Acute brain dysfunction in the form of delirium or coma affects 50% of critically ill patients and is extremely hazardous. Those suffering from intensive care unit (ICU) delirium or coma experience substantial increases in healthcare utilization, mortality, and long-term cognitive impairment. Moreover, growing evidence that many risk factors are avoidable (or reducible) has resulted in increased attention to acute brain dysfunction as an avoidable hospital outcome. In 2007, the Centers for Medicare and Medicaid Services proposed the inclusion of hospital-acquired delirium as a quality outcome measure. The designation of delirium as a quality outcome has been held back by the lack of risk-adjustment. Similar to any hospital quality outcome (e.g. mortality, surgical site infection), methods are needed to account for pre-existing risk factors. In order for acute brain dysfunction to serve as a useful and reliable outcome of hospital quality and safety, a validated prediction model for acute brain dysfunction is needed. Because levels of brain dysfunction fluctuate from day to day, models must also account for daily changes in risk. This proposal describes a career development plan that enables me to develop expertise in acute brain dysfunction, build dynamic prediction modeling tools for innovative quality measures, and develop informatics skills for future implementation studies.
The Specific Aims of the research are a) To identify clinical risk factors for acute brain dysfunction among critically ill patients through a systematic literature review, b) To develop dynamic transition models that predict daily changes in acute brain dysfunction in critically ill elderly, and c) To externally validate and update the candidate risk prediction models in a cohort of critically ill patients, utilizing clinical data sources. The career development plan integrates;a) advanced coursework in health system improvement, biostatistics, and bioinformatics, b) participation in local / national meetings to develop expertise in geriatrics, predictive modeling, and quality improvement, c) a multidisciplinary mentored research experience, and d) a highly supportive research environment. This environment includes an internationally recognized NIA funded ICU Delirium and Cognitive Impairment Study Group, an AHRQ funded Evidence-based Practice Center, a distinguished Department of Biomedical Informatics, NIH funded Clinical and Translational Science Award, and a Master of Public Health Program that places 90% of graduates into academic careers. Overall, this career development award will advance my career in quality and aging research. In addition, the award will provide critical support to guide translational studies / R01 applications. Future studies will assess the impact of daily acute brain dysfunction prediction models for risk-targeted interventions and study the impact of acute brain dysfunction surveillance to measure quality.
Over recent decades, intensive care units (ICUs) have witnessed substantial growth in the number of older patients and observed a concurrent epidemic of acute brain dysfunction in the form of delirium and coma. Although acute brain dysfunction is associated with a wide range of poor outcomes, clinicians do not have tools to predict its occurrence that can help guide clinical decisions and monitor quality of care. The candidate will therefore develop a dynamic prediction model for acute brain dysfunction and establish its potential for future applications that will improve the quality and safety for older hospitalized patients.
|Petersen, Alec W; Shah, Avantika S; Simmons, Sandra F et al. (2018) Shed-MEDS: pilot of a patient-centered deprescribing framework reduces medications in hospitalized older adults being transferred to inpatient postacute care. Ther Adv Drug Saf 9:523-533|
|Herling, Suzanne Forsyth; Greve, Ingrid E; Vasilevskis, Eduard E et al. (2018) Interventions for preventing intensive care unit delirium in adults. Cochrane Database Syst Rev 11:CD009783|
|Graham, Kelly L; Auerbach, Andrew D; Schnipper, Jeffrey L et al. (2018) Preventability of Early Versus Late Hospital Readmissions in a National Cohort of General Medicine Patients. Ann Intern Med 168:766-774|
|Han, Jin H; Hayhurst, Christina J; Chandrasekhar, Rameela et al. (2018) Delirium's Arousal Subtypes and Their Relationship with 6-Month Functional Status and Cognition. Psychosomatics :|
|Marra, Annachiara; Pandharipande, Pratik P; Shotwell, Matthew S et al. (2018) Acute Brain Dysfunction: Development and Validation of a Daily Prediction Model. Chest 154:293-301|
|Vasilevskis, Eduard E; Chandrasekhar, Rameela; Holtze, Colin H et al. (2018) The Cost of ICU Delirium and Coma in the Intensive Care Unit Patient. Med Care 56:890-897|
|Han, Jin H; Brummel, Nathan E; Chandrasekhar, Rameela et al. (2017) Exploring Delirium's Heterogeneity: Association Between Arousal Subtypes at Initial Presentation and 6-Month Mortality in Older Emergency Department Patients. Am J Geriatr Psychiatry 25:233-242|
|Vasilevskis, Eduard E; Ouslander, Joseph G; Mixon, Amanda S et al. (2017) Potentially Avoidable Readmissions of Patients Discharged to Post-Acute Care: Perspectives of Hospital and Skilled Nursing Facility Staff. J Am Geriatr Soc 65:269-276|
|Boehm, Leanne M; Dietrich, Mary S; Vasilevskis, Eduard E et al. (2017) Perceptions of Workload Burden and Adherence to ABCDE Bundle Among Intensive Care Providers. Am J Crit Care 26:e38-e47|
|Han, Jin H; Vasilevskis, Eduard E; Chandrasekhar, Rameela et al. (2017) Delirium in the Emergency Department and Its Extension into Hospitalization (DELINEATE) Study: Effect on 6-month Function and Cognition. J Am Geriatr Soc 65:1333-1338|
Showing the most recent 10 out of 69 publications