Thursday, February 26, 2015

Input to the Working Group to Chart the Future Course for the National Library of Medicine

Like many in academic informatics, my career has benefitted greatly from the support of National Library of Medicine (NLM), the institute of the National Institutes of Health (NIH) that has been devoted to, among other things, support for research and training in biomedical and health informatics. I have written over the years in this blog (in 2011 and 2014) of the myriad contributions of the NLM to biomedicine and health, including its unique role in funding basic research in informatics, especially clinical informatics.

The NLM has been guided over the past 30 years by a single leader, Dr. Donald AB Lindberg, whose vision and steady hand have led it to great success. Virtually everyone in healthcare has benefited from the NLM's successful initiatives that have been carried out during Dr. Lindberg's tenure, especially the information resources of Pubmed, MedlinePLUS,, and the myriad of genomics resources under the auspices of the National Center for Biotechnology Information (NCBI). Late last year, Dr. Lindberg announced his retirement. This has prompted the NIH to launch a working group and Request for Information (RFI) process to chart the future course of the NLM in advance of appointing a new leader.

Naturally, I view this opportunity as a chance to weigh in on the future of the NLM, which is so critical not only to my own work but also to the informatics field in general and really all of the healthcare enterprise. In the rest of this posting, I list the RFI questions in underline and then provide the answers I entered into the NIH site for collecting them. I look forward to seeing what others write as well as the final report of the working group. Appointing a leader to sustain Dr. Lindberg's contributions is one of the most essential actions for the NLM and the informatics field going forward.

(I do note that one of the challenges with the RFI structure is the lack of a section to make comment about the NLM with regards to all of its missions and constituents. As such, I have placed my comments more disproportionately in the section on the research community, since I believe the issues of basic informatics research are most important to be addressed in the transition to new leadership.)

Current NLM elements that are of the most, or least, value to the research community (including biomedical, clinical, behavioral, health services, public health, and historical researchers) and future capabilities that will be needed to support evolving scientific and technological activities and needs.

The NLM is a unique resource to all communities, especially the research community, in two areas: its basic research and education function in biomedical and health informatics and its library function. The NLM's library function is in excellent shape, and it continues to be an innovator and leader in its world-leading medical library function.

I have more serious concerns about the NLM's research function. Although there are many institutes within NIH (e.g., NCI, NHLBI, and the Fogarty International Center) and other entities outside of NIH (e.g., AHRQ and PCORI) that fund research in informatics-related areas, NLM is the only entity that funds basic research in biomedical and health informatics. Most of the other institutes and entities that fund informatics support projects that are highly applied and/or domain-focused. These projects are important, but basic informatics research is also key to improving both individual health as well as the healthcare system.

The NLM is also nearly unique in funding basic research in clinical informatics. A good deal of informatics research in the other NIH institutes is focused in basic science, e.g., genomics, bioinformatics, and computational biology. AHRQ and PCORI support clinical informatics research, but it is highly applied. Only NLM funds critical basic research in clinical informatics, and this function is vitally important as we strive to use informatics to achieve the triple aim of better health, improved healthcare, and reduced costs. Some of these areas of basic research include standards and interoperability, usability, workflow analysis, natural language understanding, and the intersection of people and organizational issues with information technology.

Informatics research within NIH and other government agencies is also very silo-ed. Why, for example, is the new Data Science (BD2K) program housed in the NIH Director's Office, when it really should be organized as a part of larger informatics science. (Indeed, many BD2K grantees, including myself, receive a good deal of their other research support from NLM.) Initiatives such as data science should really be part of an integrated approach to informatics research and be part of the NLM (or what the NLM should become).

A final critical function of NLM that has provided value and should be maintained is its training programs for those who aspire to careers in informatics research. I count myself among many whose NLM fellowship training led to a successful career as a researcher, educator, and academician generally. NLM training grants have also provided support for my university to educate the next generation of informatics researchers who have gone on to become successful researchers and other leaders in the field.

One part of the problem is that the name itself, "National Library of Medicine," does not connote all of what NLM does. Yes the NLM is a world-renowned biomedical library, and that function is critically important to continue. But NLM also provides cutting-edge research and training in informatics, and an ideal change for NLM would be a name change to something like the "National Biomedical and Health Informatics Institute," of which a robust and innovative National Library of Medicine would be a vital part.

Current NLM elements that are of the most, or least, value to health professionals (e.g., those working in health care, emergency response, toxicology, environmental health, and public health) and future capabilities that will be needed to enable health professionals to integrate data and knowledge from biomedical research into effective practice.

The NLM's library function is critical to all healthcare professionals, and this group probably benefits most from the NLM's excellent use of tax dollars in implementing its freely available resources. However, healthcare professionals have also benefitted from, and will likely continue to benefit from, NLM's basic research, especially in clinical informatics. While the adoption of knowledge systems, electronic health records, health information exchange, and other informatics applications has increased substantially in the last decade, the foundation for these applications emerged in no small part from NLM basic research in informatics. And as these applications are all far from perfect, they will likely need continued research to increase our understanding and optimization of them.

