Augmenting Predictive Modeling Tools with Clinical Insights for Care Coordination Program Design and Implementation.

CONTEXT: The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health's (DH) integrated, safety net health care system $19.8 million to implement a "population health" approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner's Chronic Care Model (CCM) to achieve the "Triple Aim": improved health for populations, care to individuals, and lower per capita costs. CASE DESCRIPTION: This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective. FINDINGS: In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables. CONCLUSIONS: We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions.

The pulmonary endothelial glycocalyx regulates neutrophil adhesion and lung injury during experimental sepsis.

Sepsis, a systemic inflammatory response to infection, commonly progresses to acute lung injury (ALI), an inflammatory lung disease with high morbidity. We postulated that sepsis-associated ALI is initiated by degradation of the pulmonary endothelial glycocalyx, leading to neutrophil adherence and inflammation. Using intravital microscopy, we found that endotoxemia in mice rapidly induced pulmonary microvascular glycocalyx degradation via tumor necrosis factor-α (TNF-α)-dependent mechanisms. Glycocalyx degradation involved the specific loss of heparan sulfate and coincided with activation of endothelial heparanase, a TNF-α-responsive, heparan sulfate-specific glucuronidase. Glycocalyx degradation increased the availability of endothelial surface adhesion molecules to circulating microspheres and contributed to neutrophil adhesion. Heparanase inhibition prevented endotoxemia-associated glycocalyx loss and neutrophil adhesion and, accordingly, attenuated sepsis-induced ALI and mortality in mice. These findings are potentially relevant to human disease, as sepsis-associated respiratory failure in humans was associated with higher plasma heparan sulfate degradation activity; moreover, heparanase content was higher in human lung biopsies showing diffuse alveolar damage than in normal human lung tissue.