshini, Department of Pharmaceutical Sciences, College of Pharmacy, East Tennessee State University, Johnson City, TN. Nitin Joshi, Department of Pharmaceutical Sciences, College of Pharmacy, East Tennessee State University, Johnson City, TN. Peter Panus, Department of Pharmaceutical Sciences, College of Pharmacy, East Tennessee State University, Johnson City, TN.

Faculty Sponsor’s Department

Pharmaceutical Sciences

Type

Oral Competitive

Classification of First Author

Pharmacy Student

Project's Category

Healthcare

Abstract Text

Falls are the second leading cause of accidental or unintentional injury deaths worldwide. Many factors contribute to an increased risk of falling, such as age, disease state, and medication use. The purpose of the current investigation was to compare an electronic medical record (EMR) fall risk calculator, the theoretical Timed Up and Go (T-TUG), which utilizes gender, age, BMI, and prescription and OTC drug counts as variables, to other established performance- and paper-based assessments of fall risk. The National Social Life, Health, and Aging Project (NSHAP) Database was used to develop the T-TUG. Data was analyzed from participants in Wave 1 of the Irish Longitudinal Study on Ageing (TILDA) to validate the T-TUG. Performance-based assessments included mean grip force for both dominant and nondominant hands, Timed Up and Go (TUG), and a paper-based assessment titled the Steadiness Index. The latter is a series of 3 questions assessing steadiness when walking, standing, or getting up from a chair. Those participants of the TILDA cohort passing the inclusion criteria were divided into those who reported a fall in the previous year (N=1159) and those reporting no falls (N=4746). Two group comparisons were analyzed by Mann-Whitney U Test (p<0.05) and a Receiver Operator Characteristics (ROC) curve analysis was used to detect separation of fall and non-fall groups. For the Mann-Whitney U test the fall and no fall groups were statistically different for the T-TUG (p<0.001), TUG (p<0.001), dominant and nondominant grip forces (p<0.001), and the steadiness index (p< 0.001). In the fall group, the grip forces were weaker, T-TUG and TUG time longer, and the steadiness index scores lower. For the grip force assessments and steadiness index, lower scores are more likely to be associated with a higher fall risk. In the T-TUG and TUG, longer times are more likely to be associated with a higher fall risk. In the ROC curve analyses, the T-TUG (0.567, p<0.001) demonstrated similar outcomes compared to dominant (AUC=547, p<0.09) and non-dominant (AUC=0.550, p<0.01) grip forces, and the TUG (AUC=0.558, p<0.001). The steadiness index ROC analysis was slightly better than the T-TUG (AUC=0.579, p<0.001). Sensitivity (52-58%) and specificity (50-57%) ranges were equivalent for all performance-based assessments, whereas for the Steadiness Index, the sensitivity (40%) was lower than the specificity (75%). The EMR fall-risk calculator (T-TUG) is a valid triage tool to estimate fall risk in older community dwellers. The EMR calculator has the potential for real-time assessment of patients using current data compared to other performance- and paper-based assessments, which would allow the healthcare team to spend more time with higher fall risk patients.

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Comparing EMR Fall Risk Calculation to Performance-based Assessments

Falls are the second leading cause of accidental or unintentional injury deaths worldwide. Many factors contribute to an increased risk of falling, such as age, disease state, and medication use. The purpose of the current investigation was to compare an electronic medical record (EMR) fall risk calculator, the theoretical Timed Up and Go (T-TUG), which utilizes gender, age, BMI, and prescription and OTC drug counts as variables, to other established performance- and paper-based assessments of fall risk. The National Social Life, Health, and Aging Project (NSHAP) Database was used to develop the T-TUG. Data was analyzed from participants in Wave 1 of the Irish Longitudinal Study on Ageing (TILDA) to validate the T-TUG. Performance-based assessments included mean grip force for both dominant and nondominant hands, Timed Up and Go (TUG), and a paper-based assessment titled the Steadiness Index. The latter is a series of 3 questions assessing steadiness when walking, standing, or getting up from a chair. Those participants of the TILDA cohort passing the inclusion criteria were divided into those who reported a fall in the previous year (N=1159) and those reporting no falls (N=4746). Two group comparisons were analyzed by Mann-Whitney U Test (p<0.05) and a Receiver Operator Characteristics (ROC) curve analysis was used to detect separation of fall and non-fall groups. For the Mann-Whitney U test the fall and no fall groups were statistically different for the T-TUG (p<0.001), TUG (p<0.001), dominant and nondominant grip forces (p<0.001), and the steadiness index (p< 0.001). In the fall group, the grip forces were weaker, T-TUG and TUG time longer, and the steadiness index scores lower. For the grip force assessments and steadiness index, lower scores are more likely to be associated with a higher fall risk. In the T-TUG and TUG, longer times are more likely to be associated with a higher fall risk. In the ROC curve analyses, the T-TUG (0.567, p<0.001) demonstrated similar outcomes compared to dominant (AUC=547, p<0.09) and non-dominant (AUC=0.550, p<0.01) grip forces, and the TUG (AUC=0.558, p<0.001). The steadiness index ROC analysis was slightly better than the T-TUG (AUC=0.579, p<0.001). Sensitivity (52-58%) and specificity (50-57%) ranges were equivalent for all performance-based assessments, whereas for the Steadiness Index, the sensitivity (40%) was lower than the specificity (75%). The EMR fall-risk calculator (T-TUG) is a valid triage tool to estimate fall risk in older community dwellers. The EMR calculator has the potential for real-time assessment of patients using current data compared to other performance- and paper-based assessments, which would allow the healthcare team to spend more time with higher fall risk patients.

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