Likelihood of Infectious Outcomes Following Infectious Risk Moments During Patient Care—An International Expert Consensus Study and Quantitative Risk Index

2018 
OBJECTIVE To elicit expert consensus on the likelihood of infectious outcomes (patient colonization or infection) following a broad range of infectious risk moments (IRMs) from observations in acute care. DESIGN Expert consensus study using modified Delphi technique. PARTICIPANTS Panel of 40 international experts including nurses, physicians and microbiologists specialized in infectious diseases and infection prevention and control (IPC). METHODS The modified Delphi process consisted of 3 online survey rounds, with feedback of mean ratings and expert comments between rounds. The Delphi survey comprised 52 care scenarios representing observed IRMs organized into 6 sections: hands, gloves, medical devices, mobile objects, invasive procedures, and additional moments. For each scenario, experts indicated the likelihood of both patient colonization and infection on a scale from 0 to 5 (high). Expert ratings were plotted against frequencies of IRMs observed during actual patient care resulting in a risk index. RESULTS Following 3 rounds, consensus was achieved for 92 of 104 items (88.5%). The mean ratings across all scenarios for likelihood of colonization and infection were 2.68 and 2.02, respectively. The likelihood of colonization was rated higher than infection for 48 of 52 scenarios. Ratings were significantly higher for colonization ( P =.001) and infection ( P CONCLUSIONS The design of effective IPC strategies requires the selection of behaviors according to their impact on patient outcomes. The IRM index reported here provides a basis for standardizing and prioritizing targets for quality improvement initiatives, training, and future research in acute health care. Infect Control Hosp Epidemiol 2018;39:280–289
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    24
    References
    6
    Citations
    NaN
    KQI
    []