An informatics infrastructure to catalyze cancer control research and practice.

PURPOSE: A disconnect often exists between those with the expertise to manage and analyze complex, multi-source data sets, and the clinical, social services, advocacy, and public health professionals who can pose the most relevant questions and best apply the answers. We describe development and implementation of a cancer informatics infrastructure aimed at broadening the usability of community cancer data to inform cancer control research and practice; and we share lessons learned. METHODS: We built a multi-level database known as The Ohio Cancer Assessment and Surveillance Engine (OH-CASE) to link data from Ohio's cancer registry with community data from the U.S. Census and other sources. Space-and place-based characteristics were assigned to individuals according to residential address. Stakeholder input informed development of an interface for generating queries based on geographic, demographic, and disease inputs and for outputting results aggregated at the state, county, municipality, or zip code levels. RESULTS: OH-CASE contains data on 791,786 cancer cases diagnosed from 1/1/2006 to 12/31/2018 across 88 Ohio counties containing 1215 municipalities and 1197 zip codes. Stakeholder feedback from cancer center community outreach teams, advocacy organizations, public health, and researchers suggests a broad range of uses of such multi-level data resources accessible via a user interface. CONCLUSION: OH-CASE represents a prototype of a transportable model for curating and synthesizing data to understand cancer burden across communities. Beyond supporting collaborative research, this infrastructure can serve the clinical, social services, public health, and advocacy communities by enabling targeting of outreach, funding, and interventions to narrow cancer disparities.

Recognition, diagnostic practices, and cancer outcomes among patients with unintentional weight loss (UWL) in primary care.

OBJECTIVES: Identify the incidence, rate of physician recognition, diagnostic practices and cancer outcomes for unintentional weight loss (UWL). METHODS: We completed a secondary analysis of structured and unstructured EHR data collected from adult patients between January 1, 2020 and December 31, 2021. We used four common definitions to define UWL, excluding patients with known causes of weight loss, intentional weight loss, and pregnancy. Unstructured physicians' notes were used to identify both intentional weight loss (e.g. dieting) as well as physician recognition of UWL. Cancer outcomes were identified within 12 months of UWL using diagnostic codes. Physician actions (lab tests, etc.) in response to UWL were identified through manual chart review. RESULTS: Among 29,494 established primary care patients with a minimum of two weight measurements in 2020 and in 2021, we identified 290 patients who met one or more criteria for UWL (1 %). UWL was recognized by physicians in only 60 (21 %). UWL was more common and more likely to be recognized among older patients. Diagnostic practices were quite variable. A complete blood count, complete metabolic profile, and thyroid stimulating hormone level were the three most common tests ordered in response to UWL. Five patients were diagnosed with cancer within 12 months of UWL (3 in whom UWL was recognized; two in whom it was not.). CONCLUSIONS: Unintentional weight loss is poorly recognized across a diverse range of patients. A lack of research-informed guidance may explain both low rates of recognition and variability in diagnostic practices.

Facilitating Cancer Epidemiologic Efforts in Cleveland via Creation of Longitudinal De-Duplicated Patient Data Sets.

BACKGROUND: Cleveland, Ohio, is home to three major hospital systems serving approximately 80% of the Northeast Ohio population. The Cleveland Clinic, University Hospitals Health System, and MetroHealth are direct competitors for primary and specialty care, and patient overlap between these systems is high. Fragmentation of health data that exist in silos at these health systems produces an overestimation of disease burden due to double and sometimes triple counting of patients. As a result, longitudinal population-based studies across the Cleveland patient population are impeded unless accurate and actionable clinically derived health data sets can be created. METHODS: The Cleveland Institute for Computational Biology has developed the De-Duplicate and De-Identify Research Engine (DeDeRE) that, without any exchange of personal health identifiers (PHI) between health systems, will effectively de-duplicate the patients between one or more health entities. RESULTS: The immediate utility of this software for cancer epidemiology is the increased accuracy in measuring cancer burden and the potential to perform longitudinal studies with de-duplicated, de-identified data sets. CONCLUSIONS: The DeDeRE software developed and tested here accomplishes its goals without exposing PHIs using a state-of-the-art, trusted privacy preservation network enabled by a hash-based matching algorithm. IMPACT: This paper will guide the reader through the functions currently developed in DeDeRE and how a healthcare organization (HCO) employing the release version of this technology can begin sharing data with one or more additional HCOs in a collaborative and noncompetitive manner to create a regional population health resource for cancer researchers.See all articles in this CEBP Focus section, "Modernizing Population Science."

Electronic Medical Record Search Engine (EMERSE): An Information Retrieval Tool for Supporting Cancer Research.

PURPOSE: The Electronic Medical Record Search Engine (EMERSE) is a software tool built to aid research spanning cohort discovery, population health, and data abstraction for clinical trials. EMERSE is now live at three academic medical centers, with additional sites currently working on implementation. In this report, we describe how EMERSE has been used to support cancer research based on a variety of metrics. METHODS: We identified peer-reviewed publications that used EMERSE through online searches as well as through direct e-mails to users based on audit logs. These logs were also used to summarize use at each of the three sites. Search terms for two of the sites were characterized using the natural language processing tool MetaMap to determine to which semantic types the terms could be mapped. RESULTS: We identified a total of 326 peer-reviewed publications that used EMERSE through August 2019, although this is likely an underestimation of the true total based on the use log analysis. Oncology-related research comprised nearly one third (n = 105; 32.2%) of all research output. The use logs showed that EMERSE had been used by multiple people at each site (nearly 3,500 across all three) who had collectively logged into the system > 100,000 times. Many user-entered search queries could not be mapped to a semantic type, but the most common semantic type for terms that did match was "disease or syndrome," followed by "pharmacologic substance." CONCLUSION: EMERSE has been shown to be a valuable tool for supporting cancer research. It has been successfully deployed at other sites, despite some implementation challenges unique to each deployment environment.

Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines.

Despite monumental advances in genomics, relatively few health care provider organizations in the United States offer personalized or precision medicine as part of the routine clinical workflow. The gaps between research and applied genomic medicine may be a result of a cultural gap across various stakeholders representing scientists, clinicians, patients, policy makers, and third party payers. Scientists are trained to assess the health care value of genomics by either quantifying population-scale effects, or through the narrow lens of clinical trials where the standard of care is compared with the predictive power of a single or handful of genetic variants. While these metrics are an essential first step in assessing and documenting the clinical utility of genomics, they are rarely followed up with other assessments of health care value that are critical to stakeholders who use different measures to define value. The limited value assessment in both the research and implementation science of precision medicine is likely due to necessary logistical constraints of these teams; engaging bioethicists, health care economists, and individual patient belief systems is incredibly daunting for geneticists and informaticians conducting research. In this narrative review, we concisely describe several definitions of value through various stakeholder viewpoints. We highlight the existing gaps that prevent clinical translation of scientific findings generally as well as more specifically using two present-day, extreme scenarios: (1) genetically guided warfarin dosing representing a handful of genetic markers and more than 10 years of basic and translational research, and (2) next-generation sequencing representing genome-dense data lacking substantial evidence for implementation. These contemporary scenarios highlight the need for various stakeholders to broadly adopt frameworks designed to define and collect multiple value measures across different disciplines to ultimately impact more universal acceptance of and reimbursement for genomic medicine.

A twelve-analyzer detector system for high-resolution powder diffraction.

A dedicated high-resolution high-throughput X-ray powder diffraction beamline has been constructed at the Advanced Photon Source (APS). In order to achieve the goals of both high resolution and high throughput in a powder instrument, a multi-analyzer detector system is required. The design and performance of the 12-analyzer detector system installed on the powder diffractometer at the 11-BM beamline of APS are presented.

A dedicated powder diffraction beamline at the advanced photon source: commissioning and early operational results.

A new dedicated high-resolution high-throughput powder diffraction beamline has been built, fully commissioned, and opened to general users at the Advanced Photon Source. The optical design and commissioning results are presented. Beamline performance was examined using a mixture of the NIST Si and Al(2)O(3) standard reference materials, as well as the LaB6 line-shape standard. Instrumental resolution as high as 1.7 x 10(-4) (DeltaQQ) was observed.