Tuesday, May 15, 2018

Kudos for the Informatics Professor - 2018 Update

It has been a while since I have posted one of my periodic kudos for the Informatics Professor, so let me take the opportunity to do so for late 2017 and early 2018.

A blog posting of mine received some unexpected attention. As I always do when responding to a government Request for Information (RFI), I posted comments in my blog that I submitted to the RFI for the NIH draft Data Science plan. My main point was that while the plan was a good start, it needed to have more to achieve the optimal value for data science related to health and research. First, the blog posting was picked up by Politico (about a third of the way down the page). I was then asked by National Library of Medicine (NLM) Director Patricia Brennan to re-write it as a guest posting to the NLM Director’s Blog.

Last month, I took part in the inaugural meeting of the International Academy for Health Sciences Informatics (IAHSI), a new Academy of 121 elected members who are leaders in informatics from around the world. With about 50 others from the Academy, I took part in a day-long meeting that was co-located with Medical Informatics Europe 2018 in Gothenburg, Sweden.

I am also honored to be invited to serve on the Scientific Advisory Board (SAB) of the Pan African Bioinformatics Network for H3Africa (H3ABionet), which provides bioinformatics support for the Human Heredity and Health in Africa Project (H3Africa). I will be attending the next meeting of the SAB in Cape Town, South Africa in July. I have been asked to contribute based on my expertise in clinical informatics.

I also gave some invited international talks, including:
Back in the US, the AMIA Clinical Informatics Fellows (ACIF) group has been publishing a series of podcasts. I was delighted to be interviewed for one of them.

Finally, I have authored a chapter in a newly published book: Rydell RL and Landa HM (eds.), The CMIO Survival Guide: A Handbook for Chief Medical Information Officers and Those Who Hire Them, 2nd Edition, CRC Press, 2018. My chapter is entitled, Education and Professional Development for the CMIO. (Surprise!)

Monday, May 7, 2018

Access to Health IT and Data Science Curricular Resources

Over the last decade, I have had the fortunate opportunity to be involved in two efforts to develop widely available curricular resources in health information technology and data science. While these resources are a great foundation for others to use to develop courses and other content in this area, the fact that they were developed with federal grants whose funding has now ended means that they will no longer be updated at their source. They will fortunately continue to be freely available on Web sites, but further development, at least from the source, will not occur for now.

Some might ask, why can’t you update the materials? Updating would be feasible if the materials were just simple textual resources or slides. But these materials contain much more, including narrated lectures, transcripts of those lectures, and packaging that makes them flexible to use. And even if we did just aim to simply update the content, I know from other teaching I do that it takes time and effort, not only the time of content authors, but also of instructional designers, technical support staff, and others who create useful products and packaging.

Nonetheless, the materials themselves will continue to be available, and I will use the rest of this posting to describe what material is available, some history on its development, and where the most recent versions can be found.

The Office of the National Coordinator for Health IT (ONC) Curriculum was developed initially under funding from the Health Information Technology for Economic and Clinical Health (HITECH) Act. Recognizing that adoption and meaningful use of electronic health records (EHRs) would require training a workforce to implement them, the ONC funded a workforce development program that included not only this curriculum development, but also funding for training in both community colleges and universities. The final version of the initial curriculum, completed in 2013, was posted on the Web site of the American Medical Informatics Association (AMIA).

In 2015, the ONC found additional funding to update the curriculum and add some new content around health IT and value-based care. The funding also included the development of short training courses, such as the Healthcare Data Analytics course that we have since developed into a standalone course that offers continuing education credit for physicians and nurses. The final curriculum itself is now available for downloading from the ONC Web site.

It should be noted that while these materials are freely available to anyone, the audience for them is focused on educators. The curriculum consists, in ONC jargon, of components, each comparable in quantity to a college-level course. In other words, the curriculum is an extensive resource that can be enhanced by those who develop and maintain courses. Self-directed learners can certainly make use of the materials, and are not discouraged from doing so, but their volume and breadth would make it challenging to design an appropriate course of study. But an experienced education should be able to adapt them appropriately.

The second resource that was developed, but for which funding has ended as well, is the OHSU Big Data to Knowledge (BD2K) Open Educational Resources (OERs) Project. The development of these materials was funded under a grant from the National Institutes of Health (NIH) BD2K Program. Like the ONC curriculum, these materials are freely available for others to use and enhance. They can be viewed on the project Web site or downloaded as source materials from a GitHub repository. While they are not quite as exhaustive as the ONC components, these modules are more manageable for self-directed learners. The Web site for these materials provides a number of examples of their use, including their being mapped to the biomedical informatics competencies of the NIH Clinical And Translational Science Awards (CTSA) Program.

One limitation to both sets of these materials is that they are not able to incorporate any copyrighted material from any other source. While those of us who teach in universities that subscribe to journals and other resources are able to use portions of such content, password-protected in learning management systems, under fair use rules, putting copyrighted material out in the public domain is not allowed. This is another role of the educator or other content expert, to make appropriate use of copyrighted matter.

The components of the ONC Health IT Curriculum consist of the following:
  1. Introduction to Health Care and Public Health in the U.S. 
  2. The Culture of Health Care 
  3. Terminology in Health Care and Public Health Settings 
  4. Introduction to Information and Computer Science 
  5. History of Health Information Technology in the U.S. 
  6. Health Management Information System 
  7. Working with Health IT Systems 
  8. Installation and Maintenance of Health IT Systems 
  9. Networking and Health Information Exchange 
  10. Health Care Workflow Process Improvement 
  11. Configuring EHRs 
  12. Quality Improvement 
  13. Public Health IT 
  14. Special Topics Course on Vendor-Specific Systems 
  15. Usability and Human Factors 
  16. Professionalism/Customer Service in the Health Environment 
  17. Working in Teams 
  18. Planning, Management and Leadership for Health IT 
  19. Introduction to Project Management 
  20. Training and Instructional Design 
  21. Population Health 
  22. Care Coordination and Interoperable Health IT Systems 
  23. Value-Based Care 
  24. Health Care Data Analytics 
  25. Patient-Centered Care 
The modules of the BD2K OERs materials consist of the following:
  • BDK01 Biomedical Big Data Science 
  • BDK02 Introduction To Big Data In Biology And Medicine 
  • BDK03 Ethical Issues In Use Of Big Data 
  • BDK04 Clinical Data Standards Related To Big Data 
  • BDK05 Basic Research Data Standards 
  • BDK06 Public Health And Big Data 
  • BDK07 Team Science 
  • BDK08 Secondary Use (Reuse) Of Clinical Data 
  • BDK09 Publication And Peer Review 
  • BDK10 Information Retrieval 
  • BDK11 Identifiers 
  • BDK12 Data Annotation And Curation 
  • BDK13 Learn FHIR 
  • BDK14 Ontologies 101 
  • BDK15 Data Metadata And Provenance 
  • BDK16 Semantic Data Interoperability 
  • BDK17 Choice Of Algorithms And Algorithm Dynamics 
  • BDK18 Visualization And Interpretation 
  • BDK19 Replication, Validation And The Spectrum Of Reproducibility 
  • BDK20 Regulatory Issues In Big Data For Genomics And Health 
  • BDK21 Hosting Data Dissemination And Data Stewardship Workshops 
  • BDK22 Guidelines For Reporting, Publications, And Data Sharing