Witness to a Great Public Health Informatics Achievement

Last week, I had the opportunity to participate in a ceremony at the Centers for Disease Control and Prevention (CDC) announcing their Public Health Informatics Fellowship being recognized as a Registered Apprenticeship by the Department of Labor (DOL). This potentially sets the stage for public health informaticians to become a DOL standard occupational code, which means they would appear in DOL labor statistics. This is good news, and hopefully will lead to DOL recognizing other types of informaticians in their statistics.

I went to the meeting to represent AMIA, and had a chance to deliver these remarks:

My name is Dr. William Hersh, and I am Professor and Chair of the Department of Medical Informatics & Clinical Epidemiology at Oregon Health & Science University in Portland, Oregon. I attend this meeting representing the 4000 members of the American Medical Informatics Association (AMIA), the professional society for health-related informatics, and bring words from our President and CEO, Dr. Kevin Fickenscher, who unfortunately could not be here today.

Today, AMIA recognizes the tremendous accomplishment of the CDC’s Scientific Education and Professional Development Program Office in their collaboration with the Department of Labor. The establishment of CDC’s Public Health Informatics Fellowship Program (PHIFP) as a Department of Labor (DOL) Registered Apprenticeship and the laying of the foundation for a standard occupation code for public health informaticians represent a very significant milestone in the decade-long effort by AMIA and its members and leaders to address the crucial issues of informatics workforce development.

The mere fact that the Department of Labor may soon give informaticians a workforce code is very encouraging.  The designation will help the nation realize its ambitions for supporting a fully-interoperable, data-driven learning healthcare system.  Key to this ambition are informaticians of all stripes, not only public health but also clinical, nursing, and even bioinformatics.

In 2001, I and more than 400 AMIA member experts and thought leaders gathered for the organization’s Spring Congress meeting here in Atlanta to develop a national agenda for public health informatics. The resulting 74 recommendations emerged with themes reflected in the CDC/DOL’s decision. Our stakeholders recognized the need to be engaged in coordinated activities related to public health information. They also forecasted the need for informatics training throughout the public health workforce.

A decade later, AMIA experts revisited the national agenda at the 2011 Spring Congress meeting, where we came up with recommendations supporting the need for informatics workforce development and underlining informatics crucial role in the future of public health and healthcare.

Many of us in AMIA are involved in complementary efforts in workforce development in other areas of informatics. I myself have had the opportunity over the last two years to play key roles in the health IT workforce development programs of the Office of the National Coordinator for Health IT, both training professionals in clinical informatics as well as developing the national health IT curriculum focused initially on community college programs but now freely available to the entire world.

Public health informatics is embedded in these efforts, as those in clinical informatics must comprehend how the public health system can benefit from our federal investment in adoption and meaningful use of electronic health records. This is exemplified at my institution, OHSU, where a CDC public health fellowship graduate serves on our faculty and teaches a course in public health informatics to a predominantly clinical informatics student body.

AMIA members will continue to lead the national discussion on informatics workforce development and on what is needed on the front lines of public health. Together with leadership from the federal government, NGOs, public health organizations, associations and specialty societies and business we know informatics professions will grow.  We are encouraged that the CDC/DOL’s ‘public health informaticians’ designation can open the door for other informatics-related designations to follow.

Informatics Professor Elsewhere on the Web

I have had the opportunity to have my blog-related work featured elsewhere on the Web. Some of these sites get more traffic than my own blog.

One site where I have been having edited versions of my blog posts re-posted is HITECH Answers. All of the postings can be found by searching on the tag assigned to them indicating they are from me. HITECH Answers also features a radio show called MULive, where I was the guest on April 3, 2012. (The audio archive of the show can be accessed by registering or going straight to audio link.)

Another site re-posting some of my blog entries of pertinence to internal medicine physicians is the American College of Physicians. Some of my postings are available on ACP Internist, aimed at all internists, while others are available on ACP Hospitalist, aimed at hospitalist physicians.

Postscript: Shortly after this entry was posted, Dr. Kevin Fickenscher, new President and CEO of AMIA, called out a recent posting of mine.

From Implementation to Analytics: The Future Work of Informatics

I am occasionally asked whether the work of informatics will be "done" when everyone is finishing implementing electronic health record (EHR) systems. Sometimes the query is further qualified by, "once everyone gets their HITECH money."

My answer is always an emphatic "No!" There is no question that some informatics implementation activity may slow down when healthcare organizations are no longer fueled by pursuit of HITECH incentive dollars. These activities may be impacted even further by bottom line woes that are likely to impact healthcare no matter what the outcome of healthcare reform, or whatever other distractions come along, such as ICD-10.

