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57 9 Recommendations Because data linkage must ultimately occur at the state level, each state will have to work out its state-specific process. In addition, states should have some flexibility in how to implement data linkage while still maintaining comparability of statistics across states. Although many issues that must be addressed, including channels of communication, state law, and agency relationships, are state-specific, many of the problems of data linkage are common across states. In particular, technical challenges follow common themes across states, and technical solutions can be widely applicable. In the context of a national program and a project meant to address this problem across the country, our recommendations focus on steps that can benefit all states and avoid having each state âreinvent the wheelâ in its effort to develop a linkage system. In principle, none of these activities is on the critical path to linkage within states. Many states, particularly those associated with the CODES program, are successfully linking crash, medical outcome, and a variety of other datasets already. However, as the CODES program demonstrated, access to technical assistance and centralized problem-solving facilitates progress. We recommend the following: A. Many aspects of the linkage process are state-specific and will need to be handled within each state accordingly. However, all states could benefit from a source of technical assistance at the national level. We recommend a broad technical support program that is dedicated to promoting data linkage at the state level through a variety of means, including, but not limited to probabilistic linkage. Specifically, we suggest the following areas of centralized support: 1. Development of a national crash data schema and corresponding XML, based on MMUCC, which would provide the same benefits that NEMSIS has provided to the EMS community. In particular, such a schema should be designed to incorporate MMUCC, additional state-specific variables, and to facilitate linkage to NEMSIS and NTDB schemas. 2. Development of clear methods and criteria for testing quality of linkage systems (probabilistic or otherwise). Levels of linkage quality (in terms of bias, accuracy, and completeness) should also be associated with guidance in how to analyze the data and how to improve linkage quality. 3. Development of a repository for lessons learned, methods used (including those tried and rejected), and contacts in states that can provide advice. This should include (but not be limited to): a) Lists of variables states use for probabilistic linkage (if appropriate) and linkage success; b) Software available and algorithms used for probabilistic linkage, along with the pros and cons of each; c) Non-probabilistic linkage approaches successes and failures; d) Background on the data warehouse model and how to build one over time; e) Lists of vendors used by states for different elements of the data linkage process; and f) Contact information for individuals involved in state data linkage projects to provide assistance or advice. 4. Development of marketing materials that TRCCs can use to advertise the benefits of linkage to all groups that need to be involved. Coordination of a message at the national level would be helpful to gain the involvement of agencies that are not as used to working together (e.g., state health agencies and state DOTs).
58 5. Development and hosting of workshops for state data holders to learn about linkage approaches and discuss challenges with other states. B. We also recommend some additional work that could be done either as part of the work of a national technical assistance program or as separate, smaller efforts: 1. Generate a clear, written interpretation of HIPAA in the context of data linkage that defines clearly what mechanisms must be put in place to link data and still maintain HIPAA compliance. While HIPAA does not prevent data linkage or even including linked (de-identified) data in a state data warehouse, it does put additional security requirements on datasets that include such information. 2. Investigate the potential for vehicle-to-vehicle (V2V) communication to aid in passing identifiers on the scene. This should include assessment of what an application would need to do, potential hurdles in implementation, and estimated short-term (software development) and long-term costs. This project could also investigate the general problem of using event-specific (but not person-specific) identifiers to improve probabilistic linkage among occupants within the event. Such work could be applied to other event-specific linkage approaches (such as passing crash report number to EMS and trauma databases). 3. Develop a more detailed sampling protocol that includes costs of sampling and estimates of sample size needed for a set of target analyses. A pilot sampling project should be included to ensure that logistical challenges and costs are fully identified.
