Studies of Welfare Populations: Data Collection and Research Issues. Data Access Principles Regarding the Organization with the Data

06/01/2002

Principle 1: Strong Political or Administrative Leadership

We found that many new and established data-matching projects were successful because they had the interest or patronage of well-connected or inspiring leaders. This, in and of itself, comes as no surprise. However, the sources of this leadership are diverse.

In some cases, this leadership was political in nature. For example, the University of Missouri at Columbia Department of Economics began its long collaboration with the Missouri Department of Social Services at the request of Governor Mel Carnahan. In January 1997, the university was asked to begin an analysis of the workforce development system for the Governor's Training and Employment Council. Because of the high-profile support for this project, the agencies providing data were forthcoming so as not to appear to be hindering the effort. A governor's directive can be powerful.

Another example of political leadership can be found in the moving force behind the Texas State Occupational Information Coordinating Committee (SOICC). The SOICC was mandated by the U.S. Congress via the federal Job Training Partnership Act (JTPA) and the Carl D. Perkins Vocational Education Act of 1976. The Texas SOICC receives no state general revenue funding and is supported by the U.S. Department of Labor through the national network organization National Occupational Information Coordinating Committee.

Data linking is facilitated when those at the top make it clear that they want to know about the impacts governmental programs are having on clients. Governors can provide this kind of leadership. More commonly, and perhaps most effectively, this leadership can be found among program administrators, bureau chiefs, and agency heads. For example, California found valuable leadership in the California Department of Social Services (CDSS) Research Branch. Staff in the Research Branch made use of many years of experience in service to the state to forge data-sharing coalitions between CDSS and the California Employment Development Department. In Illinois, the decisions to link data were made by Department of Human Services administrators who were supporting the Welfare Leavers Study.

Principle 2: Designation of a "Data Steward" in the Department and Structuring Staffing Levels and Responsibilities to Cover Data Access Requests

Adequate staffing is essential for ironing out the issues of data access. Data-linking requests require extensive administrative and analytic effort. In fact, as the rapid growth of information technology makes privacy and security policies de rigueur, information security officers in many states are requiring the completion of more and more complicated data security and confidentiality procedures for data linking.

Information security offices are not solely responsible for the time and effort it takes to get a data-linking project approved. Each state department often requires approval by a contracts office, a legal office, and the program with the data. In addition, many projects are required to submit their project for review by the state's human subjects committee. Each of these approvals can take from a few days to a few weeks, or even months in some cases.

Success in data-linking projects requires staff dedicated to shepherding data requests through the complexities of confidentiality requirements and data access issues. Although lawyers are often assigned these tasks because of their knowledge of statutorily defined notions of confidentiality, experienced government staff with a research bent must be involved as well in order to explain the technical aspects of data linking. In fact, agency staff with a strong investment in data linking and a belief in the benefits of research can overcome exaggerated fears about data linking and overly narrow interpretations of the law.

A delicate balance must be reached here. The law regarding the use of administrative data is typically sufficiently ambiguous that beliefs about the usefulness of a research project, about the risks from data matching, and about the trustworthiness of researchers can determine the outcome of a data request. It is easy for lawyers to assume that research is not very useful, that the risks of data matching are great, and that researchers cannot be trusted with the data. Yet we found in our interviews that research staff believe data matching provides extraordinary opportunities for high-quality and relatively inexpensive evaluations. Moreover, researchers can make the case that the risks from data matching for research purposes typically are quite low--certainly much lower than the risks from many other kinds of data matching projects. What is needed is a balance of agency staff committed to both the appropriate protection of data and the appropriate sharing of data for research and evaluation. We were told in our interviews that there are plenty of staff people, legal and otherwise, who are zealously "protecting" data in the name of confidentiality, but there are not enough with strong investments in data linking and a belief in the benefits of research to their department to make the case for data matching.

Our interviews provide examples. One respondent in Missouri referred to himself as the administrative data "guardian." He saw himself as the data shepherd, the person who saw that the data got to where it needed to go and got there safely. He facilitated data access, safeguarded data confidentiality, and educated researchers about the complexities of the data. Other Missouri respondents reported this administrator to be knowledgeable and helpful. In the Washington State Department of Social and Health Services, staff in the Office of Planning and Research blazed new trails of data access through state divisions that were unfamiliar with, if not uncomfortable with, providing data to researchers. One respondent from Wisconsin reported an environment of data "stewardship" coming about in the state, an environment of making data available in a responsible manner. The California Employment Development Department, Labor Market Information Division has designated a Confidential Data Coordinator. In Illinois, the Bureau of Program Design and Evaluation in the Department of Human Services frequently negotiates data access arrangements.

