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Effect of Nonpayment for Hospital-Acquired, Catheter-Associated Urinary Tract Infection: A Statewide Analysis

Jennifer A. Meddings, MD, MSc; Heidi Reichert, MA; Mary A.M. Rogers, PhD, MS; Sanjay Saint, MD, MPH; Joe Stephansky, PhD; and Laurence F. McMahon Jr., MD, MPH
[+] Article, Author, and Disclosure Information

From University of Michigan Medical School, Hospital Outcomes Program of Excellence, Ann Arbor Veterans Affairs Medical Center, and University of Michigan School of Public Health, Ann Arbor, and Michigan Health & Hospital Association, Lansing, Michigan.

Presented in part at the Society for Healthcare Epidemiology of America Fifth Decennial International Conference on Healthcare-Associated Infections, Atlanta, Georgia, 18–22 March 2010; the Society of General Internal Medicine 33rd Annual Meeting, Minneapolis, Minnesota, 28 April–1 May 2010; and the AcademyHealth 2010 Annual Research Meeting, Boston, Massachusetts, 27–29 June 2010.

Acknowledgment: The authors appreciate the insight provided by Gwendolyn Blackford, BS, about processes used and regulations followed by hospital coders while assigning diagnosis codes. They also thank Jack Hughes, MD, for his helpful suggestions and 3M for making the MS Grouper Software available to assess changes in hospital payment. The authors thank Andrew Hickner, MSI, for providing assistance with references and manuscript editing and Casey Crimmins, CPA, BGS, with the University of Michigan Department of Finance for providing crucial information to calculate the example of financial impact for the University of Michigan.

Grant Support: The study was funded by grant 1452.11 from the Blue Cross Blue Shield of Michigan Foundation. The authors were also supported by awards 1R010HS018344-01A1 (Dr. McMahon) and 1K08-HS019767-01 (Dr. Meddings) from the Agency for Healthcare Research and Quality; award R21-DK078717 (Dr. Saint) from the National Institute of Diabetes and Digestive and Kidney Diseases; and award R01-NR010700 (Dr. Saint) from the National Institute of Nursing Research. Dr. Meddings is also a recipient of the National Institutes of Health Clinical Loan Repayment Program for 2009 to 2012.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-0716.

Reproducible Research Statement:Study protocol: Available from Dr. Meddings (e-mail, meddings@umich.edu). Data set: Available by application, purchase, and data use agreement from the Healthcare Cost and Utilization Project (www.hcup-us.ahrq.gov/databases.jsp). Statistical code: Not available.

Requests for Single Reprints: Jennifer Meddings, MD, MSc, Division of General Medicine, North Campus Research Complex, 2800 Plymouth Road, Building 16, Room 430W, Ann Arbor, MI 48109-2800; e-mail, meddings@umich.edu.

Current Author Addresses: Drs. Meddings, Rogers, Saint, and McMahon and Ms. Reichert: Division of General Medicine, North Campus Research Complex, 2800 Plymouth Road, Building 16, Room 430W, Ann Arbor, MI 48109-2800.

Dr. Stephansky: Michigan Health & Hospital Association, 110 West Michigan Avenue, Suite 1200, Lansing, MI 48933.

Author Contributions: Conception and design: J.A. Meddings, M.A.M. Rogers, S. Saint, L.F. McMahon.

Analysis and interpretation of the data: J.A. Meddings, H. Reichert, M.A.M. Rogers, J. Stephansky.

Drafting of the article: J.A. Meddings, H. Reichert.

Critical revision of the article for important intellectual content: J.A. Meddings, M.A.M. Rogers, S. Saint, J. Stephansky, L.F. McMahon.

Final approval of the article: J.A. Meddings, M.A.M. Rogers, S. Saint, J. Stephansky, L.F. McMahon.

Statistical expertise: J.A. Meddings, H. Reichert, M.A.M. Rogers.

Obtaining of funding: J.A. Meddings.

Administrative, technical, or logistic support: J.A. Meddings, J. Stephansky, L.F. McMahon.

Collection and assembly of data: J.A. Meddings, H. Reichert, J. Stephansky.

Ann Intern Med. 2012;157(5):305-312. doi:10.7326/0003-4819-157-5-201209040-00003
Text Size: A A A

Background: Most (59% to 86%) hospital-acquired urinary tract infections (UTIs) are catheter-associated urinary tract infections (CAUTIs). As of 2008, claims data are used to deny payment for certain hospital-acquired conditions, including CAUTIs, and publicly report hospital performance.

Objective: To examine rates of UTIs in adults that are coded in claims data as hospital-acquired and catheter-associated events and evaluate how often nonpayment for CAUTI lowers hospital payment.

Design: Before-and-after study of all-payer cross-sectional claims data.

Setting: 96 nonfederal acute care Michigan hospitals.

Patients: Nonobstetric adults discharged in 2007 (n = 767 531) and 2009 (n = 781 343).

