Impact of an electronic sepsis initiative on antibiotic use and health care facility-onset Clostridium difficile infection rates

A five-year quasi-experimental study to evaluate the impact of empiric antibiotic order sets on antibiotic use metrics among hospitalized adult patients

OBJECTIVE

Evaluation of adult antibiotic order sets (AOSs) on antibiotic stewardship metrics has been limited. The primary outcome was to evaluate the standardized antimicrobial administration ratio (SAAR). Secondary outcomes included antibiotic days of therapy (DOT) per 1,000 patient days (PD); selected antibiotic use; AOS utilization; Clostridioides difficile infection (CDI) cases; and clinicians' perceptions of the AOS via a survey following the final study phase.

DESIGN

This 5-year, single-center, quasi-experimental study comprised 5 phases from 2017 to 2022 over 10-month periods between August 1 and May 31.

SETTING

The study was conducted in a 752-bed tertiary care, academic medical center.

INTERVENTION

Our institution implemented AOSs in the electronic medical record (EMR) for common infections among hospitalized adults.

RESULTS

For the primary outcome, a statistically significant decreases in SAAR were detected from phase 1 to phase 5 (1.0 vs 0.90; P < .001). A statistically significant decreases were detected in DOT per 1,000 PD (4,884 vs 3,939; P = .001), fluoroquinolone orders (407 vs 175; P < .001), carbapenem orders (147 vs 106; P = .024), and clindamycin orders (113 vs 73; P = .01). No statistically significant change in mean vancomycin orders was detected (991 vs 902; P = .221). A statistically significant decrease in CDI cases was also detected (7.8, vs 2.4; P = .002) but may have been attributable to changes in CDI case diagnosis. Clinicians indicated that the AOSs were easy to use overall and that they helped them select the appropriate antibiotics.

CONCLUSIONS

Implementing AOS into the EMR was associated with a statistically significant reduction in SAAR, antibiotic DOT per 1,000 PD, selected antibiotic orders, and CDI cases.

Estimating Sepsis Incidence Using Administrative Data and Clinical Medical Record Review

Importance

Despite the large health burden, reliable data on sepsis epidemiology are lacking; studies using International Statistical Classification of Diseases and Related Health Problems (ICD)-coded hospital discharge diagnosis for sepsis identification suffer from limited sensitivity. Also, ICD data do not allow investigation of underlying pathogens and antimicrobial resistance.

Objectives

To generate reliable epidemiological estimates by linking data from a population-based database to a reference standard of clinical medical record review.

Design, Setting, and Participants

This was a retrospective, observational cohort study using a population-based administrative database including all acute care hospitals of the Scania region in Sweden in 2019 and 2020 to identify hospital-treated sepsis cases by ICD codes. From this database, clinical medical records were also selected for review within 6 strata defined by ICD discharge diagnosis (both with and without sepsis diagnosis). Data were analyzed from April to October 2022.

Main outcomes and measures

Hospital and population incidences of sepsis, case fatality, antimicrobial resistance, and temporal dynamics due to COVID-19 were assessed, as well as validity of ICD-10 case identification methods compared with the reference standard of clinical medical record review.

Results

Out of 295 531 hospitalizations in 2019 in the Scania region of Sweden, 997 patient medical records were reviewed, among which 457 had sepsis according to clinical criteria. Of the patients with clinical sepsis, 232 (51%) were female, and 357 (78%) had at least 1 comorbidity. The median (IQR) age of the cohort was 76 (67-85) years. The incidence of sepsis in hospitalized patients according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria in 2019 was 4.1% (95% CI, 3.6-4.5) by medical record review. This corresponds to an annual incidence rate of 747 (95% CI, 663-832) patients with sepsis per 100 000 population. No significant increase in sepsis during the COVID-19 pandemic nor a decrease in sepsis incidence when excluding COVID-19 sepsis was observed. Few sepsis cases caused by pathogens with antimicrobial resistance were found. The validity of ICD-10-based case identification in administrative data was low.

Conclusions and Relevance

In this cohort study of sepsis epidemiology, sepsis was a considerable burden to public health in Sweden. Supplying administrative data with information from clinical medical records can help to generate reliable data on sepsis epidemiology.

Association of a sepsis initiative on broad spectrum antibiotic use and outcomes in an ED population: A retrospective cohort study

INTRODUCTION

Sepsis identification and treatment is a priority for emergency department (ED) providers and payors alike. However, aggressive metrics aimed at improving sepsis care could have unintended consequences for patients who do not have sepsis.

METHODS

All ED patient visits for a one month period before and after a quality initiative to increase early antibiotic use in septic patients were included. Overall broad spectrum (BS) antibiotic use, admission rates, and mortality were compared in the 2 time periods. A more detailed chart review was performed on those who received BS antibiotics in the before and after cohorts. Patient were excluded for pregnancy, age < 18, COVID-19 infection, hospice patients, left ED against medical advice, and if antibiotics were given for prophylaxis. In BS antibiotic treated patients, we sought to determine mortality, rates of subsequent multidrug resistant (MDR) or Clostridium Difficile (CDiff) infections and rates of non-infected patients receiving BS antibiotics.

RESULTS

There were 7967 and 7407 ED visits in the pre- and post-implementation periods, respectively. Of those, BS antibiotics were administered in a total of 3.9% pre-implementation and 6.2% post-implementation (p ≤ 0.00001). Admission was more common in the post-implementation period, but overall mortality was unchanged (0.9% pre-implementation and 0.8% post-implementation, p = 0.41). After exclusions, 654 patients treated with BS antibiotics were included in the secondary analyses. Baseline characteristics were similar between the pre-implementation and post-implementation cohorts. There was no difference in the rate of CDiff infection or the proportion of patients receiving BS antibiotics who were not infected, but there was an increase in the post-implementation period in MDR infections after ED BS antibiotics, 0.72% vs. 0.35% of the entire ED cohorts, p = 0.0009.

