Skip to main content Accessibility help
×
Home
Hostname: page-component-cf9d5c678-cnwzk Total loading time: 0.318 Render date: 2021-07-28T15:21:01.494Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

Impact of 2018 Changes in National Healthcare Safety Network Surveillance for Clostridium difficile Laboratory-Identified Event Reporting

Published online by Cambridge University Press:  30 April 2018

Alexandre R. Marra
Affiliation:
Office of Clinical Quality, Safety and Performance Improvement, University of Iowa Hospitals and Clinics, Iowa City, Iowa Division of Medical Practice, Hospital Israelita Albert Einstein, Sao Paulo, Brazil
Michael B. Edmond
Affiliation:
Office of Clinical Quality, Safety and Performance Improvement, University of Iowa Hospitals and Clinics, Iowa City, Iowa Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
Bradley A. Ford
Affiliation:
Division of Medical Microbiology, Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa
Loreen A. Herwaldt
Affiliation:
Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
Abdullah R. Algwizani
Affiliation:
Division of Infectious Diseases, Department of Medicine, King Abdulaziz Medical City, Riyadh, Saudi Arabia.
Daniel J. Diekema
Affiliation:
Office of Clinical Quality, Safety and Performance Improvement, University of Iowa Hospitals and Clinics, Iowa City, Iowa Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa Division of Medical Microbiology, Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa
Corresponding
Rights & Permissions[Opens in a new window]

Abstract

Type
Letter to the Editor
Copyright
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved. 

To the Editor—Last year we reported the impact of test method (nucleic acid amplification testing [NAAT] versus toxin enzyme immunoassay [EIA]) on the Clostridium difficile laboratory-identified event (LabID-CDI event) standardized infection ratio (SIR) during a 13-month study period (February 2015–February 2016) at the University of Iowa Hospitals and Clinics (UIHC).Reference Marra, Edmond, Ford, Herwaldt, Algwizani and Diekema 1 Our current testing algorithm involves testing all samples with combined glutamate dehydrogenase (GDH) and toxin EIA (C Diff Quik Chek Complete, Alere, Waltham, MA) followed by testing discordant samples with NAAT (GeneXpert C difficile/EpiPCR, Cepheid, Sunnyvale, CA). Using these data, we found that use of NAAT nearly doubled our hospital-onset LabID-CDI standardized incidence ratio (SIR; 0.5 for EIA versus 0.95 for NAAT). We concluded that the National Health Safety Network (NHSN) risk adjustment for test method failed to adequately account for the increased sensitivity of NAAT at our institution.Reference Marra, Edmond, Ford, Herwaldt, Algwizani and Diekema 1

Since we performed this study, the NHSN modified risk adjustment formulas for healthcare-associated infections, including LabID-CDI events, as part of their “2015 rebaseline.” 2 In addition, the NHSN changed the test results that define a LabID-CDI event. Starting in 2018, “when using a multi-testing methodology . . . the final result of the last test finding which is placed into the patient medical record will determine if the CDI positive laboratory assay definition is met.” 3

We re-examined the dataset we previously used to determine whether the new risk adjustment formula more adequately accounted for test method at UIHC. As outlined in Table 1, we found that the new LabID-CDI SIR model narrowed the difference between toxin EIA and NAAT somewhat but that the SIR was still substantially higher when NAAT was the test method reported (ie, 0.89 for NAAT vs 0.61 for toxin EIA). Although the increase in the detection rate associated with NAAT use varies across centers and regions,Reference Moehring, Lofgren and Anderson 4 our data suggest that centers using NAAT as their only CDI detection test or that use NAAT as the last test in an algorithm are being unfairly “punished” with a higher SIR than if they used toxin EIA as the primary test or as the last test in an algorithm.

