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Using predictive analytics to gauge sepsis risk

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Amy Carpenter Aquino

October 2019—How well can analytics predict the risk for sepsis? T. Scott Isbell, PhD, DABCC, director of clinical chemistry and point-of-care testing, SSM Health, Saint Louis University Hospital, at this year’s AACC annual meeting shared his hospital’s experience with Epic’s sepsis predictive tool. Launched in 2017, the tool uses predictive analytics to produce a sepsis score for admitted patients based on regular scans of key data elements in the electronic health record.

Saint Louis University Hospital previously used a systemic inflammatory response syndrome (SIRS) criteria alert system. “That thing fired all the time. Pretty much everybody presenting to our hospital triggered it,” said Dr. Isbell, who is also associate professor of pathology and pediatrics at Saint Louis University School of Medicine. It was no surprise given that the SIRS criteria are not specific to sepsis, he said. “Everybody got pop-up fatigue.”

Dr. Isbell

Epic’s sepsis predictive tool was based on an examination of 350 data elements in a training data set of more than 400,000 patient encounters at three hospital sites. “The model itself runs in the background. It’s always on in our hospital, and it’s set primarily to look at patients either in the emergency department or on the floor in the inpatient units,” Dr. Isbell said. The hospital has used the tool since early this year.

Once a patient is in a room, the Epic sepsis predictive tool begins to scan the patient’s EHR every 15 minutes for key data elements. It feeds the data into the model and generates a sepsis score. Scores of six percent or higher in the emergency department, or eight percent or higher in an inpatient room, trigger a best practice advisory. A pop-up alert indicates that the patient has a risk of developing sepsis—“not a diagnosis of sepsis,” Dr. Isbell said—and requires the clinician to open the order set if the patient’s symptoms are consistent with sepsis. The clinician also has the option to indicate through the alert that the patient’s symptoms are not consistent with sepsis, that further assessment is needed, or that appropriate treatment is already in place. Consulting physicians can defer action to the treating provider.

The Epic tool examines several parameters to generate a sepsis score: demographics; traditional vital signs (which are also the SIRS criteria), such as temperature, heart rate, and respiration rate; comorbidities, such as congestive heart failure, diabetes, and hypertension; and active lines, drains, or airways, such as feeding tubes and peripheral IVs.

The laboratory list of parameters is “fairly short,” Dr. Isbell said. The tool examines mostly hematologic parameters, such as white blood cell count with limited differentiation, particularly lymphocytes, monocytes, neutrophils, and segmented and band neutrophils. It also examines RBC, Hct, Hb, MCHC, nRBCs, RBC morphology, RDW, reticulocytes, and platelet count. Metabolic laboratory measures are creatinine, hemoglobin A1c, base excess, and procalcitonin.

“Glaringly obvious and remiss is that lactate is not on there, which is interesting,” Dr. Isbell said. “It would require digging down, and apparently they didn’t find an association.”

The Epic tool also looks for the presence of various drugs.

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