Documenting the Cancer Journey Peter Yu, MD


ata are useful only when they are transformed into knowledge. With the increasing complexity of chronic medical illness, of which cancer is a prime example, the value of medical data is realized when they are interpreted in clinical context and shared with the patient and the medical team involved in that patient’s care. Even more powerful is when the data set surrounding an individual patient is combined or aggregated with that of other similar patients and as a result informs us about the health of a population of patients. The goal of achieving both of these is embedded in the Institute of Medicine’s 5 overarching goals that underlie the Meaningful Use Program to incentivize the adoption of health information technology. To accomplish this requires 2 steps. First, an agreed-upon set of data that is valued by the health provider team and the patient must be contributed by the individuals most closely associated with the generation of those data. Second, a technical standard to message those data and achieve interoperability of information platforms, such as electronic medical records, needs to be agreed upon by all users. In this issue of the Archives of Pathology & Laboratory Medicine, Monica de Baca, MD, and coauthors lay valuable ground toward realizing the first step by describing a framework to conceptualize how data may look. By following the engineering concept of a use case, they gain insight into the type, source, and flow of valuable data that will be housed in the Integrated Disease Report. The time points where treatment decisions can be aided by clinical decision support tools become apparent. Collective intelligence derived from the contributions of patients, pathologists, radiologists, oncologists, and others will lead to less duplication of effort, more timely and correct decision making, and improved quality and value of health care. However, each medical specialty professional society that is routinely involved in caring for cancer patients must accept Accepted for publication March 18, 2014. From the Hematology-Oncology Department, Palo Alto Medical Foundation, Palo Alto, California. The author has no relevant financial interest in the products or companies described in this article. doi: 10.5858/arpa.2013-0562-ED Paul Yu, MD, is the president-elect of the American Society of Clinical Oncology. Corresponding author: Peter Yu, MD, Hematology-Oncology Department, Palo Alto Medical Foundation, 795 El Camino Real, Hematology-Oncology, SV 301, Palo Alto, CA 94301 (e-mail: yup3@ Reprints: Mary Kennedy, College of American Pathologists, 325 Waukegan Rd, Northfield, IL 60093-2750 (e-mail: mkenned@cap. org). 160 Arch Pathol Lab Med—Vol 139, February 2015

the challenge to coalesce a data set, using standard vocabularies, and drive uniform adoption by the physicians that each society represents. Also see p. 159 and p. 165. The authors recognize that caring for a cancer patient is a fluid and dynamic state. Furthermore, the data of interest to one viewer of the Integrated Disease Report will not always be those of another user. Third, whenever possible, electronic links to the source data documents, such as the full imaging or pathology report, should be available. This is a powerful example of how information technology transforms how we think, allowing us to discard outdated solutions and adopt more dynamic models that better meet our needs. Health information technology allows flexibility in formatting the user interface so that the user has access to the most relevant and up-to-date data, a significant advance over the paper document world where documents are static pieces of data and information, frozen in time and format. The American Society of Clinical Oncology has approached these same challenges by creating documentation templates that are specific to common malignancies as well as generic templates for other cancer types. A data architecture based on Health Level Seven data representation standards has been adopted to address the second step of interoperability. As each medical specialty in turn creates standards for data capture and messaging, we will need to harmonize these efforts. A standard lexicon and messaging format should be agreed upon early in this process, which means cooperation with standard development organizations such as the National Cancer Institute, National Library of Medicine, and American Joint Committee on Cancer. The promise and allure of rapid-learning health systems based on computational sciences are dependent upon data liquidity and data mining. Digital health information that is accurate and exchangeable through defined, comprehensive data sets such as the Integrated Disease Report will foster the development of learning health systems that accelerate knowledge discovery and inform medical practice.


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Documenting the cancer journey.

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