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To assess the effect of multiple sources of bias on state- and hospital-specific National Healthcare Safety Network (NHSN) laboratory-identified Clostridium difficile infection (CDI) rates.
A total of 124 New York hospitals in 2010.
New York NHSN CDI events from audited hospitals were matched to New York hospital discharge billing records to obtain additional information on patient age, length of stay, and previous hospital discharges. “Corrected” hospital-onset (HO) CDI rates were calculated after (1) correcting inaccurate case reporting found during audits, (2) incorporating knowledge of laboratory results from outside hospitals, (3) excluding days when patients were not at risk from the denominator of the rates, and (4) adjusting for patient age. Data sets were simulated with each of these sources of bias reintroduced individually and combined. The simulated rates were compared with the corrected rates. Performance (ie, better, worse, or average compared with the state average) was categorized, and misclassification compared with the corrected data set was measured.
Counting days patients were not at risk in the denominator reduced the state HO rate by 45% and resulted in 8% misclassification. Age adjustment and reporting errors also shifted rates (7% and 6% misclassification, respectively).
Changing the NHSN protocol to require reporting of age-stratified patient-days and adjusting for patient-days at risk would improve comparability of rates across hospitals. Further research is needed to validate the risk-adjustment model before these data should be used as hospital performance measures.
To determine whether the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN) laboratory-identified (LabID) event reporting module for Clostridium difficile infection (CDI) is an adequate proxy measure of clinical CDI for public reporting purposes by comparing the 2 surveillance methods.
Thirty New York State acute care hospitals.
Six months of data were collected by 30 facilities using a clinical infection surveillance definition while also submitting the NHSN LabID event for CDI. The data sets were matched and compared to determine whether the assigned clinical case status matched the LabID case status. A subset of mismatches was evaluated further, and reasons for the mismatches were quantified. Infection rates determined using the 2 definitions were compared.
A total of 3,301 CDI cases were reported. Analysis of the original data yielded a 67.3% (2,223/3,301) overall case status match. After review and validation, there was 81.3% (2,683/3,301) agreement. The most common reason for disagreement (54.9%) occurred because the symptom onset was less than 48 hours after admission but the positive specimen was collected on hospital day 4 or later. The NHSN LabID hospital onset rate was 29% higher than the corresponding clinical rate and was generally consistent across all hospitals.
Use of the NHSN LabID event minimizes the burden of surveillance and standardizes the process. With a greater than 80% match between the NHSN LabID event data and the clinical infection surveillance data, the New York State Department of Health made the decision to use the NHSN LabID event CDI data for public reporting purposes.
To efficiently validate the accuracy of surgical site infection (SSI) data reported to the National Healthcare Safety Network (NHSN) by New York State (NYS) hospitals.
176 NYS hospitals.
NYS Department of Health staff validated the data reported to NHSN by review of a stratified sample of medical records from each hospital. The four strata were (1) SSIs reported to NHSN; (2) records with an indication of infection from diagnosis codes in administrative data but not reported to NHSN as SSIs; (3) records with discordant procedure codes in NHSN and state data sets; (4) records not in the other three strata.
A total of 7,059 surgical charts (6% of the procedures reported by hospitals) were reviewed. In stratum 1, 7% of reported SSIs did not meet the criteria for inclusion in NHSN and were subsequently removed. In stratum 2, 24% of records indicated missed SSIs not reported to NHSN, whereas in strata 3 and 4, only 1% of records indicated missed SSIs; these SSIs were subsequently added to NHSN. Also, in stratum 3, 75% of records were not coded for the correct NHSN procedure. Errors were highest for colon data; the NYS colon SSI rate increased by 7.5% as a result of hospital audits.
Audits are vital for ensuring the accuracy of hospital-acquired infection (HAI) data so that hospital HAI rates can be fairly compared. Use of administrative data increased the efficiency of identifying problems in hospitals' SSI surveillance that caused SSIs to be unreported and caused errors in denominator data.
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