Measurements: Hospital rates of UTIs (categorized as catheter-associated or hospital-acquired) and frequency of reduced payment for hospital-acquired CAUTIs.

Results: Hospitals frequently requested payment for non-CAUTIs as secondary diagnoses: 10.0% (95% CI, 9.5% to 10.5%) of discharges in 2007 and 10.3% (CI, 9.8% to 10.9%) in 2009. Hospital rates of CAUTI were very low: 0.09% (CI, 0.06% to 0.12%) in 2007 and 0.14% (CI, 0.11% to 0.17%) in 2009. In 2009, 2.6% (CI, 1.6% to 3.6%) of hospital-acquired UTIs were described as CAUTIs. Nonpayment for hospital-acquired CAUTIs reduced payment for 25 of 781 343 (0.003%) hospitalizations in 2009.

Limitations: Data are from only 1 state and involved only 1 year before and after nonpayment for complications. Hospital prevention practices were not examined.

Conclusion: Catheter-associated UTI rates determined by claims data seem to be inaccurate and are much lower than expected from epidemiologic surveillance data. The financial impact of current nonpayment policy for hospital-acquired CAUTI is low. Claims data are currently not valid data sets for comparing hospital-acquired CAUTI rates for the purpose of public reporting or imposing financial incentives or penalties.

Primary Funding Source: Blue Cross Blue Shield of Michigan Foundation.


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Figure 1.

Study flow diagram.

DRG = diagnosis-related group; HCUP = Healthcare Cost and Utilization Project; LOS = length of stay; SID = State Inpatient Database; VA = Veterans Affairs.

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Figure 2.

Rates of hospital-acquired non-CAUTIs and CAUTIs in 2009 and change in rates from 2007 to 2009.

A hospital's rate of diagnosis was calculated as the percentage of each hospital's discharges of adults with the indicated diagnosis. CAUTI = catheter-associated urinary tract infection.

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Appendix Figure.

Rates of non-CAUTIs and CAUTIs as hospital-acquired and POA events in 2009.

A hospital's rate of diagnosis was calculated as the percentage of each hospital's discharges of adults with the indicated diagnosis. Four Michigan hospitals listed invalid POA codes for all diagnoses and all hospitalizations in the 2009 Healthcare Cost and Utilization Project State Inpatient Database. Because an invalid POA code generates an error, invalid codes would be corrected by hospitals before final submission to payers. CAUTI = catheter-associated urinary tract infection; POA = present-on-admission.

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Figure 3.

Rates of hospital-acquired non-CAUTIs and CAUTIs in 2009.

A hospital's rate of diagnosis was calculated as the percentage of each hospital's discharges of adults with the indicated diagnosis. Thirty-nine hospitals reported 0 hospitalizations (all-payer) with hospital-acquired CAUTIs. CAUTI = catheter-associated urinary tract infection.

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Effect of Nonpayment for Hospital-Acquired, Catheter-Associated Urinary Tract Infection: A Statewide Analysis
Posted on October 1, 2012
David B. Edwards MD FACP, Sharon Panozzo, RN MS CIC
Banner Gateway Medical Center
Conflict of Interest: None Declared

To the Editor,Although we don't take issue with Dr. Meddings (1) premise that coding data may not accurately reflect clinical outcomes, we do have an issue with a frequently cited article foundational to the argument that catheter associated UTIs are frequently underreported. The work by Klevens et al. (2) cited in Dr. Meddings’ article is widely referenced as being the epidemiological study showing excessively high catheter associated urinary tract infections (UTIs) and core to the premise that urinary tract infections are underreported. Klevens used 2002 data from a variety of sources. To calculate the total number of hospital associated infection (HAI) UTIs, the NNIS rates for HAI UTIs in the ICU of participating facilities were multiplied it by the total number of ICU days in the United States to get an estimate of 102,200 HAI UTIs in the ICU. The methodology for patients outside the ICU was based on unsubstantiated assumptions. Their model presumed that the rates of surgical site infection to the urinary tract infection rate outside the ICU would be identical to the distribution inside the ICU. Since they knew the infection rates for surgical site infections reliably both outside ICU and inside ICU, they multiplied the outside ICU surgical infection rate by the same proportion to come up with a HAI UTI rate outside of the ICU. By these calculations, they suggested there were 424,060 CAUTIs outside the ICU or more than 500,000 CAUTIs in hospitals. Their estimate of 32% of the total 9.3 HAI per 1000 patient days translates to an infection rate of 3.1 infections per 1000 patient days (or 1.5 per 100 admissions).Banner Health, a non-profit health care system with 22 hospitals and 4,330 beds, has been monitoring CAUTIs since 2011 in most of its facilities. Infection control specialists using NHSN criteria monitor for any catheter associated hospital acquired urinary tract infections. In 2011, we had 0.29 CAUTIs/1000 patient days and, so far in 2012, 0.20 CAUTIs/1000 patient days respectively, one tenth of the Kleven’s reported rate. We believe it is improper to continue to reference Klevens results as they are estimates based on 2002 data with questionable assumptions in proportionality of infection rates and, when used, overstate the infection rate by a factor of 10. Additionally, of the 6 references Dr Medding cited for epidemiological rates, 3 were published between 1981-1983. We use a lot less urinary catheters than we did back then.


