Post-doctoral and Pre-doctoral Training in Biomedical Informatics - Positions Available at OHSU

Although our educational program seems to be getting much of its recognition these days from our online program that focuses on educating informatics practitioners, we are still very committed to more intensive full-time education on our campus, especially in the training of future researchers in the field. I am pleased to report that Oregon Health & Science University (OHSU) had its National Library of Medicine Biomedical Informatics Training Grant renewed this year for another five-year cycle, with additional funding and opportunity provided by another institute of the National Institutes of Health, the National Institute of Dental and Craniofacial Research (NIDCR, which has a focus on oral and cranial health).

We are therefore seeking qualified applicants for our pre-doctoral and post-doctoral research training fellowship program in biomedical informatics for the 2013-2014 academic year. Additional support is available from the U.S. Department of Veterans Affairs and Kaiser-Permanente Northwest Region. By providing a structured research experience, with the option of course work and/or pursuit of a degree, the fellowship program prepares trainees to enter the academic community and undertake programs of independent biomedical informatics research, or to take leadership positions in the growing number of hospital and/or commercial efforts in biomedical informatics.

Our fellowship opportunities including the following:

NLM – Pre- and post-doctoral opportunities are available. The pre-doctoral positions are open to any qualified individual with a bachelor’s degree or higher, with the fellow expected to pursue a doctoral degree. The post-doctoral positions are open to any qualified individual with a doctoral degree. The fellow is expected to pursue a research project and is strongly encouraged to also pursue a master’s degree in biomedical informatics at OHSU.

U.S. Department of Veterans Affairs – The position is open to an MD and has a clinical practice component. The fellow is expected to work on a project with the VA’s advanced clinical information system and is strongly encouraged to also pursue a master’s degree in biomedical informatics at OHSU.

Kaiser-Permanente – This position is open to an MD and has a clinical practice component. The fellow is expected to work on a project with Kaiser-Permanente’s advanced clinical information systems and pursue coursework at OHSU.

NIDCR – Pre- and post-doctoral opportunities are available. Our goal is to prepare the fellow/trainee to enter the academic community and become an independent researcher, or to take leadership positions in the growing number academic and/or commercial efforts in oral health informatics. The pre-doctoral positions are open to any qualified individual with a bachelor’s degree or higher, with the fellow expected to pursue a doctoral degree. The post-doctoral positions are open to any qualified individual with a doctoral degree. The fellow is expected to pursue a research project and is strongly encouraged to also pursue a master’s degree in biomedical informatics at OHSU.

For more information about our biomedical informatics graduate program, visit our Web site. More detailed information about our fellowship programs is also available.

Program faculty and staff from OHSU will be present to meet with prospective students at the Career Expo of the AMIA 2012 Annual Symposium from November 4-7, 2012. Additional information is also available from Lauren Ludwig.

Health IT Workforce Policy: Roundtable with Rep. Susanne Bonamici

The First Congressional District of Oregon has a history of leadership in health information technology (HIT) workforce policy. As one who lives in the district, I am delighted that its Congressional representative, Susanne Bonamici, is holding a roundtable discussion on HIT workforce policy this week. I am honored to participate, especially in light of my role on the Workforce Group of the Office of the National Coordinator for HIT (ONC) HIT Policy Committee. Of course I also lead the informatics education program at Oregon Health & Science University (OHSU), an institution of which many employees are constituents of Rep. Bonamici and which is a well-known leader in HIT workforce development.

According to Rep. Bonamici, "As Oregon leads the nation in developing coordinated health delivery systems, the role of technology in managing information flow between patients, providers, and insurance companies will become increasingly important. The results of this roundtable discussion will inform legislative and oversight actions in the health IT field for the 113th Congress." She has further elaborated three topics for the roundtable:

• What can be done to better prepare practitioners to effectively use health IT and electronic health records?
• How can technology developers better design their products to fit with workflow in a medical setting?
• Does current curriculum adequately prepare technology developers and future medical service providers to meet industry and patient needs?

I heartily concur with her statement about Oregon's leadership in coordinated delivery systems and the importance of information in such systems. Regardless of one's political views, or the fate of "Obamacare" after next month's Presidential election, our healthcare system needs to become more coordinated, patient-centered, and focused on rewarding value over quantity of care. This vision is exemplified by the recent report from the Institute of Medicine, Best Care at Lower Cost: The Path to Continuously Learning Health Care in America, which makes a compelling case for a learning health care system infused with all aspects of HIT and informatics.

I also agree with the importance of the topics she raises. Namely, how do we prepare healthcare professionals to work in a data-driven healthcare system that strives for value and coordination of care? Likewise, what sort of professional workforce do we need to optimize information systems and their use? How do we best train that workforce and do so in a cost-effective manner? How do we nurture the industry in which they work? How do we advance the science, practice, and innovation?

What advice do I have for Rep. Bonamici concerning HIT workforce development? Since her first topic mentions the training of clinicians, I will begin there. In this realm, we need to insure that 21st century healthcare professionals are knowledgeable and savvy in their use of HIT to deliver optimal care, not only to individual patients, but entire populations. Current practitioners will need to be brought up to date through continuing education, while students will require their curricula to be updated to reflect what it takes to provide care in a data-driven learning healthcare system. Probably the best way to deliver this care is through the growing push for "interprofessional" education that brings all future healthcare professionals in the same classroom, preparing them to work in the future care system that is increasingly coordinated and team-based.

Delving further, all current and future healthcare professionals need to learn about tools that capture data and transform it into information and knowledge that can be used for both individual and population-based care. As such, these clinicians need to have competency in the following:

• Understanding the importance of the efficient and accurate collection of data not only for the electronic health record (EHR) of their delivery organization, but also how that data will populate other sources, such as personal health records (PHRs), health information exchange (HIE), and the public health system
• While not needing the detailed knowledge of informaticians, healthcare practitioners must learn the informatics basics of data standards, interoperability of clinical data systems, and clinical decision support
• Understanding the critical need to protect patient privacy and confidentiality
• Have skills in finding pertinent and reputable sources of knowledge to be applied to patient care, i.e., being expert in searching knowledge sources, from scientific literature (e.g., Pubmed) to summary textbooks and related sources
• Being able to deliver care in teams, using data and information to plan and guide care
• Mastering the concepts of healthcare quality measurement and improvement, i.e., understanding the rationale but also the limitations of quality measures, and how electronic data systems will facilitate them
• Being able to look forward and see other changes coming to healthcare in the future, such as personalized medicine, based on genomics and bioinformatics, and the role that it will play in the delivery of healthcare
• Understanding the ways that care is delivered over telecommunications networks, i.e., telemedicine and telehealth
• Be competent in the use of a wide variety of information devices, from computers to tablets to smartphones and the networks to which they connect

Implementing this vision and putting the technology and skills to use it will not come without the help of HIT and informatics professionals. The future HIT workforce must be ready to develop, implement, and evaluate HIT systems. These professionals will certainly need to be savvy with technology, but they will also need to be highly knowledgeable in the science and best practice of informatics to make sure these tools serve clinicians, patients, and the healthcare system. They must also be cognizant of the concerns of how HIT impacts workflow and patient safety. We must also adapt the curricula of our educational programs for future HIT professional workforce needs by increasing our experiential learning and preparing for "big data," predictive analytics, and advanced forms of clinical decision support.

Also, in settings like the First Congressional District, with its Silicon Forest, we will need to train additional individuals who will innovate and lead in industry. Our informatics program at OHSU has been working for some time to increase its collaboration with the HIT industry. It must be remembered that not only does HIT have the potential to improve health and healthcare, but in places like the First Congressional District, it can also contribute to economic development.

There must also be a cadre of academic informaticians who perform research and develop the future. In addition to education, a wide variety of innovative informatics research takes place at OHSU. Examples of the areas addressed include:

• Care coordination - the Integrated Care Coordination Information System (ICCIS) project led by Dr. David Dorr collects data and it makes available for analysis to enhance coordination of care.
• Secondary use of clinical data - my own research involves the development of data sets to augment the development of systems and algorithms to allow re-use of data in clinical systems.
• EHR simulation for patient safety - working with intensive care physician Dr. Jeffery Gold, we are developing realistic simulations to improve both users of EHRs and the systems themselves.

