BACKGROUND: Fall injuries (FI) are a priority for public health planning. Syndromic surveillance (SS) is used to detect outbreaks, environmental exposures, and bioterrorism in real time. Since information is gathered on patients, the utility of using this system for FI should be evaluated. METHODS: Strategies to integrate FI medical and SS data were compared using a cohort versus case control (CC) study design. RESULTS: The CC study was accurate 77.7% (57.7-91.3) of the time versus 100% for a cohort design. The CC study design found FI increased for older age groups, female gender, November, and December months. Dates with any freezing temperature had a higher case fatality rate. Repeat acute care visits increased the risk of FI diagnosis by over 6% and trended upward with each visit (R=.333, p<.001). CONCLUSIONS: The CC diagnostic quality of FI were better for age and gender than for area. The CC study found the indicators of increased risk of FI including freezing temperature, repeat acute care visits, older age groups, female gender, November, and December months. A gradient of increasing odds of FI with the number of acute care visits provides proof that community fall prevention programs should focus on those most likely to fall. A CC design of SS data can quickly identify indicators of FI with a lower accuracy but with less cost than a full cohort study, thus providing a method to focus local public health interventions. This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
BACKGROUND: Fall injuries (FI) are a priority for public health planning. Syndromic surveillance (SS) is used to detect outbreaks, environmental exposures, and bioterrorism in real time. Since information is gathered on patients, the utility of using this system for FI should be evaluated. METHODS: Strategies to integrate FI medical and SS data were compared using a cohort versus case control (CC) study design. RESULTS: The CC study was accurate 77.7% (57.7-91.3) of the time versus 100% for a cohort design. The CC study design found FI increased for older age groups, female gender, November, and December months. Dates with any freezing temperature had a higher case fatality rate. Repeat acute care visits increased the risk of FI diagnosis by over 6% and trended upward with each visit (R=.333, p<.001). CONCLUSIONS: The CC diagnostic quality of FI were better for age and gender than for area. The CC study found the indicators of increased risk of FI including freezing temperature, repeat acute care visits, older age groups, female gender, November, and December months. A gradient of increasing odds of FI with the number of acute care visits provides proof that community fall prevention programs should focus on those most likely to fall. A CC design of SS data can quickly identify indicators of FI with a lower accuracy but with less cost than a full cohort study, thus providing a method to focus local public health interventions. This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
Entities:
Keywords:
Accidental Falls; Case Control; Public Health Surveillance; Risk Factors
Authors: Kathryn Gevitz; Robbie Madera; Claire Newbern; José Lojo; Caroline C Johnson Journal: Public Health Rep Date: 2017 Jul/Aug Impact factor: 2.792
Authors: Victor M Castro; Thomas H McCoy; Andrew Cagan; Hannah R Rosenfield; Shawn N Murphy; Susanne E Churchill; Isaac S Kohane; Roy H Perlis Journal: BMJ Date: 2014-10-24