1. Meddings JA, Reichert H, Rogers MA, Saint S, Stephansky J, McMahon LF. Effect of nonpayment for hospital-acquired, catheter-associated urinary tract infection: a statewide analysis. Ann Intern Med. 2012;157:305-12. [PMID: 22944872]

2. Klevens RM, Edwards JR, Richards CL Jr, Horan TC, Gaynes RP, Pollock DA, et al. Estimating health care-associated infections and deaths in U.S. hospitals, 2002. Public Health Rep. 2007;122:160-6. [PMID: 17357358]


Effect of Nonpayment for Hospital-Acquired, Catheter-Associated Urinary Tract Infection: A Statewide Analysis
Posted on November 6, 2012
J. Meddings MD, MSc; M.A.M. Rogers PhD, MS; L.F. McMahon Jr, MD, MPH
University of Michigan Medical School, Ann Arbor, MI
Conflict of Interest: None Declared

To the Editor,

We congratulate Banner Health on their low catheter-associated urinary tract infection (CAUTI) rates, at 0.29 CAUTI/1000 patient-days. Studies (1) and hospital websites often report successful implementation of CAUTI prevention programs, significantly decreasing catheter use and CAUTI rates. For example, Indiana Heart Hospital reported decreased rates in 2008 from 2.3-4.8 CAUTIs per 1000 patient-days to monthly rates in 2010 from 0-1.6 per 1000 patient-days. However, the fact remains that inappropriate catheter use and CAUTIs persist as important challenges in both ICUs and non-ICUs in many hospitals as evidenced by pre-intervention rates in the literature (1) - which can be higher than National Healthcare Safety Network (NHSN) surveillance rates (2) or as estimated by the Klevens study (3.1/1000 patient-days). Nationwide surveys (3) in 2009 demonstrated that <20% hospitals use CAUTI prevention strategies such as catheter reminders or stop-orders; so, we should not expect most hospitals to have much lower CAUTI rates compared to pre-intervention rates. Although CAUTI rates have decreased somewhat by NHSN data (2, 4), large variation in hospital rates remains with no evidence to suggest large decreases in urinary catheter use nationwide (2).

The Hospital-Acquired Conditions Initiative was well-intentioned in selecting CAUTI as a common, often preventable complication from the available epidemiology studies and consistent with clinical experience. Yet, the policy’s implementation was seriously flawed by selecting claims data (without prior validation) as a national dataset conveniently linking complication events to payment changes. Our research demonstrates the hospital rates in claims data are simply too low to reflect reality – consistent with our prior investigations with medical record reviews (5) underscoring that claim data rates are dependent on physicians clearly documenting UTIs as catheter-associated and hospital-acquired. Hospitals with high rates in claims data may simply monitor and document complications better. What began as a simple idea (i.e., do not pay extra for hospital-acquired complications such as CAUTIs) quickly expanded (still without validation, and without risk-adjustment) into the use of claims data to report and compare hospitals by complication rates on websites such as CMS’s Hospital Compare, the Leapfrog Hospital Survey, and even in a recent publication from the Dartmouth Atlas Report aiming to guide medical students to select residencies with better quality and value of medical care. We encourage cessation of using complication rates from such invalid claims data for reports that the public and policymakers assume are accurate reflections of care to guide important value-based purchasing decisions.  


1. Meddings J, Rogers MA, Macy M, Saint S. Systematic review and meta-analysis: reminder systems to reduce catheter-associated urinary tract infections and urinary catheter use in hospitalized patients. Clin Infect Dis. 2010;51:550-60. [PMID: 20673003]

2. Dudeck MA, Horan TC, Peterson KD, Allen-Bridson K, Morrell G, Pollock DA, et al. National Healthcare Safety Network (NHSN) Report, data summary for 2010, device-associated module. American journal of infection control. 2011;39:798-816. [PMID: 22133532]

3. Krein SL, Kowalski CP, Hofer TP, Saint S. Preventing hospital-acquired infections: a national survey of practices reported by U.S. hospitals in 2005 and 2009. Journal of General Internal Medicine. 2011. [PMID: 22143455]

4. Lee GM, Kleinman K, Soumerai SB, Tse A, Cole D, Fridkin SK, et al. Effect of nonpayment for preventable infections in U.S. hospitals. The New England journal of medicine. 2012;367:1428-37. [PMID: 23050526]

5. Meddings J, Saint S, McMahon LF, Jr. Hospital-acquired catheter-associated urinary tract infection: documentation and coding issues may reduce financial impact of Medicare's new payment policy. Infect Control Hosp Epidemiol. 2010;31:627-33. [PMID: 20426577]

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