CONCLUSIONS

We found that a QI sepsis initiative was associated with an increase in the proportion of patients who received BS antibiotics in the ED, and a small absolute increase in associated subsequent MDR infections, with no apparent effect on mortality in all ED patients or the subset treated with BS antibiotics. Further research is needed to assess the impact on all patients affected by aggressive sepsis protocols and initiatives, rather than only those with sepsis.

Effect of appropriate empirical antimicrobial therapy on mortality of patients with Gram-negative bloodstream infections: a retrospective cohort study

BACKGROUND

Little evidence exists regarding the prevalence of pathogens in bloodstream infections (BSIs), the mortality risk, and the benefit of combination therapy over monotherapy. This study aims to describe patterns of empiric antimicrobial therapy, and the epidemiology of Gram-negative pathogens, and to investigate the effect of appropriate therapy and appropriate combination therapy on the mortality of patients with BSIs.

METHODS

This was a retrospective cohort study including all patients with BSIs of Gram-negative pathogens from January 2017 to December 2022 in a Chinese general hospital. The in-hospital mortality was compared between appropriate and inappropriate therapy, and between monotherapy and combination therapy for patients receiving appropriate therapy. We used Cox regression analysis to identify factors independently associated with in-hospital mortality.

RESULTS

We included 205 patients in the study, of whom 147 (71.71%) patients received appropriate therapy compared with 58 (28.29%) who received inappropriate therapy. The most common Gram-negative pathogen was Escherichia coli (37.56%). 131 (63.90%) patients received monotherapy and 74 (36.10%) patients received combination therapy. The in-hospital mortality was significantly lower in patients administered appropriate therapy than inappropriate therapy (16.33% vs. 48.28%, p = 0.004); adjusted hazard ratio [HR] 0.55 [95% CI 0.35-0.84], p = 0.006). In-hospital mortality was also not different in combination therapy and monotherapy in the multivariate Cox regression analyses (adjusted HR 0.42 [95% CI 0.15-1.17], p = 0.096). However, combination therapy was associated with lower mortality than monotherapy in patients with sepsis or septic shock (adjusted HR 0.94 [95% CI 0.86-1.02], p = 0.047).

CONCLUSIONS

Appropriate therapy was associated with a protective effect on mortality among patients with BSIs due to Gram-negative pathogens. Combination therapy was associated with improved survival in patients with sepsis or septic shock. Clinicians need to choose optical empirical antimicrobials to improve survival outcomes in patients with BSIs.

Quantifying the breadth of antibiotic exposure in sepsis and suspected infection using spectrum scores

A retrospective cohort study. Studies to quantify the breadth of antibiotic exposure across populations remain limited. Therefore, we applied a validated method to describe the breadth of antimicrobial coverage in a multicenter cohort of patients with suspected infection and sepsis. We conducted a retrospective cohort study across 21 hospitals within an integrated healthcare delivery system of patients admitted to the hospital through the ED with suspected infection or sepsis and receiving antibiotics during hospitalization from January 1, 2012, to December 31, 2017. We quantified the breadth of antimicrobial coverage using the Spectrum Score, a numerical score from 0 to 64, in patients with suspected infection and sepsis using electronic health record data. Of 364,506 hospital admissions through the emergency department, we identified 159,004 (43.6%) with suspected infection and 205,502 (56.4%) with sepsis. Inpatient mortality was higher among those with sepsis compared to those with suspected infection (8.4% vs 1.2%; P < .001). Patients with sepsis had higher median global Spectrum Scores (43.8 [interquartile range IQR 32.0-49.5] vs 43.5 [IQR 26.8-47.2]; P < .001) and additive Spectrum Scores (114.0 [IQR 57.0-204.5] vs 87.5 [IQR 45.0-144.8]; P < .001) compared to those with suspected infection. Increased Spectrum Scores were associated with inpatient mortality, even after covariate adjustments (adjusted odds ratio per 10-point increase in Spectrum Score 1.31; 95%CI 1.29-1.33). Spectrum Scores quantify the variability in antibiotic breadth among individual patients, between suspected infection and sepsis populations, over the course of hospitalization, and across infection sources. They may play a key role in quantifying the variation in antibiotic prescribing in patients with suspected infection and sepsis.

Antibiotics: it is all about timing, isn't it?

PURPOSE OF REVIEW

Sepsis guidelines and quality measures set aggressive deadlines for administering antibiotics to patients with possible sepsis or septic shock. However, the diagnosis of sepsis is often uncertain, particularly upon initial presentation, and pressure to treat more rapidly may harm some patients by exposing them to unnecessary or inappropriate broad-spectrum antibiotics.

RECENT FINDINGS

Observational studies that report that each hour until antibiotics increases mortality often fail to adequately adjust for comorbidities and severity of illness, fail to account for antibiotics given to uninfected patients, and inappropriately blend the effects of long delays with short delays. Accounting for these factors weakens or eliminates the association between time-to-antibiotics and mortality, especially for patients without shock. These findings are underscored by analyses of the Centers for Medicaid and Medicare Services SEP-1 measure: it has increased sepsis diagnoses and broad-spectrum antibiotic use but has not improved outcomes.

SUMMARY

Clinicians are advised to tailor the urgency of antibiotics to their certainty of infection and patients' severity of illness. Immediate antibiotics are warranted for patients with possible septic shock or high likelihood of infection. Antibiotics can safely be withheld to allow for more investigation, however, in most patients with less severe illnesses if the diagnosis of infection is uncertain.

Treatment Heterogeneity in Pseudomonas aeruginosa Pneumonia

We have previously identified substantial antibiotic treatment heterogeneity, even among organism-specific and site-specific infections with treatment guidelines. Therefore, we sought to quantify the extent of treatment heterogeneity among patients hospitalized with P. aeruginosa pneumonia in the national Veterans Affairs Healthcare System from Jan-2015 to Apr-2018. Daily antibiotic exposures were mapped from three days prior to culture collection until discharge. Heterogeneity was defined as unique patterns of antibiotic treatment (drug and duration) not shared by any other patient. Our study included 5300 patients, of whom 87.5% had unique patterns of antibiotic drug and duration. Among patients receiving any initial antibiotic/s with a change to at least one anti-pseudomonal antibiotic (n = 3530, 66.6%) heterogeneity was 97.2%, while heterogeneity was 91.5% in those changing from any initial antibiotic/s to only anti-pseudomonal antibiotics (n = 576, 10.9%). When assessing heterogeneity of anti-pseudomonal antibiotic classes, irrespective of other antibiotic/s received (n = 4542, 85.7%), 50.5% had unique patterns of antibiotic class and duration, with median time to first change of three days, and a median of two changes. Real-world evidence is needed to inform the development of treatment pathways and antibiotic stewardship initiatives based on clinical outcome data, which is currently lacking in the presence of such treatment heterogeneity.

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review

Background

Sepsis is a significant cause of morbidity and mortality worldwide. Early detection of sepsis followed promptly by treatment initiation improves patient outcomes and saves lives. Hospitals are increasingly using computerized clinical decision support (CCDS) systems for the rapid identification of adult patients with sepsis.

Objective

This scoping review aims to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of adult inpatients with sepsis.

Methods

The protocol for this scoping review was previously published. A total of 10 electronic databases (MEDLINE, Embase, CINAHL, the Cochrane database, LILACS [Latin American and Caribbean Health Sciences Literature], Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and PQDT [ProQuest Dissertations and Theses]) were comprehensively searched using terms for sepsis, CCDS, and detection to identify relevant studies. Title, abstract, and full-text screening were performed by 2 independent reviewers using predefined eligibility criteria. Data charting was performed by 1 reviewer with a second reviewer checking a random sample of studies. Any disagreements were discussed with input from a third reviewer. In this review, we present the results for adult inpatients, including studies that do not specify patient age.

Results

A search of the electronic databases retrieved 12,139 studies following duplicate removal. We identified 124 studies for inclusion after title, abstract, full-text screening, and hand searching were complete. Nearly all studies (121/124, 97.6%) were published after 2009. Half of the studies were journal articles (65/124, 52.4%), and the remainder were conference abstracts (54/124, 43.5%) and theses (5/124, 4%). Most studies used a single cohort (54/124, 43.5%) or before-after (42/124, 33.9%) approach. Across all 124 included studies, patient outcomes were the most frequently reported outcomes (107/124, 86.3%), followed by sepsis treatment and management (75/124, 60.5%), CCDS usability (14/124, 11.3%), and cost outcomes (9/124, 7.3%). For sepsis identification, the systemic inflammatory response syndrome criteria were the most commonly used, alone (50/124, 40.3%), combined with organ dysfunction (28/124, 22.6%), or combined with other criteria (23/124, 18.5%). Over half of the CCDS systems (68/124, 54.8%) were implemented alongside other sepsis-related interventions.

Conclusions

The current body of literature investigating the implementation of CCDS systems for the early detection of adult inpatients with sepsis is extremely diverse. There is substantial variability in study design, CCDS criteria and characteristics, and outcomes measured across the identified literature. Future research on CCDS system usability, cost, and impact on sepsis morbidity is needed.

International Registered Report Identifier (IRRID)

RR2-10.2196/24899

Antimicrobial Stewardship in the ICU

Increasing rates of infection and multidrug-resistant pathogens, along with a high use of antimicrobial therapy, make the intensive care unit (ICU) an ideal setting for implementing and supporting antimicrobial stewardship efforts. Overuse of antimicrobial agents is common in the ICU, as practitioners are challenged daily with achieving early, appropriate empiric antimicrobial therapy to improve patient outcomes. While early antimicrobial stewardship programs focused on the financial implications of antimicrobial overuse, current goals of stewardship programs align closely with those of critical care providers-to optimize patient outcomes, reduce development of resistance, and minimize adverse outcomes associated with antibiotic overuse and misuse such as acute kidney injury and Clostridioides difficile-associated disease. Significant opportunities exist in the ICU for critical care clinicians to support stewardship practices at the bedside, including thoughtful and restrained initiation of antimicrobial therapy, use of biomarkers in addition to rapid diagnostics, Staphylococcus aureus screening, and traditional microbiologic culture and susceptibilities to guide antibiotic de-escalation, and use of the shortest duration of therapy that is clinically appropriate. Integration of critical care practitioners into the initiatives of antimicrobial stewardship programs is key to their success. This review summarizes key components of antimicrobial stewardship programs and mechanisms for critical care practitioners to share the responsibility for antimicrobial stewardship.

Association Between Implementation of the Severe Sepsis and Septic Shock Early Management Bundle Performance Measure and Outcomes in Patients With Suspected Sepsis in US Hospitals

IMPORTANCE

In October 2015, the Centers for Medicare & Medicaid Services began requiring US hospitals to report adherence to the Severe Sepsis and Septic Shock Early Management Bundle (SEP-1).

OBJECTIVE

To evaluate the association of SEP-1 implementation with sepsis treatment patterns and outcomes in diverse hospitals.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study with interrupted time-series analysis and logistic regression models was conducted among adults admitted to 114 hospitals from October 2013 to December 2017 with suspected sepsis (blood culture orders, ≥2 systemic inflammatory response syndrome criteria, and acute organ dysfunction) within 24 hours of hospital arrival. Data analysis was conducted from September 2020 to September 2021.

EXPOSURES

SEP-1 implementation in the fourth quarter (Q4) of 2015.

MAIN OUTCOMES AND MEASURES

The primary outcome was quarterly rates of risk-adjusted short-term mortality (in-hospital death or discharge to hospice). Secondary outcomes included lactate testing and administration of anti-methicillin-resistant Staphylococcus aureus (MRSA) or antipseudomonal β-lactam antibiotics within 24 hours of hospital arrival. Generalized estimating equations with robust sandwich variances were used to fit logistic regression models to assess for changes in level or trends in these outcomes, adjusting for baseline characteristics and severity of illness.

