Accuracy of quality measurement for the Hospital Acquired Conditions Reduction Program

Assessment of a Protocol for Reducing Indwelling Urinary Catheter Usage: Reduced Infection Without Increased Acute Kidney Injury

Introduction In 2019, a level one trauma center in St. Louis, Missouri launched a campaign to reduce the use of indwelling urinary catheters (IUC) in the trauma population. Our study assesses whether the campaign achieved the intended effect of reducing catheter-associated urinary tract infection (CAUTI) and whether this came at the cost of increased acute kidney injury (AKI). Methods We examined a cohort of patients from before and after the IUC reduction campaign. We compared days with IUC, UTI, CAUTI, and AKI, both recorded in the registry and based on a direct review of laboratory results. Significance testing is performed with the Student's t-test for continuous variables and Fisher's exact test for categorical variables. For multivariate analysis, multivariate linear regression is used for continuous outcomes, and multivariate logistic regression is used for binary categorical outcomes.  Results On average, the post-campaign cohort was older and more severely injured. There was a modest decrease in IUC usage following the campaign, which was significant when adjusted for common trauma covariates, B=-0.93; p=0.04. There were 10 (0.4%) cases of CAUTI in the pre-intervention group versus 0 post-intervention (p=0.002). Pyuria was significantly lower post-intervention: 118 (40.3%) versus 84 (29.3%), p=0.007. This remained significant on multivariate analysis: odds ratio (OR): 0.52, p=0.008. There were no significant differences in creatinine (Cr) absolute values or temporal trends over the course of admission between the cohorts. There was no increased AKI measured by kidney disease improving global outcomes (KDIGO) criteria. Conclusion The IUC reduction protocol was associated with a significant decrease in CAUTI without a significant increase in AKI.

Teaching and Safety-Net Hospital Penalization in the Hospital-Acquired Condition Reduction Program

Importance

The Hospital-Acquired Condition Reduction Program (HACRP) evaluates acute care hospitals on the occurrence of patient safety events and health care-associated infections. Since its implementation, several studies have raised concerns about the overpenalization of teaching and safety-net hospitals, and although several changes in the program's methodology have been applied in the last few years, whether these changes reversed the overpenalization of teaching and safety-net hospitals is unknown.

Objective

To determine hospital characteristics associated with HACRP penalization and penalization reversal.

Design, Setting, and Participants

This retrospective cross-sectional study assessed data from 3117 acute care hospitals participating in the HACRP. The HACRP penalization and hospital characteristics were obtained from Hospital Compare (2020 and 2021), the Inpatient Prospective Payment System impact file (2020), and the American Hospital Association annual survey (2018).

Exposures

Hospital characteristics, including safety-net status and teaching intensity (no teaching and very minor, minor, major, and very major teaching levels).

Main Outcomes and Measures

The primary outcome was HACRP penalization (ie, hospitals that fell within the worst quartile of the program's performance). Multivariable models initially included all covariates, and then backward stepwise variable selection was used.

Results

Of 3117 hospitals that participated in HACRP in 2020, 779 (25.0%) were safety-net hospitals and 1090 (35.0%) were teaching institutions. In total, 771 hospitals (24.7%) were penalized. The HACRP penalization was associated with safety-net status (odds ratio [OR], 1.41 [95% CI, 1.16-1.71]) and very major teaching intensity (OR, 1.94 [95% CI, 1.15-3.28]). In addition, non-federal government hospitals were more likely to be penalized than for-profit hospitals (OR, 1.62 [95% CI, 1.23-2.14]), as were level I trauma centers (OR, 2.05 [95% CI, 1.43-2.96]) and hospitals located in the New England region (OR, 1.65 [95% CI, 1.12-2.43]). Safety-net hospitals with major teaching levels were twice as likely to be penalized as non-safety-net nonteaching hospitals (OR, 2.15 [95% CI, 1.14-4.03]). Furthermore, safety-net hospitals penalized in 2020 were less likely (OR, 0.64 [95% CI, 0.43-0.96]) to revert their HACRP penalization status in 2021.

Conclusions and Relevance

Findings from this cross-sectional study indicated that teaching and safety-net hospital status continued to be associated with overpenalization in the HACRP despite recent changes in its methodology. Most of these hospitals were also less likely to revert their penalization status. A reevaluation of the program methodology is needed to avoid depleting resources of hospitals caring for underserved populations.

