Infection Control & Hospital Epidemiology


hospitalizations within the same or following month (POA or non-POA). We aggregated hospital annual SSI rates and per- formed reliability adjustment to account for differential surgical volumes across hospitals using random-effects logistic regression.6 We examined the agreement of hospital rankings using Ken-


dall’s τ coefficient, which tests the ordinal association between 2 measures, and we compared quartiles of hospital rankings using billing or NHSN data. We considered a τ of<0.40 as poor agreement, 0.41–0.75 as fair–good agreement, and>0.75 as excellent agreement. We explored the association of hospital characteristics with a ≥2


quartile difference in NHSN versus claims-based rankings using a generalized linear mixed model. This model included the following data: region, urbanicity, number of beds, teaching status, nurse-to- patient ratio, hospital ownership, percentage of admissions covered by Medicaid or Medicare, and colon surgery volume. Analyses were completed using SAS version 9.4 software (SAS


Institute, Cary, NC) and R version 3.3.1 software (r-project.org). We considered P values<.05 to be significant. The Harvard Pil- grim Health Care Institutional Review Board approved this study.


Results


The study cohort included 6.2 million adult admissions from 2012 to 2014 in 155 hospitals. The hospital characteristics are shown in Table 1. There were 63,541 colon surgeries (median, 116 per hos- pital-year; interquartile range [IQR], 64–195) with 7,197 claims- based SSIs (median, 12 per hospital-year; IQR, 5–23) and 3,283 NHSN-reported SSIs (median, 5 per hospital-year; IQR, 1–10). Hospital annual SSI rates were higher with claims versus


NHSN data (median, 10.5% vs 4.3%). There was poor agreement between hospital claims versus NHSN-based SSI rankings (Ken- dall’s τ, 0.21). Over the 3-year period, 64 of 99 hospitals (65%) in the best quartile by claims data were ranked in worse quartiles by NHSN data; similarly, 60 of 99 hospitals (61%) in the worst quartile by claims data were ranked in better quartiles by NHSN data (Figure 1). On multivariate analysis, the only hospital characteristics


associated with a difference of ≥2 ranked quartiles between claims versus NHSN rates were higher Medicaid percentage (P=.041) and southern region (P=.038).


Discussion


higher sensitivity compared to NHSN surveillance.5 However, claims have lower specificity and may also capture complications, such as cellulitis or suture abscesses, that would not meet NHSN criteria. Other limitations of claims data include variable coding practices, changes in response to reimbursement policies, and misclassification of present-on-admission status.1,7 Prospective NHSN SSI surveillance is more rigorous but can also incorporate subjective criteria and may miss SSIs clinically diagnosed at the bedside.5,8 Prior work suggests that routine surveillance can be enhanced using claims and/or inpatient antibiotic prescribing data.9


We found that claims-based rates of SSI-colon were significantly higher than NHSN-based rates. There was poor agreement between hospital rankings derived from the 2 data sources, with>50% of hospitals ranked in the best or worst quartile by claims falling into more moderate quartiles by NHSN data. The higher SSI rates seen with claims data likely reflects their


Table 1. Study Hospital Characteristics Characteristic


Region


Northeastern United States Southern United States Western United States Midwestern United States


Location


Metropolitan Micropolitan Rural


No. of beds <100


100–399 >400


Ownership type For profit


Not for profit Public


Teaching statusa Graduate teaching Major teaching Minor teaching Nonteaching


Median % of patients with Medicare (IQR) Median % of patients with Medicaid (IQR)


139 (90) 15 (10) 1 (1)


15 (10) 102 (66) 38 (25)


45 (29) 104 (67) 6 (4)


26 (17) 31 (20) 18 (12) 80 (52)


50.4 (43.4–60.9) 19.0 (12.3–26.0)


Note. IQR, interquartile range. aTeaching status was classified as per the American Hospital Association survey: major


teaching hospitals (those that are members of the Council of Teaching Hospitals [COTH]), graduate teaching hospitals (non-COTH members with a residency training program approved by the Accreditation Council for Graduate Medical Education), minor teaching hospitals (non-COTH members with a medical school affiliation reported to the American Medical Association), and nonteaching hospitals (all other institutions).


Automating surveillance using electronic data could also reduce interobserver variation and provide more precise HAI rates.10 Hospitals in the southern United States tended to have more discrepancies in SSI rankings, suggesting regional differences in coding or hospital-based surveillance methods. Caring for more Medicaid patients was also associated with ranking discordance, perhaps reflecting differential billing practices or fewer resources to devote to infection surveillance and prevention in hospitals caring for low-income patients. Our study has several limitations. Our findings on a single


outcome in a subset of US acute-care hospitals may not be gen- eralizable. However, the hospitals were diverse with respect to region, size, and teaching status, and the relatively high rates of SSI-colon compared to other HAIs may mitigate the contribution


88 (57) 51 (33) 16 (10) 0 (0)


209


Study Hospitals (n=155), No. (%)


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