As in most scientific fields, government has funded the basic research that industry does not. Exemplary government agencies that support this research include the National Library of Medicine (NLM) and the Agency for Healthcare Research and Quality (AHRQ). I encourage Rep. Bonamici to continue her support for NLM and AHRQ, and encourage her to be in the lead in making sure to maintain and consider increasing their funding.

Another policy challenge going forward will be to maintain the investment made through the HITECH Act. Educational institutions associated with the First District were highly successful in competing for funding provided through the HITECH workforce development programs. OHSU has delivered on the work it was funded to do under the two programs for which grants were awarded to it:

• Development of national HIT curriculum, which focused initially on community colleges but then generalized to all institutions of higher education. OHSU served as one of five curriculum development centers as well as served as the National Training and Dissemination Center (NTDC) that distributed and supported the curriculum.
• Educating its share of students in the University-Based Training (UBT) Program. Most of our graduates have been highly successful in fulfilling the roles envisioned for them in the expanding HIT workforce.

Now, of course, the HITECH funding is winding down, ending in early 2013 for the curriculum project and mid-2013 for the UBT program. While student tuition and other sources of funding will fill in some of the declining federal investment, there is still a case for investing in the common good of educating not only the HIT workforce, but also clinicians who use HIT in a more coordinated and learning healthcare system.

I hope that Rep. Bonamici can spur the entire community, from academia to industry to healthcare organizations, to work together to improve healthcare delivery as well as advance the HIT industry. Both are vital to the future health and economic well-being of Oregonians.

Improving Patient Safety Through Electronic Health Record Simulation

Most tools used in medicine require knowledge and skills of both those who develop them and use them. Even tools that are themselves innocuous can lead to patient harm. For example, while it is difficult to directly harm a patient with a stethoscope, patients can be harmed when improper use of the stethoscope leads to them having tests and/or treatments they do not need (or not having tests and treatments they do need). More directly harmful interventions, such as invasive tests and treatments, can harm patients through their use as well.

To this end, health information technology (HIT) can harm patients. The direct harm from computer use in the care of patients is minimal, but the indirect harm can potentially be extraordinary. HIT usage can, for example, store results in an electronic health record (EHR) incompletely or incorrectly. Clinical decision support may lead clinician astray or may distract them with unnecessary excessive information. Medical imaging may improperly render findings. Search engines may lead clinicians or patients to incorrect information. The informatics professionals who oversee implementation of HIT may not follow best practices to maximize successful use and minimize negative consequences. All of these harms and more were well-documented in the Institute of Medicine (IOM) report published last year on HIT and patient safety [1].

One aspect of HIT safety was brought to our attention when a critical care physician at our medical center, Dr. Jeffery Gold, noted that clinical trainees were increasingly not seeing the big picture of a patient's care due to information being "hidden in plain sight," i.e., behind a myriad of computer screens and not easily aggregated into a single picture. This is especially problematic where he works, in the intensive care unit (ICU), where the generation of data is vast, i.e., found to average about 1300 data points per 24 hours [2]. This led us to perform an experiment where physicians in training were provided a sample case and asked to review an ICU case for sign-out to another physician [3]. Our results found that for 14 clinical issues, only an average of 41% of issues (range 16-68% for individual issues) were uncovered.

While this rate of error is alarmingly high, it must be remembered that the physicians reviewing the case were new to it, i.e., not taking direct care of the patient. It is also important to remember that paper-based information management in the ICU has always had its problems as well. Nonetheless, there clearly needs to be improvement both in the presentation of information as well as the training of users to access it.

As we were completing this work, a new round of funding was announced for a grant program, Improving Patient Safety Through Simulation Research, by the Agency for Healthcare Research and Quality (AHRQ). I am pleased to report that we have been awarded a three-year, $1 million grant to pursue this work. Dr. Gold is Principal Investigator of the project and several faculty in our informatics program, including myself, are Co-Investigators. Our efforts will focus on continuing the development of the simulation through development of new cases, aiming to improve both the user interface as well as user training, and disseminating our results. Of course, we are not the only research group evaluating improved methods to find and use data in the EHR, our simulation approach is novel and will hopefully add additional insights to improving the use of HIT in the clinical setting.

References
1. Anonymous (2012). Health IT and Patient Safety: Building Safer Systems for Better Care. Washington, DC. National Academies Press. http://www.iom.edu/Reports/2011/Health-IT-and-Patient-Safety-Building-Safer-Systems-for-Better-Care.aspx.
2. Manor-Shulman, O., Beyene, J., et al. (2008). Quantifying the volume of documented clinical information in critical illness. Journal of Critical Care, 23: 245-250.
3. Steiger, D., March, C., et al. (2012). Use of simulation to assess and improve electronic medical record usage. American Journal of Respiratory and Critical Care Medicine, 185: A2890. http://ajrccm.atsjournals.org/cgi/reprint/185/1_MeetingAbstracts/A2890.

Health IT Jobs Growth Outpacing Qualified People to Fill Them?

I recently wrote about the substantial growth in health information technology (HIT) employment that has exceeded all predictions. That is the good news. The less-good news is that healthcare organizations still face substantial challenges in meeting their HIT staffing needs. This was borne out by a recent survey of the College of Healthcare Information Management Executives (CHIME), which assessed HIT workforce staffing issues and found that the shortfalls of needed HIT staff still persist [1]. Perhaps this is not surprising, given the growth in the use of HIT and overall employment as noted in my previous post.

A total of 163 out of CHIME's 1400+ members, mostly chief information officers (CIOs), responded to the survey during July, 2012. A similar survey had been administered in 2010. All sizes (from 0-99 to 1000+) and types (academic, community, and multi-hospital) of healthcare provider organizations responded.

About 67% of respondents reported that their organizations were experiencing shortages. This was compared with 59% in 2010. The highest category having unmet needs was academic centers, reported by 82%. About 12% of organizations reported 15% or more positions being open.

The survey asked about skills most often in demand, which included:

• Clinical software implementation and support staff (e.g., EHR, CPOE) - 74%
• Infrastructure staff - 47%
• Business software implementation and support staff - 45%

About 71% said IT staff shortages could jeopardize an enterprise IT project, while 58% said they would definitely or possibly affect meeting meaningful use criteria for incentive funding. About 85% also expressed concerns about being able to retain current staff.

The survey also assessed awareness of the HIT Workforce Programs of the Office of the National Coordinator for Health IT (ONC) [2]. Only 67% were aware of the ONC workforce programs, with 12% of those respondents reporting that they had hired graduates from them. (Unfortunately the survey did not distinguish knowledge of and hiring from community college versus university-based programs.)

The respondents reported their chief strategies for coping with IT staff shortages, which included:

• Hiring third-party consultants - 28%
• Hiring from within the organization and retraining - 20%
• Other (multiple strategies) - 18%
• Using recruiters to find and place qualified staff - 15%
• Depending on HIT vendors to provide implementation staff - 8%
• Other kinds of outsourcing - 6%
• Developing a pipeline of students by collaborating with local colleges and universities - 2%

The most important attributes and competencies deemed to be needed by HIT professionals included:

• Actual experience in a health IT shop
• Clinical informatics experience
• Education in IT theory and practice in a real-world setting

The most important attribute or competency that was least likely to be mentioned by respondents was:

• Coding knowledge
• Willingness to start “at the bottom” in an IT shop
• Education in IT theory and practice in a classroom setting

Those surveyed were also asked what competencies or areas of knowledge were generally lacking in candidates being considered for IT staff positions. The most frequently mentioned were:

• Lack of knowledge of healthcare and related IT applications
• Lack of practical experience
• Lack of experience with an organization’s system
• Inability to interact successfully with front-line users

Overall, the CHIME survey demonstrates that adequate numbers of HIT professionals with appropriate skills are a bottleneck to HIT implementation in healthcare organizations. The highest unmet needs for staffing are in clinical areas, with individuals most sought after being those with healthcare and/or HIT experience, applied education in both theory and practice, and good people skills. Knowledge of ONC workforce programs is by no means universal, and even those with knowledge of the programs are hiring relatively few graduates, although the survey did not distinguish levels of knowledge or hiring from community college versus university-based programs. Clearly while job opportunities in HIT are strong, many organizations are experiencing challenges fulfilling their HIT hiring needs. There is also onus on educational programs to train individuals with adequate skills as quickly and efficiently as possible.

