Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Trends over time in the prevalence of Clostridium difficile within a large community hospital setting: 1997-2007

Hampton, Benjamin (2017) Trends over time in the prevalence of Clostridium difficile within a large community hospital setting: 1997-2007. Master Essay, University of Pittsburgh.

PDF (Corrected Version)
Updated Version

Download (2MB) | Preview
[img] Microsoft Word
Submitted Version

Download (1MB)


Background/Objective: The epidemiology of Clostridium difficile has changed dramatically in recent years, marked by increases in incidence and severity of disease. This growing public health problem affects both community and healthcare acquired cases, leading to increased mortality due to the emergence of hypervirulent strains and antibiotic resistance. The overall objective of this study is to determine trends in C. diff over time in a large community hospital over the twenty years from 1997-2017.
Methods: A retrospective chart review of patients at a 321-bed acute care community hospital in Western Pennsylvania from mid-1997 to the present was conducted. The server database was supplied by Meditech. ICD-9 codes of 8.45, indicating Clostridium difficile Infection (CDI or C. diff infection), either upon admission or during hospitalization were obtained in addition to age, race, gender, length of stay, disposition status, zip code of residence, admission status (nursing home, residence) and payer status for each patient. C. diff infection status was determined by enzyme immunoassay until Dec 2011 and then was switched to current PCR method.
Results: A total of 72, 884 patient encounters were tested for C.diff between 1985 and 1997 and followed forward from 1997-2017 to determine subsequent C. diff testing. Of this cohort, Butler County encounters were selected and those under 18 (3,598) as well as those who were observation encounters (1,072) were excluded, leaving a cohort of 54,789 Butler County Encounters. GIS mapping of C. diff prevalence rates indicated an increasing trend of C. diff over the 20-year period. Overall, there was a higher proportion of outpatients with both a history of C. diff and a subsequent positive C. diff test among encounters over age 65 and among nursing home residents. Analysis confirmed that the relative risk of a patient testing positive for C. diff is higher if there was a previous positive test - especially among those over 65 and nursing home residents. Logistic regression analysis indicated that a prior history of C. diff as the single biggest predictor of a subsequent positive test, controlling for other factors.
Conclusion: There is increasing evidence of C. diff prevalence in Butler County over the 20-year period, probably reflecting a large nursing home population and an overall aging population. Prevention efforts should include increased educational efforts aimed at handwashing and containment and notification of each C. diff case upon diagnosis.


Social Networking:
Share |


Item Type: Other Thesis, Dissertation, or Long Paper (Master Essay)
Status: Published
CreatorsEmailPitt UsernameORCID
Hampton, Benjaminbjh66@pitt.edubjh66
ContributionContributors NameEmailPitt UsernameORCID
Committee ChairTalbott, Evelyneot1@pitt.eduUNSPECIFIEDUNSPECIFIED
Committee MemberLove, JohnJohn.Love@butlerhealthsytem.orgUNSPECIFIEDUNSPECIFIED
Committee MemberRussell, Joannejoanne4@pitt.eduUNSPECIFIEDUNSPECIFIED
Date: 7 August 2017
Date Type: Submission
Submission Date: 2 June 2017
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 93
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Epidemiology
Degree: MPH - Master of Public Health
Thesis Type: Master Essay
Refereed: Yes
Uncontrolled Keywords: Clostridium difficile, community acquired, infectious disease, epidemiology, hospital acquired infections, C. diff, CDI
Date Deposited: 04 Dec 2017 19:59
Last Modified: 01 Jan 2020 06:15


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item