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Abstracts Background Hospital mortality for patients with sepsis has recently declined, but sepsis survivors still suffer from significant long-term mortality and morbidity. There are limited data that support effective strategies to address post-discharge management of patients hospitalized with sepsis. Methods The Improving Morbidity during Post-Acute Care Transitions for Sepsis (IMPACTS) study is a pragmatic, randomized controlled trial at three hospitals within a single healthcare delivery system comparing clinical outcomes between sepsis survivors who receive usual care versus care delivered through the Sepsis Transition and Recovery (STAR) program. The STAR program includes a centrally located nurse navigator using telephone counseling and electronic health record-based support to facilitate best-practice post-sepsis care strategies for patients during hospitalization and the 30 days after hospital discharge, including post-discharge review of medications, evaluation for new impairments or symptoms, monitoring existing comorbidities, and palliative care referral when appropriate. Adults admitted through the Emergency Department with suspected infection (i.e., antibiotics initiated, bacterial cultures drawn) and deemed, by previously developed risk-stratification models, high risk for readmission or death are included. Eligible patients are randomly allocated 1:1 to either Arm 1, usual care or Arm 2, STAR. Planned enrollment is 708 patients during a 6-month period. The primary outcome is the composite of all-cause hospital readmissions and mortality assessed 30 days post discharge. Secondary outcomes include 30- and 90-day hospital readmissions, mortality, emergency department visits, acute care-free days alive, and acute care and total costs. Discussion This pragmatic evaluation provides the most comprehensive assessment to date of a strategy to improve delivery of recommended post-sepsis care. Trial registration ClinicalTrials.gov, NCT03865602. Registered retrospectively on 6 March 2019.

Importance:. Risk prediction models for patients with suspected sepsis have been derived on and applied to various outcomes, including readily available outcomes such as hospital mortality and ICU admission as well as longer-term mortality outcomes that may be more important to patients. It is unknown how selecting different outcomes influences model performance in patients at risk for sepsis. Objectives:. Evaluate the impact of outcome selection on risk model performance and weighting of individual predictor variables. Design, Setting, and Participants:. We retrospectively analyzed adults hospitalized with suspected infection from January 2014 to September 2017 at 12 hospitals. Main Outcomes and Measures:. We used routinely collected clinical data to derive logistic regression models for four outcomes: hospital mortality, composite ICU length of stay greater than 72 hours or hospital mortality, 30-day mortality, and 90-day mortality. We compared the performance of the models using area under the receiver operating characteristic curve and calibration plots. Results:. Among 52,184 admissions, 2,030 (4%) experienced hospital mortality, 6,659 (13%) experienced the composite of hospital mortality or ICU length of stay greater than 72 hours, 3,417 (7%) experienced 30-day mortality, and 5,655 (11%) experienced 90-day mortality. Area under the receiver operating characteristic curves decreased when hospital-based models were applied to predict 30-day (hospital mortality = 0.88–0.85; –0.03, composite ICU length of stay greater than 72 hours or hospital mortality = 0.90–0.81; –0.09) and 90-day mortality (hospital mortality = 0.88–0.81; –0.07, composite ICU length of stay greater than 72 hours or hospital mortality = 0.90–0.76; –0.14; all p < 0.01). Models were well calibrated for derived (root-mean-square error = 5–15) but not alternate outcomes (root-mean-square error = 8–35). Conclusions and Relevance:. Risk models trained to predict readily available hospital-based outcomes in suspected sepsis show poorer discrimination and calibration when applied to 30- and 90-day mortality. Interpretation and application of risk models for patients at risk of sepsis should consider these findings.