Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-30T20:11:10.694Z Has data issue: false hasContentIssue false

Variable Case Detection and Many Unreported Cases of Surgical-Site Infection Following Colon Surgery and Abdominal Hysterectomy in a Statewide Validation

Published online by Cambridge University Press:  31 July 2017

Michael S. Calderwood*
Affiliation:
Section of Infectious Disease and International Health, Dartmouth Hitchcock Medical Center, Lebanon, New Hampshire
Susan S. Huang
Affiliation:
Division of Infectious Diseases, University of California Irvine School of Medicine, Orange, California
Vicki Keller
Affiliation:
Healthcare-Associated Infections Program, California Department of Public Health, Richmond, California
Christina B. Bruce
Affiliation:
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
N. Neely Kazerouni
Affiliation:
Healthcare-Associated Infections Program, California Department of Public Health, Richmond, California
Lynn Janssen
Affiliation:
Healthcare-Associated Infections Program, California Department of Public Health, Richmond, California
*
Address correspondence to Michael S. Calderwood, MD, MPH, Dartmouth-Hitchcock Medical Center, Section of Infectious Disease and International Health, One Medical Center Drive, Suite 5C, Lebanon, NH 03756 ([email protected]).

Abstract

OBJECTIVE

To assess hospital surgical-site infection (SSI) identification and reporting following colon surgery and abdominal hysterectomy via a statewide external validation

METHODS

Infection preventionists (IPs) from the California Department of Public Health (CDPH) performed on-site SSI validation for surgical procedures performed in hospitals that voluntarily participated. Validation involved chart review of SSI cases previously reported by hospitals plus review of patient records flagged for review by claims codes suggestive of SSI. We assessed the sensitivity of traditional surveillance and the added benefit of claims-based surveillance. We also evaluated the positive predictive value of claims-based surveillance (ie, workload efficiency).

RESULTS

Upon validation review, CDPH IPs identified 239 SSIs following colon surgery at 42 hospitals and 76 SSIs following abdominal hysterectomy at 34 hospitals. For colon surgery, traditional surveillance had a sensitivity of 50% (47% for deep incisional or organ/space [DI/OS] SSI), compared to 84% (88% for DI/OS SSI) for claims-based surveillance. For abdominal hysterectomy, traditional surveillance had a sensitivity of 68% (67% for DI/OS SSI) compared to 74% (78% for DI/OS SSI) for claims-based surveillance. Claims-based surveillance was also efficient, with 1 SSI identified for every 2 patients flagged for review who had undergone abdominal hysterectomy and for every 2.6 patients flagged for review who had undergone colon surgery. Overall, CDPH identified previously unreported SSIs in 74% of validation hospitals performing colon surgery and 35% of validation hospitals performing abdominal hysterectomy.

CONCLUSIONS

Claims-based surveillance is a standardized approach that hospitals can use to augment traditional surveillance methods and health departments can use for external validation.

