Thursday, October 30, 2014

OHSU Clinical Informatics Fellowship Accredited and Accepting Applications

The Oregon Health & Science University (OHSU) Clinical Informatics Fellowship Program is accepting applications for its inaugural class of fellows to begin in July, 2015. The program was notified by the Accreditation Council for Graduate Medical Education (ACGME) in September, 2014 that it received initial ACGME accreditation. The program is now launching its application process for its initial group of trainees. These fellowships are for physicians who seek to become board-certified in the new subspecialty of clinical informatics. Many graduates will likely obtain employment in the growing number of Chief Medical Information Officer (CMIO) or related positions in healthcare and vendor organizations.

This fellowship will be structured more like a traditional clinical fellowship than the graduate educational program model that our other offerings. Fellows will work through various rotations in different healthcare settings, not only at OHSU Hospital but also the Portland VA Medical Center. They will also take classes in the OHSU Graduate Certificate Program that will provide them the knowledge base of the field and prepare them for the board certification exam at the end of their fellowship. The program Web site describes the curriculum and other activities in the fellowship.

It is important to note that this clinical informatics fellowship is an addition to the suite of informatics educational offerings by OHSU and does not replace any existing programs. OHSU will continue to have its graduate program (Graduate Certificate, two master's degrees, and PhD degree) as well as its other research fellowships, including the flagship program funded by the National Library of Medicine. The student population will continue include not only physicians, but also those from other healthcare professions, information technology, and a wide variety of other fields. Job opportunities across the biomedical and health informatics continue to be strong and well-compensated.

OHSU was the third program in the country to receive accreditation in the country. Several other programs are also in the process of seeking accreditation, and a number of them will be using OHSU distance learning course materials for the didactic portion of their programs. (This summer, the first two fellows in the Stanford Packard Children's Hospital fellowship program took the introductory biomedical informatics course from OHSU.)

As defined by ACGME, clinical informatics is "the subspecialty of all medical specialties that transforms health care by analyzing, designing, implementing, and evaluating information and communication systems to improve patient care, enhance access to care, advance individual and population health outcomes, and strengthen the clinician-patient relationship." The new specialty was launched in 2013, with physicians already working in the field able to sit for the certification exam by meeting prior practice requirements. Starting in 2018, this "grandfathering" pathway will go away, and only those completing an ACGME-accredited fellowship will be board-eligible. Last year, seven OHSU faculty physicians became board-certified in the new clinical informatics subspecialty, including the program director (William Hersh, MD) and two Associate Program Directors (Vishnu Mohan, MD, MBI; Thomas Yackel, MD, MS, MPH).

We look forward to a great group of applicants and the launch of the fellowship next summer. We also look forward to working with colleagues launching similar programs at other institutions as the field of clinical informatics begins to take hold.

Tuesday, October 21, 2014

What are Realistic Goals for EHR Interoperability?

Last week, the two major advisory committees of the Office of the National Coordinator for Health IT (ONC) met to hear recommendations from ONC on the critical need to advance electronic health record (EHR) interoperability going forward. The ONC Health IT Policy Committee and the ONC Health IT Standards Committee endorsed a draft roadmap for achieving interoperability over 10 years, with incremental accomplishments at three and six years. The materials from the event are worth perusing.

The ONC has been facing pressure for more action on interoperability. Although great progress has resulted from the HITECH Act in terms of achieving near-universal adoption of EHRs in hospitals (94%) [1] and among three-quarters of physicians [2], the use of health information exchange (HIE), which requires interoperability, is far lower. Recently, about 62% of hospitals report exchanging varying amounts of data with outside organizations [3], with only 38% of physicians exchanging data with outside organizations [4]. A recent update of the annual eHI survey shows there are still considerable technical and financial challenges to HIE organizations that raise questions about their sustainability [5]. The challenges with HIE lagging behind EHR adoption was among the reasons that led ONC to publish a ten-year vision for interoperability in the US healthcare system [6].