Principle 3: Develop a Written Confidentiality and Security Procedure--Keep a Catalog of Written Documents: Contracts, Memorandums of Understanding (MOU's), Personal Security Agreements.

A written policy of confidentiality and security is a must. This document should make explicit the data security procedures required of the data requesting organizations by the agencies with the data. This written policy should include detailed standards to maintain the privacy of individual data subjects. Another necessary document is a written guideline to obtaining data. This document can be provided to data requesters to assist them in applying for access to confidential data. The confidentiality and security manual and the guideline to obtaining data can provide assurance to data-providing agencies that proper consideration will be given to maintaining the confidentiality of their data in advance of the data being requested of them. They will also reassure data-providing organizations that their staff will not waste precious staff time fielding fly-by-night data requests.

In addition to these documents, there should be an archive of exemplary memorandums of understanding, letters of understanding, contracts for goods and services, data access agreements, and confidentiality agreements for use among state agencies or between state agencies and nongovernmental organizations. These documents should have explicit sections on the maintenance of data security and confidentiality, similar to the protocol described. The archive should also contain statements regulating individual behaviors, commonly known as "personal security agreements" or "statements of confidentiality". These documents require each individual staff person on the project to acknowledge procedures required for maintaining confidentiality and penalties for a breach of these procedures. An archive promotes quick and thorough contract negotiations, and it avoids the nuisance of having to start from scratch with every data request.

The California Department of Social Services Research Branch has prepared two such model documents: "The CDSS Confidentiality and Security Policy" and "The Guidelines for the Preparation of A Protocol." Also, in the new environment of "Data Stewardship," Wisconsin is developing templates and exemplar agreements.

Principle 10, "Put in Writing Mechanisms for Monitoring Confidentiality and Security and for Sanctioning Breaches," discusses briefly which confidentiality and security procedures one might want to include in a contract and therefore in the archive of documents.

Principle 4: The Agency Architecture Encompasses All "Providing" Agencies as in "Super Agencies"

In some cases, a "super agency" organization can facilitate sharing of data among departments within the agency. For example, in response to the latest welfare reforms, some states combined state agencies under an umbrella organization. In most cases, administrative data are considered to be owned by this overarching agency. Although this does not eliminate the need for appropriate bureaucratic negotiation on data access, in most cases it makes the process easier.

One respondent referred to the Illinois Department of Human Services as a "super agency." The department handles data for AFDC/TANF, the Food Stamps Program, Substance Abuse, Mental Health, Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) (family case management), Medicaid, and Child Care programs (and their data). Gaining access to some of these data was reported to be easier because of the "super agency" structure. It was reported that gaining access to data from Substance Abuse and WIC (family case management), although by no means easy, would have been even harder had not the agencies been part of this "super agency."

The Arizona Department of Economic Security (ADES) also can be considered a super agency. ADES covers a broad range of programs, including AFDC/TANF, Food Stamp Program, Medicaid, Child Welfare, Child Care, and Child Support Enforcement and Unemployment Insurance. A respondent reported that no interagency data access agreements were necessary with any of these programs because of this all-encompassing administrative structure.

Principle 5: A Central Clearinghouse Negotiates or Assists in Legal and/or Technical Issues

A centrally located institution or center can help facilitate data access. This center can be placed in the state government or outside, and it can serve a number of purposes.

First, a central organization can serve as a data archive or data warehouse that actually stores data from multiple state agencies, departments, and divisions. In some cases, data archives match the data and provide data requesters with match-merged files. In other cases, data archives provide a place where data from multiple agencies are stored so that data requesters can obtain the data from one source and match the data themselves.

Second, a central organization can serve as a data broker. This organization does not actually store data from other agencies but "brokers" or "electronically mines" data from other agencies on an ad hoc or regular basis. This organization then performs analyses on these data and reports results back to the requesting agency. The data are stored only temporarily at the location of the data broker, before they are returned to the providing agency or destroyed.

Third, a central organization can serve another very important purpose, as a clearinghouse for legal issues around confidentiality. Organizations like this are sometimes called internal review boards. They maintain exemplar or template agreements, contracts, documents, as described earlier.

For example, the South Carolina Budget and Control Board (SC BCB) serves all three functions--data archive, data broker, and internal review board. The SC BCB plays a key role in the general management of state government. This institution is unique to South Carolina and oversees a broad array of central administrative and regulatory functions. In our interview with staff from the Welfare Leavers Study grantee in South Carolina, we learned of the office of Research and Statistics in the SC BCB. The office gathers, analyzes, and publishes data vital to the social, and economic well-being and health of residents of South Carolina. These data are used by other state agencies and by local governments to guide planning, management, and development decisions. The office also works with other agencies to prevent overlap and duplication of data-gathering activities. The Welfare Leavers Study grantee (South Carolina Department of Social Services) negotiated data access through the SC BCB and conducted their analysis inhouse. However, one South Carolina respondent noted that despite the central location of this clearinghouse, it was still necessary to obtain legal authorization to data access on an agency-by-agency basis.

