Assuring Data Quality

1. Assuring Data Quality Jennie Wilson Programme Leader – SSI Surveillance Dept. of Healthcare-Associated Infection & Antimicrobial Resistance, Health Protection Agency

2. 2005 Hip prosthesis: inter-country rate (cumulative incidence) 2005 Hip prosthesis: inter-country rate (incidence density)

3. External benchmarks • External benchmarks are a powerful driver for effecting change, but require • standardised data collection methods • standardised analysis • high data quality • central co-ordination Gaynes 1997

4. Why is data quality so important locally? • Do you know whether action is required? • real problems? • poorly collected data?

5. SSI SurveillanceBasic methodology • Targeted at categories of clinically similar operative procedures • Data collection form completed for each relevant operation (denominator) • Systematic (active) surveillance after each operation to detect infections (numerator)

6. Methods of identifying patientswith SSI (numerator) • Active • Designated, trained personnel, use a variety of data sources to determine whether an HAI has occurred • Sensitivity = 85-100% • Passive • HAI identified and reported by people other than designated, trained personnel. Requires fewer people but unreliable, definition not applied consistently • Sensitivity: 14-34% (Perl, 1998)

7. Surveillance methods:Sensitivity of case finding • Lab-based phone • Sensitivity 36% • 1.2hrs / 100 beds / week • Temperature / treatment chart • Sensitivity 65% • 6.5 hours / 100 beds / week • Lab-based, ward liaison • Sensitivity 76% • 6.4 hours / 100 beds / week Glenister et al 1992

8. Systematic surveillance for SSI Lab-based ward liaison • 1. Visit ward/patient 3 times per week • discuss patients with ward staff • check medical / nursing records • check temperature / treatment charts • 2. Review microbiology reports daily • identify positive surgical site reports

9. Definitions of surgical site infection (CDC) • Superficial incisional • involves only skin or subcutaneous tissue • occurs within 30 days of surgery • Deep incisional • involves fascial or muscle layers • occurs within 30 days, implants within 1 year • Organ/space • part of anatomy opened / manipulated • infection appears related to surgery • occurs within 30 days, implants within 1 year

10. Superficial Incisional Infection • Must meet one of the following criteria: • 1. Purulent drainage from superficial incision • 2. Culture of organisms from fluid/tissue • 3. At least 1 symptom of inflammation (pain, tenderness, localised swelling, redness, heat) and incision deliberately opened to manage infection • 4.Clinicians diagnosis of superficial SSI

11. Deep Incisional Infection • Must meet one of the following criteria: • Purulent drainage from deep incision • 2. Deep incision dehisces / deliberately opened and patient has 1 symptom :fever, localised pain/tenderness • 3. Abscess / other evidence of infection in deep incision:re-operation / histopathology / radiology • 4. Clinicians diagnosis of deep infection

12. Identifying SSI • Review patients systematically whilst they are in hospital • Do not rely on reviewing case-notes after discharge to find SSIs • If a patient is prescribed antibiotics do not assume these are for SSI – check with clinician • Check significance of positive microbiology cultures • Make sure any SSI identified post-discharge also meets the definition

13. Is this an SSI…….? • Nursing record states: • ‘Wound oozing ++ from small lower section. Pressure dressing applied’ • Oozing what: • Clear (serous) fluid, blood, pus? • What was the condition of the suture line? • Red, swollen, dehisced • Was a wound swab taken, if so why?

14. Criteria for SSI checklistWeblink data entry (SSISS)

15. Validation studies • Mannien et al 2007: PREZIES, Netherlands • Reviewed 859 medical charts; 149 SSI • Validation team = ‘gold standard’ • PPV = 0.97; NPV = 0.99 McCoubrey et al 2005: SSI surveillance, Scotland • 91 SSI reported validated by case note review • 10/27 hospitals criteria not recorded • PPV 94.6% (95%CL 87.9 – 98.2); NPV 99.4 (95% CL 98.3 – 99.9) (assuming not recorded data valid)

16. NNIS SSI ‘Risk Index’ • Each operation is scored, and results stratified, using 3 major risk factors associated with SSI*: • ASA pre-operative assessment score • Wound class • Duration of surgery (T time) • Score between 0 and 3 • *Culver et al (1991)

17. ASA classification of physical illness 1: normal healthy patient 2: mild systemic disease 3: severe systemic disease 4: incapacitating systemic disease 5: moribund, little chance of survival Wound classification Clean: no signs of infection, no body ‘tracts’ Clean-contaminated: body tract entered Contaminated: spillage form GIT, inflammation, open trauma Dirty: pus, perforated viscera, delayed open trauma, faecal contamination Changed by pre-op and intra-op events Risk Index factors

18. T timeassociation between p value and cut point for duration of operation (abdominal hysterectomy) Leong et al 2006

19. Trend in rate of SSI by Risk index group

20. Effect of indirect standardisation on crude rates of SSI (vascular surgery)

21. Percentiles 90th 75th 50th 25th 10th Distribution of the incidence of surgical site infection by category of surgical procedures October 1997 to December 2003 Source: SSI Surveillance Service, CDSC

22. Crude rates of SWI for vascular surgery (95% CL) by hospital 90th percentile 50th percentile Data to December 2001

23. Funnel plots used to account for variation in sample size Cumulative incidence Total hip prosthesis, January 2000 – March 2005

24. Cumulative incidence Incidence density

25. Funnel plots to adjust for variation in sample size and length of post-op stay Incidence density/ 1000 post-op in-patient days

26. Length of stay in elective surgery is reducing

27. Proportion of SSI detectedpre & post discharge Barrett et al 2000

28. Post-discharge surveillance study Barrett et al 2000 • Post-discharge surveillance method • Resources +++ - data collection, informing/contacting patients • General practitioners/district nurses – poor response rate to questionnaire • Patients – better response; +/- reliability • Sensitivity of case-finding • active vs. passive surveillance • reliability

29. Response rate to PDS patient questionnaires Response rate affected by ethnic group and age n = 6159 Barrett et al 2000