The success of the NLM's work has also led to a new category of health professional, which is the informatics professional, manifested most prominently in the area of clinical informatics. A growing number of healthcare provider organizations have established operational clinical informatics units, which are usually distinct from IT units. These are often directed by a Chief Medical Informatics Officer (CMIO). Another manifestation of this success is the designation of clinical informatics as a physician subspecialty. There are now 787 board-certifiied clinical informaticians, and a number of universities are establishing fellowship programs accredited by ACGME. In the meantime, AMIA has established an Advanced Interprofessional Informatics Certification process that will lead to certification of non-physicians in clinical informatics. These health professionals will play a vital role in applying the results of informatics research to innovating and improving patient care. This also gives impetus for maintaining a strong basic research effort in clinical informatics, and the NLM is uniquely poised to continue that role.

Current NLM elements that are of most, or least, value to patients and the public (including students, teachers, and the media) and future capabilities that will be needed to ensure a trusted source for rapid dissemination of health knowledge into the public domain.

The NLM's library function also ensures rapid dissemination of high-quality knowledge for patients and the general public. Its flagship site, MedlinePLUS, is a gold standard for high-quality, consumer-oriented health information. Of course, there are still a myriad of research issues about optimizing informatics for patients and the public. How do we insure the most appropriate information is delivered to such individuals at an appropriate depth and reading level? What is the role of personal health records in integrating knowledge and guidance? These research questions further demonstrate the importance of basic informatics research.

Current NLM elements that are of most, or least, value to other libraries, publishers, organizations, companies, and individuals who use NLM data, software tools, and systems in developing and providing value-added or complementary services and products and future capabilities that would facilitate the development of products and services that make use of NLM resources.

Likewise, the NLM's library function ensures rapid dissemination of high-quality knowledge for those who produce and disseminate information in the public and private sectors. The standards it sets provide interoperability unparalleled in other areas of the healthcare industry. In this area as well, the basic research of NLM is critical, contributing to more effective ways to produce and disseminate information in a vibrant marketplace.

How NLM could be better positioned to help address the broader and growing challenges associated with:

  • Biomedical informatics, “big data”, and data science;
  • Electronic health records;
  • Digital publications; or
  • Other emerging challenges/elements warranting special consideration.

The NLM, and the research it funds, is well-positioned to address all of these listed challenges.

Individuals who are trained in biomedical and health informatics not only understand Big Data and Data Science, but also bring the perspective of other aspects of informatics, such as standards and interoperability, usability, clinical workflow, and people and organizational issues. Data science transcends algorithms; it requires a thorough understanding of the quality and veracity of data. The understanding of how data, information, and knowledge are generated, organized, critiqued, and maintained is a unique skill of those who are trained in informatics. As noted earlier, the BD2K initiative should really be housed in the NLM, since it is part of larger informatics science and the fact that many who are funded by BD2K also have other funding from NLM.

The same applies to electronic health records (EHRs). While the HITECH Act has led to widespread adoption of EHRs, there are still many challenges associated with their optimal use. Basic research in clinical informatics established the foundation of modern EHRs that enabled companies such as Epic, Cerner, Allscripts, and others to thrive in the market. As such, continued research and training of researchers is necessary to ensure sustained progress, especially with the need to move to standards-based interoperable systems. The presence of academic research will also provide a bulwark against EHR development being driven solely by industry, which has an important role to play, but also requires basic research to push innovation in the market.

There are also emerging technologies, some of which we cannot foresee. When I was an NLM informatics postdoctoral fellow in the late 1980s, I could not have imagined the details of the World Wide Web, the wireless ubiquitous Internet, or modern mobile devices. There are likely new technologies coming down the road that few if any of us can predict that will have major impacts on health and healthcare. It is critical that the NLM and the research it supports enable these technologies to be put to optimal usage.

Saturday, February 7, 2015

2015 Update of Site, What is Biomedical & Health Informatics?

All through my career, I have been asked on a regular basis, What is Medical/Biomedical/Health Informatics? Years ago, to answer this question, I created a Web site that attempted to answer it. Later on, I added some voice-over-Powerpoint lectures, which also provided me the opportunity to demonstrate the technologies we use in our distance learning program at Oregon Health & Science University (OHSU).

Keeping a site like this up to date is no small feat, especially with all my other activities in research, education, and administration. As such, the site has grown out of date from time to time. I am pleased to announce that I have now updated the lecture and references on the site, perhaps being somewhat less ambitious in the breadth of material that I cover. (Though I do hope to add more up-to-date material over time.)

The educational methods I use on this site mirror my on-line teaching. I have always found great value in voice-over-Powerpoint lectures, especially using the Articulate Presenter tool that provides the slides and sound in Flash format and also allows easy navigation among the slides. I also provide PDF files of the slides as well as another PDF that has references to all of the papers, reports, books, and other citations in the lecture. The site also contains a list of key textbooks as well as links to some of my papers and to important organizations and other sites for the field.

