Variation in Identifying Sepsis and Organ Dysfunction Using Administrative Versus Electronic Clinical Data and Impact on Hospital Outcome Comparisons

Impacts of the COVID-19 pandemic on sepsis incidence, etiology and hospitalization costs in France: a retrospective observational study

BACKGROUND

Sepsis is a serious medical condition that causes long-term morbidity and high mortality, annually affecting millions of people worldwide. The COVID-19 pandemic may have impacted its burden. This study aimed to estimate the impact of the COVID-19 pandemic on sepsis incidence, etiology and associated hospitalization costs in metropolitan France.

METHODS

This retrospective observational study used data drawn from a cohort of hospitalized sepsis patients in France's national healthcare database. Sepsis was identified through both explicit International Classification of Diseases 10th revision (ICD-10) codes (E-sepsis) and implicit codes (I-sepsis). Participants included all patients aged 15 years or older hospitalized with E-sepsis or I-sepsis in metropolitan France between January 1, 2018, and December 31, 2022. Patient and hospital stay characteristics were described by sepsis type (E-sepsis, I-sepsis) and overall. The distribution of sepsis etiology was estimated for each year. Annual incidence rates were estimated overall and by sepsis type and etiology. Total and median per-stay hospitalization costs were calculated.

RESULTS

The total age- and sex-standardized sepsis incidence rate per 100,000 increased slightly from 2018 (446, 95% CI 444.2 to 447.7) to 2020 (457, 95% CI 455.1 to 458.6) and then decreased in 2022 (382, 95% CI 380.2 to 383.7) (p <.0001). Incidence rates decreased for both E-sepsis and bacterial sepsis during the pandemic period, whereas I-sepsis incidence increased in 2020 and 2021, associated with a marked increase in viral sepsis and co-infections (p <.0001 for E- and I-sepsis). Viral sepsis represented about 10% of all sepsis cases during the pandemic, but only about 1% prior to the pandemic. Total sepsis-associated hospitalization costs and extra medication costs increased during the pandemic. Characteristics of patients and their hospital stays were overall stable over the five-year study period.

CONCLUSIONS

The COVID-19 pandemic led to a higher burden of sepsis in French hospitals and an increase in hospital stay costs. Critically, our study highlights the need for introducing more explicit viral sepsis codes within the ICD classification system and for achieving a consensus on its definition in order to robustly estimate sepsis incidence.

Admissions, mortality and financial burden associated with acute hospitalisations for sepsis between 2006 and 2018: A national population-level study

Background

We assessed the healthcare and economic burden of sepsis in adult hospitalised patients in Wales, UK.

Methods

We analysed hospital admissions to all acute hospitals in Wales via the Secure Anonymised Information Linkage Databank. We included all adult patients, 2006-2018, with an inpatient admission including one or more explicit sepsis codes.

Results

38,564 patients had at least one admission for sepsis between 2006 and 2018. Most persons (86.7%) had just one admission. 3398 patients (8.4%) were admitted to ICU. The number of admissions increased yearly over the study period from 1548 in 2006 to 8708 in 2018. The largest annual increase (141.7% compared to the previous year) occurred in 2017. Admission numbers increased disproportionately amongst patients with high levels of comorbidities, but changes were consistent across all age groups, areas of deprivation and ICU admissions. Estimated inpatient sepsis costs were £340.34 million in total during the study period. The average cost per hospital spell was £7270. Patients readmitted to the hospital for sepsis amassed estimated treatment costs of over £72 million during the study period. Out of the 38,564 persons, 21,275 (55.2%) died within 3 years of their first admission. Inpatient mortality halved from 40.5% to 19.5%, and there was a trend towards reduced mortality at 6 months, 1 and 3 years post hospital discharge.

Conclusion

Sepsis related hospital admissions are increasing over time and still likely to be underreported. Although mortality appears to have fallen, prolonged hospitalisation and readmissions place a significant burden on healthcare system resources and costs.

Sepsis in silico: definition, development and application of an electronic phenotype for sepsis

Repurposing electronic health record (EHR) or electronic medical record (EMR) data holds significant promise for evidence-based epidemic intelligence and research. Key challenges include sepsis recognition by physicians and issues with EHR and EMR data. Recent advances in data-driven techniques, alongside initiatives like the Surviving Sepsis Campaign and the Severe Sepsis and Septic Shock Management Bundle (SEP-1), have improved sepsis definition, early detection, subtype characterization, prognostication and personalized treatment. This includes identifying potential biomarkers or digital signatures to enhance diagnosis, guide therapy and optimize clinical management. Machine learning applications play a crucial role in identifying biomarkers and digital signatures associated with sepsis and its sub-phenotypes. Additionally, electronic phenotyping, leveraging EHR and EMR data, has emerged as a valuable tool for evidence-based sepsis identification and management. This review examines methods for identifying sepsis cohorts, focusing on two main approaches: utilizing health administrative data with standardized diagnostic coding via the International Classification of Diseases and integrating clinical data. This overview provides a comprehensive analysis of current cohort identification and electronic phenotyping strategies for sepsis, highlighting their potential applications and challenges. The accuracy of an electronic phenotype or signature is pivotal for precision medicine, enabling a shift from subjective clinical descriptions to data-driven insights.

Impact on the Short-Term Hospital Outcomes From COVID Pandemic Among Older Adults With Sepsis

Objective: This study evaluates clinical characteristics, hospitals outcomes, and mortality determinants in older sepsis patients before and during COVID-19. Methods: Retrospective of sepsis cases (aged 65+) from nine hospitals (2018-2020) using ICD codes. Multivariate logistic regression was used to analyze mortality predictors. Results: Of 4635 sepsis patients, 515 (11.1%) passed in-hospital, with mortality rising to 13.9% during the pandemic from 10% prior (p < .01). Pandemic admissions had more racial minorities and severe comorbidities. Patient safety indicator events decreased during the pandemic (14.8% vs. 17.9%, p < .01), while home discharge rates remained consistent. Pandemic admission and lack of insurance correlated with increased mortality, alongside advanced age, ICU admission, and opioid and sedative use. Conclusion: COVID-19 pandemic admission and socioeconomic factors heightened mortality risks in older sepsis patients, highlighting the need for targeted care strategies.

Adjudication of Codes for Identifying Sepsis in Hospital Administrative Data by Expert Consensus

OBJECTIVES

Refine the administrative data definition of sepsis in hospitalized patients, including less severe cases.

DESIGN AND SETTING

For each of 1928 infection and 108 organ dysfunction codes used in Canadian hospital abstracts, experts reached consensus on the likelihood that it could relate to sepsis. We developed a new algorithm, called AlgorithmL, that requires at least one infection and one organ dysfunction code adjudicated as likely or very likely to be related to sepsis. AlgorithmL was compared with four previously described algorithms, regarding included codes, population-based incidence, and hospital mortality rates-separately for ICU and non-ICU cohorts in a large Canadian city. We also compared sepsis identification from these code-based algorithms with the Centers for Disease Control's Adult Sepsis Event (ASE) definition.

SUBJECTS

Among Calgary's adult population of 1.033 million there were 61,632 eligible hospitalizations.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

AlgorithmL includes 720 infection codes and 50 organ dysfunction codes. Comparison algorithms varied from 42-941 infection codes to 2-36 organ codes. There was substantial nonoverlap of codes in AlgorithmL vs. the comparators. Annual sepsis incidence rates (per 100,000 population) based on AlgorithmL were 91 in the ICU and 291 in the non-ICU cohort. Incidences based on comparators ranged from 28-77 for ICU to 11-266 for non-ICU cohorts. Hospital sepsis mortality rates based on AlgorithmL were 24% in ICU and 17% in non-ICU cohorts; based on comparators, they ranged 27-38% in the ICU cohort and 18-47% for the non-ICU cohort. Of AlgorithmL-identified cases, 41% met the ASE criteria, compared with 42-82% for the comparator algorithms.

CONCLUSIONS

Compared with other code-based algorithms, AlgorithmL includes more infection and organ dysfunction codes. AlgorithmL incidence rates are higher; hospital mortality rates are lower. AlgorithmL may more fully encompass the full range of sepsis severity.

Trends in Empiric Broad-Spectrum Antibiotic Use for Suspected Community-Onset Sepsis in US Hospitals

Importance

Little is known about the degree to which suspected sepsis drives broad-spectrum antibiotic use in hospitals, what proportion of antibiotic courses are unnecessarily broad in retrospect, and whether these patterns are changing over time.

Objective

To describe trends in empiric broad-spectrum antibiotic use for suspected community-onset sepsis.

Design, Setting, and Participants

This cross-sectional study used clinical data from adults admitted to 241 US hospitals in the PINC AI Healthcare Database. Eligible participants were aged 18 years or more and were admitted between 2017 and 2021 with suspected community-onset sepsis, defined by a blood culture draw, lactate measurement, and intravenous antibiotic administration on admission.

Exposures

Empiric anti-methicillin-resistant Staphylococcus aureus (MRSA) and/or antipseudomonal β-lactam agent use.

Main Outcomes and Measures

Annual rates of empiric anti-MRSA and/or antipseudomonal β-lactam agent use and the proportion that were likely unnecessary in retrospect based on the absence of β-lactam resistant gram-positive or ceftriaxone-resistant gram-negative pathogens from clinical cultures obtained through hospital day 4. Annual trends were calculated using mixed-effects logistic regression models, adjusting for patient and hospital characteristics.