The ONC was also pressed into action by a report earlier this year from the JASON group, a group of scientists who advise the government [7]. This led to formation of a JASON Report Task Force (JTF) to respond to the report's recommendations, which would feed into the larger process of developing a ten-year road map for interoperability. The JASON report was critical of the current state of the industry, noting the lack of progress on interoperability as well as criticizing current vendor practices that make exchange of data with outside organizations more difficult. The report called for a unified software architecture and public application programming interfaces (APIs) that would quickly replace existing vendor systems.

The JTF presented its recommendations at the meeting. The task force pushed back some on the JASON Report, embracing the larger vision of the report but advocating a more incremental, market-driven approach to reaching their shared goals. In particular, the JTF put forth six recommendations for advancing the health IT ecosystem, which are (mostly quoting from the report, as follows):
  • Focus on interoperability - ONC and CMS should re-align the Meaningful Use program to shift focus to expanding interoperability, and initiating adoption of public APIs. Requirements for interoperability should be added to Meaningful Use Stage 3 as well as EHR certification.
  • Industry-based ecosystem - A market-based coordinated architecture should be defined to create an ecosystem to support API-based interoperability.
  • Data sharing networks in a coordinated architecture - The architecture should loosely couple market-based data sharing networks (agreements). There should not be through a highly prescribed, top-down, approach.
  • Public API as basic conduit of interoperability - The public API should enable data- and document-level access to clinical and financial systems according to current internet standards. It should be public and secure.
  • Priority API services - Core data services and profiles should define the minimal data and document types supported by public APIs. The initial focus should be on clinician-clinician and consumer use cases.
  • Government as market motivator - ONC should proactively monitor the progress of exchange and implement non-regulatory steps to catalyze the adoption of public APIs.
The two advisory committees then presented their draft roadmap, which will be finalized following public comment in March, 2015. The draft roadmap laid out five core building blocks as well as general goals for three, five, and ten years out. The building blocks fall into the categories of:
  • Core technical standards and functions
  • Certification to support adoption and optimization of health IT products and services
  • Privacy and security protections for health information
  • Supportive business, clinical, cultural, and regulatory environments
  • Rules of engagement and governance
The general goals for 2017 advocate a focus on clinicians and individuals being able to send, receive, find, use a basic set of essential health information. Later goals focus on using expanded sources and users of information, improved quality and reduced cost of care, and Increased automation, ultimately aiming to achieve the vision of the learning health system [8].

The meeting was summarized well (as always) by John Halamka, who also described his view of the emerging core technical standards and functions, which include:
  • RESTful architectures for efficient client-server interaction - the emerging industry standard uniform interface between client and server, which is used by most Web-based software platforms (e.g., Google, Facebook)
  • OAuth2 for Internet-based security - another emerging industry standard that allows distributed secure access across systems on the Internet
  • Standard API for query/retrieval of data using standard data markup languages including eXtensible Markup Language (XML) and Javascript Object Notation (JSON). The emerging standard for a health public API is HL7's Fast Health Interoperability Resources (FHIR). They provide a nice overview aimed at clinicians.
All of the speakers noted a need for these standards to handle both documents and discrete data. While the JASON report and the infamous PCAST report of a few years back called for all data elements to be discrete, the reality is that there will always be a need for documents and the narrative text within to explain the patient's story and provide other nuance that purely discrete data cannot describe.

What solutions would I recommend for technical standards as someone who is more focused on the capture, use, and analysis of data but less expert in the nuances of implementation? I take it from the experts that RESTful architectures with OAuth2 security and FHIR APIs with some specified data standards make the most sense. I will advocate for some basic standards for documents and discrete data that will facilitate use of data. For documents, this is Consolidated Clinical Document Architecture (CCDA) with standard metadata including document and section type names. For discrete data, I advocate the use of mature terminology standards for problems and diagnoses (ICD, SNOMED), tests (LOINC), and medications (RxNorm/RXTerms) as well as the National Library of Medicine Value Set Authority Center (VSAC) for quality and other measures. Combined with public APIs, use of these data standards could vastly simplify interoperability and not require the myriad of system-to-system interfaces that add cost and complexity.