RESULTS

The cohort included 117 510 patients (median [IQR] age, 67 years [55-78] years; 60 530 [51.5%] men and 56 980 [48.5%] women) with suspected sepsis. Lactate testing rates increased from 55.1% (95% CI, 53.9%-56.2%) in Q4 of 2013 to 76.7% (95% CI, 75.4%-78.0%) in Q4 of 2017, with a significant level change following SEP-1 implementation (odds ratio [OR], 1.34; 95% CI, 1.04-1.74). There were increases in use of anti-MRSA antibiotics (19.8% [95% CI, 18.9%-20.7%] in Q4 of 2013 to 26.3% [95% CI, 24.9%-27.7%] in Q4 of 2017) and antipseudomonal antibiotics (27.7% [95% CI, 26.7%-28.8%] in Q4 of 2013 to 40.5% [95% CI, 38.9%-42.0%] in Q4 of 2017), but these trends preceded SEP-1 and did not change with SEP-1 implementation. Unadjusted short-term mortality rates were similar in the pre-SEP-1 period (Q4 of 2013 through Q3 of 2015) vs the post-SEP-1 period (Q1 of 2016 through Q4 of 2017) (20.3% [95% CI, 20.0%-20.6%] vs 20.4% [95% CI, 20.1%-20.7%]), and SEP-1 implementation was not associated with changes in level (OR, 0.94; 95% CI, 0.68-1.29) or trend (OR, 1.00; 95% CI, 0.97-1.04) for risk-adjusted short-term mortality rates.

CONCLUSIONS AND RELEVANCE

In this cohort study, SEP-1 implementation was associated with an immediate increase in lactate testing rates, no change in already-increasing rates of broad-spectrum antibiotic use, and no change in short-term mortality rates for patients with suspected sepsis. Other approaches to decrease sepsis mortality may be warranted.

The Impact of CMS SEP-1 Core Measure Implementation on Antibacterial Utilization: a retrospective multicenter longitudinal cohort study with interrupted time-series analysis

BACKGROUND

The impact of the U.S. Centers for Medicare and Medicaid Services (CMS) Severe Sepsis and Septic Shock: Management Bundle (SEP-1) Core Measure on overall antibacterial utilization is unknown.

METHODS

We performed a retrospective multicenter longitudinal cohort study with interrupted time series analysis to determine the impact of SEP-1 implementation on antibacterial utilization and patient outcomes. All adult patients admitted to 26 hospitals between October 1, 2014, and September 30, 2015 (the "SEP-1 preparation period") and between November 1, 2015, and October 31, 2016 (the "SEP-1 implementation period") were evaluated for inclusion.The primary outcome was total antibacterial utilization measured as days of therapy (DOT) per 1,000 patient days.

RESULTS

The study cohort included 701,055 eligible patient admissions and 4.2 million patient days. Overall antibacterial utilization increased 2% each month during SEP-1 preparation (RR=1.02 per month [95% CI 1.00-1.04]; p=0.02). Cumulatively, the mean monthly DOT/1,000 patient-days increased 24.4% [95% CI 18.0, 38.8] over the entire study period (October 2014-October 2016). The rate of sepsis diagnosis/1,000 patients increased 2% each month during SEP-1 preparation (RR=1.02 per month [95% CI 1.00-1.04]; p=0.04). The rate of all-cause mortality/1,000 patients decreased during the study period (SEP-1 preparation RR=0.95 [0.92-0.98]; p=0.001 and SEP-1 implementation RR=0.98 [95% CI 0.97-1.00]; p=0.01). Cumulatively, the monthly mean all-cause mortality/1,000 patients declined 38.5% [95% CI 25.9, 48.0] over the study period.

CONCLUSIONS

Announcement and implementation of the CMS SEP-1 process measure was associated with increased diagnosis of sepsis and antibacterial utilization and decreased mortality among hospitalized patients.

Electronic early notification of sepsis in hospitalized ward patients: a study protocol for a stepped-wedge cluster randomized controlled trial

Background

To evaluate the effect of screening for sepsis using an electronic sepsis alert vs. no alert in hospitalized ward patients on 90-day in-hospital mortality.

Methods

The SCREEN trial is designed as a stepped-wedge cluster randomized controlled trial. Hospital wards (total of 45 wards, constituting clusters in this design) are randomized to have active alert vs. masked alert, 5 wards at a time, with each 5 wards constituting a sequence. The study consists of ten 2-month periods with a phased introduction of the intervention. In the first period, all wards have a masked alert for 2 months. Afterwards the intervention (alert system) is implemented in a new sequence every 2-month period until the intervention is implemented in all sequences. The intervention includes the implementation of an electronic alert system developed in the hospital electronic medical records based on the quick sequential organ failure assessment (qSOFA). The alert system sends notifications of “possible sepsis alert” to the bedside nurse, charge nurse, and primary medical team and requires an acknowledgment in the health information system from the bedside nurse and physician. The calculated sample size is 65,250. The primary endpoint is in-hospital mortality by 90 days.

Discussion

The trial started on October 1, 2019, and is expected to complete patient follow-up by the end of October 2021.

Trial registration

ClinicalTrials.gov NCT04078594. Registered on September 6, 2019

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05562-5.

Identifying High-Risk Subphenotypes and Associated Harms From Delayed Antibiotic Orders and Delivery

OBJECTIVES

Early antibiotic administration is a central component of sepsis guidelines, and delays may increase mortality. However, prior studies have examined the delay to first antibiotic administration as a single time period even though it contains two distinct processes: antibiotic ordering and antibiotic delivery, which can each be targeted for improvement through different interventions. The objective of this study was to characterize and compare patients who experienced order or delivery delays, investigate the association of each delay type with mortality, and identify novel patient subphenotypes with elevated risk of harm from delays.

DESIGN

Retrospective analysis of multicenter inpatient data.

