Dataset Information

An Evaluation of Antimicrobial Prescribing and Risk-adjusted Mortality.

ABSTRACT: The Centers for Disease Control and Prevention recommends tracking risk-adjusted antimicrobial prescribing. Prior studies have used prescribing variation to drive quality improvement initiatives without adjusting for severity of illness. The present study aimed to determine the relationship between antimicrobial prescribing and risk-adjusted ICU mortality in the Pediatric Health Information Systems (PHIS) database, assessed by IBM-Watson risk of mortality. A nested analysis sought to assess an alternative risk model incorporating laboratory data from federated electronic health records.

Methods

Retrospective cohort study of pediatric ICU patients in PHIS between 1/1/2010 and 12/31/2019, excluding patients admitted to a neonatal ICU, and a nested study of PHIS+ from 1/1/2010 to 12/31/2012. Hospital antimicrobial prescription volumes were assessed for association with risk-adjusted mortality.

Results

The cohort included 953,821 ICU encounters (23,851 [2.7%] nonsurvivors). There was 4-fold center-level variability in antimicrobial use. ICU antimicrobial use was not correlated with risk-adjusted mortality assessed using IBM-Watson. A risk model incorporating laboratory data available in PHIS+ significantly outperformed IBM-Watson (c-statistic 0.940 [95% confidence interval 0.933-0.947] versus 0.891 [0.881-0.901]; P < 0.001, area under the precision recall curve 0.561 versus 0.297). Risk-adjusted mortality was inversely associated with antimicrobial prescribing in this smaller cohort using both the PHIS+ and Watson models (P = 0.05 and P < 0.01, respectively).

Conclusions

Antimicrobial prescribing among pediatric ICUs in the PHIS database is variable and not associated with risk-adjusted mortality as assessed by IBM-Watson. Expanding existing administrative databases to include laboratory data can achieve more meaningful insights when assessing multicenter antibiotic prescribing practices.

SUBMITTER: Pelletier JH

PROVIDER: S-EPMC8678007 | biostudies-literature | 2021 Nov-Dec

REPOSITORIES: biostudies-literature

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Publications

An Evaluation of Antimicrobial Prescribing and Risk-adjusted Mortality.

Pelletier Jonathan H JH Au Alicia K AK Fuhrman Dana D Zullo James J Thompson Ann E AE Clark Robert S B RSB Horvat Christopher C

Pediatric quality & safety 20211101 6

The Centers for Disease Control and Prevention recommends tracking risk-adjusted antimicrobial prescribing. Prior studies have used prescribing variation to drive quality improvement initiatives without adjusting for severity of illness. The present study aimed to determine the relationship between antimicrobial prescribing and risk-adjusted ICU mortality in the Pediatric Health Information Systems (PHIS) database, assessed by IBM-Watson risk of mortality. A nested analysis sought to assess an a ...[more]

PMID: 34934871

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Project description:BackgroundAmong inpatients, peer-comparison of prescribing metrics is challenging due to variation in patient-mix and prescribing by multiple providers daily. We established risk-adjusted provider-specific antibiotic prescribing metrics to allow peer-comparisons among hospitalists.MethodsUsing clinical and billing data from inpatient encounters discharged from the Hospital Medicine Service between January 2020 through June 2021 at four acute care hospitals, we calculated bimonthly (every two months) days of therapy (DOT) for antibiotics attributed to specific providers based on patient billing dates. Ten patient-mix characteristics, including demographics, infectious disease diagnoses, and noninfectious comorbidities were considered as potential predictors of antibiotic prescribing. Using linear mixed models, we identified risk-adjusted models predicting the prescribing of three antibiotic groups: broad spectrum hospital-onset (BSHO), broad-spectrum community-acquired (BSCA), and anti-methicillin-resistant Staphylococcus aureus (Anti-MRSA) antibiotics. Provider-specific observed-to-expected ratios (OERs) were calculated to describe provider-level antibiotic prescribing trends over time.ResultsPredictors of antibiotic prescribing varied for the three antibiotic groups across the four hospitals, commonly selected predictors included sepsis, COVID-19, pneumonia, urinary tract infection, malignancy, and age >65 years. OERs varied within each hospital, with medians of approximately 1 and a 75th percentile of approximately 1.25. The median OER demonstrated a downward trend for the Anti-MRSA group at two hospitals but remained relatively stable elsewhere. Instances of heightened antibiotic prescribing (OER >1.25) were identified in approximately 25% of the observed time-points across all four hospitals.ConclusionOur findings indicate provider-specific benchmarking among inpatient providers is achievable and has potential utility as a valuable tool for inpatient stewardship efforts.

Project description:ImportanceNational surgical quality improvement programs lack tools for early detection of quality or safety concerns, which risks patient safety because of delayed recognition of poor performance.ObjectiveTo compare the risk-adjusted cumulative sum (CUSUM) with episodic evaluation for early detection of hospitals with excess perioperative mortality.Design, setting, and participantsNational, observational, hospital-level, comparative effectiveness study of 697 566 patients. Identification of hospitals with excess, risk-adjusted, quarterly 30-day mortality using observed to expected ratios (ie, current criterion standard in the Veterans Affairs Surgical Quality Improvement Program) was compared with the risk-adjusted CUSUM. Patients included in the study underwent a noncardiac operation at a Veterans Affairs hospital, had a record in the Veterans Affairs Surgical Quality Improvement Program (January 1, 2011, through December 31, 2016), and were aged 18 years or older.Main outcome and measureNumber of hospitals identified as having excess risk-adjusted 30-day mortality.ResultsThe cohort included 697 566 patients treated at 104 hospitals across 24 quarters. The mean (SD) age was 60.9 (13.2) years, 91.4% were male, and 8.6% were female. For each hospital, the median number of quarters detected with observed to expected ratios, at least 1 CUSUM signal, and more than 1 CUSUM signal was 2 quarters (IQR, 1-4 quarters), 8 quarters (IQR, 4-11 quarters), and 3 quarters (IQR, 1-4 quarters), respectively. During 2496 total quarters of data, outlier hospitals were identified 33.3% of the time (830 quarters) with at least 1 CUSUM signal within a quarter, 12.5% (311 quarters) with more than 1 CUSUM signal, and 11.0% (274 quarters) with observed to expected ratios at the end of the quarter. The CUSUM detection occurred a median of 49 days (IQR, 25-63 days) before observed to expected ratio reporting (1 signal, 35 days [IQR, 17-54 days]; 2 signals, 49 days [IQR, 26-61 days]; 3 signals, 58 days [IQR, 44-69 days]; ≥4 signals, 49 days [IQR, 42-69 days]; trend test, P < .001). Of 274 hospital quarters detected with observed to expected ratios, 72.6% (199) were concurrently detected by at least 1 CUSUM signal vs 42.7% (117) by more than 1 CUSUM signal. There was a dose-response relationship between the number of CUSUM signals in a quarter and the median observed to expected ratio (0 signals, 0.63; 1 signal, 1.28; 2 signals, 1.58; 3 signals, 2.08; ≥4 signals, 2.49; trend test, P < .001).ConclusionsThis study found that with CUSUM, hospitals with excess perioperative mortality can be identified well in advance of standard end-of-quarter reporting, which suggests episodic evaluation strategies fail to detect out-of-control processes and place patients at risk. Continuous performance evaluation tools should be adopted in national quality improvement programs to prevent avoidable patient harm.

Dataset Information

An Evaluation of Antimicrobial Prescribing and Risk-adjusted Mortality.

Methods

Results

Conclusions

Publications

An Evaluation of Antimicrobial Prescribing and Risk-adjusted Mortality.

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