Hospital-Acquired Condition Rate of Admitting Facility Does Not Predict Mortality in Traumatically Injured Patients

Background: Hospital-acquired conditions (HACs) are increasingly scrutinized as markers of hospital quality and are subject to increasing regulatory and financial pressure. Despite this, there is little evidence that HACs are associated with poor outcomes in traumatically injured patients, or that lower HAC rates are a marker of a better quality of care. Our study compares mortality rates in hospitals with high versus low rates of HAC. Our hypothesis is that high HAC trauma centers have higher mortality.

Methods: The latest editions of the National Trauma Data Bank (NTDB) containing facility identification keys (2011 to 2015) were combined. The HACs targeted by the Centers for Medicare and Medicaid Services (CMS) Hospital-Acquired Condition Reduction Program (HACRP) were identified. Hospital-acquired conditions per 1000 patient-days were calculated for individual trauma centers, and these facilities were stratified into quartiles by HAC rate. Propensity score matching was used to match patients admitted to hospitals in the highest versus the lowest quartiles.

Results: Complete data was available for 3,510,818 patients; 58,296 (1.67%) developed HACs recorded in the NTDB. Good performing centers had a mean of 0.84 HACs per 1000 patient-days compared to 7.82 at poor-performing centers. After propensity matching, patients treated at good performing centers had higher mortality of 1.22% versus 1.02% at poor-performing centers (p<0.001). The facility characteristics most over-represented in the poor performing quartile were: University (45.19% vs 10.59%, p<0.001), American College of Surgeons (ACS) Level I Status (31.85% vs 2.24%, p<0.001), and bed size > 600 (28.15% vs 5.5%, p<0.001).

Conclusion: Injured patients treated at poor-performing centers (high HAC) have reduced mortality relative to good performing centers (low HAC). Large academic centers were overwhelmingly represented in the poor-performing quartile. Hospital-acquired conditions may be markers of a non-modifiable underlying patient and facility characteristics rather than markers of poor hospital quality.

Association of Hospital Public Quality Reporting With Electronic Health Record Medication Safety Performance

IMPORTANCE

Despite billions spent in public investment, electronic health records (EHRs) have not delivered on the promise of large quality and safety improvement. Simultaneously, there is debate on whether public quality reporting is a useful tool to incentivize quality improvement.

OBJECTIVE

To evaluate whether publicly reported feedback was associated with hospital improvement in an evaluation of medication-related clinical decision support (CDS) safety performance.

DESIGN, SETTINGS, AND PARTICIPANTS

This nonrandomized controlled trial included US hospitals that participated in the Computerized Provider Order Entry (CPOE) Evaluation Tool in the Leapfrog Hospital Survey, a national quality reporting program that evaluates safety performance of hospital CDS using simulated orders and patients, in 2017 to 2018. A sharp regression discontinuity design was used to identify the association of receiving negative feedback with hospital performance improvement in the subsequent year. Data were analyzed from January through September 2020.

EXPOSURES

Publicly reported quality feedback.

MAIN OUTCOMES AND MEASURES

The main outcome was improvement from 2017 to 2018 on the Leapfrog CPOE Evaluation Tool, using regression discontinuity model estimates of the association of receiving negative publicly reported feedback with quality improvement.

RESULTS

A total of 1183 hospitals were included, with a mean (SD) CPOE score of 59.3% (16.3%) at baseline. Hospitals receiving negative feedback improved 8.44 (95% CI, 0.09 to 16.80) percentage points more in the subsequent year compared with hospitals that received positive feedback on the same evaluation. This change was driven by differences in improvement in basic CDS capabilities (β = 8.71 [95%CI, 1.67 to 18.73]) rather than advanced CDS (β = 6.15 [95% CI, -9.11 to 26.83]).

CONCLUSIONS AND RELEVANCE

In this nonrandomized controlled trial, publicly reported feedback was associated with quality improvement, suggesting targeted measurement and reporting of process quality may be an effective policy lever to encourage improvement in specific areas. Clinical decision support represents an important tool in ensuring patient safety and decreasing adverse drug events, especially for complex patients and those with multiple chronic conditions who often receive several different drugs during an episode of care.