Results

Among 6 272 538 hospitalizations (median [IQR] age, 66 [53-78] years; 443 465 male [49.6%]; 106 095 Black [11.9%], 65 763 Hispanic [7.4%], 653 907 White [73.1%]), 894 724 (14.3%) had suspected community-onset sepsis, of whom 582 585 (65.1%) received either empiric anti-MRSA (379 987 [42.5%]) or antipseudomonal β-lactam therapy (513 811 [57.4%]); 311 213 (34.8%) received both. Patients with suspected community-onset sepsis accounted for 1 573 673 of 3 141 300 (50.1%) of total inpatient anti-MRSA antibiotic days and 2 569 518 of 5 211 745 (49.3%) of total antipseudomonal β-lactam days. Between 2017 and 2021, the proportion of patients with suspected sepsis administered anti-MRSA or antipseudomonal therapy increased from 63.0% (82 731 of 131 275 patients) to 66.7% (101 003 of 151 435 patients) (adjusted OR [aOR] per year, 1.03; 95% CI, 1.03-1.04). However, resistant organisms were isolated in only 65 434 cases (7.3%) (30 617 gram-positive [3.4%], 38 844 gram-negative [4.3%]) and the proportion of patients who had any resistant organism decreased from 9.6% to 7.3% (aOR per year, 0.87; 95% CI, 0.87-0.88). Most patients with suspected sepsis treated with empiric anti-MRSA and/or antipseudomonal therapy had no resistant organisms (527 356 of 582 585 patients [90.5%]); this proportion increased from 88.0% in 2017 to 91.6% in 2021 (aOR per year, 1.12; 95% CI, 1.11-1.13).

Conclusions and Relevance

In this cross-sectional study of adults admitted to 241 US hospitals, empiric broad-spectrum antibiotic use for suspected community-onset sepsis accounted for half of all anti-MRSA or antipseudomonal therapy; the use of these types of antibiotics increased between 2017 and 2021 despite resistant organisms being isolated in less than 10% of patients treated with broad-spectrum agents.

Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data

PURPOSE

Timely and accurate data on the epidemiology of sepsis are essential to inform policy decisions and research priorities. We aimed to investigate the validity of inpatient administrative health data (IAHD) for surveillance and quality assurance of sepsis care.

METHODS

We conducted a retrospective validation study in a disproportional stratified random sample of 10,334 inpatient cases of age ≥ 15 years treated in 2015-2017 in ten German hospitals. The accuracy of coding of sepsis and risk factors for mortality in IAHD was assessed compared to reference standard diagnoses obtained by a chart review. Hospital-level risk-adjusted mortality of sepsis as calculated from IAHD information was compared to mortality calculated from chart review information.

RESULTS

ICD-coding of sepsis in IAHD showed high positive predictive value (76.9-85.7% depending on sepsis definition), but low sensitivity (26.8-38%), which led to an underestimation of sepsis incidence (1.4% vs. 3.3% for severe sepsis-1). Not naming sepsis in the chart was strongly associated with under-coding of sepsis. The frequency of correctly naming sepsis and ICD-coding of sepsis varied strongly between hospitals (range of sensitivity of naming: 29-71.7%, of ICD-diagnosis: 10.7-58.5%). Risk-adjusted mortality of sepsis per hospital calculated from coding in IAHD showed no substantial correlation to reference standard risk-adjusted mortality (r = 0.09).

CONCLUSION

Due to the under-coding of sepsis in IAHD, previous epidemiological studies underestimated the burden of sepsis in Germany. There is a large variability between hospitals in accuracy of diagnosing and coding of sepsis. Therefore, IAHD alone is not suited to assess quality of sepsis care.

Improving Sepsis Outcomes in the Era of Pay-for-Performance and Electronic Quality Measures: A Joint IDSA/ACEP/PIDS/SHEA/SHM/SIDP Position Paper

The Centers for Medicare & Medicaid Services (CMS) introduced the Severe Sepsis/Septic Shock Management Bundle (SEP-1) as a pay-for-reporting measure in 2015 and is now planning to make it a pay-for-performance measure by incorporating it into the Hospital Value-Based Purchasing Program. This joint IDSA/ACEP/PIDS/SHEA/SHM/SIPD position paper highlights concerns with this change. Multiple studies indicate that SEP-1 implementation was associated with increased broad-spectrum antibiotic use, lactate measurements, and aggressive fluid resuscitation for patients with suspected sepsis but not with decreased mortality rates. Increased focus on SEP-1 risks further diverting attention and resources from more effective measures and comprehensive sepsis care. We recommend retiring SEP-1 rather than using it in a payment model and shifting instead to new sepsis metrics that focus on patient outcomes. CMS is developing a community-onset sepsis 30-day mortality electronic clinical quality measure (eCQM) that is an important step in this direction. The eCQM preliminarily identifies sepsis using systemic inflammatory response syndrome (SIRS) criteria, antibiotic administrations or diagnosis codes for infection or sepsis, and clinical indicators of acute organ dysfunction. We support the eCQM but recommend removing SIRS criteria and diagnosis codes to streamline implementation, decrease variability between hospitals, maintain vigilance for patients with sepsis but without SIRS, and avoid promoting antibiotic use in uninfected patients with SIRS. We further advocate for CMS to harmonize the eCQM with the Centers for Disease Control and Prevention's (CDC) Adult Sepsis Event surveillance metric to promote unity in federal measures, decrease reporting burden for hospitals, and facilitate shared prevention initiatives. These steps will result in a more robust measure that will encourage hospitals to pay more attention to the full breadth of sepsis care, stimulate new innovations in diagnosis and treatment, and ultimately bring us closer to our shared goal of improving outcomes for patients.

Care pathways of sepsis survivors: sequelae, mortality and use of healthcare services in France, 2015-2018

BACKGROUND

Individuals who survive sepsis are at high risk of chronic sequelae, resulting in significant health-economic costs. Several studies have focused on aspects of healthcare pathways of sepsis survivors but comprehensive, longitudinal overview of their pathways of care are scarce. The aim of this retrospective, longitudinal cohort study is to identify sepsis survivor profiles based on their healthcare pathways and describe their healthcare consumption and costs over the 3 years following their index hospitalization.

METHODS

The data were extracted from the French National Hospital Discharge Database. The study population included all patients above 15 years old, with bacterial sepsis, who survived an incident hospitalization in an acute care facility in 2015. To identify survivor profiles, state sequence and clustering analyses were conducted over the year following the index hospitalization. For each profile, patient characteristics and their index hospital stay and sequelae were described, as well as use of care and its associated monetary costs, both pre- and post-sepsis.

RESULTS

New medical (79.2%), psychological (26.9%) and cognitive (18.5%) impairments were identified post-sepsis, and 65.3% of survivors were rehospitalized in acute care. Cumulative mortality reached 36.6% by 3 years post-sepsis. The total medical cost increased by 856 million € in the year post-sepsis. Five patient clusters were identified: home (65.6% of patients), early death (12.9%), late death (6.8%), short-term rehabilitation (11.3%) and long-term rehabilitation (3.3%). Survivors with early and late death clusters had high rates of cancer and primary bacteremia and experienced more hospital-at-home care post-sepsis. Survivors in short- or long-term rehabilitation clusters were older, with higher percentage of septic shock than those coming back home, and had high rates of multiple site infections and higher rates of new psychological and cognitive impairment.

CONCLUSIONS

Over three years post-sepsis, different profiles of sepsis survivors were identified with different mortality rates, sequels and healthcare services usage and cost. This study confirmed the importance of sepsis burden and suggests that strategies of post-discharge care, in accordance with patient profile, should be further tested in order to reduce sepsis burden.

Validation of an ICD-Based Algorithm to Identify Sepsis: A Retrospective Study

Background

Sepsis surveillance was important for resources allocation, prevention, and development of health policy.

Objective

The aim of the study was to validate a modified International Classification of Diseases (ICD)-10 based algorithm for identifying hospitalized patients with sepsis.

Methods

We retrospectively analyzed a prospective, single-center cohort of adult patients who were consecutively admitted to one medical ICU ward and ten non-ICU wards with suspected or confirmed infections during a 6-month period. A modified ICD-10 based algorithm was validated against a reference standard of Sequential Organ Failure Assessment (SOFA) score based on Sepsis-3. Sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), and areas under the receiver operating characteristic curves (AUROCs) were calculated for modified ICD-10 criteria, eSOFA criteria, Martin's criteria, and Angus's criteria.

Results

Of the 547 patients in the cohort, 332 (61%) patients met Sepsis-3 criteria and 274 (50%) met modified ICD-10 criteria. In the ICU setting, modified ICD-10 criteria had SE (84.47%), SP (88.57%), PPV (95.60), and NPV (65.96). In non-ICU settings, modified ICD-10 had SE (64.19%), SP (80.00%), PPV (80.33), and NPV (63.72). In the whole cohort, the AUROCs of modified ICD-10 criteria, eSOFA, Angus's criteria, and Martin's criteria were 0.76, 0.75, 0.62, and 0.62, respectively.

Conclusion

This study demonstrated that modified ICD-10 criteria had higher validity compared with Angus's criteria and Martin's criteria. Validity of the modified ICD-10 criteria was similar to eSOFA criteria. Modified ICD-10 algorithm can be used to provide an accurate estimate of population-based sepsis burden of China.

