generate a unique set of limitations and challenges—all of which seem to be responsive to unique incentives and drivers.

This chapter highlights some notable existing and emerging efforts to coordinate clinical data into more readily available and usable resources; describes incentives for these activities; examines the shortfalls, limitations, and challenges related to various approaches to organizing and aggregating data; and looks at the dynamics pushing integration.

The National Cancer Institute (NCI), for example, has determined that the scale of its enterprise has reached a level that demands new, more highly coordinated approaches to informatics resource development and management. As discussed by Peter Covitz, chief operating officer of NCI, at NCI’s Center for Bioinformatics, the Cancer Biomedical Informatics Grid (caBIG) program was launched to meet this challenge. The caBIG infrastructure is a voluntary network that facilitates data sharing and interpretation with aims to translate knowledge from the laboratory bench to patient bedside. As a tool designed to link resources within the cancer research community, caBIG would ultimately function as a template for sharing and communicating in a common language as well as a platform for building tools to collect and analyze information. The caBIG project is an essential resource to complement other cancer research projects. Moreover, Covitz suggests, caBIG might serve as a possible model for engaging the broader challenge of developing nationwide, interoperable health information networks.

Translational health research draws information from institutional entities as the primary source of analysis. Such an approach has historically enabled researchers to compare outcomes and differences in practice patterns within organizations. Pierre-André La Chance, chief information officer and research privacy officer at the Kaiser Permanente Center for Health Research, offers strategies on cross-institution data sharing through local, interoperable data warehouses and data networks. With an interconnected approach to data, researchers can access data resources more efficiently; the data have higher quality and reliability for generating analyses and decisions that affect both treatment and policy. At Kaiser Permanente, work is underway to develop sharable administrative, disease registry, and clinical data resources as well as a biolibrary to increase access to Kaiser Permanente tumor registries and histology data.

One attainable goal of health information technology (HIT) is the ability to continuously enhance quality and safety in the delivery of health care. Current healthcare financial incentives, which encourage high-cost, high-volume care, steer clinicians away from fully achievable low-cost, high-quality care. Steven Waldren, director of the Center for Health Information Technology at the American Academy of Family Physicians (AAFP), notes that the AAFP highlights the principle that data aggregation can drive and support multiple aspects of healthcare delivery, including quality initiatives, health services and

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