Disparities between asthma management and insurance type among children.

Asthma is a chronic illness among children. Minority children may be vulnerable to asthma complications since more than half are from households that are poor or near poor, and some have no health insurance. Asthma management plans are important for the long-term treatment of asthma and beneficial for self-management. This study analyzed insurance type and the relationship between having an asthma management plan among children across all races with asthma. This study utilized the 2002 and 2003 National Health Interview Survey. Findings showed that whites were significantly more likely than Non-Hispanic blacks and Hispanics to have an asthma management plan (OR, 1.66; p = .0031). In this study, children who reported Children's Health insurance Program (CHIP) coverage were twice as likely to have an asthma management plan (OR, 2.67; p = .0004). Mandating all insurers to provide an asthma management plan to children with asthma may reduce the race-based inequities and differences in asthma management plan status.

Data mining for health executive decision support: an imperative with a daunting future!

Data mining is highly profiled. It has the potential to enhance executive information systems. Such enhancement would mean better decision-making by management, which in turn would mean better services for customers. While the future of data mining as technology should be exciting, some are worried about privacy concerns, which make the future of data mining daunting. This paper examines why data mining is highly profiled - the imperative toward data mining, data mining models and processes. Additionally, the paper examines some of the benefits and challenges of using data mining processes within the health-care arena. We cast the future of data mining by highlighting two of the many data mining tools available - one commercial and one freely available. Subsequently, we discuss a number of social and technical factors that may thwart the extensive deployment of data mining, especially when the intent is to know more about the people that organizations have to serve and cast a view of what the future holds for data mining. This component is especially important when attempting to determine the longevity of data mining within health-care organizations. It is hoped that our discussions would be useful to organizations as they engage data mining, strategies for executive information systems and information policy issues.