Comparison of Administrative versus Electronic Health Record–based Methods for Identifying Sepsis Hospitalizations

Karlic, Kevin J.; Clouse, T.; Hogan, Cainnear K; Garland, Allan; Seelye, Sarah; Sussman, Jeremy B.; Prescott, Hallie C.

doi:10.1513/annalsats.202302-105oc

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Most promising are probably algorithms, which use electronic health record data to combine information indicating the presence of infection with information indicating the presence of organ dysfunction to identify sepsis. These achieved higher sensitivity compared to explicit ICD-coding of sepsis [ 29 ], but a recent study indicated that this might also come at the cost of reduced specificity and PPV [ 43 ]. Such algorithms might be less prone to differences in diagnosis and documentation of sepsis [ 40 ], but the variation of their precision across hospitals still needs to be investigated.…”

Section: Discussionmentioning

confidence: 99%

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

Schwarzkopf,

Rose,

Fleischmann-Struzek

et al. 2023

Infection

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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.

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Section: Discussionmentioning

confidence: 99%

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

Schwarzkopf,

Rose,

Fleischmann-Struzek

et al. 2023

Infection

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“…We defined the outcome of infection as receiving four Qualifying Antimicrobial Days based on the Centers for Disease Control and Prevention (CDC) Adult Sepsis Event (ASE) criteria (5). This criterion has been shown to be a valid measure of infection (6,7). Consistent with ASE definitions, if a patient dies or transitions to comfort measures or is discharged to another hospital or hospice before four qualifying antimicrobial days (QADs) have elapsed, then the presumed infection criteria are met if they have consecutive QADs until day of, or 1 day before, death, or discharge.…”

Section: Creating Risk Stratification Categoriesmentioning

confidence: 96%

Real-World Implications of Updated Surviving Sepsis Campaign Antibiotic Timing Recommendations

Taylor,

Kowalkowski,

Skewes

et al. 2024

Critical Care Medicine

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Objective: To evaluate real-world implications of updated Surviving Sepsis Campaign (SSC) recommendations for antibiotic timing. Design: Retrospective cohort study. Setting: Twelve hospitals in the Southeastern United States between 2017 and 2021. Patients: One hundred sixty-six thousand five hundred fifty-nine adult hospitalized patients treated in the emergency department for suspected serious infection. Interventions: None. Measurements and Main Results: We determined the number and characteristics of patients affected by updated SSC recommendations for initiation of antibiotics that incorporate a risk- and probability-stratified approach. Using an infection prediction model with a cutoff of 0.5 to classify possible vs. probable infection, we found that 30% of the suspected infection cohort would be classified as shock absent, possible infection and thus eligible for the new 3-hour antibiotic recommendation. In real-world practice, this group had a conservative time to antibiotics (median, 5.5 hr; interquartile range [IQR], 3.2–9.8 hr) and low mortality (2%). Patients categorized as shock absent, probable infection had a median time to antibiotics of 3.2 hours (IQR, 2.1–5.1 hr) and mortality of 3%. Patients categorized as shock present, the probable infection had a median time to antibiotics 2.7 hours (IQR, 1.7–4.6 hr) and mortality of 17%, and patients categorized as shock present, the possible infection had a median time to antibiotics 6.9 hours (IQR, 3.5–16.3 hr) and mortality of 12%. Conclusions: These data support recently updated SSC recommendations to align antibiotic timing targets with risk and probability stratifications. Our results provide empirical support that clinicians and hospitals should not be held to 1-hour targets for patients without shock and with only possible sepsis.

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Heterogeneity of Benefit from Earlier Time-to-Antibiotics for Sepsis

Hechtman,

Kipnis,

Cano

et al. 2024

Am J Respir Crit Care Med

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Comparison of Administrative versus Electronic Health Record–based Methods for Identifying Sepsis Hospitalizations

Cited by 4 publications

References 16 publications

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

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

Real-World Implications of Updated Surviving Sepsis Campaign Antibiotic Timing Recommendations

Heterogeneity of Benefit from Earlier Time-to-Antibiotics for Sepsis

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