900
period, there were 935 acute care, nonfederal US hospitals with at least 1 discharge containing a CAUTI HAC code, and 102 of these hospitals had the DRG assignment impacted for at least 1 dis- charge. Table 2 compares the hospital characteristics between the hospitals with DRG changes and those with no DRG changes. For CLABSI, the following characteristics were significantly
more common among hospitals impacted by the CMS HAC policy: hospital in the Northeast region (P=0.05), bed size≥400 (P<.01), and major teaching status (P<.01). For CAUTI, no characteristics were significantly more common among hospitals impacted by the CMS HAC policy, although hospitals in the Northeast region appear to have been impacted the most (P=0.06), similar to CLABSI.
Discussion
One of the main reasons that the 2008 CMS HAC policy may not have accelerated the rate of decline in central line–associated bloodstream infections and catheter-associated urinary tract infections is that the financial penalties were minimal. Billing codes for CLABSI and CAUTI were rarely used, were commonly listed as present on admission in the post-policy period, and infrequently impacted the DRG assignment determining hospital reimbursement. Based on billing for CLABSI and CAUTI not POA in the
postpolicy period, an average of ~6,800 Medicare discharges per year (2009–2011) had a hospital-acquired CLABSI and ~750 Medicare discharges per year (2009–2011) had a hospital- acquired CAUTI. To put this into context, US estimates for annual CLABSI infections range from 60,000 to 92,000, and estimates for annual CAUTI infections range from 63,000 to 450,000.11,12 Even accounting for the fact that Medicare pays for only 39% of US hospitalizations,13 these numbers suggest that claims identified a much lower number of infections than pub- lished surveillance data. This finding is consistent with prior findings in a statewide analysis looking at the use of the CAUTI HAC code.14 Our finding that the majority of HAC codes submitted for
reimbursement shifted to being coded as POA in the postpolicy period deserves further investigation. One study looking at coding practices for CAUTI found that at least one-third of infections listed as POA actuallymet criteria as hospital-acquired infections.15 This result calls into question the accuracy of the POA designation. Delving into this further, our finding that major teaching
hospitals were most impacted by the HAC policy for CLABSI was actually predicted based on an analysis of coding practices in academic medical centers.16 In fact, a prior CAUTI study looking at data through 2009 showed that teaching hospitals were more impacted by the HAC policy than nonteaching hospitals, with private, for-profit hospitals having the greatest decline in coded, non-POA CAUTIs in the year following the policy.17 In the context of a profit incentive, earlier adoption of changes in coding practice may have occurred for certain hospitals. When determining hospital reimbursement based on DRG assignment, other diagnosis codes may be submitted for reim- bursement, limiting the magnitude of change due to ICD-9 codes selected to identify CLABSI and CAUTI.15,18 In addition, the position of a given HAC code in the list of submitted diagnoses may impact the likelihood of change in DRG assignment.19 Thus, recognizing the limitations of HAI performance metrics based on claims for CLABSI and CAUTI, there has been a shift
Michael S. Calderwood et al
toward collecting data using clinical surveillance definitions. The current Hospital-Acquired Condition Reduction Program tracks outcomes for CLABSI and CAUTI based on data self-reported by hospitals to the Centers for Diseases Control and Prevention’s National Healthcare Safety Network (NHSN).20,21 It is hoped that this will lead to better accountability and will increase efforts to reduce preventable healthcare-associated infections. At the same time, concerns have been raised about the impact of financial incentives on the adjudication of which cases are publicly reported. Time will tell if this new HAC Reduction Program has a positive impact on patient outcomes. As for the 2008 CMS HAC policy targeting CLABSI and
CAUTI, the financial disincentives were minimal due to coding practices. Therefore, it is not surprising that there was not a significant impact on reported CLABSI and CAUTI trends based on clinical surveillance definitions. However, our study has a few limitations. First, we only analyzed data through 2011 (3 years postpolicy), although there is no reason to suspect that coding practices have changed. Second, we took the diagnosis codes in Medicare claims to be true, although it is possible that non– device-associated infections could have been erroneously coded as CLABSI or CAUTI (ie, false positives). Third, we only included hospitals subject to IPPS rules, excluding cancer hospitals with a potentially higher risk of both CLABSI and CAUTI. With the evolution of the HAC Reduction Program, hospitals
ranked in the worst quartile based on NHSN reported rates of CLABSI and CAUTI take a percentage reduction on their entire Medicare reimbursement for the year, rather than just on a single encounter. While this has definitely attracted the attention of hospital leadership, it will be important to be vigilant about the impact of these policies on patient outcomes and to monitor for unintended consequences as these payment policies continue to evolve.
Acknowledgments. We are grateful to the members of the Preventing Avoidable Infectious Complications by Adjusting Payment (PAICAP) study team (Ken Kleinman, ScD; Ashish Jha, MD, MPH; and Stephen Soumerai, ScD). We also thank the PAICAP Advisory Board for their guidance and input (Neil Fishman, MD, MA; Scott Fridkin, MD; Don Goldmann, MD; Patricia Grant, RN, BSN, MS; Teresa Horan, MPH; John Jernigan, MD, MS; William Kassler, MD, MPH; and Clifford McDonald, MD).
Financial support. This study was funded by the Agency for Healthcare Research and Quality (grant no. HS018414).
Potential conflicts of interest. All authors report no conflicts of relevant to this article.
References
1. Centers for Medicare and Medicaid Services; Department of Health and Human Services. Medicare program: changes to the hospital inpatient prospective payment systems and fiscal year. 2008 rates. Fed Regist 2007;72:47379–47428.
2. Acute inpatient PPS. Centers for Medicare and Medicaid Services website.
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/Acute- inpatientPPS/
index.html. Updated 2017. Accessed February 21, 2018.
3. Nguyen OK, Halm EA, Makam AN. Relationship between hospital financial performance and publicly reported outcomes. J Hosp Med 2016;11:481–488.
4. Lee GM, Kleinman K, Soumerai SB, et al. Effect of nonpayment for preventable infections in US hospitals. N Engl J Med 2012;367:1428–1437.
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