References

1. Anonymous (2012). Demand Persists for Experienced Health IT Staff. Ann Arbor, MI, College of Healthcare Information Management Executives. http://www.cio-chime.org/chime/press/surveys/pdf/CHIME_Workforce%20_survey_report.pdf.

2. Hersh, W. (2012). Update on the ONC for Health IT Workforce Development Program. HIMSS Clinical Informatics Insights. July, 2012. http://www.himss.org/ASP/ContentRedirector.asp?ContentId=80559&type=HIMSSNewsItem;src=cii20120709.

Challenges for Building Capacity of the Clinical Informatics Subspecialty

The new clinical informatics subspecialty promises to provide professional recognition to the increasing number of physicians who work in the specialty of combining information with their medical expertise to improve quality and safety while lowering the cost of healthcare. The American Board of Preventive Medicine (ABPM), the administrative home for the subspecialty, is currently defining the criteria for those who will be eligible to take the certification exam without formal training (i.e., “grandfathering” by virtue of previous work in the field - whether by the “practice pathway” or prior training - which will be allowed for the first five years of the subspecialty's existence), developing the first board certification exam, and defining criteria for future fellowship training.

The new subspecialty will provide a great opportunity for professional recognition of physicians who work in clinical informatics. One concern, however, is how our field will build capacity to train the critical mass of those who wish to become trained and certified in the subspecialty. There are a number of unique aspects of this discipline that will make this task challenging. In this posting, I will speak to these from my position as a program director of one of the largest clinical informatics educational programs in the United States.

There will be challenges both during the grandfathering era as well as when formal fellowship training is required. For the former, there will likely be exclusion of some who have the knowledge or the experience, but not both, to be deemed clinical informatics subspecialists. For the latter, if this field follows a “traditional” path of requiring all entrants to the field to obtain training only in 1-2 year, on-site fellowships, then we may be unlikely to match the need for these specialists or the aspirations of those who often enter the field in middle of their careers.

Data and Perspectives

Our informatics educational program at Oregon Health & Science University (OHSU) has been an extremely popular approach for all, including physicians, to receive training in clinical informatics. The program is available both on-campus and via distance learning, with the asynchronous nature of courses in the on-line program allowing students to train without having to move or leave their current jobs. A total of 1359 individuals have enrolled in the OHSU informatics program since its inception in 1996. During that time, 441 people have received a total of 12 PhD degrees, 184 master's degrees, and 278 graduate certificates. (The graduate certificate is a subset of the master’s degree program covering the core content of the field. While it has been in existence for over a decade, its numbers increased significantly from funding by the Office of the National Coordinator for Health IT [ONC] University-Based Training [UBT] Program for “short-term training,” especially in the workforce role of “clinician leader.”)

There are currently 291 students actively enrolled in the OHSU informatics program, 95 (32%) of whom are physicians. A similar proportion of our graduates are physicians, many of whom have gone on to leadership roles in clinical informatics, such as that of Chief Medical Informatics Officer (CMIO). A not-insignificant number of them were already CMIOs or other leaders upon entering the program, and some of those negotiated enrollment in the program or at least some courses within it as a condition of employment. Our data and experience clearly show that informatics via distance learning is a credible pathway for physicians and others to become clinical informatics professionals.

Our experience has also shown that essentially all types of informatics experiential learning can take place in a distance learning program. One concern we have always had in our program is the ability to gain experience through a practicum or internship. We have been able to institute such programs that allow students to carry out a mentored experience in “real-world” settings of health care organizations, companies, government agencies, and others. Our process tracks deliverables of the documentation of experiences and includes faculty monitoring of progress. It has even sometimes led to employment in those settings.

Some additional data from our program is relevant to the following discussion of challenges for building clinical informatics capacity of physicians. One is the median age of our students, which is about 41.5 years at matriculation into the program. The following chart shows the average age of physicians currently enrolled in the program. These data clearly show that most physicians in our program pursue informatics training and positions in the middle of their careers, i.e., do not follow the traditional contiguous progression from medical school to residency to subspecialty training and employment.

Another data point concerns the mapping of our curriculum to the core content of the new subspecialty, as laid out by Garnder et al. (2009) and included in the proposal for the subspecialty approved by the American Board of Medical Specialties (ABMS). We recently mapped the core content to our existing curriculum and found the material spread over 23 academic-quarter courses. Clearly the core content of clinical informatics will need to be consolidated into many fewer courses, but it is unlikely that any course of study will require the equivalent of a master's degree or at least a graduate certificate.

But clear unlike most other medical subspecialties, the knowledge base of clinical informatics is not a refinement of what the physician learned in medical school and built upon in residency. Consider, for example, a trainee in the area of critical care medicine. A future intensivist physician will have learned the basics of the diseases, treatments, tests, etc. starting in medical school. In medical school, the student will have started in basic science courses with the fundamentals of the cardiovascular system, the pulmonary system, and other applicable biomedical areas. As a clinical student, he or she will see their first cases of conditions such as sepsis, heart failure, and severe pulmonary disease in critical care units and other areas of the hospital. If interested in a career in critical care medicine, that medical student may then pursue a residency in internal medicine, surgery, anesthesiology, or other areas, but will continue to build upon the foundation of diseases and treatments learned in medical school. He or she will complete their training in a clinical fellowship, where more detailed knowledge emanating from the basics started in medical school will be mastered. Those who aspire to train in clinical informatics, however, will enter a new world of knowledge. While clinical expertise certainly will provide a partial foundation to the knowledge he or she must master, entire new areas of study will be brought into the equation. These include topics such as clinical decision support, organizational behavior and management, health information exchange, and standards and interoperability.

Challenges in the Grandfathering Era

The ABPM will soon be announcing what will qualify as “already working in the field,” which will determine who will be eligible to sit for the certification exam in the first five years of the subspecialty. The proposal submitted to the American Board of Medical Specialties (ABMS) suggested that working in the field be defined as either having worked in the field at 25% or more effort for at least three years or by having completed a “non-accredited fellowship” of at least 24 months duration. What exactly is meant by the latter is unclear, especially since many who have entered the field have done so through graduate-level educational programs, such as the OHSU program described above, that meet or exceed the depth of a fellowship program, even if they are not pursued in a full-time manner.

I have concerns that there will be disappointment with the criteria, both from those who are not eligible and could likely pass the exam as well as those who will be eligible but find the knowledge content of the exam overwhelming despite their substantial experience working in the field. I know this is true of all new medical specialties that become formalized, and that it takes some time for a field to synchronize its training and its practice knowledge base. But as noted above, clinical informatics has some unique differences, especially with regards to a knowledge base that is not just a refinement of what is learned starting in medical school.

There will likely be many in the category of physicians who are deemed not to meet the grandfathering requirements for experience yet could likely pass the test. This may include those who have completed educational programs such as a master’s degree or graduate certificate, either in informatics or a related discipline. Depending on how many of these programs qualify as a “non-accredited fellowship,” there could be many physicians who pursued formal training in the field only to not be eligible under the initial certification process.

By the same token, there will also likely be many physicians who have been working in CMIO or other clinical informatics positions, thus meeting the practice requirements, but whom have little or no formal training in the field and lack mastery of the knowledge base to be able to pass the certification exam. Clearly there must be some bar set for knowledge in the field, but many experienced clinical informaticians will require substantial education to achieve the level of knowledge required to pass the exam. Some challenges will include where to set the bar and how to help those who fall below it achieve the knowledge to move above it.

Challenges in the Clinical Fellowship Era

There will be additional challenges for building capacity after the grandfathering era has ended and formal fellowship training is required. These challenges will likely be more daunting, especially if we want to broadly expand the capacity of the field to meet perceived needs for individuals trained and certificated in clinical informatics. Depending on how stringent the requirements are for full-time, in-residence fellowship training, it could be quite difficult to build the needed capacity.

The first challenge for clinical informatics training will be how new trainees learn the core content. Clearly a subspecialty fellowship in clinical informatics will require a more formal educational program than the usual half-day per week of lectures by local subject experts in a typical clinical fellowship. This point is driven home by an analysis of the core content mapped to courses in the OHSU biomedical informatics graduate program described above, where we found the material to be mapped over 23 academic-quarter courses. Certainly a course of study will need to be consolidated into many fewer courses, but the mastery of this knowledge will not be provided the usual half-day per week of lectures provided in a conventional clinical fellowship. Organizations that offer clinical informatics fellowships will need to provide this educational activity, or at least partner with others who can do so.

