TY - JOUR
T1 - Identification of medicare recipients at highest risk for clostridium difficile infection in the US by population attributable risk analysis
AU - Dubberke, Erik R.
AU - Olsen, Margaret A.
AU - Stwalley, Dustin
AU - Kelly, Ciarán P.
AU - Gerding, Dale N.
AU - Young-Xu, Yinong
AU - Mahé, Cedric
N1 - Publisher Copyright:
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - Background Population attributable risk percent (PAR%) is an epidemiological tool that provides an estimate of the percent reduction in total disease burden if that disease could be entirely eliminated among a subpopulation. As such, PAR% is used to efficiently target prevention interventions. Due to significant limitations in current Clostridium difficile Infection (CDI) prevention practices and the development of new approaches to prevent CDI, such as vaccination, we determined the PAR% for CDI in various subpopulations in the Medicare 5% random sample. Methods This was a retrospective cohort study using the 2009 Medicare 5% random sample. Comorbidities, infections, and healthcare exposures during the 12 months prior to CDI were identified. CDI incidence and PAR% were calculated for each condition/exposure. Easy to identify subpopulations that could be targeted from prevention interventions were identified based on PAR%. Findings There were 1,465,927 Medicare beneficiaries with 9,401 CDI cases for an incidence of 677/ 100,000 persons. Subpopulations representing less than 15% of the entire population and with a PAR% ô 30% were identified. These included deficiency anemia (PAR% = 37.9%), congestive heart failure (PAR% = 30.2%), fluid and electrolyte disorders (PAR% = 29.6%), urinary tract infections (PAR% = 40.5%), pneumonia (PAR% = 35.2%), emergent hospitalization (PAR% = 48.5%) and invasive procedures (PAR% = 38.9%). Stratification by age and hospital exposures indicates hospital exposures are more strongly associated with CDI than age. Significance Small and identifiable subpopulations that account for relatively large proportions of CDI cases in the elderly were identified. These data can be used to target specific subpopulations for CDI prevention interventions.
AB - Background Population attributable risk percent (PAR%) is an epidemiological tool that provides an estimate of the percent reduction in total disease burden if that disease could be entirely eliminated among a subpopulation. As such, PAR% is used to efficiently target prevention interventions. Due to significant limitations in current Clostridium difficile Infection (CDI) prevention practices and the development of new approaches to prevent CDI, such as vaccination, we determined the PAR% for CDI in various subpopulations in the Medicare 5% random sample. Methods This was a retrospective cohort study using the 2009 Medicare 5% random sample. Comorbidities, infections, and healthcare exposures during the 12 months prior to CDI were identified. CDI incidence and PAR% were calculated for each condition/exposure. Easy to identify subpopulations that could be targeted from prevention interventions were identified based on PAR%. Findings There were 1,465,927 Medicare beneficiaries with 9,401 CDI cases for an incidence of 677/ 100,000 persons. Subpopulations representing less than 15% of the entire population and with a PAR% ô 30% were identified. These included deficiency anemia (PAR% = 37.9%), congestive heart failure (PAR% = 30.2%), fluid and electrolyte disorders (PAR% = 29.6%), urinary tract infections (PAR% = 40.5%), pneumonia (PAR% = 35.2%), emergent hospitalization (PAR% = 48.5%) and invasive procedures (PAR% = 38.9%). Stratification by age and hospital exposures indicates hospital exposures are more strongly associated with CDI than age. Significance Small and identifiable subpopulations that account for relatively large proportions of CDI cases in the elderly were identified. These data can be used to target specific subpopulations for CDI prevention interventions.
UR - https://www.scopus.com/pages/publications/84959144376
U2 - 10.1371/journal.pone.0146822
DO - 10.1371/journal.pone.0146822
M3 - Article
C2 - 26859403
AN - SCOPUS:84959144376
SN - 1932-6203
VL - 11
JO - PloS one
JF - PloS one
IS - 2
M1 - e0146822
ER -