The Arizona Department of Economic Security is in the process of building a data warehouse, referred to as the "data mart." The data mart will automatically receive and link data from all the programs covered by ADES. The Welfare Leavers Study researchers used this resource to access data. At this point, the data mart provides only data-archiving and data-matching functions. However, eventually the data mart will include front-end data analysis functions.

The Texas State Occupational Information Coordinating Committee (SOICC) serves as a data broker. SOICC does not archive or store data at all. Our respondent reported that SOICC "mines data electronically" from relevant agencies, conducts analysis, and provides requesters with results of these analyses.

In Florida, the Florida Education and Training Placement Information Program (FETPIP) serves a data brokerage role by archiving data and providing analysis. However, our respondent reported that FETPIP did not archive data or provide analyses for the Florida Welfare Leavers Study grantee.

The Chapin Hall Center for Children at the University of Chicago has developed an extensive archive of child welfare and family welfare data. The center uses these data to assess the impacts of welfare reform and other programs on child well-being. Chapin Hall's archive of data on children's welfare is called the Integrated Database on Children's Services in Illinois (IDB). Built from administrative data collected over two decades by Illinois human services programs, the IDB allows researchers to create a comprehensive picture of the interactions children and their families have with social programs offered by the state. One respondent cited this database as an absolutely invaluable resource.

The University of Missouri at Columbia Department of Economics is another example of a center that archives and analyzes data. Here data from multiple state agencies are matched, merged, and analyzed. The archive contains data from five state agencies: the Department of Economic Development, the Department of Social Services, the Department of Labor and Industrial Relations, the Department of Elementary and Secondary Education, and the Department of Higher Education. The staff provide research and analysis for many of the separate agencies on an ad hoc and a contractual basis.

In Washington State, the Institutional Review Board serves a role as a central place to resolve legal issues of data access. The IRB assisted the Welfare Leavers Study grantee in ironing out legal issues. The IRB serves as a human subjects review board and maintains exemplar documents.

Principle 6: Plan for Data Access in the Development of Information Systems

It would be difficult to include all the requirements for the development of information systems in a single principle. The development of information systems requires a set of its own guiding principles, including, but not limited to, adoption of common identifiers and establishment of standardized data definitions.

Rather than try to list all of the relevant principles, we cite the following example from California: The Family Health Outcomes Project (FHOP). It is a joint project of the Department of Family and Community Medicine and the Institute for Health Policy Studies (both at the University of California at San Francisco). Initiated in 1992, FHOP is a planning and training effort to streamline and standardize the administrative aspects of state child and family health programs in California.

FHOP has developed an information structure for an extremely fragmented and difficult-to-access system--health care and health-related services for women and children in California. California has many categorical health and social service programs serving women, children, and families. Each has a separate application and eligibility process, although all require similar application information. Clients must complete an application for each service they wish to receive, often at different times and in different locations. To bring these programs "together," FHOP has developed CATS, a "Common Application Transaction System." CATS addresses the need for a uniform, accessible application and eligibility determination process and provides aggregate data for state and local planning and management.

CATS is a methodology for integrating registration and eligibility determination across numerous state-funded family health programs. CATS establishes unique client identification through the use of core data elements (birth name, birth date, birth place, mother's first name, and gender) and confirmatory data elements (social security number, other client number, father's name, mother's maiden name, current name/client alias/nickname, county of client's residence, and zip code of client's residence). Utilizing probabilistic matching and relative weighting of the core data elements, CATS can uniquely identify clients and find duplicate records for the same client.

Health care providers can link local automated registration systems to the state CATS hub, which can then return eligibility and demographic information. The CATS goal is to simplify the eligibility process so that the necessary demographic and self-declared financial information need only be collected and entered once.

In summary, CATS includes a standardized approach to collecting demographic, race, ethnic, and financial eligibility information; standardized confidentiality procedures and informed consent for sharing information; information on client eligibility status for Medi-Cal, Family Planning, Healthy Families Children's Health Insurance Program (CHIP), and Children's Medical Services; methods for the discovery of duplicate client records for tracking and case management; and a secure Internet connection option for community clinics and private providers. By providing a common method for collecting information on participation in state child and family health programs, CATS makes it possible to identify clients across programs, track them over time, and monitor outcomes. From a researcher's perspective, systems such as CATS make matching data across data systems much simpler.

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