A second challenge for building the capacity is that many physicians (and others) enter the field of informatics in the middle of their careers. This is not a negative for the field, as many clinicians come to realization that some of the biggest challenges in healthcare involve managing and making best use of data and information. As such, they decide to pursue careers in informatics that will allow them to do that. This pursuit of informatics in mid-career is one of the major reasons for the popularity of distance learning programs. We have found that despite the large numbers of students in our program, one of our biggest challenges is filling classrooms on our campus. Even “local” students in the Portland area want to take “distance” classes due to convenience and/or daytime working constraints.

A third challenge for developing capacity concerns the ability of organizations to stand up on-site training programs to handle building overall capacity. In order to maintain a clinical informatics fellowship program, according to the training requirements laid out by Safran et al. (2009), organizations will need to provide not only practical, hands-on training under supervised certified clinical informatics subspecialists, but also a robust educational experience. A scan of existing informatics training programs shows that some have strong hands-on components and others have well-developed educational programs but few have both. While the quantity of clinical informatics subspecialists needed is not precisely known, it is clear that only a small number of programs would be able to stand up programs that could meet the requirements spelled out by Safran et al. in contrast to the potentially hundreds if not thousands of hospitals and other clinical settings that could benefit from these specialists. This necessitates a more efficient approach to training, a contribution of which distance learning approaches could provide.

A fourth challenge is who will bear the cost of fellowship training. While most educational programs are funded by tuition, clinical fellowships are usually paid positions where the cost is covered by a combination of graduate medical education subsidy through Medicare as well as patient care services provided by the trainee. While both of these traditional sources of fellowship funding might work in some settings, it is not clear in this era of reduced federal funding for medical training and squeezed hospital budgets that paid fellowships will be viable in many places.

A final challenge could be the accreditation of fellowship sites by the Accreditation Council for Graduate Medical Education (ACGME). This challenge is not limited to the clinical informatics subspecialty. While the ACGME has accredited some programs that allow elements of remote learning, e.g., (Emmett and Green-McKenzie, 2001), its view, like most of medicine, is that subspecialty training is mostly an activity that takes place in a full-time fellowship at one or more physical sites.

Road Ahead

The need for clinical informatics subspecialists is clear, and the aggregate capacity to train adequate numbers is probably available. However, the traditional fellowship where experiential and didactic learning takes place in a single organization is likely impractical, certainly for the numbers that most estimate are needed for the subspecialty. Based on our experience in training physicians and others for careers in informatics, we believe the approach that is most effective and scalable will be to combine the online curricular delivery with practical experience on the ground augmented with additional interactions among trainees, including in-person or virtual approaches.

There are likely creative ways to build the capacity of clinical informatics training programs. One would be to allow institutions that could offer up robust experiential training to partner with those can provide the education, with the latter in a remote manner. Our program is already in discussion with two organizations that are considering melding our educational programs with their on-site training. Not only will we provide “out-sourcing” of coursework to these institutions, but we will also engage with their faculty in faculty development. We also plan to make use of telecommunications modalities to allow interaction among their trainees, our faculty, and even our local trainees.

There are other reasons why clinical informatics fellowship training should be more distributed. The world of clinical informatics is very different in high-resource academic centers compared to community hospitals and other clinical settings. The latter types of organizations are less likely to achieve “meaningful use” of information technology (Desroches, Worzala et al., 2012). A robust training experience should include these types of settings as well. Distributed training experiences will also allow for more interaction among trainees. As a single healthcare organization is likely to only be able to accommodate a few trainees, an integrated multisite program will allow more trainees to interact and share knowledge and experiences.

Clinical subspecialty training has historically been provided at one or a small number of sites, with educational activities also provided at those locations. However, with the growing proliferation of specializations that physicians can undertake today (Cassel and Reuben, 2011), many of which did not exist during their initial training, clinical informatics will not only benefit from novel approaches but could also provide an opportunity for medicine to reconsider how physicians train in many other specialties. Regulatory bodies will need to recognize these problems and authorize training programs that achieve their educational goals, even if in non-traditional ways. Just as the rest of education has adapted to and embraced the use of technology, medicine must do likewise.

References

Cassel, C. and Reuben, D. (2011). Specialization, subspecialization, and subsubspecialization in internal medicine. New England Journal of Medicine, 364: 1169-1173.
Desroches, C., Worzala, C., et al. (2012). Small, nonteaching, and rural hospitals continue to be slow in adopting electronic health record systems. Health Affairs, 31: 1092-1099.
Emmett, E. and Green-McKenzie, J. (2001). External practicum-year residency training in occupational and environmental medicine: the University of Pennsylvania Medical Center Program. Journal of Occupational and Environmental Medicine, 43: 501-511.
Gardner, R., Overhage, J., et al. (2009). Core content for the subspecialty of clinical informatics. Journal of the American Medical Informatics Association, 16: 153-157.
Safran, C., Shabot, M., et al. (2009). ACGME program requirements for fellowship education in the subspecialty of clinical informatics. Journal of the American Medical Informatics Association, 16: 158-166.

Health IT Job Creation Predictions Come True: More Than 60,000 Since 2008

Back in 2008, when searching to find an estimate of the magnitude of health information technology workforce (HIT) needs, I came up empty-handed, which led me to try to answer the question myself. The best source of data I was able to find was the HIMSS Analytics Database. I knew that this was not the ideal information source, i.e., it was self-reported data not really aiming to capture detailed HIT staffing information. While the analysis did make some adjustments to the data that passed muster with peer reviewers, it gave us an estimate of a need for approximately 41,000 additional people needed as electronic health record (EHR) adoption advanced to the level associated with improved clinical outcomes, which coincided with use of clinical decision support and computerized provider order entry. This was based on best research at the time [1] and still holds true today [2]. This corresponded to Stage 4 of the HIMSS Analytics EMR Adoption Model (EMRAM). (This was before the era of "meaningful use," although the following year, HIMSS Analytics noted that EMRAM Stage 4 was approximately the level needed to meet the early conceptions of what meaningful use would be [3].)

I had the opportunity to present the results of my research at a briefing on Capitol Hill in the spring of 2008, with their publication later that year at the AMIA Annual Symposium [4]. I believe I can argue without too much bravado that this was one of a few happenings that put HIT workforce on the map, leading to its inclusion in Section 3016 of the Health Information Technology for Economic and Clinical Health (HITECH) Act of the American Recovery and Reinvestment Act (ARRA) of 2009.

Acting on the Section 3016 statute in the HITECH Act, the Office of the National Coordinator for Health IT (ONC) followed through by combining my data with other sources to come up with an estimate of HIT workforce needs to meet the coming incentives to implement meaningful use. They estimated more than 50,000 new HIT personnel would be required in addition to those already working in the field to achieve the goals for meaningful use [5]. This led to the specific programs created under the ONC Workforce Development Program [6].

While it will take much longer to know how successful the ONC-funded programs will be, or what the long-term HIT job market will look like, the recent release of an ONC Data Brief bore out an estimate of the jobs [7]. Proving early estimates quite prescient, the ONC analysis found that indeed, employment in HIT has increased by over 60,000 between 2008 and 2011, as shown in the figure reproduced from the Data Brief below. The total employment in HIT, according to these government figures, was 362,265 in 2011.

It has been quite rewarding to be part of this national effort to identify, develop, and observe the outcomes of these efforts to achieve one part of the informatics agenda. Although the future is uncertain, as the course of technology, healthcare reform, and government programs is unpredictable, with the interaction among the three of them even more unknowable. However, the need for skilled informatics professionals will continue to be an important part of the HIT landscape [8].