Electronic health record data quality assessment and tools: a systematic review

OBJECTIVE

We extended a 2013 literature review on electronic health record (EHR) data quality assessment approaches and tools to determine recent improvements or changes in EHR data quality assessment methodologies.

MATERIALS AND METHODS

We completed a systematic review of PubMed articles from 2013 to April 2023 that discussed the quality assessment of EHR data. We screened and reviewed papers for the dimensions and methods defined in the original 2013 manuscript. We categorized papers as data quality outcomes of interest, tools, or opinion pieces. We abstracted and defined additional themes and methods though an iterative review process.

RESULTS

We included 103 papers in the review, of which 73 were data quality outcomes of interest papers, 22 were tools, and 8 were opinion pieces. The most common dimension of data quality assessed was completeness, followed by correctness, concordance, plausibility, and currency. We abstracted conformance and bias as 2 additional dimensions of data quality and structural agreement as an additional methodology.

DISCUSSION

There has been an increase in EHR data quality assessment publications since the original 2013 review. Consistent dimensions of EHR data quality continue to be assessed across applications. Despite consistent patterns of assessment, there still does not exist a standard approach for assessing EHR data quality.

CONCLUSION

Guidelines are needed for EHR data quality assessment to improve the efficiency, transparency, comparability, and interoperability of data quality assessment. These guidelines must be both scalable and flexible. Automation could be helpful in generalizing this process.

Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data

Sepsis is a leading cause of mortality and early identification improves survival. With increasing digitalization of health care data automated sepsis prediction models hold promise to aid in prompt recognition. Most previous studies have focused on the intensive care unit (ICU) setting. Yet only a small proportion of sepsis develops in the ICU and there is an apparent clinical benefit to identify patients earlier in the disease trajectory. In this cohort of 82,852 hospital admissions and 8038 sepsis episodes classified according to the Sepsis-3 criteria, we demonstrate that a machine learned score can predict sepsis onset within 48 h using sparse routine electronic health record data outside the ICU. Our score was based on a causal probabilistic network model-SepsisFinder-which has similarities with clinical reasoning. A prediction was generated hourly on all admissions, providing a new variable was registered. Compared to the National Early Warning Score (NEWS2), which is an established method to identify sepsis, the SepsisFinder triggered earlier and had a higher area under receiver operating characteristic curve (AUROC) (0.950 vs. 0.872), as well as area under precision-recall curve (APR) (0.189 vs. 0.149). A machine learning comparator based on a gradient-boosting decision tree model had similar AUROC (0.949) and higher APR (0.239) than SepsisFinder but triggered later than both NEWS2 and SepsisFinder. The precision of SepsisFinder increased if screening was restricted to the earlier admission period and in episodes with bloodstream infection. Furthermore, the SepsisFinder signaled median 5.5 h prior to antibiotic administration. Identifying a high-risk population with this method could be used to tailor clinical interventions and improve patient care.

Comparative Effectiveness of Fludrocortisone and Hydrocortisone vs Hydrocortisone Alone Among Patients With Septic Shock

Importance

Patients with septic shock may benefit from the initiation of corticosteroids. However, the comparative effectiveness of the 2 most studied corticosteroid regimens (hydrocortisone with fludrocortisone vs hydrocortisone alone) is unclear.

Objective

To compare the effectiveness of adding fludrocortisone to hydrocortisone vs hydrocortisone alone among patients with septic shock using target trial emulation.

Design, Setting, and Participants

This retrospective cohort study from 2016 to 2020 used the enhanced claims-based Premier Healthcare Database, which included approximately 25% of US hospitalizations. Participants were adult patients hospitalized with septic shock and receiving norepinephrine who began hydrocortisone treatment. Data analysis was performed from May 2022 to December 2022.

Exposure

Addition of fludrocortisone on the same calendar day that hydrocortisone treatment was initiated vs use of hydrocortisone alone.

Main Outcome and Measures

Composite of hospital death or discharge to hospice. Adjusted risk differences were calculated using doubly robust targeted maximum likelihood estimation.

Results

Analyses included 88 275 patients, 2280 who began treatment with hydrocortisone-fludrocortisone (median [IQR] age, 64 [54-73] years; 1041 female; 1239 male) and 85 995 (median [IQR] age, 67 [57-76] years; 42 136 female; 43 859 male) who began treatment with hydrocortisone alone. The primary composite outcome of death in hospital or discharge to hospice occurred among 1076 (47.2%) patients treated with hydrocortisone-fludrocortisone vs 43 669 (50.8%) treated with hydrocortisone alone (adjusted absolute risk difference, -3.7%; 95% CI, -4.2% to -3.1%; P < .001).

Conclusions and Relevance

In this comparative effectiveness cohort study among adult patients with septic shock who began hydrocortisone treatment, the addition of fludrocortisone was superior to hydrocortisone alone.

Patterns, Predictors, and Intercenter Variability in Empiric Gram-Negative Antibiotic Use Across 928 United States Hospitals

BACKGROUND

Empiric antibiotic use among hospitalized adults in the United States (US) is largely undescribed. Identifying factors associated with broad-spectrum empiric therapy may inform antibiotic stewardship interventions and facilitate benchmarking.

METHODS

We performed a retrospective cohort study of adults discharged in 2019 from 928 hospitals in the Premier Healthcare Database. "Empiric" gram-negative antibiotics were defined by administration before day 3 of hospitalization. Multivariable logistic regression models with random effects by hospital were used to evaluate associations between patient and hospital characteristics and empiric receipt of broad-spectrum, compared to narrow-spectrum, gram-negative antibiotics.

RESULTS

Of 8 017 740 hospitalized adults, 2 928 657 (37%) received empiric gram-negative antibiotics. Among 1 781 306 who received broad-spectrum therapy, 30% did not have a common infectious syndrome present on admission (pneumonia, urinary tract infection, sepsis, or bacteremia), surgery, or an intensive care unit stay in the empiric window. Holding other factors constant, males were 22% more likely (adjusted odds ratio [aOR], 1.22 [95% confidence interval, 1.22-1.23]), and all non-White racial groups 6%-13% less likely (aOR range, 0.87-0.94), to receive broad-spectrum therapy. There were significant prescribing differences by region, with the highest adjusted odds of broad-spectrum therapy in the US West South Central division. Even after model adjustment, there remained substantial interhospital variability: Among patients receiving empiric therapy, the probability of receiving broad-spectrum antibiotics varied as much as 34+ percentage points due solely to the admitting hospital (95% interval of probabilities: 43%-77%).

CONCLUSIONS

Empiric gram-negative antibiotic use is highly variable across US regions, and there is high, unexplained interhospital variability. Sex and racial disparities in the receipt of broad-spectrum therapy warrant further investigation.

Defining Posttraumatic Sepsis for Population-Level Research

IMPORTANCE

Multiple classification methods are used to identify sepsis from existing data. In the trauma population, it is unknown how administrative methods compare with clinical criteria for sepsis classification.

OBJECTIVES

To characterize the agreement between 3 approaches to sepsis classification among critically ill patients with trauma and compare the sepsis-associated risk of adverse outcomes when each method was used to define sepsis.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used data collected between January 1, 2012, and December 31, 2020, from patients aged 16 years or older with traumatic injury, admitted to the intensive care unit of a single-institution level 1 trauma center and requiring invasive mechanical ventilation for at least 3 days. Statistical analysis was conducted from August 1, 2021, to March 31, 2022.

EXPOSURE

Hospital-acquired sepsis, as classified by 3 methods: a novel automated clinical method based on data from the electronic health record, the National Trauma Data Bank (NTDB), and explicit and implicit medical billing codes.

MAIN OUTCOMES AND MEASURES

The primary outcomes were chronic critical illness and in-hospital mortality. Secondary outcomes included number of days in an intensive care unit, number of days receiving mechanical ventilation, discharge to a skilled nursing or long-term care facility, and discharge to home without assistance.

RESULTS

Of 3194 patients meeting inclusion criteria, the median age was 49 years (IQR, 31-64 years), 2380 (74%) were male, and 2826 (88%) sustained severe blunt injury (median Injury Severity Score, 29 [IQR, 21-38]). Sepsis was identified in 747 patients (23%) meeting automated clinical criteria, 118 (4%) meeting NTDB criteria, and 529 (17%) using medical billing codes. The Light κ value for 3-way agreement was 0.16 (95% CI, 0.14-0.19). The adjusted relative risk of chronic critical illness was 9.9 (95% CI, 8.0-12.3) for sepsis identified by automated clinical criteria, 5.0 (95% CI, 3.4-7.3) for sepsis identified by the NTDB, and 4.5 (95% CI, 3.6-5.6) for sepsis identified using medical billing codes. The adjusted relative risk for in-hospital mortality was 1.3 (95% CI, 1.0-1.6) for sepsis identified by automated clinical criteria, 2.7 (95% CI, 1.7-4.3) for sepsis identified by the NTDB, and 1.0 (95% CI, 0.7-1.2) for sepsis identified using medical billing codes.

CONCLUSIONS AND RELEVANCE

In this cohort study of critically ill patients with trauma, administrative methods misclassified sepsis and underestimated the incidence and severity of sepsis compared with an automated clinical method using data from the electronic health record. This study suggests that an automated approach to sepsis classification consistent with Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) clinical criteria is feasible and may improve existing approaches to health services and population-based research in this population.

