Much of what is discussed previously is required because public policy organizations are still, for the most part, in their first generation of information systems. These "legacy" systems are typically a decade or older mainframe installations that do not take advantage of much of today's technology. Data entry in the legacy systems, for example, is often quite cumbersome and requires a specialized data entry function. Frontline workers are typically not trained to do this or do not have the time or resources to take on the data entry task. An exception is in entitlement programs in some jurisdictions, where the primary activity for eligibility workers is collecting information from individuals and entering it into a computerized eligibility determination tool. The development of new graphical user interfaces that are more worker friendly--in that the screens flow in a way that is logical to a worker--is likely to have a positive effect on data entry both because of the ease of entry and because the worker may be able to retrieve information more easily. If this is the case, the worker will have a greater stake in the quality of the data.
The development of integrated online information systems, where a worker can obtain information on a client's use of multiple programs, also may have a positive effect on the quality of the data. First, the actual job of linking across the programs will likely be an improvement over the after-the-fact linking of records. For example, if an integrated system already exists, when a mental health case is opened for an individual with Medicaid eligibility, his or her records should be linked immediately. This, of course, requires an online record-linkage process for the one case or individual. Even though a researcher would still want to check whether an individual has multiple IDs, the process at the front end will greatly improve the quality of the analytic database.
Many states are now creating data warehouses in order to analyze many of the issues of multiple-program use and caseload overlap. These data warehouses "store" data extracts from multiple systems and link records from individuals across programs. If states are successful in creating comprehensive, well-implemented data warehouses, researchers may not have to undertake many of the cleaning or linking activities discussed in this paper. Government will have already done the data manipulations. The researchers, just as is typically done with survey data, will have to verify that the warehouse was well built. Although this may require some confidential information, it should make it easier to access administrative data.