References

1. Chaudhry, B., Wang, J., et al. (2006). Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine, 144: 742-752.
2. Buntin, M., Burke, M., et al. (2011). The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Affairs, 30: 464-471.
3. Davis, M. (2009). The State of U.S. Hospitals Relative to Achieving Meaningful Use Measurements. Chicago, IL, HIMSS Analytics. http://www.himssanalytics.org/docs/HA_ARRA_100509.pdf.
4. Hersh, W. and Wright, A. (2008). What workforce is needed to implement the health information technology agenda? An analysis from the HIMSS Analytics™ Database. AMIA Annual Symposium Proceedings, Washington, DC. American Medical Informatics Association. 303-307. http://skynet.ohsu.edu/~hersh/amia-08-workforce.pdf.
5. Conn, J. (2010). 50,000 new health IT workers might be needed. Modern Healthcare. May 25, 2010. http://www.modernhealthcare.com/apps/pbcs.dll/article?AID=/20100525/NEWS/100529949/.
6. Hersh, W. (2012). Update on the ONC for Health IT Workforce Development Program. HIMSS Clinical Informatics Insights. July, 2012. http://www.himss.org/ASP/ContentRedirector.asp?ContentId=80559&type=HIMSSNewsItem;src=cii20120709.
7. Furukawa, M., Vibbert, D., et al. (2012). HITECH and Health IT Jobs: Evidence from Online Job Postings. Washington, DC, Department of Health and Human Services. Data Brief No. 2, May, 2012, http://www.healthit.gov/sites/default/files/pdf/0512_ONCDataBrief2_JobPostings.pdf.
8. Leviss, J., Gugerty, B., et al. (2010). H.I.T. or Miss: Lessons Learned from Health Information Technology Implementations. Chicago, IL. American Health Information Management Association.

New IOM Report on Implementing the Learning Healthcare System: It's All in the Information

Some of the most important reports for setting the context of the work of informatics have been those from the Institute of Medicine (IOM). These reports have now spanned over 20 years, with many serving to raise awareness of problems and provide a context for informatics solutions. Some of the IOM's seminal reports have covered the topics of electronic health records [1, 2], telemedicine [3], computer networks and the Internet [4], privacy and security [5], medical errors and patient safety [6, 7], healthcare quality [8], health professions education [9], reducing costs while improving outcomes [10], and safety of health information technology [11].

More recently, these reports have coalesced around the notion of the learning health system, a system that learns from its experiences, incorporates the best science, and provides patient-centered care [12]. Additional reports have focused on issues that heavily involve informatics, such as developing the human and organizational [13] as well as digital [14] infrastructures for the learning healthcare system. The former Chief Science Officer of the Office of the National Coordinator for Health Information Technology tied its efforts to the notion of the learning healthcare system [15].

This past week, the IOM provided another "smash hit" in its series of reports. Entitled, Best Care at Lower Cost, this report notes the urgent need to address both the increasing complexity of the healthcare system as well as its continually increasing costs [16]. The report relates that many industries, from banking to manufacturing to transportation, operate with increasing coordination and efficiency in recent times, especially when aided by modern information technology. Yet healthcare is mired in the past, being highly uncoordinated and excessively labor-intensive.

The full report is available for viewing online and as a downloadable PDF. There are some condensed versions as well, including a report brief, the main recommendations, a list of the characteristics of a continuously learning healthcare system, and an infographic that highlights the main points. An article in JAMA also provides an overview of the report's motivations, findings, and recommendations [17].

The report asserts that implementing standard practices from those of other industries could result in:

• Records immediately updated and available for use by patients
• Care delivered the has been proven "reliable at the core and tailored at the margins"
• Patient and family needs and preferences are a central part of the decision process
• All healthcare team members are fully informed about each other’s activities in real time
• Prices and total costs are fully transparent to all participants in the care process
• Incentives for payment are structured to "reward outcomes and value, not volume"
• Errors are promptly identified and corrected
• Outcomes are routinely captured and used for continuous improvement

These results could be possible now because of human and technological changes that have been adopted in most industries, including:

• Substantial computational power that is affordable and widely available
• Network connectivity that allows information to be accessed instantaneously from almost anywhere
• Human and organizational capabilities that improve the reliability and efficiency of care processes
• The recognition that effective care must be delivered collaboratively by teams of clinicians and patients, with each playing a vital role in the process

The report was motivated in part by the conclusions of a previous report that noted annual excess costs of care in the US to be around $750 billion (out of $2.5 trillion expended), resulting in approximately 75,000 annual premature deaths. It grouped the causes of this waste and harm as due to:

• Unnecessary services provided
• Services inefficiently delivered
• Prices too high relative to costs
• Excess administrative costs
• Missed opportunities for prevention
• Fraud

Also identified in the report are four "characteristics of a continuously learning healthcare system." These include:

1. Science and informatics - real-time access to knowledge and digital capture of the entire care experience
2. Patient-clinician partnerships - engaged, empowered patients
3. Incentives - aligned for value with full transparency
4. Culture - instilled by leadership and with supportive system competencies

The report concludes with a series of recommendations for the continuously learning healthcare system group into three categories (verbatim):

I - Foundational Elements
1. The digital infrastructure. Improve the capacity to capture clinical, care delivery process, and financial data for better care, system improvement, and the generation of new knowledge.
2. The data utility. Streamline and revise research regulations to improve care, promote the capture of clinical data, and generate knowledge.
II - Care Improvement Targets
3. Clinical decision support. Accelerate integration of the best clinical knowledge into care decisions.
4. Patient-centered care. Involve patients and families in decisions regarding health and health care, tailored to fit their preferences.
5. Community links. Promote community-clinical partnerships and services aimed at managing and improving health at the community level.
6. Care continuity. Improve coordination and communication within and across organizations.
7. Optimized operations. Continuously improve health care operations to reduce waste, streamline care delivery, and focus on activities that improve patient health.
III - Supportive Policy Environment
8. Financial incentives. Structure payment to reward continuous learning and improvement in the provision of best care at lower cost.
9. Performance transparency. Increase transparency on health care system performance.
10. Broad leadership. Expand commitment to the goals of a continuously learning health care system.

Informatics is of course central to the notion of the learning healthcare system by capturing, analyzing, and acting on data from the entire spectrum of care. There is another figure in the report that provides a "schematic" of the healthcare system that allows all of the critical informatics challenges and opportunities to be enumerated. This figure shows that the overall patient care experience begins from science, moving to evidence of what from the science improves patient care, followed by the delivery of that best care that will ideally result in the optimal patient outcomes and satisfaction. When any of these elements is carried out suboptimally, there are missed opportunities, waste, and harm. The only additions I would make to this figure would be feedback loops among the elements, i.e., the patient experience informs new science, evidence, and care, while the care experience feeds back to science and evidence, and so forth.

Informatics plays a role in each of these elements as well as the transitions between them. Starting with science, informatics increasingly plays a role in both driving and facilitating science. Informatics allows the science to learn from new discoveries in the data and also helps the scientist manage and analyze that data. It helps the clinical researchers select the best science to select and then evaluate for the evidence. Informatics also allows the best evidence to get implemented as care through methods such as clinical decision support. It also optimizes the care experience through quality measurement and improvement. In addition, informatics engages not only the patient and their caregivers but also other providers through health information exchange. Informatics also provides "safety rails" of sorts through maintaining safety, reducing error, facilitating privacy and security, and promoting adherence to standards. There is really no aspect of informatics that cannot be connected to this schematic.

By the same token, there is no aspect of informatics that cannot be related in some way to the continuous learning healthcare system. For this reason, this new IOM report presents a vision and all the grand challenges for the entire healthcare system as well as the role of informatics within it. Of course, vision alone is not enough, and we now must turn our attention to implementing it. Encouraging studies and reports are already coming out, such as the learning healthcare system operationalized at Group Health in Seattle [18], coordinated care projects implemented by Medicare to reduce hospital readmissions [19], the "Choosing Wisely" initiative to reduce unnecessary and potential harmful tests and treatments [20], and new science making the vast findings of genomics clinically "actionable" [21]. As with many other IOM reports, this report presents a robust context for the work of informatics to improve health and the healthcare system and points a way forward for doing so.