SETTING

Two tertiary care medical centers (2008-2018, 2006-2017) and four community-based hospitals (2008-2017).

PATIENTS

All patients admitted through the emergency department who met clinical criteria for infection.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patient demographics, vitals, laboratory values, medication order and administration times, and in-hospital survival data were obtained from the electronic health record. Order and delivery delays were calculated for each admission. Adjusted logistic regression models were used to examine the relationship between each delay and in-hospital mortality. Causal forests, a machine learning method, was used to identify a high-risk subgroup. A total of 60,817 admissions were included, and delays occurred in 58% of patients. Each additional hour of order delay (odds ratio, 1.04; 95% CI, 1.03-1.05) and delivery delay (odds ratio, 1.05; 95% CI, 1.02-1.08) was associated with increased mortality. A patient subgroup identified by causal forests with higher comorbidity burden, greater organ dysfunction, and abnormal initial lactate measurements had a higher risk of death associated with delays (odds ratio, 1.07; 95% CI, 1.06-1.09 vs odds ratio, 1.02; 95% CI, 1.01-1.03).

CONCLUSIONS

Delays in antibiotic ordering and drug delivery are both associated with a similar increase in mortality. A distinct subgroup of high-risk patients exist who could be targeted for more timely therapy.

Infectious Diseases Society of America Position Paper: Recommended Revisions to the National Severe Sepsis and Septic Shock Early Management Bundle (SEP-1) Sepsis Quality Measure

The Centers for Medicare & Medicaid Services' Severe Sepsis and Septic Shock Early Management Bundle (SEP-1) measure has appropriately established sepsis as a national priority. However, the Infectious Diseases Society of America (IDSA and five additional endorsing societies) is concerned about SEP-1's potential to drive antibiotic overuse because it does not account for the high rate of sepsis overdiagnosis and encourages aggressive antibiotics for all patients with possible sepsis, regardless of the certainty of diagnosis or severity of illness. IDSA is also concerned that SEP-1's complex "time zero" definition is not evidence-based and is prone to inter-observer variation. In this position paper, IDSA outlines several recommendations aimed at reducing the risk of unintended consequences of SEP-1 while maintaining focus on its evidence-based elements. IDSA's core recommendation is to limit SEP-1 to septic shock, for which the evidence supporting the benefit of immediate antibiotics is greatest. Prompt empiric antibiotics are often appropriate for suspected sepsis without shock, but IDSA believes there is too much heterogeneity and difficulty defining this population, uncertainty about the presence of infection, and insufficient data on the necessity of immediate antibiotics to support a mandatory treatment standard for all patients in this category. IDSA believes guidance on managing possible sepsis without shock is more appropriate for guidelines that can delineate the strengths and limitations of supporting evidence and allow clinicians discretion in applying specific recommendations to individual patients. Removing sepsis without shock from SEP-1 will mitigate the risk of unnecessary antibiotic prescribing for noninfectious syndromes, simplify data abstraction, increase measure reliability, and focus attention on the population most likely to benefit from immediate empiric broad-spectrum antibiotics.

Impact of the Centers for Medicare and Medicaid Services Sepsis Core Measure on Antibiotic Use

BACKGROUND

The Centers for Medicare and Medicaid Services (CMS) implemented a core measure sepsis (SEP-1) bundle in 2015. One element was initiation of broad-spectrum antibiotics within 3 hours of diagnosis. The policy has the potential to increase antibiotic use and Clostridioides difficile infection (CDI). We evaluated the impact of SEP-1 implementation on broad-spectrum antibiotic use and CDI occurrence rates.

METHODS

Monthly adult antibiotic data for 4 antibiotic categories (surgical prophylaxis, broad-spectrum for community-acquired infections, broad-spectrum for hospital-onset/multidrug-resistant [MDR] organisms, and anti-methicillin-resistant Staphylococcus aureus [MRSA]) from 111 hospitals participating in the Clinical Data Base Resource Manager were evaluated in periods before (October 2014-September 2015) and after (October 2015-June 2017) policy implementation. Interrupted time series analyses, using negative binomial regression, evaluated changes in antibiotic category use and CDI rates.

RESULTS

At the hospital level, there was an immediate increase in the level of broad-spectrum agents for hospital-onset/MDR organisms (+2.3%, P = .0375) as well as a long-term increase in trend (+0.4% per month, P = .0273). There was also an immediate increase in level of overall antibiotic use (+1.4%, P = .0293). CDI rates unexpectedly decreased at the time of SEP-1 implementation. When analyses were limited to patients with sepsis, there was a significant level increase in use of all antibiotic categories at the time of SEP-1 implementation.

CONCLUSIONS

SEP-1 implementation was associated with immediate and long-term increases in broad-spectrum hospital-onset/MDR organism antibiotics. Antimicrobial stewardship programs should evaluate sepsis treatment for opportunities to de-escalate broad therapy as indicated.

Early Detection of Septic Shock Onset Using Interpretable Machine Learners

BACKGROUND

Developing a decision support system based on advances in machine learning is one area for strategic innovation in healthcare. Predicting a patient's progression to septic shock is an active field of translational research. The goal of this study was to develop a working model of a clinical decision support system for predicting septic shock in an acute care setting for up to 6 h from the time of admission in an integrated healthcare setting.

METHOD

Clinical data from Electronic Health Record (EHR), at encounter level, were used to build a predictive model for progression from sepsis to septic shock up to 6 h from the time of admission; that is, T = 1, 3, and 6 h from admission. Eight different machine learning algorithms (Random Forest, XGBoost, C5.0, Decision Trees, Boosted Logistic Regression, Support Vector Machine, Logistic Regression, Regularized Logistic, and Bayes Generalized Linear Model) were used for model development. Two adaptive sampling strategies were used to address the class imbalance. Data from two sources (clinical and billing codes) were used to define the case definition (septic shock) using the Centers for Medicare & Medicaid Services (CMS) Sepsis criteria. The model assessment was performed using Area under Receiving Operator Characteristics (AUROC), sensitivity, and specificity. Model predictions for each feature window (1, 3 and 6 h from admission) were consolidated.