Infect Control Hosp Epidemiol 2017;38:1091–1097

Type
Original Articles
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Notice on requirements for reporting surgical site infections. California Department of Public Health website. http://www.cdph.ca.gov/programs/hai/Documents/LNC-AFL-11-32.pdf. Published 2011. Accessed February 15, 2017.Google Scholar
2. Department of Health and Human Services, Centers for Medicare & Medicaid Services. Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and FY 2012 Rates. Federal Register 2011;76:5147651846.Google Scholar
3. Medicare. Hospital Compare website. https://www.medicare.gov/hospitalcompare/search.html. Updated 2017. Accessed February 15, 2017.Google Scholar
4. Hospital value-based purchasing. Centers for Medicare and Medicaid Services website. https://www.cms.gov/Medicare/Quality-initiatives-patient-assessment-instruments/hospital-value-based-purchasing/index.html. Updated 2017. Accessed February 15, 2017.Google Scholar
5. Hospital-acquired condition reduction program. Centers for Medicare and Medicaid Services website. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/HAC-Reduction-Program.html. Updated 2017. Accessed February 15, 2017.Google Scholar
6. Department of Health and Human Services, Centers for Medicare & Medicaid Services. . Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long Term Care Hospital Prospective Payment System and Proposed Fiscal Year 2014 Rates. Federal Register 2013;78:2748527823.Google Scholar
7. Centers for Disease Control and Prevention National Healthcare Safety Network website. http://www.cdc.gov/nhsn/. Updated 2017. Accessed February 15, 2017.Google Scholar
8. Avato, JL, Lai, KK. Impact of postdischarge surveillance on surgical-site infection rates for coronary artery bypass procedures. Infect Control Hosp Epidemiol 2002;23:364367.CrossRefGoogle ScholarPubMed
9. Manien, J, Willie, JC, Snoeren, RL, van den Hof, S. Impact of postdischarge surveillance on surgical site infection rates for several surgical procedures: results from the nosocomial surveillance network in The Netherlands. Infect Control Hosp Epidemiol 2006;27:809816.Google Scholar
10. Ming, DY, Chen, LF, Miller, BA, Anderson, DJ. The impact of depth of infection and postdischarge surveillance on rate of surgical-site infections in a network of community hospitals. Infect Control Hosp Epidemiol 2012;33:276282.CrossRefGoogle Scholar
11. Koek, MB, Willie, JC, Isken, MR, Voss, A, van Benthem, BH. Post-discharge surveillance (PDS) for surgical site infections: a good method is more important than a long duration. Euro Surveillance 2015;20:21042.Google Scholar
12. Huang, SS, Placzek, H, Livingston, J, et al. Use of Medicare claims to rank hospitals by surgical site infection risk following coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2011;32:775783.CrossRefGoogle ScholarPubMed
13. Calderwood, MS, Ma, A, Khan, YM, et al. Use of Medicare diagnosis and procedure codes to improve detection of surgical site infections following hip arthroplasty, knee arthroplasty, and vascular surgery. Infect Control Hosp Epidemiol 2012;33:4049.CrossRefGoogle ScholarPubMed
14. Yokoe, DS, Khan, Y, Olsen, MA, et al. Enhanced surgical site infection surveillance following hysterectomy, vascular, and colorectal surgery. Infect Control Hosp Epidemiol 2012;33:768773.Google Scholar
15. Letourneau, AR, Calderwood, MS, Huang, SS, Bratzler, DW, Ma, A, Yokoe, DS. Harnessing claims to improve detection of surgical site infections following hysterectomy and colorectal surgery. Infect Control Hosp Epidemiol 2013;34:13211323.CrossRefGoogle ScholarPubMed
16. Anderson, DJ, Podgorny, K, Berrios-Torres, SI, et al. Strategies to prevent surgical site infections in acute care hospitals: 2014 update. Infect Control Hosp Epidemiol 2014;35:605627.Google Scholar
17. Department of Health and Human Services, Centers for Medicare & Medicaid Services. Targeting SSI for validation. Fed Register 2012;77:5354553547.Google Scholar
18. Procedure-associated module for surgical site infection. Centers for Disease Control and Prevention National Healthcare Safety Network website. http://www.cdc.gov/nhsn/PDFs/pscManual/9pscSSIcurrent.pdf. Published 2017. Accessed February 15, 2017.Google Scholar
19. Horan, TC, Andrus, M, Dudeck, MA. CDC/NHSN surveillance definition for health care-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control 2008;36:309332.Google Scholar
20. General equivalence mappings (GEMs)—diagnosis codes. Centers for Medicare and Medicaid Services website. http://www.cms.gov/Medicare/Coding/ICD10/2015-ICD-10-CM-and-GEMs.html. Published 2015. Accessed February 15, 2017.Google Scholar
21. Calderwood, MS, Kleinman, K, Bratzler, DW, et al. Medicare claims can be used to identify US hospitals with higher rates of surgical site infection following vascular surgery. Med Care 2014;52:918925.Google Scholar
22. Calderwood, MS, Kleinman, K, Murphy, VK, Platt, R, Huang, SS. Improving public reporting and data validation for complex surgical site infections after coronary artery bypass graft surgery and hip arthroplasty. Open Forum Infect Dis 2014;1:ofu106.Google Scholar
23. Stone, PW, Pogorzelska-Maziarz, M, Reagan, J, et al. Impact of laws aimed at healthcare-associated infection reduction: a qualitative study. BMJ Qual Saf 2015;24:637644.Google Scholar
24. Lee, GM, Hartmann, CW, Graham, D, et al. Perceived impact of the Medicare policy to adjust payment for health care-associated infections. Am J Infect Control 2012;40:314319.Google Scholar
25. Calderwood, MS, Kleinman, K, Soumerai, SB, et al. Impact of Medicare’s payment policy on mediastinitis following coronary artery bypass graft surgery in US hospitals. Infect Control Hosp Epidemiol 2014;35:144151.Google Scholar
26. Kawai, AT, Calderwood, MS, Jin, R, et al. Impact of the Centers for Medicare and Medicaid Services hospital-acquired conditions policy on billing rates for 2 targeted healthcare-associated infections. Infect Control Hosp Epidemiol 2015;36:871877.Google Scholar
27. Use of ICD-CM diagnosis codes to “flag” post-operative patients for further evaluation of possible SSI. California Department of Public Health Healthcare-Associated Infections Program website. https://www.cdph.ca.gov/Programs/CHCQ/HAI/Pages/UseOfICD-CMDiagnosisCodesToFlagPost-operativePatientsForFurtherEvaluationOfPossibleSSI-.aspx. Published 2016. Accessed June 22, 2017.Google Scholar