Robert Hauser

CancerLinQ and the Future of Cancer Care

Patients, health care providers, and payers all have a similar interest in a health care system that is both efficient and intelligent. The attributes of such a system are widely recognized: we want a system that provides widespread access to consistently high-quality, science-based medical care; we want that system to be efficient, avoiding unnecessary waste, while delivering the right treatments to the right patients in a timely fashion; we want a system that allows us to both learn from our experience and generate new knowledge that will inform future treatment options; and we want a system that is compassionate and caring. What we want from a health care system often runs up against real-life obstacles and challenges: a fragmented delivery system, varying levels (or lack of) insurance, a growing burden of regulation and paperwork, and an increasingly complex understanding of tumor biology and the therapeutic approaches derived from this biology. New challenges are on the horizon-emerging genomic and imaging technology, with their enormous cognitive and data burdens, and a looming demographic challenge, where inadequate personnel resources face an aging population and an explosion of new treatments. Not all problems have technologic solutions, but many of the issues described above have potential solutions related to information technology. ASCOs CancerLinQ, described in this article, is an evolving attempt by the Society to improve the quality and efficiency of cancer care, while supporting education and research in the cancer field.

ASCO's Approach to a Learning Health Care System in Oncology

The promise of emerging science and the challenges confronting todays health care system can both be addressed by fully embracing the IoMs vision of a learning health care system. ASCOs initial foray into realizing this vision for oncology shows great promise.

Assessment and Stratification of High-Impact Data Elements in Electronic Clinical Quality Measures: A Joint Data Quality Initiative Between CancerLinQ® and Cancer Treatment Centers of America

PURPOSE A joint data quality initiative between the Cancer Treatment Centers of America and the ASCO big data health technology platform CancerLinQ® was initiated to document and codify the steps taken to evaluate, stratify, and determine the potential effect of data elements used for electronic clinical quality measures as captured within structured fields in electronic health records. METHODS The processes involved the identification of clinical concepts required in measure population criteria and then to map these to the corresponding components of the CancerLinQ data model. A quantitative assessment of mappings between electronic clinical quality measure clinical concepts and attributes from the CancerLinQ clinical database was performed. In parallel, a qualitative analysis of high-impact data elements from the Cancer Treatment Centers of America clinical measures was made using local, expert consensus. RESULTS An impact assessment was derived using a count of the data elements across measures and the specific population criteria affected. CONCLUSION A list of putative high-impact data elements can provide guidance for clinicians to facilitate specific data element capture related to quality metrics in an electronic environment.