References

1. Dick, R., Steen, E., et al., eds. (1991). The Computer-Based Patient Record: An Essential Technology for Health Care. Washington, DC. National Academies Press.
2. Dick, R., Steen, E., et al., eds. (1997). The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC. National Academies Press.
3. Anonymous (1996). Telemedicine: A Guide to Assessing Telecommunications in Health Care. Washington, DC. National Academies Press.
4. Anonymous (2000). Networking Health: Prescriptions for the Internet. Washington, DC. National Academies Press.
5. Anonymous (1997). For the Record: Protecting Electronic Health Information. Washington, DC. National Academies Press.
6. Kohn, L., Corrigan, J., et al., eds. (2000). To Err Is Human: Building a Safer Health System. Washington, DC. National Academies Press.
7. Aspden, P., Corrigan, J., et al., eds. (2004). Patient Safety - A New Standard for Care. Washington, DC. National Academies Press.
8. Anonymous (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC. National Academies Press.
9. Greiner, A. and Knebel, E., eds. (2003). Health Professions Education: A Bridge to Quality. Washington, DC. National Academies Press.
10. Yong, P. and Olsen, L. (2010). The Healthcare Imperative: Lowering Costs and Improving Outcomes - Workshop Series Summary. Washington, DC. National Academies Press. http://iom.edu/Reports/2011/The-Healthcare-Imperative-Lowering-Costs-and-Improving-Outcomes.aspx.
11. Anonymous (2012). Health IT and Patient Safety: Building Safer Systems for Better Care. Washington, DC. National Academies Press. http://www.iom.edu/Reports/2011/Health-IT-and-Patient-Safety-Building-Safer-Systems-for-Better-Care.aspx.
12. Eden, J., Wheatley, B., et al., eds. (2008). Knowing What Works in Health Care: A Roadmap for the Nation. Washington, DC. National Academies Press. http://www.iom.edu/Reports/2008/Knowing-What-Works-in-Health-Care-A-Roadmap-for-the-Nation.aspx.
13. Olsen, L., Grossman, C., et al. (2011). Learning What Works: Infrastructure Required for Comparative Effectiveness Research. Washington, DC. National Academies Press. http://www.iom.edu/Reports/2011/Learning-What-Works-Infrastructure-Required-for-Comparative-Effectiveness-Research.aspx.
14. Grossman, C. and McGinnis, J. (2010). The Digital Infrastructure for a Learning Health System: Foundation for Continuous Improvement in Health and Health Care - Workshop Summary. Washington, DC. National Academies Press. http://www.iom.edu/Reports/2011/Digital-Infrastructure-for-a-Learning-Health-System.aspx.
15. Friedman, C., Wong, A., et al. (2010). Achieving a nationwide learning health system. Science Translational Medicine, 2(57): 57cm29. http://stm.sciencemag.org/content/2/57/57cm29.full.
16. 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. http://iom.edu/Reports/2012/Best-Care-at-Lower-Cost-The-Path-to-Continuously-Learning-Health-Care-in-America.aspx.
17. Redberg, R. (2012). Getting to best care at lower cost. Archives of Internal Medicine: Epub ahead of print.
18. Greene, S., Reid, R., et al. (2012). Implementing the learning health system: from concept to action. Annals of Internal Medicine, 157: 207-210.
18. Brown, R., Peikes, D., et al. (2012). Six features of Medicare coordinated care demonstration programs that cut hospital admissions of high-risk patients. Health Affairs, 31: 1156-1166.
20. Cassel, C. and Guest, J. (2012). Choosing wisely: helping physicians and patients make smart decisions about their care. Journal of the American Medical Association, 307: 1801-1802.
21. Feero, W. (2012). Determining actionability of genetic findings in clinical practice. ACP Internist, July/August 2012. http://www.acpinternist.org/archives/2012/07/genomics.htm.

What is "DMICE," a "Track," a "Certificate?" The Jargon of the OHSU Informatics Program

In my paper that gave my definitions of the terminology of the biomedical and health informatics (BMHI) field, I noted the challenge of how confusing all the jargon could be. I realize now that this problem is exacerbated by the additional jargon we add on top of it in our educational program at Oregon Health & Science University (OHSU). Unfortunately, the complexity of our program makes there no simple solution, and the best approach is to try to define the jargon as simply and succinctly as possible.

So let me start with the first sub-question in the title of this post: What is DMICE? DMICE is the Department of Medical Informatics & Clinical Epidemiology, which is one of 26 academic departments in the School of Medicine at OHSU. A public university in the state of Oregon focused mostly on the health sciences, OHSU has Schools of Medicine, Nursing, and Dentistry, along with a School of Pharmacy administered jointly with Oregon State University. DMICE sits among other more traditionally named departments in the OHSU School of Medicine, such as Medicine, Surgery, and Medical & Molecular Genetics. As Chair of DMICE, I report to the Dean of the OHSU School of Medicine.

As in most departments in universities, DMICE has a wide variety of educational and research programs. One of those is the Biomedical Informatics Graduate Program. This is the umbrella term used to describe all of the educational programs dealing with informatics and related disciplines in DMICE. The program is offered at graduate level, i.e., students must have a baccalaureate degree to be admitted.

The Biomedical Informatics Graduate Program features several tracks, each of which represent a focus of study within BMHI. The tracks are partially overlapping, representing our view that our overall program is focused on the larger BMHI, even though students and professionals work within specific areas of the field.

Before there were tracks in the program, the original focus of the program was in clinical informatics, which was originally called medical informatics. We prefer to call this portion of the program the clinical informatics track now, which indicates its broader focus beyond informatics related to the work of medical doctors. Clinical informatics includes other branches of healthcare and even areas beyond the healthcare system, such as consumer health informatics. The clinical informatics track of our program focuses on informatics delivered mainly at the level of individual, whether in the role of a patient or as a consumer outside of the healthcare system.

The second track of our program, the bioinformatics and computational biology (BCB) track, has more of a focus on informatics at cellular and molecular level. The term bioinformatics refers to a focus on genomics and related areas, while the computational biology term indicates a strong emphasis on computational methods.

We recently added a third track to the program, the health information management (HIM) track. There is actually substantial overlap between HIM and clinical informatics, recognizing that HIM is evolving from management of paper records to electronic records. HIM has a different history from informatics as a so-called allied health profession, but it is increasingly moving toward electronic data systems in healthcare, i.e., clinical informatics. Our HIM track is accredited by the Commission on the Accreditation of Health Informatics and Information Management (CAHIIM), and students completing the program are eligible to sit for the Registered Health Information Administrator (RHIA) credential.

One of the advantages of the system of tracks is the ability to add additional tracks. I would like to see us add in the future a track for public health informatics, which would certainly have overlap with the clinical informatics and probably the others as well.

The tracks in our programs offer various degrees and certificates. One degree offered by all of the tracks is the Master of Science (MS). This was the original degree offered by the program and is a traditional research master's degree, which culminates in a thesis. The clinical informatics and HIM tracks also offer a non-thesis master's degree, sometimes referred to as a professional master's degree, the Master of Biomedical Informatics (MBI). The MBI has the same curriculum as the MS but replaces the master's thesis with a less-intensive capstone project. We also allow the capstone project to be an internship experience where the student gains real-world experience in an operational setting, such as a healthcare organization or a company.

Perhaps one of the lesser understood credentials in our program is the Graduate Certificate, which is offered in the clinical informatics and HIM tracks. Unlike master's degrees (which actually vary greatly but represent a generally known quantity), certificates between and even within different fields vary substantially. In many disciplines, the term Graduate Certificate is coming to represent a graduate-level educational experience that is not quite as much as a master's degree. In some universities, a Graduate Certificate is part of a continuing education or professional development program, sometimes even distinct from the graduate program. In our program, the Graduate Certificate is properly viewed as a subset of our master's degree (even though the eight three-credit one-quarter courses are enough to be a master's degree in some institutions). Students in the Graduate Certificate program take the same courses as those in the master's degree, only fewer of them.

The Graduate Certificate was developed when we first started offering distance learning courses in what we then called medical informatics. We thought that many of the students in our program who already had doctoral degrees would not be interested in a whole master's degree. Over time we did find that some were interested in a master's degree, so eventually expanded the distance learning offerings to that level.

Our graduate program also offers a Doctor of Philosophy (PhD) program in the clinical informatics and BCB tracks. (In reality, someone in the HIM track could progress to the PhD level in the clinical informatics track.) Just as the Graduate Certificate is a subset of the master's degree program (for the clinical informatics and HIM tracks), the master's degree programs are in turn a subset of the PhD program. We call the master's curriculum within the PhD the knowledge base, to which students add advanced research courses and a dissertation.

Because the higher-level programs are supersets of the more basic programs, we call this the building-block model of our program, indicating that students can start at the entry level for a given track and potentially progress all the way to the PhD (if their career goals warrant). The following figure depicts the building-block model of the program.