Prevalence and Outcomes of Previously Healthy Adults Among Patients Hospitalized With Community-Onset Sepsis

BACKGROUND

Devastating cases of sepsis in previously healthy patients have received widespread attention and have helped to catalyze state and national mandates to improve sepsis detection and care. However, it is unclear what proportion of patients hospitalized with sepsis previously were healthy and how their outcomes compare with those of patients with comorbidities.

RESEARCH QUESTION

Among adults hospitalized with community-onset sepsis, how many previously were healthy and how do their outcomes compare with those of patients with comorbidities?

STUDY DESIGN AND METHODS

We retrospectively identified all adults with community-onset sepsis hospitalized in 373 US hospitals from 2009 through 2015 using clinical indicators of presumed infection and organ dysfunction (Centers for Disease Control and Prevention's Adult Sepsis Event criteria). Comorbidities were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. We applied generalized linear mixed models to measure the associations between the presence or absence of comorbidities and short-term mortality (in-hospital death or discharge to hospice), adjusting for severity of illness on admission.

RESULTS

Of 6,715,286 hospitalized patients, 337,983 (5.0%) were hospitalized with community-onset sepsis. Most patients with sepsis (329,052 [97.4%]) had received a diagnosis of at least one comorbidity; only 2.6% previously were healthy. Patients with sepsis who previously were healthy were younger than those with comorbidities (mean age, 58.0 ± 19.8 years vs 67.0 ± 16.5 years), were less likely to require ICU care on admission (37.9% vs 50.5%), and were more likely to be discharged home (57.9% vs 45.6%), rather than to subacute facilities (16.3% vs 30.8%), but showed higher short-term mortality rates (22.8% vs 20.8%; P < .001 for all). The association between previously healthy status and higher short-term mortality persisted after risk adjustment (adjusted OR, 1.99; 95% CI, 1.87-2.13).

INTERPRETATION

The vast majority of patients hospitalized with community-onset sepsis harbor pre-existing comorbidities. However, previously healthy patients may be more likely to die when they seek treatment at the hospital with sepsis compared with patients with comorbidities. These findings underscore the importance of early sepsis recognition and treatment for all patients.

Trends in bacterial sepsis incidence and mortality in France between 2015 and 2019 based on National Health Data System (Système National des données de Santé (SNDS)): a retrospective observational study

OBJECTIVE

This study aims to provide a case definition of sepsis of presumed bacterial aetiology based on 10th revision of the International Classification of Diseases (ICD-10) codes, to assess trends in sepsis incidence and mortality between 2015 and 2019 in France, and to describe the characteristics of affected patients and hospital stays.

DESIGN

Nationwide, population-based, retrospective observational study.

SETTING

Metropolitan France between 2015 and 2019.

PARTICIPANTS

Between 2015 and 2019, 1 224 433 patients with sepsis of presumed bacterial aetiology were selected from the French National Hospital Discharge Database (Programme de Médicalisation des Systèmes d'Information) and were identified from corresponding ICD-10 codes for explicit sepsis or implicit sepsis.

MAIN OUTCOMES MEASURES

Annual overall and age-specific and gender-specific incidence and 95% CI, as well as trends in sepsis incidence and mortality, were estimated. Comorbidities, length of hospital stay and outcomes were described.

RESULTS

The sex-standardised and age-standardised incidence per 100 000 (95% CI) increased from 357 (356.0 to 359.0) in 2015 to 403 (401.9 to 405.0) in 2019 and remained higher for males compared with females. Children under 1 year and patients over 75 years consistently had the highest incidence. The most common comorbidities were cancer and chronic heart failure. The median hospital length of stay was 12 days. Most patients came from home, but only half returned home after their hospital stay and approximately 15% were discharged to long-term care. In-hospital mortality was about 25% and declined along the study period.

CONCLUSIONS

Medico-administrative databases can be used to provide nationwide estimates of the in-hospital burden of bacterial sepsis. The results confirm the high burden of sepsis in France. These data should be complemented by estimating the additional burden associated with fungal and viral infections during the COVID-19 pandemic.

Consensus Current Procedural Terminology Code Definition of Source Control for Sepsis

INTRODUCTION

Unlike antibiotic and perfusion support, guidelines for sepsis source control lack high-quality evidence and are ungraded. Internally valid administrative data methods are needed to identify cases representing source control procedures to evaluate outcomes.

METHODS

Over five modified Delphi rounds, two independent reviewers identified Current Procedural Terminology (CPT) codes pertinent to source control. In each round, codes with perfect agreement were retained or excluded, whereas disagreements were reviewed by the panelists. Manual review of 400 patient records meeting Sepsis-3 criteria (2010-2017) clinically adjudicated which encounters included source control procedures (gold standard). The performance of consensus codes was compared with the gold standard to assess sensitivity, specificity, predictive values, and likelihood ratios.

RESULTS

Of 5752 CPT codes, 609 consensus codes represented source control procedures. Of 400 hospitalizations for sepsis, 39 (9.8%; 95% confidence interval [CI] 7.0%-13.1%) underwent gold standard source control procedures and 29 (7.3%; 95% CI 4.9-10.3%) consensus code-defined source control procedures. Thirty consensus codes were identified (20.0% gastrointestinal/intraabdominal, 10.0% genitourinary, 13.3% hepatopancreatobiliary, 23.3% orthopedic/cranial, 23.3% soft tissue, and 10.0% intrathoracic), which had 61.5% (95% CI 44.6%-76.6%) sensitivity, 98.6% (95% CI 96.8%-99.6%) specificity, 83.2% (95% CI 66.6%-92.4%) positive, and 95.9% (95% CI 93.9%-97.2%) negative predictive values. With pretest probability at sample prevalence, an identified consensus code had a posttest probability of 83.0% (95% CI 66.0%-92.0%), whereas consensus code absence had a probability of 4.0% (95% CI 3.0-6.0) for undergoing a source control procedure.

CONCLUSIONS

Using modified Delphi methodology, we created and validated CPT codes identifying source control procedures, providing a framework for evaluation of the surgical care of patients with sepsis.

Should hospital-onset Adult Sepsis Event surveillance be routine… or even mandatory?

Hospital-onset sepsis accounts for 10%-15% of all sepsis cases and is associated with very high mortality rates, yet to date most hospitals have paid little attention to tracking its incidence and outcomes. This contrasts sharply with the substantial effort that hospitals and regulatory agencies spend tracking and reporting a limited subset of healthcare-associated infections. The recent development of the Center for Disease Control and Prevention's hospital-onset Adult Sepsis Event (ASE) definition, however, provides a validated and standardized mechanism for facilities to identify patients with nosocomial sepsis using routinely available electronic health record data. Recent data have demonstrated that hospital-onset ASE surveillance identifies many infections that are largely missed by current reportable healthcare-associated infections and that are associated with much higher mortality rates. Expanding the breadth of surveillance to include these highly consequential infections could help identify new targets for prevention and quality improvement and ultimately catalyze better outcomes for hospitalized patients. More work is needed, however, to characterize the preventability of hospital-onset ASE, develop and validate robust case-mix adjustment tools, and facilitate widespread uptake in hospitals with limited resources.

Prevalence, Characteristics, and Outcomes of Emergency Department Discharge Among Patients With Sepsis

IMPORTANCE

Sepsis guidelines and research have focused on patients with sepsis who are admitted to the hospital, but the scope and implications of sepsis that is managed in an outpatient setting are largely unknown.

OBJECTIVE

To identify the prevalence, risk factors, practice variation, and outcomes for discharge to outpatient management of sepsis among patients presenting to the emergency department (ED).

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted at the EDs of 4 Utah hospitals, and data extraction and analysis were performed from 2017 to 2021. Participants were adult ED patients who presented to a participating ED from July 1, 2013, to December 31, 2016, and met sepsis criteria before departing the ED alive and not receiving hospice care.

EXPOSURES

Patient demographic and clinical characteristics, health system parameters, and ED attending physician.

MAIN OUTCOMES AND MEASURES

Information on ED disposition was obtained from electronic medical records, and 30-day mortality data were acquired from Utah state death records and the US Social Security Death Index. Factors associated with ED discharge rather than hospital admission were identified using penalized logistic regression. Variation in ED discharge rates between physicians was estimated after adjustment for potential confounders using generalized linear mixed models. Inverse probability of treatment weighting was used in the primary analysis to assess the noninferiority of outpatient management for 30-day mortality (noninferiority margin of 1.5%) while adjusting for multiple potential confounders.

RESULTS

Among 12 333 ED patients with sepsis (median [IQR] age, 62 [47-76] years; 7017 women [56.9%]) who were analyzed in the study, 1985 (16.1%) were discharged from the ED. After penalized regression, factors associated with ED discharge included age (adjusted odds ratio [aOR], 0.90 per 10-y increase; 95% CI, 0.87-0.93), arrival to ED by ambulance (aOR, 0.61; 95% CI, 0.52-0.71), organ failure severity (aOR, 0.58 per 1-point increase in the Sequential Organ Failure Assessment score; 95% CI, 0.54-0.60), and urinary tract (aOR, 4.56 [95% CI, 3.91-5.31] vs pneumonia), intra-abdominal (aOR, 0.51 [95% CI, 0.39-0.65] vs pneumonia), skin (aOR, 1.40 [95% CI, 1.14-1.72] vs pneumonia) or other source of infection (aOR, 1.67 [95% CI, 1.40-1.97] vs pneumonia). Among 89 ED attending physicians, adjusted ED discharge probability varied significantly (likelihood ratio test, P < .001), ranging from 8% to 40% for an average patient. The unadjusted 30-day mortality was lower in discharged patients than admitted patients (0.9% vs 8.3%; P < .001), and their adjusted 30-day mortality was noninferior (propensity-adjusted odds ratio, 0.21 [95% CI, 0.09-0.48]; adjusted risk difference, 5.8% [95% CI, 5.1%-6.5%]; P < .001). Alternative confounder adjustment strategies yielded odds ratios that ranged from 0.21 to 0.42.

