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Surveillance of nosocomial infections Johnny, Courtesy, Brocolli.

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Presentation on theme: "Surveillance of nosocomial infections Johnny, Courtesy, Brocolli."— Presentation transcript:

1 Surveillance of nosocomial infections Johnny, Courtesy, Brocolli

2 Nosocomial infections (NCI) "nosus" = disease "komeion" = to take care of Infections that occur during hospitalization but are not present nor incubating upon hospital admission

3 Characteristics of hospitals Treatment is main focus Many stakeholders Shift work A lots of data, easily defined cohorts Different patient population Variation of length of stay Vulnerable patients Community vs. hospital


5 The problem of NCI USA –Urinary tract infections: 2.4 per 100 admissions –Pneumonia: 1 case per 100 admissions –Surgical site infections: 2.8 per 100 operations –NCI; one death every 6 th minutes Norway –One of 19 patients have a NCI

6 The problem of NCI Regional hospital, Zimbabwe: –1 of 6 developed SSI 2 referral hospitals, Ethiopia: –38.7% developed SSI –14 of 18 deaths attributed to SSI

7 Cost of NCI England Average cost per NCI: 3.000 pounds Extra days: Urinary tract infections: 6 Pneumonia:12 Surgical site infections: 7

8 Why surveillance? NCI cause of morbidity and mortality One third may be preventable Surveillance = key factor –an infection control measure –overview of the burden and distribution of NCI –allocate preventive resources Surveillance is cost-efficient!!

9 The surveillance loop Event Action Data Information Health care system Surveillance centre Reporting Feedback, recommendations Analysis, interpretation

10 Considerations when creating a surveillance system Goal of the surveillance system (why) Engage the stakeholders (who) Surveillance method (what, how, when) –definition –what to collect –how to collect (operation of system) Available resources

11 I may not have gone where I intended to go, but I think I have ended up where I needed to be Douglas Adams

12 Objectives Reducing infection rates Establishing endemic baseline rates Identifying outbreaks Identifying risk factors Persuading medical personnel Evaluate control measures Satisfying regulators Document quality of care Compare hospitals NCI rates

13 Who All hospitals? All departments? All specialties? Other health institutions?

14 Surveillance of surgical site infections Central adm. Local adm. ICP It- dep. Surgical wards Surgical ward. 2 PatientsLab Service dep. Ministry Of health Directorat Public Health instituteI ….. Stakeholders

15 Surveillance of one or more types of NCI Urinary tract infections Lower respiratory tract infections Surgical site infections Bloodstream infections Conjunctivitis Others…

16 Targeted surveillance Special patient population (surgical, medical, paediatric, intensive) Diagnostic and therapeutic procedures (endoscope, haemodialysis, catheterization, blood transfusion) Specific pathogens (staphylococcus aureus, MRSA, clostridium difficile, norovirus)

17 Variables Administrative data –Id, address, dates of admission, discharge.. Patient related factors: –Age, sex, severity of underlying disease Procedures –Surgery –Devices (e.g. catheters) Treatment, diagnosis –Use of antibiotics ……

18 Stratification points, surgical site infections

19 When? During hospital stay? –Frequency of data collection After discharge? –When and how?

20 How? Two main surveillance methods –incidence –prevalence Variations within these methods

21 Incidence (cohort) studies marching towards outcomes

22 Cohort design PAR = Population at Risk T = Time period PAR Study group Exposed Not exposed NCI Not NCI T NCI Not NCI T Retrospective Prospective

23 Measure Percentage –#NCI / # patients Incidence density –Patient-days as denominator Risk factors RR= risk in patients exposed risk in patients not exposed


25 Positive aspects Provide information on several risk factors Exposure measures before outcome Information on consequences of NCI Can identify outbreak Ongoing attention

26 Limitations Resource demanding Loss of follow-up Seldom NCI Confounding and bias is possible

27 Prevalence Measures number of current NCI Within a defined population at risk At a given time #NCI / #patients at risk *100 Point or period prevalence


29 Use of prevalence surveys Show trends Estimate –distribution of NCI –surveillance accuracy –incidence from prevalence?? –antimicrobial usage patterns Rise awareness

30 Limitations Do not identify causes Duration of NCI affects the prevalence Not very suitable for small institutions Difficult to adjust prevalence

31 Prevalence survey UTI n=6 SSI n=2 Incidence surveillance

32 Define method Identify and review –Protocols used elsewhere e.g. HELICS incidence, Norway's prevalence –Literature Minimum dataset


34 Methodological issues Definitions NCI –Cut off 48 or 72 hours? –Criterias from Centers for Disease Control and Prevention (hospital) –McGeer (long-term care facilities) Risk variables Case finding –Active or passive –By whom? –After discharge? –Prospective or retrospective?

35 Case finding Active: by surveillance personnel Passive: by medical personnel Laboratory or clinical based Source of data –Clinical examinations –Medical records, reports from laboratories –Forms or interviews

36 Ongoing systematic collection? Cohort –Continual? –Periodical? Prevalence –Weekly? –Yearly? –Depends on objectives

37 Precision of estimate

38 Dummy table

39 Implementing surveillance system Administrators responsibility Involvement of stakeholders Identify available resources –Personnel –Money –Time –Equipment –It- solutions Realistic project plan –Organization map –Making forms and letters –It-solutions –Training –Use of data

40 Making surveillance work Support by the administrators Involve local experts Simple Minimize resources required by hospitals Training Feedback and use of data Flexibility

41 Training topics Why surveillance? How? –Definition –Case finding –Case studies –It-solution Use of data


43 Quality controls Define acceptable loss of follow-up Make sure all patients are included Identify infections –Use several sources –Compare data, conduct surveys –Training Clean data –Completeness –Logical values

44 Use of data Prevent NCI Ward audits Present data to hospitals, administrators, MoH, patients Argument for resource allocation Audits for medical personnel Raise awareness


46 Incidence of SSI over time

47 Conclusion Hospital PathogenUnhappy patients Unhappy director Hospital SurveillanceHappy Patients Happy director

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