Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Predicting the Risk of Clostridium Difficile Infections Following an Outpatient Visit KUNTZ

520 views

Published on

Pharmacoepidemiology

  • Be the first to comment

  • Be the first to like this

Predicting the Risk of Clostridium Difficile Infections Following an Outpatient Visit KUNTZ

  1. 1. Predicting The Risk of Clostridium difficile Infections Following an Outpatient Visit: Development And External Validation of a Pragmatic, Prognostic Risk Score Jennifer L. Kuntz, PhD Kaiser Permanente Northwest Center for Health Research May 2, 2012© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  2. 2. Research question How accurately can routinely collected, patient characteristics predict the one-year risk of C. difficile infection (CDI) among patients having a routine outpatient healthcare visit?© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  3. 3. Methods  Retrospective cohort study of KPNW patients with an index outpatient visit between 2005 and 2008  Outcome: Time to first occurrence of CDI during the one year after an index outpatient visit  We modeled the occurrence of CDI using Cox regression and translated regression coefficients into risk score points.  We calculated and plotted the observed one-year CDI risk for each decile of predicted risk.  The risk score was validated and recalibrated using a KPCO cohort and the same patient characteristics.© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  4. 4. Results: Development of the risk score The failure curves show the incidence of CDI during the first year after an outpatient visit among KPNW cohort members. The curves show the observed risk (solid lines) and the predicted risk (dotted lines) of CDI according to deciles of predicted risk.© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  5. 5. Assigning risk score points to patients: Translating the tool into practice at KPNW A 65-year-old male patient in our cohort who was recently hospitalized for 8 days. This patient has diabetes and has recently used a fluoroquinolone. Age 65 (51 pts) + Hospitalization of 8 days (47 pts) + Diabetes (8 pts) + Fluoroquinolone use (27 pts) = 133 points© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  6. 6. Results: Validation of the risk score The failure curves show 0.020 the incidence of CDI during the first year after an outpatient visit 0.015 among KPCO cohortCumulative Risk of Infection members. 0.010 The curves show the observed risk (solid lines) and the predicted 0.005 risk (dotted lines) of CDI according to deciles of predicted risk. 0.000 0 2 4 6 8 10 12© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH Months
  7. 7. Results: Validation of the risk score Each point indicates the predicted risk plotted against the observed risk among patients in each decile of predicted risk.© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  8. 8. Conclusions  We developed a pragmatic risk score which:  Successfully discriminated between patients at the highest and lowest one-year risk for CDI.  Provided predictions which agreed closely with the observed risk for CDI.  Provided important information about the risk for CDI among patients who would likely benefit the most from clinician recognition of this risk.© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
  9. 9. Acknowledgements  Kaiser Permanente Northwest  Funding source Eric S. Johnson, PhD Amanda F. Petrik, MS Sanofi pasteur David H. Smith, PhD Micah L. Thorp, DO, MPH Xiuhai Yang, MS  Kaiser Permanente Colorado Marsha A. Raebel, PharmD Karen A. Glenn  Decision Research Nancy Neil, PhD© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH

×