Transition Networks in a Cohort of Patients with Congestive Heart Failure: A Novel Application of Informatics Methods to Inform Care Coordination.

BACKGROUND: Unnecessary hospital readmissions are one source of escalating costs that may be reduced through improved care coordination, but how best to design and evaluate coordination programs is poorly understood. Measuring patient flow between service visits could support decisions for coordinating care, particularly for conditions such as congestive heart failure (CHF) which have high morbidity, costs, and hospital readmission rates. OBJECTIVES: To determine the feasibility of using network analysis to explore patterns of service delivery for patients with CHF in the context of readmissions. METHODS: A retrospective cohort study used de-identified records for patients ≥18 years with an ICD-9 diagnosis code 428.0-428.9, and service visits between July 2011 and June 2012. Patients were stratified by admission outcome. Traditional and novel network analysis techniques were applied to characterize care patterns. RESULTS: Patients transitioned between services in different order and frequency depending on admission status. Patient-to-service CoUsage networks were diffuse suggesting unstructured flow of patients with no obvious coordination hubs. In service-to-service Transition networks a specialty heart failure service was on the care path to the most other services for never admitted patients, evidence of how specialist care may prevent hospital admissions for some patients. For patients admitted once, transitions expanded for a clinic-based internal medicine service which clinical experts identified as a Patient Centered Medical Home implemented in the first month for which we obtained data. CONCLUSIONS: We detected valid patterns consistent with a targeted care initiative, which experts could understand and explain, suggesting the method has utility for understanding coordination. The analysis revealed strong but complex patterns that could not be demonstrated using traditional linear methods alone. Network analysis supports measurement of real world health care service delivery, shows how transitions vary between services based on outcome, and with further development has potential to inform coordination strategies.

Perceived information needs and communication difficulties of inpatient physicians and nurses.

In order to understand the differing perceptions of information needs and communication patterns of healthcare professionals as they relate to medical errors, we conducted a survey and 5 focus group sessions of inpatient physicians and nurses. Although nurses and physicians stated differing information needs, both groups expressed significant problems with obtaining patient, domain and institution-specific information in a timely manner. Identification of appropriate providers and establishing contact with those people was perceived as the most pressing communication need. All focus group participants felt that communication difficulties were common and could give examples in which such difficulties led to adverse events. Our studies suggest that information needs and communication difficulties are common and can lead to medical errors or near misses. Many of these problems may be amenable to information technology solutions.

Development of an ontology to model medical errors, information needs, and the clinical communication space.

Medical errors are common, costly and often preventable. Work in understanding the proximal causes of medical errors demonstrates that systems failures predispose to adverse clinical events. Most of these systems failures are due to lack of appropriate information at the appropriate time during the course of clinical care. Problems with clinical communication are common proximal causes of medical errors. We have begun a project designed to measure the impact of wireless computing on medical errors. We report here on our efforts to develop an ontology representing the intersection of medical errors, information needs and the communication space. We will use this ontology to support the collection, storage and interpretation of project data. The ontology's formal representation of the concepts in this novel domain will help guide the rational deployment of our informatics interventions. A real-life scenario is evaluated using the ontology in order to demonstrate its utility.