RESULTS

Retrospective data from April 2005 to September 2018 were extracted from the EHR, Insurance Claims, Billing, and Laboratory Systems to create a dataset for septic shock detection. The clinical criteria and billing information were used to label patients into two classes-septic shock patients and sepsis patients at three different time points from admission, creating two different case-control cohorts. Data from 45,425 unique in-patient visits were used to build 96 prediction models comparing clinical-based definition versus billing-based information as the gold standard. Of the 24 consolidated models (based on eight machine learning algorithms and three feature windows), four models reached an AUROC greater than 0.9. Overall, all the consolidated models reached an AUROC of at least 0.8820 or higher. Based on the AUROC of 0.9483, the best model was based on Random Forest, with a sensitivity of 83.9% and specificity of 88.1%. The sepsis detection window at 6 h outperformed the 1 and 3-h windows. The sepsis definition based on clinical variables had improved performance when compared to the sepsis definition based on only billing information.

CONCLUSION

This study corroborated that machine learning models can be developed to predict septic shock using clinical and administrative data. However, the use of clinical information to define septic shock outperformed models developed based on only administrative data. Intelligent decision support tools can be developed and integrated into the EHR and improve clinical outcomes and facilitate the optimization of resources in real-time.

Surgical Infection Society Research Priorities: A Narrative Review of Fourteen Years of Progress

Background: In 2006, the Surgical Infection Society (SIS) utilized a modified Delphi approach to define 15 specific priority research questions that remained unanswered in the field of surgical infections. The aim of the current study was to evaluate the scientific progress achieved during the ensuing period in answering each of the 15 research questions and to determine if additional research in these fields is warranted. Methods: For each of the questions, a literature search using the National Center for Biotechnology Information (NCBI) was performed by the Scientific Studies Committee of the SIS to identify studies that attempted to address each of the defined questions. This literature was analyzed and summarized. The data on each question were evaluated by a surgical infections expert to determine if the question was answered definitively or remains unanswered. Results: All 15 priority research questions were studied in the last 14 years; six questions (40%) were definitively answered and 9 questions (60%) remain unanswered in whole or in part, mainly because of the low quality of the studies available on this topic. Several of the 9 unanswered questions were deemed to remain research priorities in 2020 and warrant further investigation. These included, for example, the role of empiric antimicrobial agents in nosocomial infections, the use of inotropes/vasopressors versus volume loading to raise the mean arterial pressure, and the role of increased antimicrobial dosing and frequency in the obese patient. Conclusions: Several surgical infection-related research questions prioritized in 2006 remain unanswered. Further high-quality research is required to provide a definitive answer to many of these priority knowledge gaps. An updated research agenda by the SIS is warranted at this time to define research priorities for the future.

Developing an Institute for Health Care Delivery Science: successes, challenges, and solutions in the first five years

Medical knowledge is increasing at an exponential rate. At the same time, unexplained variations in practice and patient outcomes and unacceptable rates of medical errors and inefficiencies in health care delivery have emerged. Our Institute for Health Care Delivery Science (I-HDS) began in 2014 as a novel platform to conduct multidisciplinary healthcare delivery research. We followed ten strategies to develop a successful institute with excellence in methodology and strong understanding of the value of team science. Our work was organized around five hubs: 1) Quality/Process Improvement and Systematic Review, 2) Comparative Effectiveness Research, Pragmatic Clinical Trials, and Predictive Analytics, 3) Health Economics and Decision Modeling, 4) Qualitative, Survey, and Mixed Methods, and 5) Training and Mentoring. In the first 5 years of the I-HDS, we have identified opportunities for change in clinical practice through research using our health system's electronic health record (EHR) data, and designed programs to educate clinicians in the value of research to improve patient care and recognize efficiencies in processes. Testing the value of several model interventions has guided prioritization of evidence-based quality improvements. Some of the changes in practice have already been embedded in the EHR workflow successfully. Development and sustainability of the I-HDS has been fostered by a mix of internal and external funding, including philanthropic foundations. Challenges remain due to the highly competitive funding environment and changes needed to adapt the EHR to healthcare delivery research. Further stakeholder engagement and culture change working with hospital leadership and I-HDS core and affiliate members continues.

Prevalence of Antibiotic-Resistant Pathogens in Culture-Proven Sepsis and Outcomes Associated With Inadequate and Broad-Spectrum Empiric Antibiotic Use

IMPORTANCE

Broad-spectrum antibiotics are recommended for all patients with suspected sepsis to minimize the risk of undertreatment. However, little is known regarding the net prevalence of antibiotic-resistant pathogens across all patients with community-onset sepsis or the outcomes associated with unnecessarily broad empiric treatment.

OBJECTIVE

To elucidate the epidemiology of antibiotic-resistant pathogens and the outcomes associated with both undertreatment and overtreatment in patients with culture-positive community-onset sepsis.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included 17 430 adults admitted to 104 US hospitals between January 2009 and December 2015 with sepsis and positive clinical cultures within 2 days of admission. Data analysis took place from January 2018 to December 2019.

EXPOSURES

Inadequate empiric antibiotic therapy (ie, ≥1 pathogen nonsusceptible to all antibiotics administered on the first or second day of treatment) and unnecessarily broad empiric therapy (ie, active against methicillin-resistant Staphylococcus aureus [MRSA]; vancomycin-resistant Enterococcus [VRE]; ceftriaxone-resistant gram-negative [CTX-RO] organisms, including Pseudomonas aeruginosa; or extended-spectrum β-lactamase [ESBL] gram-negative organisms when none of these were isolated).

MAIN OUTCOMES AND MEASURES

Prevalence and empiric treatment rates for antibiotic-resistant organisms and associations of inadequate and unnecessarily broad empiric therapy with in-hospital mortality were assessed, adjusting for baseline characteristics and severity of illness.