TABLE 1 Comparison Between the Previous and the Current Clostridium difficile Infection (CDI) Model of Hospital-Onset (HO) LabID-CDI Event Standardized Infection Ratio (SIR) When Using Enzyme Immunoassay (EIA) Versus Nucleic Acid Amplification Test (NAAT)

NOTE. ED, emergency department; 24 h Obs, 24-hour observation location. UIHC total facility bed size, 761.

a No. of predicted LabID events=exp (β0+β1X1+β2X2+…) × patient days

b No. of predicted (expected) HO CDI LabID events=exp[−7.8983+0.385 (CDI test type=NAAT*)+0.0160 (CDI test type=EIA*)+0.3338*(CO CDI prevalence rate)+0.2164 (bed size >245*)+0.0935 (bed size=101–245 beds*)+0.187 (medical school affiliation=major*)+0.0918 (medical school affiliation=graduate*)] × CDI patient days

c The CDI LabID SIR is calculated by dividing the number of observed HO CDI LabID events by the number of expected events.

d No. of predicted LabID events=exp[−7.8983+0.385*0+0.1606*1+0.3338*(0.43)+0.2164*1+0.0935*0+0.187*1+0.0918*1]*213,404, where EIA=1

e No. of predicted LabID events= exp[−7.8983+0.385*1+0.1606*0+0.3338*(0.92)+0.2164*1+0.0935*0+0.187*1+0.0918*1]*213,404, where NAAT=1 and EIA=0. Assumes that EIA positive samples are all NAAT positive.

f No. of predicted LabID events=exp(β0+β1X1+β2X2+…)*patient days

g No. of predicted (expected) HO CDI LabID events=EXP[−8.9463+0.7339*(CO CDI prevalence rate) −0.1579 (CDI test type=EIA*)+0.1307 (CDI test type=NAAT*)+0.7465 (ICU beds ≥43*)+0.7145 (ICU beds: 20–42*)+0.6261 (ICU beds: 10–19*)+0.4394 (ICU beds: 5–9*)+1.2420 (oncology hospital*)+0.3740 (general hospital)+0.0003 (total facility bed size*)+0.1119 (reporting from ED or 24 h Obs)+0.0331 (teaching hospital*)] × CDI patient days

h The CDI LabID SIR is calculated by dividing the number of observed HO CDI LabID events by the number of expected events.

i No. of predicted LabID events=exp[−8.9463+0.7339*(0.43) −0.1579*1+0.1307*0+0.7465*1+0.7145*0+0.6261*0+0.4394*0+1.2420*0+0.3740*1+0.0003*761+0.1119*1+0.0331*1]*213,404, where EIA=1

j No. of predicted LabID events=EXP [−8.9463+0.7339*(0.92) −0.1579*0+0.1307*1+0.7465*1+0.7145*0+0.6261*0+0.4394*0+1.2420*0+0.3740*1+0.0003*761+0.1119*1+0.0331*1]*213,404, where NAAT=1 and EIA=0. Assumes that EIA-positive samples are all NAAT positive.

Several different approaches can be used to identify CDI, and the diagnostic tests used to identify these patients will vary substantially by healthcare facility.Reference McDonald, Gerding and Johnson 5 More centers have now begun using algorithms for testing that include toxin EIA testing in combination with a more sensitive test (ie, GDH, NAAT, or both) in an effort to reduce costs, to obtain additional information about toxin production (to support clinical management), and to maintain the sensitivity of NAAT testing (to help guide infection control efforts).Reference Bartsch, Umscheid, Nachamkin, Hamilton and Lee 6

We are concerned that the continued inadequacy of risk adjustment by test method, combined with new guidance about the temporal sequence of test result reporting in the event definition, will have unintended adverse consequences. Choice of test approach may be driven primarily by a desire to have LabID-CDI events defined by toxin EIA results rather than NAAT rather than by a desire to choose the test approach that best balances lab resources, clinical management, and infection prevention efforts.