I do recognize that the presence of standardized data alone does not guarantee its provenance. For example, many organizations (and people within them) take different approaches to managing problem lists. Likewise, the mere listing of a drug in a patient record is no guarantee it was actually prescribed, filled at the pharmacy, or taken by the patient. Nonetheless, starting to get data into standardized forms will greatly advance interoperability and, as a result, clinical care and secondary uses of the data.

Certainly there will continue to be challenges around interoperability, data standards, and related areas. But the ONC's plans are a good step in moving us toward the vision of a connected, learning healthcare system. I look forward to adding my comments to the public comment process and seeing an achievable and implementable vision for the future.


A number of other nice postings about this meeting, the JASON Task Force Report, and related topics from:

1. Charles, D, Gabriel, M, et al. (2014). Adoption of Electronic Health Record Systems among U.S. Non-federal Acute Care Hospitals: 2008-2013. Washington, DC, Department of Health and Human Services.
2. Hsiao, CJ and Hing, E (2014). Use and Characteristics of Electronic Health Record Systems Among Office-based Physician Practices: United States, 2001–2013. Hyattsville, MD, National Center for Health Statistics.
3. Swain, M, Charles, D, et al. (2014). Health Information Exchange among U.S. Non-federal Acute Care Hospitals: 2008-2013. Washington, DC, Department of Health and Human Services.
4. Furukawa, MF, King, J, et al. (2014). Despite substantial progress in EHR adoption, health information exchange and patient engagement remain low in office settings. Health Affairs. 33: 1672-1679.
5. Anonymous (2014). 2014 eHI Data Exchange Survey Key Findings. Washington, DC, eHealth Initiative.
6. Anonymous (2014). Connecting Health and Care for the Nation: A 10-Year Vision to Achieve an Interoperable Health IT Infrastructure. Washington, DC, Department of Health and Human Services.
7. Anonymous (2014). A Robust Health Data Infrastructure. McLean, VA, MITRE Corp.
8. Smith, M, Saunders, R, et al. (2012). Best Care at Lower Cost: The Path to Continuously Learning Health Care in America. Washington, DC, National Academies Press.

Saturday, October 11, 2014

OHSU Informatics Awarded NIH Grants Focused on Big Data and Analytics

The Oregon Health & Science University (OHSU) Department of Medical Informatics & Clinical Epidemiology (DMICE) has been awarded two grants to develop educational content and skills courses in the new National Institutes of Health (NIH) Big Data to Knowledge (BD2K) Program. In addition, DMICE was awarded an additional grant in collaboration with Mayo Clinic that makes use of Big Data from electronic health records (EHRs) for the purpose of identifying patients who might be eligible for clinical research studies.

On Thursday, October 9, this first round of BD2K grants were announced. A total of $32 million was awarded for 38 grants in the areas of enabling data utilization, developing analysis methods and software, enhancing training, and establishing centers of excellence. The two DMICE grants total about $1 million over three years. The two grants awarded to OHSU were among nine grants awarded for development of open educational resources and courses. Eight other institutions in addition to OHSU received more than one grant.

The BD2K initiative was launched by NIH in 2012, when it was recognized that an increasingly important aspect of biomedical research was to leverage data from clinical and biological sources. Its mission is to enable biomedical scientists to use big data effectively and appropriately to enhance reproducible research.

The two OHSU BD2K grants were R25 educational grants. Although national in scope, they will also have important local benefits for OHSU, Oregon, and the rest of the Pacific Northwest. One of the R25 grants will develop open educational resources (OERs) that can be adapted for a variety of educational programs, from the undergraduate to graduate and professional levels. The materials will use the same format as the Office of the National Coordinator for Health IT (ONC) curricular materials.