RESULTS

Of 17 430 patients with culture-positive community-onset sepsis (median [interquartile range] age, 69 [57-81] years; 9737 [55.9%] women), 2865 (16.4%) died in the hospital. The most common culture-positive sites were urine (9077 [52.1%]), blood (6968 [40.0%]), and the respiratory tract (2912 [16.7%]). The most common pathogens were Escherichia coli (5873 [33.7%]), S aureus (3706 [21.3%]), and Streptococcus species (2361 [13.5%]). Among 15 183 cases in which all antibiotic-pathogen susceptibility combinations could be calculated, most (12 398 [81.6%]) received adequate empiric antibiotics. Empiric therapy targeted resistant organisms in 11 683 of 17 430 cases (67.0%; primarily vancomycin and anti-Pseudomonal β-lactams), but resistant organisms were uncommon (MRSA, 2045 [11.7%]; CTX-RO, 2278 [13.1%]; VRE, 360 [2.1%]; ESBLs, 133 [0.8%]). The net prevalence for at least 1 resistant gram-positive organism (ie, MRSA or VRE) was 13.6% (2376 patients), and for at least 1 resistant gram-negative organism (ie, CTX-RO, ESBL, or CRE), it was 13.2% (2297 patients). Both inadequate and unnecessarily broad empiric antibiotics were associated with higher mortality after detailed risk adjustment (inadequate empiric antibiotics: odds ratio, 1.19; 95% CI, 1.03-1.37; P = .02; unnecessarily broad empiric antibiotics: odds ratio, 1.22; 95% CI, 1.06-1.40; P = .007).

CONCLUSIONS AND RELEVANCE

In this study, most patients with community-onset sepsis did not have resistant pathogens, yet broad-spectrum antibiotics were frequently administered. Both inadequate and unnecessarily broad empiric antibiotics were associated with higher mortality. These findings underscore the need for better tests to rapidly identify patients with resistant pathogens and for more judicious use of broad-spectrum antibiotics for empiric sepsis treatment.

Performance of the MEDS score in predicting mortality among emergency department patients with a suspected infection: a meta-analysis

OBJECTIVES

To carry out a meta-analysis to examine the prognostic performance of the Mortality in Emergency Department Sepsis (MEDS) score in predicting mortality among emergency department patients with a suspected infection.

METHODS

Electronic databases-PubMed, Embase, Scopus, EBSCO and the Cochrane Library-were searched for eligible articles from their respective inception through February 2019. Sensitivity, specificity, likelihood ratios and receiver operator characteristic area under the curve were calculated. Subgroup analyses were performed to explore the prognostic performance of MEDS in selected populations.

RESULTS

We identified 24 studies involving 21 246 participants. The pooled sensitivity of MEDS to predict mortality was 79% (95% CI 72% to 84%); specificity was 74% (95% CI 68% to 80%); positive likelihood ratio 3.07 (95% CI 2.47 to 3.82); negative likelihood ratio 0.29 (95% CI 0.22 to 0.37) and area under the curve 0.83 (95% CI 0.80 to 0.86). Significant heterogeneity was seen among included studies. Meta-regression analyses showed that the time at which the MEDS score was measured and the cut-off value used were important sources of heterogeneity.

CONCLUSION

The MEDS score has moderate accuracy in predicting mortality among emergency department patients with a suspected infection. A study comparison MEDS and qSOFA in the same population is needed.

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy

PURPOSE

Early clinical recognition of sepsis can be challenging. With the advancement of machine learning, promising real-time models to predict sepsis have emerged. We assessed their performance by carrying out a systematic review and meta-analysis.

METHODS

A systematic search was performed in PubMed, Embase.com and Scopus. Studies targeting sepsis, severe sepsis or septic shock in any hospital setting were eligible for inclusion. The index test was any supervised machine learning model for real-time prediction of these conditions. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology, with a tailored Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklist to evaluate risk of bias. Models with a reported area under the curve of the receiver operating characteristic (AUROC) metric were meta-analyzed to identify strongest contributors to model performance.

RESULTS

After screening, a total of 28 papers were eligible for synthesis, from which 130 models were extracted. The majority of papers were developed in the intensive care unit (ICU, n = 15; 54%), followed by hospital wards (n = 7; 25%), the emergency department (ED, n = 4; 14%) and all of these settings (n = 2; 7%). For the prediction of sepsis, diagnostic test accuracy assessed by the AUROC ranged from 0.68-0.99 in the ICU, to 0.96-0.98 in-hospital and 0.87 to 0.97 in the ED. Varying sepsis definitions limit pooling of the performance across studies. Only three papers clinically implemented models with mixed results. In the multivariate analysis, temperature, lab values, and model type contributed most to model performance.

CONCLUSION

This systematic review and meta-analysis show that on retrospective data, individual machine learning models can accurately predict sepsis onset ahead of time. Although they present alternatives to traditional scoring systems, between-study heterogeneity limits the assessment of pooled results. Systematic reporting and clinical implementation studies are needed to bridge the gap between bytes and bedside.

Timeliness of antibiotics for patients with sepsis and septic shock

For many years, sepsis guidelines have focused on early administration of antibiotics. While this practice may benefit some patients, for others it might have detrimental consequences. The increasingly shortened timeframes in which administration of antibiotics is recommended, have forced physicians to sacrifice diagnostic accuracy for speed, encouraging the overuse of antibiotics. The evidence supporting this practice is based on retrospective data, with all the limitations attached, while the only randomized trial on this subject does not show a mortality benefit from early administration of antibiotics in a population of patients with sepsis as often seen in the emergency department (ED). Physicians are challenged to treat patients suspected of having sepsis within a short period of time, while the real challenge should be to identify patients who would not be harmed by withholding treatment with antibiotics until the diagnosis of infection with a bacterial origin is confirmed and the appropriateness of a course of antibiotics can be evaluated more adequately. Therefore, in the general population of patients with sepsis, taking the time to gather additional data to confirm the diagnosis should be encouraged without a specific timeframe, although physicians should be encouraged to perform an adequate work-up as soon as possible. Patients with suspected sepsis and signs of shock should immediately be treated with antibiotics, as there is no margin for error.

