Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System.

BACKGROUND: Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings. OBJECTIVE: The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality. RESEARCH DESIGN: Observational cohort study with hospital-specific template matching assessment. For each VA hospital, the 30-day mortality of a representative subset of hospitalizations was compared with the pooled mortality from matched hospitalizations at a set of comparison VA hospitals treating sufficiently similar patients. The simulation was used to determine power to detect greater-than-expected mortality. SUBJECTS: A total of 556,266 hospitalizations at 122 VA hospitals in 2017. MEASURES: A number of comparison hospitals identified per hospital; 30-day mortality. RESULTS: Each hospital had a median of 38 comparison hospitals (interquartile range: 33, 44) identified, and 116 (95.1%) had at least 20 comparison hospitals. In total, 8 hospitals (6.6%) had a significantly lower 30-day mortality than their benchmark, 5 hospitals (4.1%) had a significantly higher 30-day mortality, and the remaining 109 hospitals (89.3%) were similar to their benchmark. Power to detect a standardized mortality ratio of 2.0 ranged from 72.5% to 79.4% for a hospital with the fewest (6) versus most (64) comparison hospitals. CONCLUSIONS: Hospital-specific template matching may be feasible for assessing hospital performance in the diverse VA health care system, but further refinements are needed to optimize the approach before operational use. Our findings are likely applicable to other large and diverse multihospital systems.

Temporal Trends and Hospital Variation in Time-to-Antibiotics Among Veterans Hospitalized With Sepsis.

Importance: It is unclear whether antimicrobial timing for sepsis has changed outside of performance incentive initiatives. Objective: To examine temporal trends and variation in time-to-antibiotics for sepsis in the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants: This observational cohort study included 130 VA hospitals from 2013 to 2018. Participants included all patients admitted to the hospital via the emergency department with sepsis from 2013 to 2018, using a definition adapted from the Centers for Disease Control and Prevention Adult Sepsis Event definition, which requires evidence of suspected infection, acute organ dysfunction, and systemic antimicrobial therapy within 12 hours of presentation. Data were analyzed from October 6, 2020, to July 1, 2021. Exposures: Time from presentation to antibiotic administration. Main Outcomes and Measures: The main outcome was differences in time-to-antibiotics across study periods, hospitals, and patient subgroups defined by presenting temperature and blood pressure. Temporal trends in time-to-antibiotics were measured overall and by subgroups. Hospital-level variation in time-to-antibiotics was quantified after adjusting for differences in patient characteristics using multilevel linear regression models. Results: A total of 111 385 hospitalizations for sepsis were identified, including 107 547 men (96.6%) men and 3838 women (3.4%) with a median (interquartile range [IQR]) age of 68 (62-77) years. A total of 7574 patients (6.8%) died in the hospital, and 13 855 patients (12.4%) died within 30 days. Median (IQR) time-to-antibiotics was 3.9 (2.4-6.5) hours but differed by presenting characteristics. Unadjusted median (IQR) time-to-antibiotics decreased over time, from 4.5 (2.7-7.1) hours during 2013 to 2014 to 3.5 (2.2-5.9) hours during 2017 to 2018 (P < .001). In multilevel models adjusted for patient characteristics, median time-to-antibiotics declined by 9.0 (95% CI, 8.8-9.2) minutes per calendar year. Temporal trends in time-to-antibiotics were similar across patient subgroups, but hospitals with faster baseline time-to-antibiotics had less change over time, with hospitals in the slowest tertile decreasing time-to-antibiotics by 16.6 minutes (23.1%) per year, while hospitals in the fastest tertile decreased time-to-antibiotics by 7.2 minutes (13.1%) per year. In the most recent years (2017-2018), median time-to-antibiotics ranged from 3.1 to 6.7 hours across hospitals (after adjustment for patient characteristics), 6.8% of variation in time-to-antibiotics was explained at the hospital level, and odds of receiving antibiotics within 3 hours increased by 65% (95% CI, 56%-77%) for the median patient if moving to a hospital with faster time-to-antibiotics. Conclusions and Relevance: This cohort study across nationwide VA hospitals found that time-to-antibiotics for sepsis has declined over time. However, there remains significant variability in time-to-antibiotics not explained by patient characteristics, suggesting potential unwarranted practice variation in sepsis treatment. Efforts to further accelerate time-to-antibiotics must be weighed against risks of overtreatment.

Measurement of Sepsis in a National Cohort Using Three Different Methods to Define Baseline Organ Function.

Rationale: In 2017, the U.S. Centers for Disease Control and Prevention (CDC) developed a new surveillance definition of sepsis, the adult sepsis event (ASE), to better track sepsis epidemiology. The ASE requires evidence of acute organ dysfunction and defines baseline organ function pragmatically as the best in-hospital value. This approach may undercount sepsis if new organ dysfunction does not resolve by discharge.Objectives: To understand how sepsis identification and outcomes differ when using the best laboratory values during hospitalization versus methods that use historical lookbacks to define baseline organ function.Methods: We identified all patients hospitalized at 138 Veterans Affairs hospitals (2013-2018) admitted via the emergency department with two or more systemic inflammatory response criteria, were treated with antibiotics within 48 hours (i.e., had potential infection), and completed 4+ days of antibiotics (i.e., had suspected infection). We considered the following three approaches to defining baseline renal, hematologic, and liver function: the best values during hospitalization (as in the Centers for Disease Control and Prevention's ASE), the best values during hospitalization plus the prior 90 days (3-mo baseline), and the best values during hospitalization plus the prior 180 days (6-mo baseline). We determined how many patients met the criteria for sepsis by each approach, and then compared characteristics and outcomes of sepsis hospitalizations between the three approaches.Results: Among 608,128 hospitalizations with potential infection, 72.1%, 68.5%, and 58.4% had creatinine, platelet, and total bilirubin measured, respectively, in the prior 3 months. A total of 86.0%, 82.6%, and 74.8%, respectively, had these labs in the prior 6 months. Using the hospital baseline, 100,568 hospitalizations met criteria for community-acquired sepsis. By contrast, 111,983 and 117,435 met criteria for sepsis using the 3- and 6-month baselines, for a relative increase of 11% and 17%, respectively. Patient characteristics were similar across the three approaches. In-hospital mortality was 7.2%, 7.0%, and 6.8% for sepsis hospitalizations identified using the hospital, 3-month baseline, and 6-month baseline. The 30-day mortality was 12.5%, 12.7%, and 12.5%, respectively.Conclusions: Among veterans hospitalized with potential infection, the majority had laboratory values in the prior 6 months. Using 3- and 6-month lookbacks to define baseline organ function resulted in an 11% and 17% relative increase, respectively, in the number of sepsis hospitalizations identified.

Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system.

Template matching is a proposed approach for hospital benchmarking, which measures performance based on matching a subset of comparable patient hospitalizations from each hospital. We assessed the ability to create the required matched samples and thus the feasibility of template matching to benchmark hospital performance in a diverse healthcare system.Nationwide Veterans Affairs (VA) hospitals, 2017.Observational cohort study.We used administrative and clinical data from 668,592 hospitalizations at 134 VA hospitals in 2017. A standardized template of 300 hospitalizations was selected, and then 300 hospitalizations were matched to the template from each hospital.There was substantial case-mix variation across VA hospitals, which persisted after excluding small hospitals, hospitals with primarily psychiatric admissions, and hospitalizations for rare diagnoses. Median age ranged from 57 to 75 years across hospitals; percent surgical admissions ranged from 0.0% to 21.0%; percent of admissions through the emergency department, 0.1% to 98.7%; and percent Hispanic patients, 0.2% to 93.3%. Characteristics for which there was substantial variation across hospitals could not be balanced with any matching algorithm tested. Although most other variables could be balanced, we were unable to identify a matching algorithm that balanced more than ∼20 variables simultaneously.We were unable to identify a template matching approach that could balance hospitals on all measured characteristics potentially important to benchmarking. Given the magnitude of case-mix variation across VA hospitals, a single template is likely not feasible for general hospital benchmarking.

Late Vasopressor Administration in Patients in the ICU: A Retrospective Cohort Study.

BACKGROUND: Little is known about the prevalence, predictors, and outcomes of late vasopressor administration which evolves after admission to the ICU. RESEARCH QUESTION: What is the epidemiology of late vasopressor administration in the ICU? STUDY DESIGN AND METHODS: We retrospectively studied a cohort of veterans admitted to the Veterans Administration ICUs for ≥ 4 days from 2014 to 2017. The timing of vasopressor administration was categorized as early (only within the initial 3 days), late (on day 4 or later and none on day 3), and continuous (within the initial 2 days through at least day 4). Regressions were performed to identify patient factors associated with late vasopressor administration and the timing of vasopressor administration with posthospitalization discharge mortality. RESULTS: Among the 62,206 hospitalizations with at least 4 ICU days, late vasopressor administration occurred in 5.5% (3,429 of 62,206). Patients with more comorbidities (adjusted OR [aOR], 1.02 per van Walraven point; 95% CI, 1.02-1.03) and worse severity of illness on admission (aOR, 1.01 per percentage point risk of death; 95% CI, 1.01-1.02) were more likely to receive late vasopressor therapy. Nearly 50% of patients started a new antibiotic within 24 h of receiving late vasopressor therapy. One-year mortality after survival to discharge was higher for patients with continuous (adjusted hazard ratio [aHR], 1.48; 95% CI, 1.33-1.65) and late vasopressor administration (aHR, 1.26; 95% CI, 1.15-1.38) compared with only early vasopressor administration. INTERPRETATION: Late vasopressor administration was modestly associated with comorbidities and admission illness severity. One-year mortality was higher among those who received late vasopressor administration compared with only early vasopressor administration. Research to understand optimization of late vasopressor therapy administration may improve long-term mortality.

Template matching for benchmarking hospital performance in the veterans affairs healthcare system.

Comparing hospital performance in a health system is traditionally done with multilevel regression models that adjust for differences in hospitals' patient case-mix. In contrast, "template matching" compares outcomes of similar patients at different hospitals but has been used only in limited patient settings.Our objective was to test a basic template matching approach in the nationwide Veterans Affairs healthcare system (VA), compared with a more standard regression approach.We performed various simulations using observational data from VA electronic health records whereby we randomly assigned patients to "pseudo hospitals," eliminating true hospital level effects. We randomly selected a representative template of 240 patients and matched 240 patients on demographic and physiological factors from each pseudo hospital to the template. We varied hospital performance for different simulations such that some pseudo hospitals negatively impacted patient mortality.Electronic health record data of 460,213 hospitalizations at 111 VA hospitals across the United States in 2015.We assessed 30-day mortality at each pseudo hospital and identified lowest quintile hospitals by template matching and regression. The regression model adjusted for predicted 30-day mortality (as a measure of illness severity).Regression identified the lowest quintile hospitals with 100% accuracy compared with 80.3% to 82.0% for template matching when systematic differences in 30-day mortality existed.The current standard practice of risk-adjusted regression incorporating patient-level illness severity was better able to identify lower-performing hospitals than the simplistic template matching algorithm.