We also offer fellowship programs at both the predoctoral (PhD student) and postdoctoral (those with a doctoral degree already, who usually pursue a master's degree as a fellow) levels. Those who are fellows are mostly funded by training grants and other scholarships. Our main training grant is funded by the National Library of Medicine (NLM), a institute within the National Institutes of Health (NIH). In some ways, the fellowship program is a form of financial aid, as except for the funding provided and a work area, we treat fellows no different from other students.

There is some additional jargon from our program to round out this discussion. One is the 10x10 ("ten by ten") course. The 10x10 course is a program we started in partnership with our professional association, the American Medical Informatics Association (AMIA), in 2005. Its name was based on an estimated need to train 10,000 physicians and nurses (one each in all of the 5000+ US hospitals) in informatics by the year 2010. Of course we encouraged others, even non-healthcare professionals, to enroll in the course. The reason for mentioning the course here is that its curriculum is identical to the introductory course in the OHSU clinical informatics and HIM track, BMI 510 - Introduction to Biomedical & Health Informatics. In fact, those who complete the 10x10 course (which is a continuing education course) can optionally take the BMI 510 final exam and, if they obtain a grade of B or better, receive credit for BMI 510 in our graduate program. About 30% of the 1300+ people who have completed the 10x10 course have done so, and many have gone to further courses in the program. In fact, because of the building-block model, some of have progressed up from the Graduate Certificate to the master's degree programs and in two cases all the way to the PhD program.

Another item of jargon is the clinical informatics subspecialty. This refers to the new subspecialty for physicians that was recognized by the American Board of Medical Specialties in 2011. While plans for the certification process and training programs are still under development, this will represent a career pathway for physicians that gives professional recognition for the work they do in informatics. Unlike any other subspecialty in medicine, it will be available to physicians from all primary specialties, such as Medicine, Surgery, Radiology, and Pathology.

I hope this post clarifies and demystifies some of the confusing jargon of the informatics field and the educational program at OHSU. There is no easy answer to simplifying all this terminology, since there are so many distinct paths and credentials within the field. The approach is to try to understand it all from a comprehensive framework like the one I laid out here.

Data Entry: An Under-Discussed Grand Challenge for Informatics

Everyone, including this blog writer, has been touting the virtues of the vast troves of data already or soon to be available in the electronic health record (EHR), which will usher in the learning healthcare system [1, 2]. There is sometimes unbridled enthusiasm that the data captured in clinical systems, perhaps combined with research data such as gene sequencing, will effortlessly provide us knowledge of what works in healthcare and how new treatments can be developed [3, 4]. The data is unstructured? No problem, just apply natural language processing [5].

I honestly share in this enthusiasm, but I also realize that it needs to be tempered, or at least given a dose of reality. In particular, we must remember that our great data analytics and algorithms will only get us so far. If we have poor underlying data, the analyses may end up misleading us. We must be careful for problems of data incompleteness and incorrectness.

There are all sorts of reasons for inadequate data in EHR systems. Probably the main one is that those who enter data, i.e., physicians and other clinicians, are usually doing so for reasons other than data analysis. I have often said that clinical documentation can be what stands between a busy clinician and going home for dinner, i.e., he or she has to finish charting before ending the work day.

I also know of many clinicians whose enthusiasm for entering correct and complete data is tempered by their view of the entry of it as a data blackhole. That is, they enter data in but never derive out its benefits. I like to think that most clinicians would relish the opportunity to look at aggregate views of their patients in their practices and/or be able to identify patients who are outliers in one measure or another. Yet a common complaint I hear from clinicians is that data capture priorities are more driven by the hospital or clinic trying to maximize their reimbursement than to aid clinicians in providing better patient care.

Another challenge for clinicians is the time required for electronic data entry. There is no question that the 20th century means of clinical documentation, mostly consisting of scribbling illegible notes on paper, was much easier and faster than typing and/or clicking. While I think that few clinicians want to go back to hand-written notes, there is an appeal of their ease of use, at least for the person doing the entry.

Related to the time for electronic data entry is the "tension" between structured data, which makes aggregation and analysis easier, and "flexible" (or narrative) data, which allows the clinician to tell the story of the patient [6]. Many clinicians report that excess structuring of data (i.e., pointing and clicking) loses the story of the patient, although those who process the data know that structured data is easier to analyze.

An additional challenge for electronic data entry for clinicians is the shift of the focus from the patient to the computer. This was exemplified in a cartoon published earlier this year in JAMA that showed a 7-year-old's sketch of an exam room with the physician hunched over the computer, his back turned away from the patient and her family [7] (the sketch viewable at http://jama.jamanetwork.com/article.aspx?articleid=1187932).

An excellent example of the promise but limitations of current data entry systems was recently documented by Parsons et al. [8], who found in a wide sample of primary care EHRs in New York City that the accuracy of data for measuring breast cancer screening quality measures was highly variable due to differing practices in documentation, workflow, and related factors. While some physicians had the quality of their care measured accurately, for many others it was underestimated due to data limitations and not the care they provided.

I cannot claim to have easy answers to this grand challenge, but two related aspects of it sit in front of us:

1. We need to find better and faster ways for clinicians to enter data into the EHR that allow data whose quality is good enough to be re-used for other purposes, such as research, quality measurement and improvement, and public health.
2. We must reward clinicians for their efforts in entering high-quality data. We must allow them to see aggregate views of patients in their practices and be able to identify outliers. We must also engage them in research, quality improvement, and other system uses of their data.

In short, the concept of "garbage in, garbage out" still remains a problem for computers and information technology nearly a half-century after it was coined. In healthcare, we must give clinicians the best tools and incentives for them to participate in the learning healthcare system. For informatics, the problem of data entry is a grand challenge every bit as important as how to make use of its growing quantity, since the knowledge derived from that data will only be as good as the quality of what is input.

References

1. Friedman, C., Wong, A., et al. (2010). Achieving a nationwide learning health system. Science Translational Medicine, 2(57): 57cm29. http://stm.sciencemag.org/content/2/57/57cm29.full.
2. Greene, S., Reid, R., et al. (2012). Implementing the learning health system: from concept to action. Annals of Internal Medicine, 157: 207-210.
3. McCarty, C., Chisholm, R., et al. (2010). The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Genomics, 4(1): 13. http://www.biomedcentral.com/1755-8794/4/13.
4. Rea, S., Pathak, J., et al. (2012). Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project. Journal of Biomedical Informatics, 45: 763-771.
5. Nadkarni, P., Ohno-Machado, L., et al. (2011). Natural language processing: an introduction. Journal of the American Medical Informatics Association, 18: 544-551.
6. Rosenbloom, S., Denny, J., 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.
7. Toll, E. (2012). The cost of technology. Journal of the American Medical Association, 307: 2497-2498.
8. Parsons, A., McCullough, C., et al. (2012). Validity of electronic health record-derived quality measurement for performance monitoring. Journal of the American Medical Informatics Association, 19: 604-609.

The Internationalization of 10x10

One of the most gratifying aspects of my work in informatics has been its international acceptance. I also enjoy my interactions with international colleagues, both professionally and personally. In addition, I obtain great satisfaction interacting internationally with students, whether they study under myself or others. All told, I enjoy making contributions that are known and valued around the entire world.

As I have written before, I have come to learn that many of the problems faced by informatics are global in nature, i.e., not unique to the United States. All who work in healthcare, public health, and research face challenges in collecting, organizing, and making best use of data and information. All types of information systems present challenges to workflow, usability, and value, among other things.

In recent years, one of my major collaborations has been with colleagues in South America, particularly in Argentina. One of these activities has been for them to translate my well-known 10x10 ("ten by ten") course into Spanish. They have offered the course all across Latin America, with nearly 1000 having completed it. The Spanish 10x10 course uses the same basic approach as my original course, consisting of a series of online units with an in-person session where students meet, learn more together, and/or present projects. While the original version of the Spanish course was a close translation of the English one, the content has now evolved to take on a more Latin American perspective. The core informatics issues are still global, but there are some regional differences, e.g., no delving into the details of HIPAA!