Early Infectious Disease Consultation Is Associated With Lower Mortality in Patients With Severe Sepsis or Septic Shock Who Complete the 3-Hour Sepsis Treatment Bundle

Objective

Severe sepsis and septic shock (SS/SS) treatment bundles reduce mortality, and early infectious diseases (ID) consultation also improves patient outcomes. We retrospectively examined whether early ID consultation further improves outcomes in Emergency Department (ED) patients with SS/SS who complete the sepsis bundle.

Method

We included 248 adult ED patients with SS/SS who completed the 3-hour bundle. Patients with ID consultation within 12 hours of ED triage (n = 111; early ID) were compared with patients who received standard care (n = 137) for in-hospital mortality, 30-day readmission, length of hospital stay (LOS), and antibiotic management. A competing risk survival analysis model compared risks of in-hospital mortality and discharge alive between groups.

Results

In-hospital mortality was lower in the early ID group unadjusted (24.3% vs 38.0%, P = .02) and adjusted for covariates (odds ratio, 0.47; 95% confidence interval (CI), 0.25–0.89; P = .02). There was no significant difference in 30-day readmission (22.6% vs 23.5%, P = .89) or median LOS (10.2 vs 12.1 days, P = .15) among patients who survived. A trend toward shorter time to antibiotic de-escalation in the early ID group (log-rank test P = .07) was observed. Early ID consultation was protective of in-hospital mortality (adjusted subdistribution hazard ratio (asHR), 0.60; 95% CI 0.36–1.00, P = .0497) and predictive of discharge alive (asHR 1.58, 95% CI, 1.11–2.23; P-value .01) after adjustment.

Conclusions

Among patients receiving the SS/SS bundle, early ID consultation was associated with a 40% risk reduction for in-hospital mortality. The impact of team-based care and de-escalation on SS/SS outcomes warrants further study.

Recent advances in understanding the epidemiology of healthcare-associated infections

Since the 2014 publication of updates to the Society for Healthcare Epidemiology of America (SHEA) compendium of strategies to reduce healthcare-associated infections, there have been several advances in understanding the epidemiology of these diseases. This review article captures many of the key advances but does not include all of them.

Towards precision medicine in sepsis: a position paper from the European Society of Clinical Microbiology and Infectious Diseases

BACKGROUND

Our current understanding of the pathophysiology and management of sepsis is associated with a lack of progress in clinical trials, which partly reflects insufficient appreciation of the heterogeneity of this syndrome. Consequently, more patient-specific approaches to treatment should be explored.

AIMS

To summarize the current evidence on precision medicine in sepsis, with an emphasis on translation from theory to clinical practice. A secondary objective is to develop a framework enclosing recommendations on management and priorities for further research.

SOURCES

A global search strategy was performed in the MEDLINE database through the PubMed search engine (last search December 2017). No restrictions of study design, time, or language were imposed.

CONTENT

The focus of this Position Paper is on the interplay between therapies, pathogens, and the host. Regarding the pathogen, microbiologic diagnostic approaches (such as blood cultures (BCs) and rapid diagnostic tests (RDTs)) are discussed, as well as targeted antibiotic treatment. Other topics include the disruption of host immune system and the use of biomarkers in sepsis management, patient stratification, and future clinical trial design. Lastly, personalized antibiotic treatment and stewardship are addressed (Fig. 1).

IMPLICATIONS

A road map provides recommendations and future perspectives. RDTs and identifying drug-response phenotypes are clear challenges. The next step will be the implementation of precision medicine to sepsis management, based on theranostic methodology. This highly individualized approach will be essential for the design of novel clinical trials and improvement of care pathways.

A Comparison of the Quick-SOFA and Systemic Inflammatory Response Syndrome Criteria for the Diagnosis of Sepsis and Prediction of Mortality: A Systematic Review and Meta-Analysis

BACKGROUND

Several studies were published to validate the quick Sepsis-related Organ Failure Assessment (qSOFA), namely in comparison with the systemic inflammatory response syndrome (SIRS) criteria. We performed a systematic review and meta-analysis with the aim of comparing the qSOFA and SIRS in patients outside the ICU.

METHODS

We searched MEDLINE, CINAHL, and the Web of Science database from February 23, 2016 until June 30, 2017 to identify full-text English-language studies published after the Sepsis-3 publication comparing the qSOFA and SIRS and their sensitivity or specificity in diagnosing sepsis, as well as hospital and ICU length of stay and hospital mortality. Data extraction from the selected studies followed the recommendations of the Meta-analyses of Observational Studies in Epidemiology group and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

RESULTS

From 4,022 citations, 10 studies met the inclusion criteria. Pooling all the studies, a total of 229,480 patients were evaluated. The meta-analysis of sensitivity for the diagnosis of sepsis comparing the qSOFA and SIRS was in favor of SIRS (risk ratio [RR], 1.32; 95% CI, 0.40-2.24; P < .0001; I² = 100%). One study described the specificity for the diagnosis of infection comparing SIRS (84.4%; 95% CI, 76.2-90.6) with the qSOFA (97.3%; 95% CI < 92.1-99.4); the qSOFA demonstrated better specificity. The meta-analysis of the area under the receiver operating characteristic curve of six studies comparing the qSOFA and SIRS favored the qSOFA (RR, 0.03; 95% CI, 0.01-0.05; P = .002; I² = 48%) as a predictor of inhospital mortality.

CONCLUSIONS

The SIRS was significantly superior to the qSOFA for sepsis diagnosis, and the qSOFA was slightly better than the SIRS in predicting hospital mortality. The association of both criteria could provide a better model to initiate or escalate therapy in patients with sepsis.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017067645.