Identification of Pediatric Sepsis for Epidemiologic Surveillance Using Electronic Clinical Data

Abstract

Objectives: A method to identify pediatric sepsis episodes that is not affected by changing diagnosis and claims-based coding practices does not exist. We derived and validated a surveillance algorithm to identify pediatric sepsis using routine clinical data and applied the algorithm to study longitudinal trends in sepsis epidemiology.

Design: Retrospective observational study.

Setting: Single academic children's hospital.

Patients: All emergency and hospital encounters from January 2011 to January 2019, excluding neonatal ICU and cardiac center.

Exposure: Sepsis episodes identified by a surveillance algorithm using clinical data to identify infection and concurrent organ dysfunction.

Interventions: None.

Measurements and main results: A surveillance algorithm was derived and validated in separate cohorts with suspected sepsis after clinician-adjudication of final sepsis diagnosis. We then applied the surveillance algorithm to determine longitudinal trends in incidence and mortality of pediatric sepsis over 8 years. Among 93,987 hospital encounters and 1,065 episodes of suspected sepsis in the derivation period, the surveillance algorithm yielded sensitivity 78% (95% CI, 72-84%), specificity 76% (95% CI, 74-79%), positive predictive value 41% (95% CI, 36-46%), and negative predictive value 94% (95% CI, 92-96%). In the validation period, the surveillance algorithm yielded sensitivity 84% (95% CI, 77-92%), specificity of 65% (95% CI, 59-70%), positive predictive value 43% (95% CI, 35-50%), and negative predictive value 93% (95% CI, 90-97%). Notably, most "false-positives" were deemed clinically relevant sepsis cases after manual review. The hospital-wide incidence of sepsis was 0.69% (95% CI, 0.67-0.71%), and the inpatient incidence was 2.8% (95% CI, 2.7-2.9%). Risk-adjusted sepsis incidence, without bias from changing diagnosis or coding practices, increased over time (adjusted incidence rate ratio per year 1.07; 95% CI, 1.06-1.08; p < 0.001). Mortality was 6.7% and did not change over time (adjusted odds ratio per year 0.98; 95% CI, 0.93-1.03; p = 0.38).

Conclusions: An algorithm using routine clinical data provided an objective, efficient, and reliable method for pediatric sepsis surveillance. An increased sepsis incidence and stable mortality, free from influence of changes in diagnosis or billing practices, were evident.

Figure 1:. Sepsis Incidence and Mortality, 2011–2018

The incidence of sepsis among all hospital encounters (including all ED visits and hospital admissions, blue line), incidence of sepsis among hospital admissions (orange line), and the in-hospital mortality among sepsis episodes (green line) from 2011 through 2018. Sepsis episodes were identified using the surveillance algorithm. Data are presented as number of episodes per 1000 emergency/hospital encounters for incidence and percentage of episodes for mortality. Error bars indicate 95% confidence intervals.

Figure 2:. Organ Dysfunction and Associated Mortality in Sepsis Episodes

A, Percentage of sepsis episodes identified by the surveillance algorithm with each organ dysfunction and associated in-hospital mortality for episodes that included each organ dysfunction. For example, cardiovascular dysfunction was present in 59% of sepsis episodes, and of those with cardiovascular dysfunction, 10% died prior to hospital discharge. B, Percentage of sepsis episodes identified by the surveillance algorithm by number of organ dysfunctions and associated in-hospital mortality for episodes that included each number of organ dysfunctions. For example, one organ dysfunction was present in 54% of sepsis episodes, and of those with one organ dysfunction, 2% died prior to hospital discharge. Organ dysfunctions included in the number count were >60 mL/kg isotonic fluid boluses within seven hours, new/increased vasoactive infusion, blood lactate ≥2.0 mmol/L, new invasive/non-invasive mechanical ventilation, increase in non-invasive ventilation to >20 hours/day, platelet <100,00 cells/μL with ≥50% decline from baseline, and serum creatinine ≥2x baseline and exceeding threshold for age.