I often further qualify my answer by noting that for many of us, the real interesting work of informatics begins when the EHR platform is in place and we can truly start to do interesting things with the data. These are the so-called "secondary uses" or "reuses" of clinical data [1], things like quality measurement and improvement, improved clinical research, or indeed the "learning health system" first envisioned by the Institute of Medicine [2] and put in the context of the HITECH investment by Friedman et al. [3]. Some call this the "optimization" stage of EHR implementation [4].

One buzzword that is used increasingly in healthcare (and was already in use outside of healthcare over the last few years) is analytics. As with all buzzwords, there is a copious volume of material that has been written. I find a couple books by Tom Davenport and associates [5, 6] to provide good overviews. Davenport is Research Director for a company in Portland called the International Institute for Analytics. A recent primer by The Advisory Board Company, a healthcare consulting firm, gives a good overview of analytics in the context of healthcare [7].  Another recent report comes from PwC, which paints a similar picture of the near future, although (to my content!) describes this as clinical informatics (rather than analytics) [8], The phrase business intelligence is sometimes used to describe this work, and I suspect we will see another phrase, big data, appearing more frequently, especially with the recent Obama Administration initiative in this area [9].

The Advisory Board Company primer nicely paints an overview of the use of analytics and business intelligence in healthcare. They distinguish between different uses of the data, each requiring a higher level of analysis and complexity:

• Descriptive - reporting and querying of data to identify problems and solutions
• Predictive - modeling, forecasting, and simulating outcomes based on the data
• Prescriptive - recommend the best course of action based on the data

Of course, those of us who work in clinical informatics know that gleaning value from clinical data is challenging. Indeed, those who have learned from implementation in the trenches may be best qualified to understand the limitations of their data. As I often say, documentation is not usually the highest priority for busy clinicians. Indeed, it is often what stands between a tired clinician at the end of the day and being able to go home for dinner. Clinical data also suffers from the lack of standards in structure and terminology of data, and it is often fragmented across different systems, both within and across different healthcare organizations.

Nonetheless, the growing platform of electronic clinical data, fueled initially by EHR adoption and now augmented by efforts at health information exchange in the proposed rules for Stage 2 of meaningful use, point the way forward [10]. Regardless of one's political views of healthcare reform, it is clear that the system needs to change to become more accountable and efficient. This will be drawn out with the move to new delivery systems, such as accountable care organizations [11]. Thus, analytics and related activities are the future of clinical informatics, realizing the goal of my definition of the field, which is the use of information to improve individual health, healthcare, public health, and biomedical research [12].

References

[1] Safran, C., Bloomrosen, M., et al. (2007). Toward a national framework for the secondary use of health data: an American Medical Informatics Association white paper. Journal of the American Medical Informatics Association, 14: 1-9.

[2] Olsen, L., Aisner, D., et al., eds. (2007). The Learning Healthcare System - Workshop Summary. Washington, DC. National Academies Press.

[3] 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.

[4] Walker, J., Richards, F., et al., eds. (2006). Implementing an Electronic Health Record System New York, NY. Springer.

[5] Davenport, T. and Harris, J. (2007). Competing on Analytics : The New Science of Winning. Cambridge, MA. Harvard Business School Press.

[6] Davenport, T., Harris, J., et al. (2010). Analytics at Work: Smarter Decisions, Better Results. Cambridge, MA. Harvard Business Review Press.

[7] Adams, J. and Klein, J. (2011). Business Intelligence and Analytics in Health Care - A Primer. Washington, DC, The Advisory Board Company. http://www.advisory.com/Research/IT-Strategy-Council/Research-Notes/2011/Business-Intelligence-and-Analytics-in-Health-Care.

[8] Anonymous (2012). Needles in a haystack: Seeking knowledge with clinical informatics, PriceWaterhouseCoopers. http://www.pwc.com/us/en/health-industries/publications/needles-in-a-haystack.jhtml.

[9] Anonymous (2012). Obama Administration Unveils “Big Data” Initiative: Announces $200 Million in New R&D Investments. Washington, DC, White House. http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf.

[10] Copoulos, M., Raiford, R., et al. (2012). The Next Chapter - First Look at the Proposed Rule on Stage 2 of Meaningful Use. Washington, DC, The Advisory Board Company. http://www.advisory.com/Research/IT-Strategy-Council/Research-Notes/2012/~/media/Advisory-com/Research/ITSC/Research-Notes/2012/The-Next-Chapter-Stage-2.pdf.

[11] Fisher, E., McClellan, M., et al. (2011). Building the path to accountable care. New England Journal of Medicine, 365: 2445-2447.

[12] Hersh, W. (2009). A stimulus to define informatics and health information technology. BMC Medical Informatics & Decision Making, 9: 24. http://www.biomedcentral.com/1472-6947/9/24/.