CONCLUSIONS AND RELEVANCE

In this cohort study, discharge to outpatient treatment of patients who met sepsis criteria in the ED was more common than previously recognized and varied substantially between ED physicians, but it was not associated with higher mortality compared with hospital admission. Systematic, evidence-based strategies to optimize the triage of ED patients with sepsis are needed.

Identifying children at high risk for infection-related decompensation using a predictive emergency department-based electronic assessment tool

OBJECTIVES

Electronic alert systems to identify potential sepsis in children presenting to the emergency department (ED) often either alert too frequently or fail to detect earlier stages of decompensation where timely treatment might prevent serious outcomes.

METHODS

We created a predictive tool that continuously monitors our hospital's electronic health record during ED visits. The tool incorporates new standards for normal/abnormal vital signs based on data from ∼1.2 million children at 169 hospitals. Eighty-two gold standard (GS) sepsis cases arising within 48 h were identified through retrospective chart review of cases sampled from 35,586 ED visits during 2012 and 2014-2015. An additional 1,027 cases with high severity of illness (SOI) based on 3 M's All Patient Refined - Diagnosis-Related Groups (APR-DRG) were identified from these and 26,026 additional visits during 2017. An iterative process assigned weights to main factors and interactions significantly associated with GS cases, creating an overall "score" that maximized the sensitivity for GS cases and positive predictive value for high SOI outcomes.

RESULTS

Tool implementation began August 2017; subsequent improvements resulted in 77% sensitivity for identifying GS sepsis within 48 h, 22.5% positive predictive value for major/extreme SOI outcomes, and 2% overall firing rate of ED patients. The incidence of high-severity outcomes increased rapidly with tool score. Admitted alert positive patients were hospitalized nearly twice as long as alert negative patients.

CONCLUSIONS

Our ED-based electronic tool combines high sensitivity in predicting GS sepsis, high predictive value for physiologic decompensation, and a low firing rate. The tool can help optimize critical treatments for these high-risk children.

A Comparative Analysis of the Respiratory Subscore of the Sequential Organ Failure Assessment Scoring System

Rationale: The Sequential Organ Failure Assessment (SOFA) tool is a commonly used measure of illness severity. Calculation of the respiratory subscore of SOFA is frequently limited by missing arterial oxygen pressure (PaO2) data. Although missing PaO2 data are commonly replaced with normal values, the performance of different methods of substituting PaO2 for SOFA calculation is unclear. Objectives: The study objective was to compare the performance of different substitution strategies for missing PaO2 data for SOFA score calculation. Methods: This retrospective cohort study was performed using the Weill Cornell Critical Care Database for Advanced Research from a tertiary care hospital in the United States. All adult patients admitted to an intensive care unit (ICU) from 2011 to 2019 with an available respiratory SOFA score were included. We analyzed the availability of the PaO2/fraction of inspired oxygen (FiO2) ratio on the first day of ICU admission. In those without a PaO2/FiO2 ratio available, the ratio of oxygen saturation as measured by pulse oximetry to FiO2 was used to calculate a respiratory SOFA subscore according to four methods (linear substitution [Rice], nonlinear substitution [Severinghaus], modified respiratory SOFA, and multiple imputation by chained equations [MICE]) as well as the missing-as-normal technique. We then compared how well the different total SOFA scores discriminated in-hospital mortality. We performed several subgroup and sensitivity analyses. Results: We identified 35,260 unique visits, of which 9,172 included predominant respiratory failure. PaO2 data were available for 14,939 (47%). The area under the receiver operating characteristic curve for each substitution technique for discriminating in-hospital mortality was higher than that for the missing-as-normal technique (0.78 [0.77-0.79]) in all analyses (modified, 0.80 [0.79-0.81]; Rice, 0.80 [0.79-0.81]; Severinghaus, 0.80 [0.79-0.81]; and MICE, 0.80 [0.79-0.81]) (P < 0.01). Each substitution method had a higher accuracy for discriminating in-hospital mortality (MICE, 0.67; Rice, 0.67; modified, 0.66; and Severinghaus, 0.66) than the missing-as-normal technique. Model calibration for in-hospital mortality was less precise for the missing-as-normal technique than for the other substitution techniques at the lower range of SOFA and among the subgroups. Conclusions: Using physiologic and statistical substitution methods improved the total SOFA score's ability to discriminate mortality compared with the missing-as-normal technique. Treating missing data as normal may result in underreporting the severity of illness compared with using substitution. The simplicity of a direct oxygen saturation as measured by pulse oximetry/FiO2 ratio-modified SOFA technique makes it an attractive choice for electronic health record-based research. This knowledge can inform comparisons of severity of illness across studies that used different techniques.

Descriptors of Sepsis Using the Sepsis-3 Criteria: A Cohort Study in Critical Care Units Within the U.K. National Institute for Health Research Critical Care Health Informatics Collaborative

Supplemental Digital Content is available in the text.

To describe the epidemiology of sepsis in critical care by applying the Sepsis-3 criteria to electronic health records.

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.

Physiological machine learning models for prediction of sepsis in hospitalized adults: An integrative review

BACKGROUND

Diagnosing sepsis remains challenging. Data compiled from continuous monitoring and electronic health records allow for new opportunities to compute predictions based on machine learning techniques. There has been a lack of consensus identifying best practices for model development and validation towards early identification of sepsis.

OBJECTIVE

To evaluate the modeling approach and statistical methodology of machine learning prediction models for sepsis in the adult hospital population.

METHODS

PubMed, CINAHL, and Cochrane databases were searched with the Preferred Reporting Items for Systematic Reviews guided protocol development. We evaluated studies that developed or validated physiologic sepsis prediction models or implemented a model in the hospital environment.

RESULTS

Fourteen studies met the inclusion criteria, and the AUROC of the prediction models ranged from 0.61 to 0.96. We found a variety of sepsis definitions, methods used for event adjudication, model parameters used, and modeling methods. Two studies tested models in clinical settings; the results suggested that patient outcomes were improved with implementation of machine learning models.

CONCLUSION

Nurses have a unique perspective to offer in the development and implementation of machine learning models detecting patients at risk for sepsis. More work is needed in developing model harmonization standards and testing in clinical settings.

Surveillance Strategies for Tracking Sepsis Incidence and Outcomes

Sepsis is a leading cause of death and the target of intense efforts to improve recognition, management and outcomes. Accurate sepsis surveillance is essential to properly interpreting the impact of quality improvement initiatives, making meaningful comparisons across hospitals and geographic regions, and guiding future research and resource investments. However, it is challenging to reliably track sepsis incidence and outcomes because sepsis is a heterogeneous clinical syndrome without a pathologic reference standard, allowing for subjectivity and broad discretion in assigning diagnoses. Most epidemiologic studies of sepsis to date have used hospital discharge codes and have suggested dramatic increases in sepsis incidence and decreases in mortality rates over time. However, diagnosis and coding practices vary widely between hospitals and are changing over time, complicating the interpretation of absolute rates and trends. Other surveillance approaches include death records, prospective clinical registries, retrospective medical record reviews, and analyses of the usual care arms of randomized controlled trials. Each of these strategies, however, has substantial limitations. Recently, the US Centers for Disease Control and Prevention released an "Adult Sepsis Event" definition that uses objective clinical indicators of infection and organ dysfunction that can be extracted from most hospitals' electronic health record systems. Emerging data suggest that electronic health record-based clinical surveillance, such as surveillance of Adult Sepsis Event, is accurate, can be applied uniformly across diverse hospitals, and generates more credible estimates of sepsis trends than administrative data. In this review, we discuss the advantages and limitations of different sepsis surveillance strategies and consider future directions.

Physician documentation matters. Using natural language processing to predict mortality in sepsis

Background/objective

Sepsis remains without good outcome prediction. Technological advances, specifically, natural language processing (NLP), has an opportunity to approach sepsis mortality prediction in a novel way.

Methods

Using the MIMIC III dataset, patients diagnosed with sepsis from 2008 to 2013 had physician progress notes analyzed using NLP. Researchers utilized concepts from analysis to build a model to predict for in-hospital-mortality, using notes in the first 24 hours of a patient admission. This model was retrospectively validated on septic admissions to University of California Irvine Medical Center (UCIMC) from 2013 to 2018 and compared to SOFA and qSOFA.

Results

An 80-concept model was developed and validated on 7117 admissions to UCIMC. For severe sepsis, an Area Under Curve or AUC of 0.687 (95% CI 0.618-0.748) was demonstrated which was greater than SOFA at 0.571 (0.497-0.643). Additionally, for simple sepsis the model demonstrated an AUC of 0.696 (0.649-0.738) which was greater than qSOFA at 0.590 (0.545-0.638).

Conclusions

Physician clinical judgement extracted from notes using NLP has greater performance in predicting mortality and survival in sepsis compared to structured data used in SOFA and qSOFA.