I am pleased to report that the collaboration with Argentina and its translation of the 10x10 course into Spanish has now come full circle, in that the Spanish course has made its way back to the United States via Puerto Rico. As Puerto Rico is fully eligible for funding through the HITECH programs, it has made efforts to help its eligible professionals and hospitals achieve meaningful use of electronic health records. One aspect of this has been the establishment of a regional extension center (REC), the Ponce School of Medicine REC (PSMREC). One of the activities of the PSMREC has been to bring informatics education to clinicians, and it has done this by engaging my Spanish-speaking colleagues and their version of 10x10 to create a new instance of the course, Certificado en Informática Médica para Puerto Rico. The course organizers invited me to participate in their in-person session in San Juan to kick off the course. I spent an enjoyable day with faculty and students, giving talks on the HITECH program as well as the secondary use of clinical data. I was also impressed with the backgrounds of the students taking the course, representing leaders from the REC, academic institutions, healthcare organizations, and others. It is always gratifying as an educator to help those you teach make a difference, which I am certain will happen in this course and what follows in Puerto Rico.

Another active collaboration involving the 10x10 course is in Singapore, with my colleague Dr. KC Lun of Gateway Consulting and the National University of Singapore. This offering of 10x10 uses my English version of the course, with my traveling to Singapore for the end-of-course in-person session. A total of 126 people have completed six offerings of the course over the last several years, with a seventh slated to start this month. I have enjoyed this offering of the course, both through the various people I have met in the Singapore healthcare community as well as the chance to learn about the Singapore healthcare system, which delivers high-quality care at about one-half the per-capita cost of the US.

I also remain active internationally in a number of other ways. I have served for six years as Chair of the Health and Medical Informatics Education Working Group of the International Medical Informatics Association (IMIA). I am a member of the Editorial Board of the International Journal of Medical Informatics. I serve on a number of institutional advisory committees in Europe, Asia, and Africa.

I cannot deny that being able to travel to many of these places has been one of the best perks of my job. Although the real beauty of this travel is that I do not just visit these places as a detached tourist. Rather, I enjoy being welcomed into the work and even home environments of my colleagues. I value seeing firsthand the informatics-related work that they do. I look forward to continuing my work with all of them.

Accolades for the Informatics Professor: Update

As readers of this blog know, I periodically point to other places on the Web where the Informatics Professor has been mentioned or honored. One recent accolade is an article in the magazine, For the Record, describing the recent update to the ONC Health IT Curriculum. I also wrote another article myself for HIMSS Clinical Informatics Insights, a perspective piece about the entire ONC Health IT Workforce Program.

Another accolade is being asked to serve on the (get ready for a mouthful!) Workforce Subgroup of the Certification and Adoption Workgroup of the ONC Health IT Policy Committee. The Health IT Policy Committee sets policy for ONC initiatives, including implementation of meaningful use. The Certification and Adoption Workgroup is tasked with making recommendations "on issues related to the adoption of certified electronic health records that support meaningful use, including issues related to certification, health information extension centers and workforce training." The Workforce Subgroup on which I will be serving is tasked with making "recommendations to the Health IT Policy Committee on ways to provide health IT education to all health care workers."

An additional accolade I have received is being elected as a Fellow of the American College of Medical Informatimusicology (ACMImimi). This honor is bestowed upon those who "see the perfect harmony found in combining healthcare, information technology and music" and manifest it by performing music in a public setting, in my case a recent rendition of some Neil Young songs at the National Library of Medicine Trainees meeting in Madison, Wisconsin on June 26, 2012.

ACMImimi is run by Ross Martin, MD, MHA, an accomplished informatician in many ways, but perhaps most distinctive by his making informatics concepts, especially the HITECH program, accessible via music. I have steered students in recent years to some of his most entertaining and educational pieces:
HITECH: An Interoperetta in Three Acts
The Meaningful Yoose Rap

MOOCs Coming to Informatics?

A few months ago, I wrote a post about the new development of massive open online courses (MOOCs) and what disruptive innovation they might have on higher education. While noting that academic biomedical and health informatics sat at the intersection of the two industries having the least amount of disruptive innovation - healthcare and higher education - I did note that MOOCs could have an impact, if they ever came to our field.

Well now they have, and it turns out that one of my projects is playing a major role in their development. The Health Informatics Forum, an international blogging and social network site for informatics, has started to turn the entire ONC Health IT Curriculum into a MOOC. They recently posted Unit 1 of Component 1 on their site, with announcement of plans to add a new component every four weeks.

How successful will this effort be? There will certainly be value in providing learning materials to the entire world. But there are some caveats. First, as those of us in the ONC Health IT Curriculum project have noted, the materials are designed more for educators than learners. While they provide a rich amount of learning substrate, like all good education they require more, including a teacher, a structured learning process, and ideally fellow learners. In addition, any professional educational experience also requires a connection to the real world through practical opportunities, such as internships. Furthermore, in any rapidly changing field, such as health IT and informatics, the curricular materials must be regularly updated and otherwise improved. It will be interesting to see how sites like The Health Informatics Forum address this latter challenge, particularly as the field evolves. (For example, the Stage 2 meaningful use rules as well as new HIPAA regulations are due out in the next few weeks. As of now, neither of these are covered in the ONC curriculum.)

One final caveat is that the total quantity of these materials represent about 20 college-level courses. This means that any one person will require a great deal of time and effort to work through all of them. By the same token, there are a number of advanced informatics topics that are not covered by the ONC curriculum, such as secondary use of data, natural language processing, and analytics, to name a few. Still, I will be eager to see how this all works out, and hope to lend my expertise to increase its likelihood of success.

It turns out that The Health Informatics Forum is not the only organization that has utilized the totality of the ONC materials as a large learning experience. Two other organizations have done this as well, one of which charges a fee, which is allowable under the Creative Commons license under which the materials have been released:

• http://www.vcn.org/healthcare/online-courses/hit
• http://education.ehrtrainingacademy.com/course/category.php?id=24

The discussion around MOOCs also continues to flourish in the press. The New York Times has run a series of articles, mostly focused on the two efforts led by Stanford (Coursera) and Harvard/MIT (edX) but now expanding to include other universities in their partnerships. This has included articles about the expansion of Coursera as well as the the early experiences of Coursera and edX and one call for caution:

• Expansion of Coursera
• Early experience of Coursera
• Early experience of edX
• One professor's concern about the impersonal aspects of online learning - I actually disagree that online courses need to be impersonal, but I do agree there is no better form of education that the close interaction between the teacher and learner.

It is still too early to tell how these efforts will fare, and what their impact will be on higher education. As one who has been teaching online for 13 years, I can say that learning is very possible, and often desirable, especially when the learner is separated from the learning experience by distance or time. We have many students in our distance learning program at Oregon Health & Science University (OHSU) who desire our education but live far from Oregon and/or work during the time that on-campus classes are offered. In fact, we have a number of "local distance" who live in the area but value the convenience of the online classes.

But our courses at OHSU are anything but MOOCs. They feature direct interaction from our faculty. Furthermore, students can participate in and get credit from structured practicum and internship experiences. This leads one to wonder whether MOOCs might become a means to deliver higher education rather than complete experience in and of themselves. Nonetheless, it will be interesting to see the outcome of this natural experiment in education.

Mapping the AMIA Clinical Informatics Core Content into the OHSU Biomedical Informatics Curriculum

One of the most exciting developments in the clinical informatics field in recent years has been its designation as a new medical subspecialty. Even if one is not a physician, the professional recognition of the work of clinical informatics is important. Hopefully we will see others who work professionally in informatics achieve comparable professional recognition. Indeed, AMIA has established an Advanced Interprofessional Informatics Certification Task Force to explore the best approaches for certification of non-physician informaticians.

Another valuable outcome of the clinical informatics certification process was the development of the core content for the clinical informatics subspecialty (Gardner, R., Overhage, J., et al. (2009). Core content for the subspecialty of clinical informatics. Journal of the American Medical Informatics Association, 16: 153-157. http://jamia.bmj.com/content/16/2/153.full.pdf+html.). This content is by no means limited to physicians and should serve as the basis for the curricular content for all clinical informatics programs.

We recently undertook an analysis of the curricular content in our Biomedical Informatics Graduate Program at Oregon Health & Science University (OHSU) to see how our existing courses mapped into the AMIA core content. We were pleased to discover that just about everything in it is covered by one or more courses in our master's degree program. We are planning to undertake a more detailed analysis in the future to make sure our curricular materials are covered adequately and reflect the most state-of-the-art content. But in the meantime, I am pleased to report that we will be ready to provide education for certification in the field when such programs are ready to be launched. The results of this analysis can be viewed in this PDF file.