Identifying patient subgroups and processes of care that cause outcome differences following ICU vs. ward triage among patients with acute respiratory failure and sepsis
- Institution
- University of Pennsylvania, PA
- Principal investigator
- George L Anesi
- Funding
- $735K
- Duration
- 2023–2027
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Abstract
PROJECT SUMMARY Decisions to admit patients with acute respiratory failure (ARF) and sepsis (the most common and lethal cause of the acute respiratory distress syndrome) to intensive care units (ICUs) are highly variable across the US. And, yet, these triage decisions have a substantial impact on patient outcomes. In our prior work, we used detailed electronic health record (EHR) data from 9.2 million hospitalizations and found that decisions to admit ARF patients to wards were associated with a 3.8% absolute increase in mortality. In contrast, choices to admit sepsis patients to ICUs resulted in considerably longer length of stay and a 5.1% absolute increase in death. The nationwide impact of such discretionary triage would be exponentially greater. Our findings highlight tremendous opportunities to improve ARF and sepsis outcomes by identifying the patient subgroups and processes of care that most strongly contribute to the benefits and harms of ICU- versus ward-based care. This application proposes to update our ARF and sepsis cohort such that it includes all admissions from 2013 through 2022 across 29 hospitals in the Kaiser Permanente Northern California and University of Pennsylvania health systems, and incorporate more than 100 more data fields per patient. This curation of highly granular EHR data will enable us to identify the: (1) distinct patient subgroups and phenotypes among those meeting the syndromic criteria of `ARF' and `sepsis;' and the (2) processes of care and (3) inpatient complications that causally explain the observed associations of ICU vs. ward triage with patient outcomes. Our multidisciplinary team will apply diverse expertise in instrumental variable regression, mediation analyses, machine learning, complex EHR data, and probabilistic phenotyping to complete three aims that promote our long-term goal of improving care, and hence outcomes, for patients with ARF and sepsis regardless of where they are treated. Several methodological innovations will enable us to achieve these goals, and, in turn, to not only surmount key limitations of prior studies that sought to determine which acutely ill patients benefit from ICU admission, but identify the mechanisms underlying such triage effects. These data will also allow us to quantify the impact of COVID-19 on ICU and ward triage patterns, care processes, and outcomes among ARF and sepsis patients, thereby modernizing our results and enabling their applicability to pandemic eras. Completing the aims of this study will improve public health by identifying ways in which emergency departments, ICUs, and wards can improve outcomes for the more than 4 million Americans hospitalized each year with ARF and/or sepsis. Such results will enable development and testing of personalized triage algorithms, and guide optimal care for patients without always requiring ICU admission, thereby improving patient outcomes, reducing health care costs, and preserving ICU capacity for patients who truly need it.
Research team
- George L AnesiPI
- Scott D HalpernPI
- Vincent LiuPI
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