حمایت از خود ارزیابی در دولت های محلی از طریق کشف دانش و داده کاوی

The business sector has already recognized the importance of information flow for good management, with many businesses adopting new technology in data mining and data warehousing for intelligent operation based on free flow of information. Free flow of information in government agencies is just as important. For example, in child welfare, entities that fund social services programs have increasingly demanded improved outcomes for clients in return for continued financial support. To this end, most child welfare agencies are paying more attention to the outcomes of children in their care. In North Carolina, many county departments of social services have successfully adopted the self-evaluation model to monitor the effects of their programs on the outcomes of children. Such efforts in self-evaluation require good information flow from state division of social services to county departments of social services. In this paper, we propose a comprehensive KDD (Knowledge Discovery and Data mining) information system that could upgrade information flow in government agencies. We present the key elements of the information system and demonstrate how such a system could be successfully implemented via a case study in North Carolina. The next generation infrastructure in digital government must incorporate such information system to enable effective information flow in government agencies without compromising individual privacy.

In recent years, government agencies have been under pressure to be more effective and are increasingly held accountable for outcomes. To support this new mode of operation, resources are being set aside for quality evaluations that go beyond simple counts of services provided. For example, in child welfare, the Adoption and Safe Families Act (ASFA) of 1997 identified a national set of outcome measures that can be used to gauge state and national progress in reaching the goals of child safety, permanency, and well-being. A key factor in such evaluations is the free flow of government information, which is used to evaluate the operations of government organizations and measure real outcomes that result from its services while still protecting individual privacy. With advances in information technology, the business sector has already realized the importance of effective information flow for good management (Gavirneni, Kapuscinski, & Tayur, 1999) and many have implemented large-scale information systems to enable information flow. The next generation infrastructure in digital government must also enable effective information flow in government agencies without compromising individual privacy. A good example of the need for effective information flow in government agencies is demonstrated in the use of self-evaluation in child welfare agencies. Self-evaluation is a form of empowerment evaluation that is collaborative and participatory. Through self-evaluation, a county social services agency, with the assistance of experts, can design, monitor, and improve indicators that ultimately improve the outcomes that are important to their local community. A key element in the self-evaluation efforts is the availability of timely and accurate data that appropriately measure the outcomes of interest. In the case of social services agencies, comprehensive data on families and children served by the agency is required. However, many of the local agencies lack the resources to collect and analyze the data for such evaluations. In addition, as many of the local agencies in a state would have similar goals, much effort would be duplicated if each local agency built its own capacity for such data analysis. Furthermore, it would be easier to have consistency across similar outcomes in different local governments if the state provided the technical assistance for such efforts (Usher, Wildfire, & Schneider, 2001). In North Carolina, a KDD information system was built to support self-evaluation efforts at the local level. In collaboration with the North Carolina Department of Health and Human Services (NC-DHHS), the Jordan Institute for Families at the School of Social Work at the University of North Carolina at Chapel Hill (UNC-CH) built an information system to publish comprehensive outcome measures at the local level for child welfare. The project built a dynamic website that contains information on various state and federal outcome measures for child welfare for all 100 counties in North Carolina. These outcome measures are provided at various units such as county, groups of counties, state, as well as different time periods and sub-categories like age, race, and gender. Counties can use this vast amount of information to construct their own self-evaluation system and monitor their progress from different perspectives. In this paper, we propose a comprehensive KDD (Knowledge Discovery and Data mining) information system that could upgrade information flow in government agencies via a case study in North Carolina. We first describe the different policies in child welfare that have played a key role in its success as well as the details of how information is being used. Next we will demonstrate how effective information flow among state and county government agencies has empowered both to better serve their communities via self-evaluation. We then follow by presenting the key elements of the information system and demonstrate how similar systems could be successfully implemented. Such a KDD information system should be an integral part of the next generation information infrastructure in digital government. The remainder of the paper is organized as follows. Chapter 2 provides an overview of the related works in KDD and self-evaluation. In Chapter 3 we introduce the language used in child welfare with a full discussion of child welfare policies and how it uses technology and information to better serve its community. Chapter 4 demonstrates the use of self-evaluation in Guilford County, NC. Chapter 5 details the KDD information system built for the project highlighting the important technical details. And finally, Chapter 6 concludes with a discussion of lessons learned and future works.

A number of enhancements are planned for the KDD system. These enhancements involve both the information that is available as well as the way it is presented to the users. We have plans to add information about the fiscal aspects of the child welfare system, as well as information on earnings and incarceration of former foster care youth. There are also plans to revamp the website using CSS (Cascading Style Sheets) technology to improve usability and different online training methods so more people can use our website readily. The use of operational data to improve management practices in business is not new. The private sector has been using KDD technology for effective marketing and sales since the early 1990s (Fayyad et al., 1996). Such technology transfer to the public sector can greatly enhance federal and state government practices as it can effectively share information between many diverse entities. KDD technology makes it possible to have consistency and diversity at the same time. To effectively address the many local problems, diversity is a must while accountability requires consistency of measurements. The next generation information infrastructure in digital government should incorporate such KDD information systems to enable effective information flow in government agencies without compromising individual privacy. We have learned that trust, real support through policies and funds, access to good technical expertise in both the content area and IT, and training are key factors to successfully implementing the KDD information infrastructure in government (Kum et al., 2004). Access to the required expertise can be obtained through strong partnerships between government agencies and interdisciplinary teams at universities. The partnerships can lead to successful implementation of KDD information systems in the public sector while providing a priceless opportunity for research.