This is an ARRA competitive revision of P30-NR005043 Center for Nursing Outcomes Research. We seek to extend the scope of the parent grant to create a new interdisciplinary collaboration with the Cartographic Modeling Laboratory (CML) and investigators in human geography and spatial analysis and to apply a novel approach, Geographic Information Systems (GIS) technology, to nursing outcomes research focused on reducing racial and ethnic disparities in hospital outcomes. Our work is motivated by recent research suggesting that features of hospitals, as contrasted with individual characteristics of patients, are important determinants of racial/ ethnic inequalities in outcomes of hospital care. We want to explore further, and with more complete data than has been available previously, the effects of socioeconomic status of individual patients on outcomes as well as the compositional effects of aggregations of sub-groups of patients by hospital. The latter addresses evidence that outcomes are worse for all patients in hospitals that care for a large proportion of minority patients. We will match the zip codes of the millions of patients in our 2005-06 database of 859 hospitals in 4 states with detailed information from CML on a variety of data about their neighborhoods, including income and education, and we will compute the distance from their home to the hospital where they received care. Likewise we will add to our comprehensive survey-based information on nurses who practice at these hospitals by deriving from their zip codes information including the travel time from their homes to their employing hospitals. Finally, we will enrich our information about hospitals with detailed information on their locations and market areas. The proposed study has the following aims: 1) to estimate patient characteristics not included in administrative databases (such as socioeconomic status and time traveled from home to hospital) in an effort to learn more about how previously unmeasured characteristics of patients and their communities impact outcomes of hospital care;2) to determine hospital characteristics (beyond teaching status and size) that potentially contribute to disparities in outcomes including mapping the geographic distribution of nurses relative to hospital location, whether nurses travel longer to work at hospitals with good work environments, and socioeconomic conditions and market factors associated with hospital location;and 3) to integrate the new information derived from spatial analyses into predictive models of hospital outcomes developed previously by CNOR investigators to shed new light on to what extent targeted nursing resource interventions could be successful in reducing disparities.
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