The other R25 grant will develop a Big Data skills course that will make available curricula and data sets to provide training in methods for basic, clinical and translational researchers as well as clinicians, librarians, and others. All researchers, especially graduate students, will be eligible to take the skills course and hone their skills in data.

DMICE plans to incorporate the materials from both grants in its own courses in its biomedical informatics graduate program, while the OHSU Library will utilize the materials via its educational outreach efforts. The OERs will also join the existing ONC curriculum materials on the American Medical Informatics Association (AMIA) Web site.

The OER project will be led by three PIs: William Hersh, MD; Shannon McWeeney, PhD; and Melissa Haendel, PhD. The skills development course will be led by David Dorr, MD, MS, and Drs. McWeeney and Haendel. These four OHSU faculty will also become part of the BD2K national community that NIH is establishing to widely disseminate knowledge, tools, and educational materials around Big Data.

The additional R01 grant is funded by the National Library of Medicine, the NIH institute devoted to basic research in biomedical informatics. Dr. Hersh will be collaborating with new DMICE faculty Stephen Wu, PhD, Adjunct Assistant Professor, as well as colleagues from Mayo Clinic, led by overall project PI, Hongfang Liu, PhD of Mayo Clinic. Both institutions will investigate techniques to use data from 100,000 patients each in their EHR systems for the task of cohort discovery, i.e., identifying patients who might be candidates for research studies.

Monday, October 6, 2014

Ebola in Texas: Who is to "Blame?"

One of the unfortunate consequences of our 24/7 cable news cycle as well as America's political polarization is that every negative event that takes place in society needs to have blame assigned to some person or organization. Sometimes the reactions to adverse news events seems to take the form of a political Rorschach Test, where an individual's reaction to the event demonstrates their underlying political views.

This was no more true recently than the unfortunate story of Thomas Eric Duncan, the man from Liberia who presented to a Dallas hospital with fever, chills, and joint pains. A nurse who saw the patient dutifully documented that the man had traveled from Liberia in the hospital's electronic health record (EHR). However, as is often the case, the physician did not see the nurse's note. The nurse failed to verbally communicate the travel history to the physician, and the physician who saw the patient did not ask about travel history. Thinking this was just a viral illness, the physician discharged the patient home. (An additional challenge with this story is that the facts keep changing. Later reports stated that the physician indeed knew about the patient's travel from Liberia. Either way, this does not change the basic premise of this posting.)

There were certainly things that were done wrong here by many people: The nurse did not verbally report the travel history to the physician. The physician did not read the nurse's note nor take a complete history from the patient. Those who implemented the EHR did not create a workflow that easily allowed the nurse's documentation to be seen by the physician. By the way, physicians not reading nurses' notes is a problem that long predates EHRs.

It would be unfortunate if the lessons learned from this episode are just figuring out who to blame, and then shaming them in the media. Our media, especially the cable news cycle that seems to thrive on pinpointing blame, with political ideologues of all stripes then chiming in with a shibboleth that indicates to which ideology they belong. And of course, the situation is not helped by the right-wing political echo chamber that seeks to tie everything-Obama to every possible adverse news event. It is fascinating to scroll through the readers' comments on various news sites and see how easily people make the "obvious" connections between this event and Obamacare, illegal immigration, the threat of terrorism, and so forth.

The reality is that although the US healthcare and public health systems are far from perfect, we do have the means to isolate and prevent the spread of Ebola. By the same token, we need to remember that the majority of people who walk into emergency departments with fever and joint pains do not have Ebola. In fact, we run the risk now of excessive testing and other resource use because of this one case.

A good outcome of this unfortunate episode would be our learning from it, and figuring out how to build systems of care, which include use of EHRs, that make sure front-line healthcare professionals do not miss cases like this while not interfering with the assessment of the overwhelming majority of routine cases of fever and joint pains that are from more common causes than Ebola. It might even be nice to have the means to prevent the spread of untruthful memes about cases like this, but I am not overly optimistic.