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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedKaravite DJ, Miller MW, Ramos MJ
User testing an information foraging tool for ambulatory surgical site infection surveillance.
Surveillance for surgical site infections (SSIs) after ambulatory surgery in children requires a detailed manual chart review to assess criteria defined by the National Health and Safety Network. Electronic health records (EHRs) impose an inefficient search process. Using text mining and business intelligence software, the authors developed an information foraging application, the SSI Workbench, to visually present which postsurgical encounters included SSI-related terms and synonyms, antibiotic, and culture orders. This study compares the Workbench and EHR.
AHRQ-funded; HS020921.
Citation: Karavite DJ, Miller MW, Ramos MJ .
User testing an information foraging tool for ambulatory surgical site infection surveillance.
Appl Clin Inform 2018 Oct;9(4):791-802. doi: 10.1055/s-0038-1675179..
Keywords: Surgery, Ambulatory Care and Surgery, Children/Adolescents, Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare-Associated Infections (HAIs), Patient Safety
Grundmeier RW, Xiao R, Ross RK
Grundmeier RW, Xiao R, Ross RK, Ramos MJ, Karavite DJ, Michel JJ, Gerber JS, et al. Identifying surgical site infections in electronic health data using predictive models,.
The objective of this study was to prospectively derive and validate a prediction rule for detecting cases warranting investigation for surgical site infections (SSI) after ambulatory surgery. The investigators concluded that electronic health record data can facilitate SSI surveillance with adequate sensitivity and positive predictive value.
AHRQ-funded; HS020921.
Citation: Grundmeier RW, Xiao R, Ross RK .
Grundmeier RW, Xiao R, Ross RK, Ramos MJ, Karavite DJ, Michel JJ, Gerber JS, et al. Identifying surgical site infections in electronic health data using predictive models,.
J Am Med Inform Assoc 2018 Sep;25(9):1160-66. doi: 10.1093/jamia/ocy075..
Keywords: Healthcare-Associated Infections (HAIs), Injuries and Wounds, Surgery, Electronic Health Records (EHRs), Health Information Technology (HIT), Risk, Patient Safety, Adverse Events, Ambulatory Care and Surgery