Documentation
Download A Blueprint for Trustworthy Data: How a Collaborative Knowledge Foundation Can Elevate Everyday Data for More Accurate, Actionable, and Trusted Healthcare Insights for a comprehensive overview of our work or explore individual Volumes for in-depth coverage of specific topics.
A Blueprint for Trustworthy Data is a textbook-style resource that distills key information and major topics from the project into an accessible reference for both technical and non-technical audiences. A Blueprint for Trustworthy builds upon content described in the learning series and offers thorough insights into major areas, including Komet, Tinkar, ANF, use cases, and additional relevant topics.
The Volumes segment out information and documentation from A Blueprint for Trustworthy Data covering 12 distinct areas of knowledge. Each Volume offers streamlined and in-depth information and documentation on a particular subject, allowing users to explore topics of interest in greater detail.
Volume 1:
Today's healthcare ecosystem faces challenges ensuring data accuracy, interoperability, and quality. Addressing these issues requires a solution that harmonizes disparate clinical terminology standards to improve the quality of patient care and support clinical decision making. This series of Integrated Knowledge Management (IKM) Volumes provides a framework for managing healthcare knowledge, focusing on simplifying and integrating knowledge assets to support efficient and reliable delivery of care. Volume 1 provides a high-level introduction to this body of work and particular areas of interest.
Introduction to IKM
Volume 2:
Volume 2 provides background context on the efforts since 2015 to enhance the interoperability and effectiveness of in vitro diagnostic test data. It emphasizes collaborative engagement, analytic data storage improvements, systems re-engineering, and effective knowledge management to ensure the reliability, integrity, and evolution of laboratory data within the healthcare ecosystem.
IKM Book Background
Volume 3:
Volume 3 emphasizes the role of IKM in enhancing healthcare data management, particularly in overcoming challenges surrounding data loss and misinterpretation. It highlights the need for integrated terminology standards and collaboration across the healthcare system to improve data interoperability, data quality, and ultimately patient safety. This volume explores how a unified representation model would facilitate better patient outcomes and effective data analysis.
IKM Overview
Volume 4:
Volume 4 provides an overview of the Versioned Foundation Layer and Terminology Knowledge Architecture (Tinkar), focusing on Tinkar’s role in harmonizing biomedical terminologies like SNOMED CT®, LOINC®, and RxNorm within healthcare IT systems. Using the Tinkar Modeling Guide, it highlights the importance of standardization for interoperability and efficient data exchange, presenting Tinkar's logical framework as a solution to the complexities of integrating and managing diverse terminologies to support seamless health information exchange.
Versioned Foundation
Volume 5:
This section introduces common terminologies, which standardize health measurements and observations to improve data consistency in healthcare, compares them to CIMINO’s Desiderata, and highlights some key principles of terminology standards.
Terminology Knowledge
Volume 6:
Volume 6 describes the Assertional Knowledge Layer and explains how the versioned foundation and terminology knowledge are used to represent non-defining facts, such as relationships between data elements, which can inform knowledge algorithms.
Assertional Knowledge
Statement Model Knowledge
Volume 7:
This Volume highlights the importance of using a standardized representation of clinical statements, like the Analysis Normal Form (ANF), to ensure they are uniformly understood, reproducible, and useful across and within healthcare systems. ANF aims to address issues in data consistency and patient safety by providing a uniform representation model for documenting clinical statements, thereby improving data analysis, clinical decision support, and research. The goal is to achieve a high-reliability organization standard in healthcare through precise and high-quality data management.
Volume 8:
Volume 8 describes how the standardized representation of healthcare data and the earlier layers can be used to improve Clinical Decision Support (CDS), such as standard ways of performing a procedure, treatment protocols for diseases, and standard evidence-based Order Sets.
Imperative Knowledge
Engagement with the Healthcare Ecosystem
Volume 9:
Volume 9 focuses on the significance of open-source software within the tech ecosystem, spotlighting the collaborative, community-driven development model. It emphasizes the benefits of open source for enhancing interoperability, community testing, and overcoming proprietary barriers, particularly in healthcare IT. This volume guides users on engaging with open-source projects and adopting open-source licensing models to foster innovation and flexibility in software development.
Volume 10:
Volume 10 focuses on the various considerations and decisions that went into the design and implementation of the Knowledge Management Environment (Komet) and contains the Komet User Guide that outlines the steps for downloading, installing, and using the contributed application. It covers importing and reading-in data, searching concepts using both the Komet and Journal interfaces, distinguishing concept versions and history, editing and modifying data, exporting and sharing data, viewing concept timeline properties, and more.
Komet
Use Case and Summary of Findings
Volume 11:
This section dives into practical use cases, illustrating how Komet and this work can have a lasting impact across the industry, and highlights potential avenues for continued work, including Artificial Intelligence (AI) and Large Language Models (LLMs).
Real World Applications
Volume 12:
Volume 12 showcases the transformative role of Integrated Knowledge Management (IKM) and Terminology Knowledge Architecture (Tinkar) across a variety of healthcare topics, including patient data privacy, managing and integrating diverse sources of health data to enhance patient care, healthcare quality improvement, emergency disaster response, return on investment (ROI) for healthcare organizations and systems. This volume offers insights into leveraging advanced data management strategies for improved healthcare outcomes.