Prevalence and Clinical Characteristics of Patients With Sepsis Discharge Diagnosis Codes and Short Lengths of Stay in U.S. Hospitals

OBJECTIVES

Some patients diagnosed with sepsis have very brief hospitalizations. Understanding the prevalence and clinical characteristics of these patients may provide insight into how sepsis diagnoses are being applied as well as the breadth of illnesses encompassed by current sepsis definitions.

DESIGN

Retrospective observational study.

SETTING

One-hundred ten U.S. hospitals in the Cerner HealthFacts dataset (primary cohort) and four hospitals in Eastern Massachusetts (secondary cohort used for detailed medical record reviews).

PATIENTS

Adults hospitalized from April 2016 to December 2017.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We identified hospitalizations with International Classification of Diseases, 10th Edition codes for sepsis (including sepsis, septicemia, severe sepsis, and septic shock) and compared "short stay sepsis" patients (defined as discharge alive within 3 d) versus nonshort stay sepsis patients using detailed electronic health record data. In the Cerner cohort, 67,733 patients had sepsis discharge diagnosis codes, including 6,918 (10.2%) with short stays. Compared with nonshort stay sepsis patients, short stay patients were younger (median age 60 vs 67 yr) and had fewer comorbidities (median Elixhauser score 5 vs 13), lower rates of positive blood cultures (8.2% vs 24.1%), lower rates of ICU admission (6.2% vs 31.6%), and less frequently had severe sepsis/septic shock codes (13.5% vs 36.6%). Almost all short stay and nonshort stay sepsis patients met systemic inflammatory response syndrome criteria at admission (84.5% and 87.5%, respectively); 47.2% of those with short stays had Sequential Organ Failure Assessment scores of 2 or greater at admission versus 73.2% of those with longer stays. Findings were similar in the secondary four-hospital cohort. Medical record reviews demonstrated that physicians commonly diagnosed sepsis based on the presence of systemic inflammatory response syndrome criteria, elevated lactates, or positive blood cultures without concurrent organ dysfunction.

CONCLUSIONS

In this large U.S. cohort, one in 10 patients coded for sepsis were discharged alive within 3 days. Although most short stay patients met systemic inflammatory response syndrome criteria, they met Sepsis-3 criteria less than half the time. Our findings underscore the incomplete uptake of Sepsis-3 definitions, the breadth of illness severities encompassed by both traditional and new sepsis definitions, and the possibility that some patients with sepsis recover very rapidly.

Antecedent treat-and-release diagnoses prior to sepsis hospitalization among adult emergency department patients: a look-back analysis employing insurance claims data using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) methodology

OBJECTIVES

The aim of this study was to identify delays in early pre-sepsis diagnosis in emergency departments (ED) using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach.

METHODS

SPADE methodology was employed using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (KPMAS). Study cohort included KPMAS members ≥18 years with ≥1 sepsis hospitalization 1/1/2013-12/31/2018. A look-back analysis identified treat-and-release ED visits in the month prior to sepsis hospitalizations. Top 20 diagnoses associated with these ED visits were identified; two diagnosis categories were distinguished as being linked to downstream sepsis hospitalizations. Observed-to-expected (O:E) and temporal analyses were performed to validate the symptom selection; results were contrasted to a comparison group. Demographics of patients that did and did not experience sepsis misdiagnosis were compared.

RESULTS

There were 3,468 sepsis hospitalizations during the study period and 766 treat-and-release ED visits in the month prior to hospitalization. Patients discharged from the ED with fluid and electrolyte disorders (FED) and altered mental status (AMS) were most likely to have downstream sepsis hospitalizations (O:E ratios of 2.66 and 2.82, respectively). Temporal analyses revealed that these symptoms were overrepresented and temporally clustered close to the hospitalization date. Approximately 2% of sepsis hospitalizations were associated with prior FED or AMS ED visits.

CONCLUSIONS

Treat-and-release ED encounters for FED and AMS may represent harbingers for downstream sepsis hospitalizations. The SPADE approach can be used to develop performance measures that identify pre-sepsis.

Sepsis Among Medicare Beneficiaries: 1. The Burdens of Sepsis, 2012-2018

Supplemental Digital Content is available in the text.

To provide contemporary estimates of the burdens (costs and mortality) associated with acute inpatient Medicare beneficiary admissions for sepsis.

Sepsis and septic shock in France: incidences, outcomes and costs of care

Background

Sepsis is one of the leading causes of death worldwide. The associated incidence, mortality and trends do not differ greatly between documented reports. The purpose of this study was to provide an in-depth description of patients with sepsis and septic shock hospitalized in France from 2010 to 2015 and to explore the temporal trends of their clinical characteristics, costs and outcomes.

Methods

Retrospective cohort study of the French hospital administrative database in which organ failure therapies and severity scores are systematically registered. All patients admitted between 2010 and 2015 for sepsis and septic shock as defined by an ICD-10 code for infection, and for organ failure or the use of organ failure supplementation were included. Incidence, outcomes and trends were analyzed. Subgroup analyses based on several coding strategies and adjusted for severity scores were performed.

Results

A total of 737,147 patients with sepsis and 492,902 patients with septic shock were included. From 2010 to 2015, the incidence of sepsis and septic shock increased, respectively, from 206 to 243 and from 135 to 171 cases per 100,000 population. Case fatality remained at 34% for sepsis, but decreased from 46 to 44% for septic shock.

Median hospital stay costs amounted to €11,400 (IQR: 5036; 24,364) for patients with sepsis and €16,439 (IQR: 7339; 29,360) for patients with septic shock.

After adjustment for case-mix and illness severity, the risk of death was stable for sepsis (0.08% [− 0.04; 0.20] per year), but decreased for sepsis patients admitted to the intensive care unit and for cases of septic shock (− 0.33%[ − 0.40; − 0.27] per year).

Conclusions

Sepsis is common, frequently fatal and expensive to treat. Its incidence has increased. Case fatality has decreased in most severely affected patients, owing partly to general improvements in care.

Needs assessment for novel Gram-negative antibiotics in US hospitals: a retrospective cohort study

BACKGROUND

Evidence-based needs assessments for novel antibiotics against highly-resistant Gram-negative infections (GNIs) are scarce. We aimed to use real-world data from an electronic health record repository to identify treatment opportunities in US hospitals for GNIs resistant to all first-line drugs.

METHODS

For this retrospective cohort study, population estimates with an unmet need for novel Gram-negative antibiotics were quantified using the Cerner Health Facts database (2009-15), aggregating episodes of infection in US hospitals with pathogens displaying difficult-to-treat resistance (DTR; resistance to carbapenems, other β-lactams, and fluoroquinolones) and episodes involving empirical coverage with reserve drugs (colistin or polymyxin B and aminoglycosides). Episodes displaying extended-spectrum cephalosporin resistance (ECR) were also estimated. Episodes were multiplied by site-specific and fixed 14-day treatment durations for conservative and liberal days-of-therapy (DOT) estimates and stratified by site and taxon. Hospital type-specific DOT rates were reliability adjusted to account for random variation; cluster analyses quantified contribution from outbreaks.

FINDINGS

Across 2 996 271 inpatient encounters and 134 hospitals, there were 1352 DTR-GNI episodes, 1765 episodes involving empirical therapy with colistin or polymyxin B, and 16 632 episodes involving aminoglycosides. Collectively, these yielded 39·0 (conservative estimate) to 138·2 (liberal estimate) DOT per 10 000 encounters for a novel DTR-GNI-targeted drug, whereas greater treatment opportunities were identified for ECR (six times greater) and β-lactam susceptible GNIs (70 times greater). The most common DTR-GNI site and pathogen was lower respiratory (14·3 [43·3%] of 33 DOT per 10 000 encounters) and Pseudomonas aeruginosa (522 [38·1%] of 1371 episodes), whereas Enterobacteriaceae urinary-tract infections dominated the ECR or carbapenem-sparing niche (59·0% [5589 of 9535 episodes]) equating to 210·7 DOT per 10 000 encounters. DTR Stenotrophomonas maltophilia, Burkholderia spp, and Achromobacter spp represented less than 1 DOT per 10 000 encounters each. The estimated need for DTR-GNI-targeted antibiotics saw minor contributions by outbreaks and varied from 0·5 to 73·1 DOT per 10 000 encounters by hospital type.

INTERPRETATION

Suspected or documented GNIs with no or suboptimal treatment options are relatively infrequent. Non-revenue-based strategies and innovative trial designs are probably essential to the development of antibiotics with improved effectiveness for these GNIs.

FUNDING

Center for Drug Evaluation and Research, US Food and Drug Administration; Intramural Research Program, National Institutes of Health Clinical Center and the National Institute of Allergy and Infectious Diseases and the National Cancer Institute.

Epidemiology of sepsis and septic shock in intensive care units between sepsis-2 and sepsis-3 populations: sepsis prognostication in intensive care unit and emergency room (SPICE-ICU)

Background

Diagnosing sepsis remains difficult because it is not a single disease but a syndrome with various pathogen- and host factor-associated symptoms. Sepsis-3 was established to improve risk stratification among patients with infection based on organ failures, but it has been still controversial compared with previous definitions. Therefore, we aimed to describe characteristics of patients who met sepsis-2 (severe sepsis) and sepsis-3 definitions.

Methods

This was a multicenter, prospective cohort study conducted by 22 intensive care units (ICUs) in Japan. Adult patients (≥ 16 years) with newly suspected infection from December 2017 to May 2018 were included. Those without infection at final diagnosis were excluded. Patient’s characteristics and outcomes were described according to whether they met each definition or not.