I also hope the site will whet peoples' appetites for the AMIA-OHSU 10x10 ("ten by ten") program, the OHSU biomedical informatics graduate program, or other educational programs in the field. I look forward to receiving feedback from people and take full responsibility for any errors in any of the materials I have produced.

Friday, February 6, 2015

The Conundrum of Structured vs. Unstructured Data

As in all complex endeavors, the push for a healthcare system underpinned by structured and interoperable electronic health record (EHR) data has turned out to be more complicated than we might have anticipated when acceleration of EHR adoption was begun about a decade ago. This does not mean that anyone was right or wrong; it just shows the inherent complexities of trying to solve the real problems that motivate data-related problems in healthcare. These healthcare problems have been well-documented over the past couple decades by the Institute of Medicine (IOM) and others, and include incomplete and unavailable records [1], medical errors [2], and suboptimal quality of care [3]. These problems are still every bit as real as they were when the IOM and others first brought them to light, but the solutions have been more challenging to find.

It is almost a holy grail of informatics that the value of EHR data stems from structured and interoperable data, which in turn allows not only better primary use for patient safety, clinical decision support, and other benefits, but also secondary use, such as quality measurement, public health surveillance, and clinical research. Yet it has been known for some time that there is a "tension" between the entry and use of structured vs. unstructured data [4].

A few months ago, I wrote a post on what are realistic goals for EHR interoperability, based on what I saw was positive prioritization by the Office of National Coordinator for Health IT (ONC) on data interoperability within the EHR. There is no question that data flowing seamlessly, and maintaining its meaning, is critical to advance the value of health IT.

That discussion, however, uncovers a challenge of major magnitude within informatics, which is how much data should be structured, and how to best deploy that data. A number of commentators I greatly respect have weighed in on this issue.

My spurring to write on this topic was motivated by Wes Rishel, formerly of Gartner. Mr. Rishel used the challenges of patient summaries to avoid against "de-motivating" interoperability [5]. In particular, he noted the challenge between two views of the interoperable patient summary, one driven by a human-generated narrative that communicates the patient's situation succinctly and other generated by a computer with the goal of transfer of data. He (and others before him, such as Dr. Peter Basch [6]) have noted that clinicians have dissatisfaction and distrust with records generated from structured data.

Other groups have weighed in on this problem as well. Last year, the American Medical Association (AMA) had put forth a succinct piece on improving EHR usability, noting that while data "liquidity" is important, it takes a back seat to the primacy of clinician usage of the EHR for improving care to be its primary motivation [7]. And just recently, the American College of Physicians advocated in a similar manner, releasing a policy paper on clinical documentation also calling for the primary needs to be focused on meeting the needs of clinicians [8].

A major challenge for informatics is how to balance the desire for structured data to add value versus providing readable and succinct documentation to enable the best patient care. Unfortunately, the two can be at odds with each other. If physicians do not like, let alone trust, the kind of structured data that enables other value for EHR data, what is the solution?

When in situations like this, I always remember the words of an elder sage of informatics, Dr. Clement McDonald of the National Library of Medicine, who has noted, Informatics is a journey, not a destination.  We may never achieve the perfect solution, but must continually strive to find the right balance of structure and interoperability. Or, to quote from the decades-old Ten Commandments of Informatics [9], penned by another elder statesman of the field, Dr. Octo Barnett, who stated, Be optimistic about the future, supportive of good work that is being done, passionate in your commitment, but always be guided by a fundamental skepticism.

Or, to be guided by a quote often attributed to Voltaire, which is that we should not let perfect be the enemy of good. It is obvious that the EHR will never, like all of medicine, be perfect. Therefore, we should strive to find the best solution that balances the value of optimally devliered care balanced with the value that structured data can bring.


1. Dick, RS, Steen, EB, et al., Eds. (1997). The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC, National Academies Press.
2. Kohn, LT, Corrigan, JM, et al., Eds. (2000). To Err Is Human: Building a Safer Health System. Washington, DC, National Academies Press.
3. Anonymous (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC, National Academies Press.
4. Rosenbloom, ST, Denny, JC, et al. (2011). Data from clinical notes: a perspective on the tension between structure and flexible documentation. Journal of the American Medical Informatics Association. 18: 181-186.
5. Rishel, W (2015). How to Avoid DE-Motivating Interoperability? Retired Healthcare IT Nerd, January 5, 2015.
6. Basch, P (2014). ONC’s 10-Year Roadmap Towards Interoperability Requires Changes To The Meaningful Use Program. Health Affairs Blog, November 3, 2014.
7. Anonymous (2014). Improving Care: Priorities to Improve Electronic Health Record Usability. Chicago, IL, American Medical Association.
8. Kuhn, T, Basch, P, et al. (2015). Clinical documentation in the 21st century: executive summary of a policy position paper from the American College of Physicians. Annals of Internal Medicine. Epub ahead of print.
9. Barnett, GO (1979). The use of computers in clinical data management: the ten commandments. Society for Computer Medicine Newsletter. 4: 6-8.