A Novel Graph Processing Architecture to Ascertain & Monitor Care Coordination

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Well-orchestrated, multidisciplinary care improves patient outcomes and decreases medical costs. Federal agencies including CMS and AHRQ seek to increase care coordination nationally as a means of improving healthcare quality. However, the ability to define and measure care coordination remains an elusive target. The AHRQ "Care Coordination Measures Atlas" suggests care coordination measures depend on: 1) HIT systems that track essential data elements. 2) Effective workflows for clinicians and staff. The overall goal of this research is to improve the ascertainment of care coordination through an exhaustive encoding of healthcare actors, interactions, and data elements into a graph representation across the ambulatory and inpatient setting. The specific aims of the proposed research are to: 1) Using the Northwestern University Biomedical Informatics Core (NUBIC) Enterprise Data Warehouse (EDW), comprehensively characterize all clinical and non-clinical Northwestern Memorial Hospital (NMH) personnel and their interactions with patients as documented in either inpatient or outpatient medical record systems. 2) Represent the network of health care personnel and their interactions as a care coordination graph. 3) Identify how important characteristics of care teams including but not limited to size, composition, and intensity of interaction effect patient readmission rates for heart failure patients through retrospective graph analysis. The candidate, Nicholas Soulakis, is an Assistant Professor of Preventive Medicine at the Northwestern University Feinberg School of Medicine. His strong training in general epidemiology, public health surveillance and investigation, and biomedical informatics has allowed him to pursue a research agenda focused on novel methods of public health reporting using emerging health information technology in primary care. This K01 award provides a unique opportunity for Dr. Soulakis to expand into a new direction of quality informatics and patient outcomes, to better understand the ascertainment of healthcare networks, and to develop a more comprehensive scientific approach to understanding the dynamics of care coordination for hospitalized patient populations. It will also enable him to strengthen his curren research agenda by learning diverse, new methodologies to better quantify complex interactions between individuals and their healthcare teams and by building collaborative relationships among the Northwestern University engineering and social science research communities. This training will help Dr. Soulakis achieve his long-term goal of developing an independent research program that focuses on 1) understanding how well-coordinated, prevention focused care improves population outcomes across healthcare settings 2) using this knowledge to develop the most promising multi-level interventions to continuously improve and monitor medical quality using health information technology.