Results

In total, 618 patients with suspected infection were admitted to 22 ICUs during the study, of whom 530 (85.8%) met the sepsis-2 definition and 569 (92.1%) met the sepsis-3 definition. The two groups comprised different individuals, and 501 (81.1%) patients met both definitions. In-hospital mortality of study population was 19.1%. In-hospital mortality among patients with sepsis-2 and sepsis-3 patients was comparable (21.7% and 19.8%, respectively). Patients exclusively identified with sepsis-2 or sepsis-3 had a lower mortality (17.2% vs. 4.4%, respectively). No patients died if they did not meet any definitions. Patients who met sepsis-3 shock definition had higher in-hospital mortality than those who met sepsis-2 shock definition.

Conclusions

Most patients with infection admitted to ICU meet sepsis-2 and sepsis-3 criteria. However, in-hospital mortality did not occur if patients did not meet any criteria. Better criteria might be developed by better selection and combination of elements in both definitions.

Trial registration

UMIN000027452

Impact of Risk Adjustment Using Clinical vs Administrative Data on Hospital Sepsis Mortality Comparisons

Background

A reliable risk-adjusted sepsis outcome measure could complement current national process metrics by identifying outlier hospitals and catalyzing additional improvements in care. However, it is unclear whether integrating clinical data into risk adjustment models identifies similar high- and low-performing hospitals compared with administrative data alone, which are simpler to acquire and analyze.

Methods

We ranked 200 US hospitals by their Centers for Disease Control and Prevention Adult Sepsis Event (ASE) mortality rates and assessed how rankings changed after applying (1) an administrative risk adjustment model incorporating demographics, comorbidities, and codes for severe illness and (2) an integrated clinical and administrative model replacing severity-of-illness codes with laboratory results, vasopressors, and mechanical ventilation. We assessed agreement between hospitals’ risk-adjusted ASE mortality rates when ranked into quartiles using weighted kappa statistics (к).

Results

The cohort included 4 009 631 hospitalizations, of which 245 808 met ASE criteria. Risk-adjustment had a large effect on rankings: 22/50 hospitals (44%) in the worst quartile using crude mortality rates shifted into better quartiles after administrative risk adjustment, and a further 21/50 (42%) of hospitals in the worst quartile using administrative risk adjustment shifted to better quartiles after incorporating clinical data. Conversely, 14/50 (28%) hospitals in the best quartile using administrative risk adjustment shifted to worse quartiles with clinical data. Overall agreement between hospital quartile rankings when risk-adjusted using administrative vs clinical data was moderate (к = 0.55).

Conclusions

Incorporating clinical data into risk adjustment substantially changes rankings of hospitals’ sepsis mortality rates compared with using administrative data alone. Comprehensive risk adjustment using both administrative and clinical data is necessary before comparing hospitals by sepsis mortality rates.

Validation of automated sepsis surveillance based on the Sepsis-3 clinical criteria against physician record review in a general hospital population: observational study using electronic health records data

BACKGROUND

Surveillance of sepsis incidence is important for directing resources and evaluating quality-of-care interventions. The aim was to develop and validate a fully-automated Sepsis-3 based surveillance system in non-intensive care wards using electronic health record (EHR) data, and demonstrate utility by determining the burden of hospital-onset sepsis and variations between wards.

METHODS

A rule-based algorithm was developed using EHR data from a cohort of all adult patients admitted at an academic centre between July 2012 and December 2013. Time in intensive care units was censored. To validate algorithm performance, a stratified random sample of 1000 hospital admissions (674 with and 326 without suspected infection) was classified according to the Sepsis-3 clinical criteria (suspected infection defined as having any culture taken and at least two doses of antimicrobials administered, and an increase in Sequential Organ Failure Assessment (SOFA) score by >2 points) and the likelihood of infection by physician medical record review.

RESULTS

In total 82 653 hospital admissions were included. The Sepsis-3 clinical criteria determined by physician review were met in 343 of 1000 episodes. Among them, 313 (91%) had possible, probable or definite infection. Based on this reference, the algorithm achieved sensitivity 0.887 (95% CI: 0.799 to 0.964), specificity 0.985 (95% CI: 0.978 to 0.991), positive predictive value 0.881 (95% CI: 0.833 to 0.926) and negative predictive value 0.986 (95% CI: 0.973 to 0.996). When applied to the total cohort taking into account the sampling proportions of those with and without suspected infection, the algorithm identified 8599 (10.4%) sepsis episodes. The burden of hospital-onset sepsis (>48 hour after admission) and related in-hospital mortality varied between wards.

CONCLUSIONS

A fully-automated Sepsis-3 based surveillance algorithm using EHR data performed well compared with physician medical record review in non-intensive care wards, and exposed variations in hospital-onset sepsis incidence between wards.

Time to Recognition of Sepsis in the Emergency Department Using Electronic Health Record Data: A Comparative Analysis of Systemic Inflammatory Response Syndrome, Sequential Organ Failure Assessment, and Quick Sequential Organ Failure Assessment

OBJECTIVES

Early identification of sepsis is critical to improving patient outcomes. Impact of the new sepsis definition (Sepsis-3) on timing of recognition in the emergency department has not been evaluated. Our study objective was to compare time to meeting systemic inflammatory response syndrome (Sepsis-2) criteria, Sequential Organ Failure Assessment (Sepsis-3) criteria, and quick Sequential Organ Failure Assessment criteria using electronic health record data.

DESIGN

Retrospective, observational study.

SETTING

The emergency department at the University of California, San Francisco.

PATIENTS

Emergency department encounters between June 2012 and December 2016 for patients greater than or equal to 18 years old with blood cultures ordered, IV antibiotic receipt, and identification with sepsis via systemic inflammatory response syndrome or Sequential Organ Failure Assessment within 72 hours of emergency department presentation.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We analyzed timestamped electronic health record data from 16,612 encounters identified as sepsis by greater than or equal to 2 systemic inflammatory response syndrome criteria or a Sequential Organ Failure Assessment score greater than or equal to 2. The primary outcome was time from emergency department presentation to meeting greater than or equal to 2 systemic inflammatory response syndrome criteria, Sequential Organ Failure Assessment greater than or equal to 2, and/or greater than or equal to 2 quick Sequential Organ Failure Assessment criteria. There were 9,087 patients (54.7%) that met systemic inflammatory response syndrome-first a median of 26 minutes post-emergency department presentation (interquartile range, 0-109 min), with 83.1% meeting Sequential Organ Failure Assessment criteria a median of 118 minutes later (interquartile range, 44-401 min). There were 7,037 patients (42.3%) that met Sequential Organ Failure Assessment-first, a median of 113 minutes post-emergency department presentation (interquartile range, 60-251 min). Quick Sequential Organ Failure Assessment was met in 46.4% of patients a median of 351 minutes post-emergency department presentation (interquartile range, 67-1,165 min). Adjusted odds of in-hospital mortality were 39% greater in patients who met systemic inflammatory response syndrome-first compared with those who met Sequential Organ Failure Assessment-first (odds ratio, 1.39; 95% CI, 1.20-1.61).

CONCLUSIONS

Systemic inflammatory response syndrome and Sequential Organ Failure Assessment initially identified distinct populations. Using systemic inflammatory response syndrome resulted in earlier electronic health record sepsis identification in greater than 50% of patients. Using Sequential Organ Failure Assessment alone may delay identification. Using systemic inflammatory response syndrome alone may lead to missed sepsis presenting as acute organ dysfunction. Thus, a combination of inflammatory (systemic inflammatory response syndrome) and organ dysfunction (Sequential Organ Failure Assessment) criteria may enhance timely electronic health record-based sepsis identification.

Comparison of Automated Sepsis Identification Methods and Electronic Health Record-based Sepsis Phenotyping: Improving Case Identification Accuracy by Accounting for Confounding Comorbid Conditions

Supplemental Digital Content is available in the text.

To develop and evaluate a novel strategy that automates the retrospective identification of sepsis using electronic health record data.

Risk Adjustment for Sepsis Mortality to Facilitate Hospital Comparisons Using Centers for Disease Control and Prevention's Adult Sepsis Event Criteria and Routine Electronic Clinical Data

Variability in hospital-level sepsis mortality rates may be due to differences in case mix, quality of care, or diagnosis and coding practices. Centers for Disease Control and Prevention's Adult Sepsis Event definition could facilitate objective comparisons of sepsis mortality rates between hospitals but requires rigorous risk-adjustment tools. We developed risk-adjustment models for Adult Sepsis Events using administrative and electronic health record data.

DESIGN

Retrospective cohort study.

SETTING

One hundred thirty-six U.S. hospitals in Cerner HealthFacts (derivation dataset) and 137 HCA Healthcare hospitals (validation dataset).

PATIENTS

A total of 95,154 hospitalized adult patients (derivation) and 201,997 patients (validation) meeting Centers for Disease Control and Prevention Adult Sepsis Event criteria.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We created logistic regression models of increasing complexity using administrative and electronic health record data to predict in-hospital mortality. An administrative model using demographics, comorbidities, and coded markers of severity of illness at admission achieved an area under the receiver operating curve of 0.776 (95% CI, 0.770-0.783) in the Cerner cohort, with diminishing calibration at higher baseline risk deciles. An electronic health record-based model that integrated administrative data with laboratory results, vasopressors, and mechanical ventilation achieved an area under the receiver operating curve of 0.826 (95% CI, 0.820-0.831) in the derivation cohort and 0.827 (95% CI, 0.824-0.829) in the validation cohort, with better calibration than the administrative model. Adding vital signs and Glasgow Coma Score minimally improved performance.