The 2 most common algorithms employ toxin EIA testing at different points in the algorithm. A center that starts with GDH/toxin EIA and then settles discrepant results with NAAT will report both toxin EIA- and NAAT-positive results as events, whereas a center that begins with NAAT and follows each positive NAAT with an EIA will only report toxin EIA-positive results as events. Therefore, the same result combination (NAAT-positive, toxin EIA-negative) will be counted as a LabID-CDI event at one center but not at another. If risk adjustment by test method fails to account for the difference, hospitals will be inclined to switch to an “NAAT first” algorithm so that they can report lower rates and SIRs. While an “NAAT first” algorithm is an adequate diagnostic approach, it is far more expensive than the “GDH/toxin EIA first” algorithm because it requires that laboratories test all samples with the more costly NAAT rather than testing the 10%–15% of samples that are not resolved by GDH/toxin EIA testing.

Finally, the text of the NHSN document refers to “the last test finding which is placed into the patient medical record” rather than the last test performed. 3 Thus, some healthcare providers have suggested that the laboratory enter the toxin EIA results into the medical record after the other results, regardless of when the toxin EIA test was performed in an algorithm. 7 The mere fact that some healthcare providers have suggested this interpretation indicates that facilities could “game the system” and that the definition must be more specific.

In summary, we found that changes in NHSN LabID-CDI event reporting do not adequately risk adjust for test method. Furthermore, changes in the event definition for algorithmic C. difficile testing approaches may further complicate the problem by driving laboratories to select testing approaches based upon the NHSN definition rather than on local laboratory and clinical factors. We propose that CDC address these problems (1) by further improving risk adjustment for hospitals using NAAT-only to detect C. difficile and (2) by allowing all hospitals that use toxin EIA in combination with a more sensitive test (ie, GDH EIA, NAAT, or both) for C. difficile detection to report only toxin EIA-positive results as LabID-CDI events, regardless of the “direction” of the test algorithm.

ACKNOWLEDGMENTS

Financial support: No financial support was provided relevant to this article.

Potential conflicts of interest: All authors report no conflicts of interest relevant to this article.

References

1. Marra, AR, Edmond, MB, Ford, BA, Herwaldt, LA, Algwizani, AR, Diekema, DJ. Failure of risk-adjustment by test method for C. difficile laboratory-identified event reporting. Infect Control Hosp Epidemiol 2017;38:109111.CrossRefGoogle ScholarPubMed
2. The NHSN standardized infection ration (SIR)—a guide to the SIR. Centers for Disease Control and Prevention website. https://www.cdc.gov/nhsn/pdfs/ps-analysis-resources/nhsn-sir-guide.pdf. Updated July 2017. Accessed February 19, 2018.Google Scholar
3. Multi-resistant organism and Clostridium difficile infection (MDRO/CDI) module. Centers for Disease Control and Prevention website. https://www.cdc.gov/nhsn/pdfs/pscmanual/12pscmdro_cdadcurrent.pdf. Accessed February 19, 2018.Google Scholar
4. Moehring, RW, Lofgren, ET, Anderson, DJ. Impact of change to molecular testing for Clostridium difficile infection on healthcare facility associated incidence rates. Infect Control Hosp Epidemiol 2013;34:10551061.CrossRefGoogle ScholarPubMed
5. McDonald, LC, Gerding, DN, Johnson, S, et al. Clinical practice guidelines for Clostridium difficile infection in adults and children: 2017 update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA). Clin Infect Dis 2018;66:e1e48.CrossRefGoogle Scholar
6. Bartsch, SM, Umscheid, CA, Nachamkin, I, Hamilton, K, Lee, BY. Comparing the economic and health benefits of different approaches to diagnosing Clostridium difficile infection. Clin Microbiol Infect 2015;21:19.CrossRefGoogle ScholarPubMed
7. Updated guidance on the diagnosis and reporting of Clostridium difficile. United Kingdom National Health Service website. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/215135/dh_133016. pdf. Accessed March 13, 2018.Google Scholar
You have Access
5
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Impact of 2018 Changes in National Healthcare Safety Network Surveillance for Clostridium difficile Laboratory-Identified Event Reporting
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Impact of 2018 Changes in National Healthcare Safety Network Surveillance for Clostridium difficile Laboratory-Identified Event Reporting
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Impact of 2018 Changes in National Healthcare Safety Network Surveillance for Clostridium difficile Laboratory-Identified Event Reporting
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *