This course will explore the concept of learning health systems and closely examine the specific data standards required to support the data exchange and re-use in this context. Learners will appreciate the heterogeneity and complexity of existing standards and identify opportunities to use them in organizational and research activities, including observational studies, pragmatic trials and quality improvement projects. Active and relevant Standards Development Organizations and processes for developing and defining standards will be discussed. Specific topics covered will include tools related to the planning phases for health information systems, as well as standards that support interoperability, including information models, terminology and coding systems, data transport syntax, and structured documents. The development, functionality, uptake, and usability of standards from both national and international perspectives are discussed, along with models for continuous use of clinical data for quality improvement and research. Students will have an opportunity to define a clinical question and the various standards that can support the application and evaluation of evidence in a health care setting.
Suggested pre-requisites include an introductory informatics course and training and/or experience in a health care discipline or clinical research.
Major Topics and Course Schedule
|Week||Start Date||Lecture Topics||Assigned Reading Chapters from Benson (2016)|
Learning Health Systems; background reading and seminal reports
|IOM, PCAST, & JASON Rpts|
|1||March 11||Learning Health Systems defined; Interoperability; Introduction to Standards|
Making of Standards and Standards Development Organizations (SDOs)
|Chp, 1, 2, & 6|
|2||March 18||Coding Systems-focus on Diagnoses, Billing, and Medication Coding Systems; the Unified Medical Language System (UMLS)||TBA|
|3||March 25||Coding Systems - Focus on SNOMED-CT Information Models & Terminology-Information model interactions||Chp. 8|
|4||April 1||Controlled Terminologies-focus on SNOMED CT; Nursing Terminologies|
Information Models and Terminology-Information Model Interactions
Reference Information Models
|Chp. 9 & 10|
|5||April 8||Data Interchange Standards; HL7 v2 & 3; Clinical Document Architecture,|
Fast Healthcare Interoperability Resources (FHIR)
|Chp. 12-15, 18|
|6||April 15||Research Networks & Common Data Models|
Registries and HIE
|7||April 22||Quality Measurement; Current Standards Topics|
Modeling; Tying it all together; Learning Health Care System examples, challenges and future directions
|8||April 29||Learning Health Care System Challenges and Future|
Focus on challenges and future directions
Online; optional in-person session being held at the AMIA Annual Symposium in November in Washington, DC. (Full meeting Nov. 16-20)
FormatPosted lectures; online discussion forum and weekly quizzes.
One live interaction session will be offered via Web-ex for discussion and Q&A. This will be scheduled after the course opening for a date and time that works well for most of the class.
Rachel L. Richesson, PhD, MS, MPH, FACMI
Duke University School of Nursing
307 Trent Drive
Durham, NC 27710
Office phone: 919-681-0825
Office hours are flexible; please email for an appointment
Assignments, Grading and Homework
The course grade will be calculated from the average of 6 homework assignments (some in the form of on-line quizzes) and a standards project that will be hand-graded by the instructor.
Homework assignments (6) 50%
Project #1 50%
An AMIA Certificate of Completion will be awarded to all students whose final total grade is 75% or greater.
This course will include hands-on learning exercises in the form of homework. The assignments might require narrative response (2-3 paragraphs) or might be in the form of an online quiz to assess the student’s ability to search and retrieve content from various coding systems. 6 total assignments are required for the final grade; 8 assignments will be offered, allowing students the option to miss a couple of assignments.
The homework assignments are designed to provoke thought about current standards issues, to build skills, and to define standards in specific areas of particular interest to each student. As such, each homework submission will reflect the interests and work of each individual student. Homework assignments should be completed individually, should reflect the efforts and thoughts of the submitting student (i.e., no group submissions or student collaboration on homework, please), and should not be shared with other students prior to submission date. There is valuable learning opportunity from sharing homework assignments with the class, so that students might learn from other students, and be exposed to new approaches, ideas, and contexts for implementing data standards. To ensure that everyone has the opportunity to complete their assignments free from influence of others, as well as maintain a sense of privacy and control, students will have the option to share submitted homework assignments by posting them on the Resource section or posting on the Discussion Forum *after the due date*.
Quiz-style homework assignments will consist of 5-10 questions and carry a total weight of 5 points. Narrative-style homework assignments will be graded on a 5 point scale and grades/comments will be recorded by the instructor in Sakai prior to the next class.
Students should submit Homework assignments via the “assignments” tab of the Sakai (or Sakai-like) online learning platform administered by Duke University. In addition, students are encouraged to post their narrative homework assignments to the Discussion form, and review and comment on other students’ homework postings.
CLARIFICATION ON ASSIGNED READINGS:
Students will be provided with weekly reading assignments. Students having difficulty understanding topics presented in the assigned reading are encouraged to seek out additional sources of information that may be outside of the assigned and supplemental readings. The instructor will be available for questions, either by telephone or e-mail. If you find other good references for class topic areas, please share with instructors and the other students using the discussion forums in Sakai.
There is a heavy amount of required and optional reading for the course. Many of the assigned readings are quite long. Students are encouraged to preview the readings and thoughtfully determine whether or not there is value in printing them. (In most cases, I suggest that there is not.) Many of the readings are meant to be skimmed, allowing the reader to see the scope and components to the reading topic. Within each reading or set of readings there will be areas of greater interest and importance, depending upon each student’s background and career and learning objectives. Students should listen to guidance in lectures and discussion regarding important points from each reading. Also, it should be noted that because there are no exams, the assigned and suggested readings should be considered as resources rather than documents to be memorized or studied. As with any course, you get out what you put in. In that regard, students that address all of the readings will reap more knowledge and insight. However, the assessment for the class is based on skills, homework assignments and projects, so students should take the readings in the spirit of understanding the breadth, depth, and dynamic nature of data exchange models and standards.
Upon successful completion of this course, the student will be able to:
- • Explain the term ‘Learning Health Care System’ and identify factors driving the movement toward learning health systems.
- • Describe the types of activities required for learning health care.
- • Describe the infrastructure requirements and informatics challenges for learning health systems.
- • Explain the term ‘interoperability’ and discuss the major challenges to achieving interoperability across healthcare information systems.
- • Explain the role of data standards in learning health systems.
- • List and describe desirable features of coding and terminological systems, and analyze how existing systems embody each of these features.
- • Identify important U.S. and international standards-developing organizations (SDOs) and explain the scope and role of each.
- • Discuss seminal reports related to achieving interoperability, and summarize the approach of federal agencies to a national health information infrastructure.
- • Explain a problem or area of activity that is a current challenge for a health data standards development organization, and identify how to engage in discussion and resolution of this problem.
- • Explain the term ‘Learning Health Care System’ and identify factors driving their development.
- • Describe the types of activities required for learning health.
- • Define interoperability and give examples of how interoperability supports learning health systems.
- • Summarize and describe the major challenges to uniform adoption of data standards.
- • Learn how standards are created, and name organizations that developing and endorse standards.
- • Identify the sponsor, purpose, scope, and structure of RxNorm.
- • Give examples of 3 proprietary medication management systems that feed into RxNorm.
- • Articulate the sponsor, purpose, scope, and structure of various ICD systems.
- • Understand the ICD-10-CM coding system structure and differences from ICD-9-CM.
- • List different coding systems used in healthcare and describe their similarities and differences.
- • Describe the UMLS and how it can support the access and use of different healthcare coding systems.
- • Define the VSAC and state its purpose.
- • Define LOINC and identify and describe the six LOINC code components.
- • Demonstrate ability to query the LOINC coding system using RELMA.
- • Define the terms ‘clinical phenotypes’ and ‘computable phenotypes’, describe their importance in Learning Health Systems.
- • Discuss the role of standardized coding systems to clinical phenotyping and consider approaches to standardizing clinical phenotype definitions.
- • Describe the sponsor, scope, and purpose of the Value Set Authority Center.
- • Define the word “terminology” and identify defining structural features of a terminology.
- • Identify and describe desirable features of a terminology.
- • Describe the scope of content and the structural organization of SNOMED CT.
- • Identify the benefits of networked research and list 3 national research networks.
- • Define the term common data model and describe the importance of common data models to the re-use of electronic health record data for research purposes.
- • Name two prominent common data models.
Please refer to the 10x10 course syllabus for the full list of course goals.
Author: Benson, Tim and Grieve, Grahame.
Title: Principles of Health Interoperability. SNOMED CT, HL7, and FHIR.
Date of publication: 2016
ISBN: 978-1447128007 for softcover edition, publisher list price $79.95
ISBN: 978-1447128014 for e-book edition, publisher list price $59.95
Institute of Medicine (IOM). Best Care at Lower Cost: The Path to Continuously Learning Health Care in America. 2012. Note that this book can be purchased for approximately $70 or is available free online in .pdf format at: http://www.iom.edu/Reports/2012/Best-Care-at-Lower-Cost-The-Path-to-Cont... Students are encouraged to review the free online version rather than purchase.
Shortliffe, E.H. & Cimino, J.J. (Eds.). (2013). Biomedical informatics: Computer applications in health care and biomedicine (health informatics), 4th edition. New York: Springer.
Shortliffe, E.H. & Cimino, J.J. (Eds.). (2006). Biomedical informatics: Computer applications in health care and biomedicine (health informatics), 3rd edition. New York: Springer.
- • A computer with an Internet connection.
- • Internet Explorer 8 or higher, Firefox 4.x or higher, Safari 2.x or higher, or any other W3C standards compliant browser
- • HTML5-capable browser for video or audio play or download
- • Additional software such as PowerPoint® or Adobe Acrobat Reader software
The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
Credit Designation Statement
The American Medical Informatics Association designates this enduring material for a maximum of 49.5 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Estimated Time Expected to Complete Activity
Estimated time to complete this activity: 49.5 hours.
Criteria for Successful Completion
Completion of this enduring material is demonstrated by scoring at least 75% on the homework assignments, any quizzes, and the completion of one course project.
Instructions for Claiming CME Credit
The instructor will send a list of all participants who satisfied course requirements to AMIA. Participant will communicate with Susanne Arnold, Education Program Manager, email@example.com, about completing the evaluation and receiving the CME certificate.
No commercial support was received for this activity.
As a provider accredited by the ACCME, AMIA requires that everyone who is in a position to control the content of an educational activity disclose all relevant financial relationships with any commercial interest for 12 months prior to the educational activity.
The ACCME considers relationships of the person involved in the CME activity to include financial relationships of a spouse or partner.
Faculty and planners who refuse to disclose relevant financial relationships will be disqualified from participating in the CME activity. For an individual with no relevant financial relationship(s), the participants must be informed that no conflicts of interest or financial relationship(s) exist.
AMIA uses a number of methods to resolve potential conflicts of interest, including: limiting content of the presentation to that which has been reviewed by one or more peer reviewers; ensuring that all scientific research referred to conforms to generally accepted standards of experimental design, data collection, and analysis; undertaking review of the educational activity by a content reviewer to evaluate for potential bias, balance in presentation, evidence-based content or other indicators of integrity, and absence of bias; monitoring the educational activity to evaluate for commercial bias in the presentation; and/or reviewing participant feedback to evaluate for commercial bias in the activity.
Disclosures for this Activity
Rachel Richesson, PhD, MS, MPH, FACMI, and Blake Cameron, MD, MBI, Co-Director, Duke Learning Health System Training Program, and content reviewer Gilad Kuperman, MD, PhD, disclose that neither they nor their life partners have relevant financial relationships with commercial interests.