CONCLUSIONS

Models incorporating electronic health record data accurately predict hospital mortality for patients with Adult Sepsis Events and outperform models using administrative data alone. Utilizing laboratory test results, vasopressors, and mechanical ventilation without vital signs may achieve a good balance between data collection needs and model performance, but electronic health record-based models must be attentive to potential variability in data quality and availability. With ongoing testing and refinement of these risk-adjustment models, Adult Sepsis Event surveillance may enable more meaningful comparisons of hospital sepsis outcomes and provide an important window into quality of care.

Epidemiology of Sepsis-3 in a sub-district of Beijing: secondary analysis of a population-based database

BACKGROUND

With the publication of Sepsis-3 definition, epidemiological data based on Sepsis-3 definition from middle-income countries including China are scarce, which prohibits understanding of the disease burden of this newly defined syndrome in these settings. The purpose of this study was to describe incidence and outcome of Sepsis-3 in Yuetan sub-district of Beijing and to estimate the incidence rate of Sepsis-3 in China.

METHODS

The medical records of all adult residents hospitalized from July 1, 2012 to June 30, 2014 in Yuetan sub-district of Beijing were reviewed. Patients with sepsis-3 and severe sepsis/septic shock were identified. The incidence rates and mortality rate of sepsis-3 and sepsis/septic shock were calculated, incidence rates and in-hospital mortality rates were normalized to the population distribution in the 2010 National Census. Population incidence rate and case fatality rate between sexes were compared with the Z test, as the data conformed to Poisson distribution.

RESULTS

Of the 21,191 hospitalized patients, 935 patients were diagnosed with Sepsis-3, and 498 cases met severe sepsis/septic shock criteria. The crude annual incidence rate of Sepsis-3 in Yuetan sub-district was 363 cases per 100,000 population, corresponding to standardized incidence rates of 236 cases per 100,000 population per year, respectively. The overall case fatality rate of Sepsis-3 was 32.0%, the crude population mortality rates of Sepsis-3 was 116 cases per 100,000 population per year, the standardized mortality rate was 67 cases per 100,000 population per year, corresponding to a speculative extrapolation of 700,437 deaths in China. The incidence rate and mortality rate of Sepsis-3 were significantly higher in males, elderly people, and patients with more comorbidities. The 62.1% of patients with Sepsis-3 had community-acquired infections, compared with 75.3% of infected patients without Sepsis-3 (P < 0.001). The most common infection in patients with Sepsis-3 was lower respiratory tract infection. When compared with patients with Sepsis-3, patients diagnosed as severe sepsis/septic shock were more likely to have higher case fatality rate (53.4% vs. 32.0%, P < 0.001) CONCLUSIONS:: This study found the standardized incidence rate of 236 cases per 100,000 person-year for Sepsis-3, which was more common in males and elderly population. This corresponded to about 2.5 million new cases of Sepsis-3 per year, resulting in more than 700,000 deaths in China.

CLINICAL TRIAL REGISTRATION

NCT02285257, https://clinicaltrials.gov/ct2/show/record/NCT02285257.

Epidemiology of Hospital-Onset Versus Community-Onset Sepsis in U.S. Hospitals and Association With Mortality: A Retrospective Analysis Using Electronic Clinical Data

OBJECTIVES

Prior studies have reported that hospital-onset sepsis is associated with higher mortality rates than community-onset sepsis. Most studies, however, have used inconsistent case-finding methods and applied limited risk-adjustment for potential confounders. We used consistent sepsis criteria and detailed electronic clinical data to elucidate the epidemiology and mortality associated with hospital-onset sepsis.

DESIGN

Retrospective cohort study.

SETTING

136 U.S. hospitals in the Cerner HealthFacts dataset.

PATIENTS

Adults hospitalized in 2009-2015.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We identified sepsis using Centers for Disease Control and Prevention Adult Sepsis Event criteria and estimated the risk of in-hospital death for hospital-onset sepsis versus community-onset sepsis using logistic regression models. In patients admitted without community-onset sepsis, we estimated risk of death associated with hospital-onset sepsis using Cox regression models with sepsis as a time-varying covariate. Models were adjusted for baseline characteristics and severity of illness. Among 2.2 million hospitalizations, there were 95,154 sepsis cases: 83,620 (87.9%) community-onset sepsis and 11,534 (12.1%) hospital-onset sepsis (0.5% of hospitalized cohort). Compared to community-onset sepsis, hospital-onset sepsis patients were younger (median 66 vs 68 yr) but had more comorbidities (median Elixhauser score 14 vs 11), higher Sequential Organ Failure Assessment scores (median 4 vs 3), higher ICU admission rates (61% vs 44%), longer hospital length of stay (median 19 vs 8 d), and higher in-hospital mortality (33% vs 17%) (p < 0.001 for all comparisons). On multivariate analysis, hospital-onset sepsis was associated with higher mortality versus community-onset sepsis (odds ratio, 2.1; 95% CI, 2.0-2.2) and patients admitted without sepsis (hazard ratio, 3.0; 95% CI, 2.9-3.2).

CONCLUSIONS

Hospital-onset sepsis complicated one in 200 hospitalizations and accounted for one in eight sepsis cases, with one in three patients dying in-hospital. Hospital-onset sepsis preferentially afflicted ill patients but even after risk-adjustment, they were twice as likely to die as community-onset sepsis patients; in patients admitted without sepsis, hospital-onset sepsis tripled the risk of death. Hospital-onset sepsis is an important target for surveillance, prevention, and quality improvement initiatives.

Robustness of sepsis-3 criteria in critically ill patients

Background

Early recognition of sepsis is challenging, and diagnostic criteria have changed repeatedly. We assessed the robustness of sepsis-3 criteria in intensive care unit (ICU) patients.

Methods

We studied the apparent incidence and associated mortality of sepsis-3 among patients who were prospectively enrolled in the Molecular Diagnosis and Risk Stratification of Sepsis (MARS) cohort in the Netherlands, and explored the effects of minor variations in the precise definition and timing of diagnostic criteria for organ failure.

Results

Among 1081 patients with suspected infection upon ICU admission, 648 (60%) were considered to have sepsis according to prospective adjudication in the MARS study, whereas 976 (90%) met sepsis-3 criteria, yielding only 64% agreement at the individual patient level. Among 501 subjects developing ICU-acquired infection, these rates were 270 (54%) and 260 (52%), respectively (yielding 58% agreement). Hospital mortality was 234 (36%) vs 277 (28%) for those meeting MARS-sepsis or sepsis-3 criteria upon presentation (p < 0.001), and 121 (45%) vs 103 (40%) for those having sepsis onset in the ICU (p < 0.001). Minor variations in timing and interpretation of organ failure criteria had a considerable effect on the apparent prevalence of sepsis-3, which ranged from 68 to 96% among those with infection at admission, and from 22 to 99% among ICU-acquired cases.

Conclusion

The sepsis-3 definition lacks robustness as well as discriminatory ability, since nearly all patients presenting to ICU with suspected infection fulfill its criteria. These should therefore be specified in greater detail, and applied more consistently, during future sepsis studies.

Trial registration

The MARS study is registered at ClinicalTrials.gov (identifier NCT 01905033).

Electronic supplementary material

The online version of this article (10.1186/s40560-019-0400-6) contains supplementary material, which is available to authorized users.

An administrative model for benchmarking hospitals on their 30-day sepsis mortality

Background

Given the increased attention to sepsis at the population level there is a need to assess hospital performance in the care of sepsis patients using widely-available administrative data. The goal of this study was to develop an administrative risk-adjustment model suitable for profiling hospitals on their 30-day mortality rates for patients with sepsis.

Methods

We conducted a retrospective cohort study using hospital discharge data from general acute care hospitals in Pennsylvania in 2012 and 2013. We identified adult patients with sepsis as determined by validated diagnosis and procedure codes. We developed an administrative risk-adjustment model in 2012 data. We then validated this model in two ways: by examining the stability of performance assessments over time between 2012 and 2013, and by examining the stability of performance assessments in 2012 after the addition of laboratory variables measured on day one of hospital admission.

Results

In 2012 there were 115,213 sepsis encounters in 152 hospitals. The overall unadjusted mortality rate was 18.5%. The final risk-adjustment model had good discrimination (C-statistic = 0.78) and calibration (slope and intercept of the calibration curve = 0.960 and 0.007, respectively). Based on this model, hospital-specific risk-standardized mortality rates ranged from 12.2 to 24.5%. Comparing performance assessments between years, correlation in risk-adjusted mortality rates was good (Pearson’s correlation = 0.53) and only 19.7% of hospitals changed by more than one quintile in performance rankings. Comparing performance assessments after the addition of laboratory variables, correlation in risk-adjusted mortality rates was excellent (Pearson’s correlation = 0.93) and only 2.6% of hospitals changed by more than one quintile in performance rankings.

Conclusions

A novel claims-based risk-adjustment model demonstrated wide variation in risk-standardized 30-day sepsis mortality rates across hospitals. Individual hospitals’ performance rankings were stable across years and after the addition of laboratory data. This model provides a robust way to rank hospitals on sepsis mortality while adjusting for patient risk.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4037-x) contains supplementary material, which is available to authorized users.