An Application of an Electronic Health Record System in order to integrate clinical and molecular data and guide therapeutic strategy in Paraguay.

Improve data management in two public hospitals in Paraguay - Hospital de Clínicas and Instituto Nacional del Cáncer (INCAN). Currently, data management in oncology department is complex and requires advanced Information System to process data where "omic" information should be integrated together with patient's clinical data to improve data analysis and decision-making process. Conceptual Modelling is an important and essential activity that helps us not only to design an abstract model of an advanced Information System but also facilitates the development process.CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI

An application of an EHR based on conceptual modeling to integrate clinical and genomic data and guide therapeutic strategy

Currently, data management in oncology department is complex and requires advanced Information Systems (ISs) to process data where “omic” information should be integrated together with patient’s clinical data to improve data analysis and decision-making process. This research paper reports a practical experience in this context. A Conceptual Model (CM) has been designed to develop an Information System (IS) in order to manage clinical, pathological, and molecular data in a holistic way at the oncology department of two main Hospitals in Paraguay. Additionally, model-based archetypes have been proposed to specify the selected user interaction strategy. The CM and its associated archetypes are the basis to develop a clinical IS in order to load -firstly- and manage -secondly- all the clinical data that the domain requires, showing how feasible the approach is in practice, and how much the corresponding clinical data management is improved. In this work, we want to reinforce with this real experience how using a CM along with archetypes correctly helps to design, develop and manage better information systems, emphasizing the relevance of the selected clinical domain

Development of a Strategy to Implement an Oncology Clinical Research Program at a Rural Hospital

The purpose of this Capstone Project was to design a strategy for implementing an oncology clinical research program at a rural hospital cancer center. The rural cancer center is part of a large healthcare system (Healthcare System) that encompasses several hospitals located throughout northern Illinois. Healthcare System administrators prioritized development of a research program at the rural hospital as part of an institution initiative to expand access to oncology clinical trials in the community and rural settings. The author of this project was tasked with the responsibility of developing a strategy for building this research program at the rural cancer center. The project was accomplished by conducting a literature review, completing a needs assessment, and reviewing hospital analytic data. The literature review was used to identify best practices for opening and managing clinical research programs and to identify concerns specific to rural hospitals. The needs assessment was completed with key individuals in the oncology and research departments in the Healthcare System to gather information to ensure that the proposed strategy met the requirements of the oncology physicians and oncology and research leadership. The information from the literature review was then combined with feedback from the needs assessment and hospital analytic data to create a strategy that will provide a foundation for an oncology research program at the rural hospital that meets the needs of the patients, physicians, and Healthcare System administrators

An Integrated Oncology Data Warehouse for Clinical Decision Support and Complex Patient Cohort Identification in a Hybrid Cancer Center

BACKGROUND: A data warehouse is a repository that centralizes and integrates data from disparate systems to provide the ability to easily access historical, consistent data. Integration of disparate source systems into one centralized location can enable rapid identification of more robust research cohorts and enable data-driven decision making. The objective of the Miami Cancer Institute (MCI) Oncology Data Warehouse (ODW) is to collect and organize data from clinical records, research, and administrative systems to support information retrieval, business intelligence, and analytics for high-level decision making for oncology patients. The design, architecture, and implementation aligns with industry best practices which includes Data Governance, Enterprise Data Modeling, and Metadata Management. METHODS: We integrated structured and unstructured data from disparate sources into one centralized data model optimized for querying known as the ODW. The ODW is modeled as a star schema, with fact tables and conformed dimension tables, and expands to a galaxy schema with constellation facts and dimensions that can snowflake to other data models as needed. Each fact table represents a subject area (i.e. pathology), that is directly related to the conformed dimension tables using surrogate and foreign keys. Conformed dimensions represent the attributes associated to the subject area (i.e. date of encounter). The source data is extracted, transformed and loaded (ETL) automatically from different databases into a set of tables. The ETL code performs incremental loads at regular prescribed intervals into two parallel storage areas, a relational database management system (RDMS) as well as a Big Data file storage system. RESULTS: An interdisciplinary team of physicians, engineers, scientists, and subject matter experts at the Miami Cancer Institute of Baptist Health South Florida, has designed, developed, and implemented the ODW with information originating from different data sources which include: Electronic Medical Record (EMR) systems, Financial Systems, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Pathology synoptic reports and archives, and Next Generation Sequencing services. Structurally it is a subject-oriented, integrated collection of data leveraging conformed dimensions. The ODW is capable of connecting most business intelligence (i.e. Tableau) or statistical (i.e. SAS) tools for automated or static report development. CONCLUSION: The growing ODW enables physicians, clinical management teams, and medical analysts to systematically mine and review the molecular, genomic, and associated clinical or administrative information of patients, and identify patterns that may influence treatment decisions and potential outcomes. By implementing an innovative combination of technology tools and methods, we were able to organize enterprise information about oncology patients which can be utilized for clinical decision support and precision medicine use cases

Focal Spot, Spring 2005

https://digitalcommons.wustl.edu/focal_spot_archives/1099/thumbnail.jp

Focal Spot, Spring 2002

https://digitalcommons.wustl.edu/focal_spot_archives/1090/thumbnail.jp

An Open-Source Tool for Anisotropic Radiation Therapy Planning in Neuro-oncology Using DW-MRI Tractography.

There is evidence from histopathological studies that glioma tumor cells migrate preferentially along large white matter bundles. If the peritumoral white matter structures can be used to predict the likely trajectory of migrating tumor cells outside of the surgical margin, then this information could be used to inform the delineation of radiation therapy (RT) targets. In theory, an anisotropic expansion that takes large white matter bundle anatomy into account may maximize the chances of treating migrating cancer cells and minimize the amount of brain tissue exposed to high doses of ionizing radiation. Diffusion-weighted MRI (DW-MRI) can be used in combination with fiber tracking algorithms to model the trajectory of large white matter pathways using the direction and magnitude of water movement in tissue. The method presented here is a tool for translating a DW-MRI fiber tracking (tractography) dataset into a white matter path length (WMPL) map that assigns each voxel the shortest distance along a streamline back to a specified region of interest (ROI). We present an open-source WMPL tool, implemented in the package Diffusion Imaging in Python (DIPY), and code to convert the resulting WMPL map to anisotropic contours for RT in a commercial treatment planning system. This proof-of-concept lays the groundwork for future studies to evaluate the clinical value of incorporating tractography modeling into treatment planning

Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders' titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was "intersections between informatics, data science, and population science." We conclude with a discussion on "hot topics" on the horizon for cancer informatics

AAPM medical physics practice guideline 10.a.: Scope of practice for clinical medical physics.

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline (MPPG) represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiation requires specific training, skills, and techniques as described in each document. As the review of the previous version of AAPM Professional Policy (PP)-17 (Scope of Practice) progressed, the writing group focused on one of the main goals: to have this document accepted by regulatory and accrediting bodies. After much discussion, it was decided that this goal would be better served through a MPPG. To further advance this goal, the text was updated to reflect the rationale and processes by which the activities in the scope of practice were identified and categorized. Lastly, the AAPM Professional Council believes that this document has benefitted from public comment which is part of the MPPG process but not the AAPM Professional Policy approval process. The following terms are used in the AAPM's MPPGs: Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances