What is the Evidence Base for Informatics, Health IT, and Related Areas? Some Recent Analyses

The first part of 2011 has brought a number of publications, and subsequent discussion, about the "evidence base" for the efficacy of biomedical and health informatics interventions, including electronic health records. These publications and conversations come against a backdrop of a very poisoned political environment in the United States, where everything about healthcare, including informatics, has become unfortunately very politicized. In this posting, however, I will stick to the science.

The first high-profile study of the year was the on-line posting of the Archives of Internal Medicine paper by Romano and Stafford [1], which I discussed in an earlier posting. The official publication of the paper, as well as letters about it, will be published in May, 2011.

Probably the next most high-profile study was the publication of an update of a systematic review of studies of outcomes from health information technology interventions by Buntin and colleagues [2]. This was actually the second update of an original systematic review that was published in 2006 by Chaudhry and associates [3], the first update of which was published by Goldzweig and colleagues in 2009 [4].

Systematic reviews are comprehensive reviews of all research evidence on a given area or question [5]. When studies are homogeneous enough (e.g., all studies assessing the treatment of hypertension to reduce cardiovascular disease), a mathematical technique known as meta-analysis can be performed to combine results across studies to achieve larger a sample size and more statistical power. But most areas, certainly so in informatics, have research questions too heterogeneous to enable use of meta-analysis. Nonetheless, studies can be categorized to look at general questions asked, such as efficacy of decision support to reduce medical error or access to data in a more timely manner to reduce cost of care.

The three successive systematic reviews [2-4] using relatively similar methodology have summarized outcomes of studies of health information technology (HIT) over particular time periods:

• Chaudhry, 2006 – studies from 1995-2004 [3]
• Goldzweig, 2009 – studies from 2004-2007 [4]
• Buntin, 2011 – studies from 2007-2010 [2]

As with most systematic reviews, these captured a broad net of literature and reviewed it for quality of methodology and its results.

Chaudhry et al. identified 257 studies, with the most benefit shown for:

• Adherence to guideline-based care
• Enhanced surveillance and monitoring
• Decreased medical errors

An interesting caveat of the results that the authors noted was that 25% of the identified studies came from four institutions (Partners Healthcare, Veteran's Administration, Indiana University/Regenstrief Institute, and Vanderbilt University) and there were few studies of commercial systems, raising concerns about generalizability.

In their update, Goldzweig et al. found 179 new studies. They noted comparable results to the study of Chaudhry et al., but also found an increased number of studies of patient-focused applications that ran external to EHR, e.g., Web-based care management. They note a small increase in the number of studies of commercial, off-the-shelf systems, though 20% of studies still came from the four leading institutions. They also found there was still a paucity of cost-benefit analyses.

In the new systematic review, Buntin et al. identified 154 new studies with 278 individual outcome measures. While acknowledging wide divergence of study quality and methodologies, not to mention outcomes studied, they noted that 96 (62%) of studies had positive improvement in one or more aspects of care, with 142 (92%) showing positive or mixed positive-negative outcomes. They found that the studies used quantitative and qualitative approaches, with those using statistical hypothesis testing more likely to have positive outcomes. They slightly redefined “health IT leader” institutions, but noted that a large number (28) still came from these institutions, but did decreased somewhat to 18% of the studies. Somewhat reassuring  was that the “leader” studies did not differ in methods or results from the other studies.

Buntin et al. grouped the outcomes into seven categories, noting document improvement in all of them:

• Access to care
• Preventive care
• Care process
• Patient satisfaction
• Provider satisfaction
• Effectiveness of care
• Efficiency of care

Another bit of evidence from early 2011 was a review of all eHealth systematic reviews took exception to direction and quality of evidence [6]. The authors note that many studies of eHealth, including clinical applications (i.e., health IT), had poor methodology, raising concern over validity of the results. The results echo those of a systematic review I led about telemedicine studies several years ago [7]. One concern about this new review is that its methodology of being a review of reviews might magnify poor evidence. But someone needs to reconcile this review with the one of Buntin et al. [2].

It should be noted that another line of thought has been critical of the experimental approach to evaluation of health IT. Two recent commentaries note that these approaches cannot capture the whole picture of a health IT intervention, especially ones that occur in real-world implementations in complex settings, like states or even whole countries [8, 9]. I acknowledge these criticisms, though would argue back that we should not view these approaches as either-or. There is hopefully plenty of room for all types of disciplined evaluation of informatics, with clinical trials and similar experiments

References

1. Romano, M. and Stafford, R. (2011). Electronic health records and clinical decision support systems: impact on national ambulatory care quality. Archives of Internal Medicine, Epub ahead of print.
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. Goldzweig, C., Towfigh, A., et al. (2009). Costs and benefits of health information technology: new trends from the literature. Health Affairs, 28: w282-w293.
4. 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.
5. Anonymous (2011). Finding What Works in Health Care: Standards for Systematic Reviews. Washington, DC, Institute of Medicine.
6. Black, A., Car, J., et al. (2011). The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Medicine, 8(1): e1000387.
7. Hersh, W., Hickam, D., et al. (2006). Diagnosis, access, and outcomes: update of a systematic review on telemedicine services. Journal of Telemedicine & Telecare, 12(Supp 2): 3-31.
8. Greenhalgh, T. and Russell, J. (2010). Why do evaluations of eHealth programs fail? An alternative set of guiding principles. PLoS Medicine, 7(11): e1000360.
9. Patrick, J. (2011). The validity of personal experiences in evaluating HIT. Applied Clinical Informatics, 1: 462-465.

PCAST Report: What's the Big Deal?

As anyone who works in informatics knows, there is unremitting stream of reports, white papers, blog entries, and other writings from various government agencies, non-profit organizations, consultants, research organizations, and others involved in health information technology (HIT). Some of these reports promote various points of view, including policy directions, while others present interesting ideas to read. (Some do neither!)

One recent report has garnered more attention than any in the last several months (perhaps since the release of the meaningful use rules). This is of course the recent report from the President's Council of Advisors on Science and Technology (PCAST) entitled, Realizing the Full Potential of Health Information Technology to Improve Healthcare for Americans: The Path Forward, which was released in December, 2010. This report, called the “PCAST report” by many, has gained high visibility, perhaps reflecting its origin from the White House. It has led the Office of National Coordinator for HIT (ONC) to ask its HIT Policy Committee to create a workgroup tasked with collecting and analyzing public comments and making recommendations relative to current and future ONC activities.

The report states its case by noting that current HIT systems do not meet their potential, mainly due to the lack of interoperability that results from proprietary data stores (mostly in proprietary systems) that blunt the free flow of data. This is hardly new. The report goes on to advocate what it views as the critical solution to the problem, which is the development of a “universal exchange language” (abbreviated by some though not in the report as “UEL”) based on the notion of data elements being reduced to their atomic core. It advocates that each of these core elements have metadata (“data about data”) tagging that includes the element and its value along with an identity of the patient, a patient-controlled privacy designation, and other provenance information about the element.

The report has certainly generated a great deal of discussion, with most of the major organizations involved in HIT having weighed in during the ONC comment period. The report certainly piqued my interest, since I have always held the view that data is the most critical aspect of everything we do with HIT. I agree with Dr. Blumenthal that data is the “lifeblood” of medicine, and my informatics nirvana consists of data freely flowing between systems and the appropriately authorized people to use it. In my dream world, one could be in one EHR and “Save as…” the data for loading into another EHR or some other application. The data would be so interoperable that any application would recognize documents (e.g., discharge summaries or progress notes), measurements (e.g., vital signs or lab values, and structure data (e.g., prescriptions).

So where does PCAST fit into all of this? In this posting, I will review the PCAST Report, summarize the commentary and criticisms, and give my own further analysis to get others thinking (as a good educator should!).

The report begins with the usual accolades for how HIT has the potential to transform healthcare. In addition to the usual improving clinician access to patient data and decision support, involving patients in their care, and enabling public health and clinical research, the report also notes that HIT can create new markets and jobs for technology as well as support healthcare reforms, including economic changes in the system. It lays out nine use cases that benefit patients, clinicians, public health, and clinical research.

However, the report notes, HIT has fallen short of its promise for four reasons. First, most current systems are proprietary applications not easily adapted into clinical workflow, with proprietary data formats not easily exchangeable. Data is not easily disaggregated or re-aggregated. Second, most healthcare organizations focus on the internal value of EHRs and have no incentive for secondary or external uses of their data for patients, other healthcare organizations, public health, or research. A third reason is that patients have concerns about the privacy and security of information of their data. Finally, the report notes that HIT has been largely focused toward administrative functions and not on improving healthcare.

The UEL will require a common infrastructure for locating and assembling data elements of a patient’s records via secure data element access services (DEAS). Data would remain local, and DEAS would be distributed, intercommunicating, and interoperable. A single appropriately authorized query would be able to locate and assemble a patient’s record across multiple DEAS.

The essential core of the report is Chapters 4-5 (pp. 39-52), which deal with the core of the technology and privacy. Chapter 4 asserts that the approach of applications as “services” does not scale up. (Though the authors seem to violate the notion of separating the application and the data.) It is argued that a better approach for healthcare data is the UEL, which is coded in (eXtensible Mark-up Language) XML and tagged with three metadata elements (in addition to the data and its value):

• Identifying information about patient – including information enabling location of the data (not necessarily a universal identifier)
• Privacy protection information – who may access the data, for what purposes, and either in an identified or de-identified state
• Provenance of data – date, time, equipment used to collect data, personnel who collected it, etc.

The UEL would aim for semantic interoperability. While adherence to specific controlled terminology sets would not be required, it would be strongly encouraged. This would allow over time for data to truly be represented in a universal way.

DEAS activities would include “crawling, indexing, security, identity, authentication, authorization, and privacy.” Queries would be issued against all DEAS on the Internet, and results could be re-constituted into a complete picture of patient. Governments, healthcare organizations, and others would operate the DEAS. In some way, this process would act like Web search engines, although they would need to have very high recall and precision to insure all the appropriate data was retrieved, while incorrect data was not. In conclusion, the chapter claims the UEL is extensible, extractable by middleware, and will lead to innovative uses and applications.

Chapter 5 lays out the privacy and security aspects of the UEL and DEAS. In essence, each and every data element would have a patient-controlled privacy attribute, allowing access to the element and its use in identified or de-identified scenarios. All data would be encrypted, which would not only protect security, but also insert a mechanism to audit access.

A number of leading HIT organizations took the opportunity of the ONC comment period to state their positions. While all applauded the raising of awareness of issues related to data and its interoperability, they also raised a number of criticisms. Many advocated that the PCAST Report serve as a broader vision rather than holding concrete solutions.

The comments about the report can be summarized as follows:

1. The constellation of current standards, as imperfect as they are, meet many of the data-related goals laid out by the report.
2. Many of the ideas of the report, while interesting and worthy of further research, are untested. Having them be the drivers of Stage 2 of meaningful use would be a substantial change in direction and put the larger HITECH Program at risk.
3. Clinical data has context, and reducing its entirety to atomic elements has the potential to lose that context. Re-constituting it may not be possible if that context is lost.
4. Much of the context in clinical data requires that records be more document-centric or at least structured in groups of elements. Disaggregating documents could lose the context they provide.
5. While everyone agrees that structured data is most desirable, some data in healthcare is too nuanced, and unstructured text is required to describe it.
6. While industry-wide standards are important, no industry with data as complex as healthcare has tried an approach like this.
7. The notion of setting privacy at the individual element is highly problematic. Allowing the patient to choose which elements can be seen or not seen by clinicians, researchers, or others could introduce many unintended consequences. It would be preferable for the patient to specify general privacy policies that are then referenced by the data elements.
8. Patients’ views of privacy may change over time, as diseases change and their own disease course changes.
9. Search engines are imperfect. The DEAS would need to operate at high levels of recall and precision that are unprecedented for Internet-based search mechanisms.
10. While the report correctly notes that current HIE efforts are struggling, it ignores that major reasons for this, which have more to do with the lack of a business model for HIE than anything about the technology.

A number of specific comments from these organizations are poignant:

• American Hospital Association (AHA) - The report should set a broader vision rather than focus on concrete solutions. Setting privacy at element level could fracture the patient record. Tagging each piece of data could be costly and inefficient. DEAS are likely to face same challenges as HIEs, with lack of a business model. ONC should change policy direction for Stage 2 of meaningful use only with great caution.
• Radiological Society of North America (RSNA)/American College of Radiology (ACR) - Echoed many of the same comments and noted we need a uniform method to manage patient identity.
• Integrating the Healthcare Enterprise (IHE) USA - Noted that the current IHE profiles cover most of the functionality required for the 9 use cases.
• Healthcare Information and Management Systems Society (HIMSS) -Privacy is contextual and changing, especially as diseases change and information about them becomes less sensitive. Encryption of the data elements provides security and an audit trail but can adversely impact workflow. The objectives of the report might not be possible without a universal patient identifier. By atomizing data, we run risk of data becoming dissociated and not being able to detect errors, so any grouping in the source data should be maintained. Metadata tagging should be virtual and not physical. Tags should be referenced and not attached, since some (e.g., privacy) might change over time. Data elements separated from documents and records potentially robs them of their context.
• HIMSS Electronic Health Record Association (EHRA) -It is better to tag data on document or record level. The privacy approach is potentially unworkable. A large-scale effort of this approach is untested.
• AMIA - Chapter 4 provides general ideas but no details nor references. There is no evidence that this approach will lead to improved care. The report was for the most part silent about other federal agencies, especially the National Library of Medicine, which has great expertise in some aspects of the proposed approach, especially related to terminology development and usage. The report underestimates the complexity of modeling the domain of medicine. It ignores past failed efforts along similar lines, such as the caBIG caDSR project. The DEAS may not be scalable or practical. ONC should not deviate from already tight timeline of Stage 2 of meaningful use. We can learn lessons from the slow adoption of HL7 Version 3, which is not suited to efficient description of task information models. There is too much focus on healthcare and not enough on health.

Other organizations that weighed included:

• HL7
• Federation of American Hospitals (FAH)
• Center for Democracy in Technology
• Project HealthDesign
• Markle Foundation
• Clinical Groupware Collaborative
• Faster Cures
• Society for Participatory Medicine
  

And of course, a number of bloggers had things to say. As always, John Halamka provided great early summaries of the report and the deliberations of the ONC HIT Policy Committee:
http://geekdoctor.blogspot.com/2010/12/spirit-of-pcast.html
http://geekdoctor.blogspot.com/2011/01/primer-on-xml-rdf-json-and-metadata.html
http://geekdoctor.blogspot.com/2011/01/example-for-pcast.html
http://geekdoctor.blogspot.com/2011/01/general-principles-of-universal.html

In a widely cited posting, Wes Rishel noted some critical points: Information flow for patient care occurs at the level of documents. Taking elements out of larger context can lose context. PCAST data elements are actually molecules, not atoms. There are plenty of molecule definitions, these should be used. Another well-known blogger, Keith Boone, added that a good deal of what the report hopes to accomplish can be done with existing standards.

What will be the impact of the PCAST report? We will find out for sure in April when the ONC releases its analysis and plans for incorporating the report’s ideas and proposals. If nothing else, the report has led to increased discussion about the importance of data interoperability, which even its critics applaud. My hope is that there is at least an acceleration toward the vision of interoperable data that most in informatics share.

Some Supplemental Information from the PCAST Report

The nine use cases were lumped into three categories based upon to whom they provided value.

Value to patients:

• Patient on warfarin wanting to know if it is safe to take an NSAID drug for an injury.
• Woman with lung mass newly discovered in a community hospital referred to a large academic medical center.

Value to clinicians:

• Internist developing primary care medical home.
• Small practice with clinicians sharing records and communicating with patients via email.
• Cardiology clinics in a part of country collaborating to improve care for patients with recent myocardial infarction.
• Family physician embedding alerts in practice to improve preventive care.

Value to research and public health:

• Physician caring for a patient enrolled in a national clinical trial.
• FDA carrying out post-marketing surveillance of adverse reactions to drugs.
• Communities or states measuring improvement toward health goals.

The final published conclusions of the report were:

1. HHS and ONC have laid a foundation for progress under meaningful use and HITECH.
2. Achievement of goals for healthcare involves accelerated progress toward robust health information exchange.
3. Effort should now focus on development of a universal exchange language that enables data to be shared and re-assembled across institutions, subject to strong privacy safeguards based on patient privacy preferences.
4. Creating these requirements is technically feasible.
5. ONC should move rapidly to develop these capabilities for stages 2 and 3 of meaningful use.
6. CMS should modernize and restructure its IT platforms to serve as a driver for progress in health IT.

Health IT Destination: Portland and Oregon

For several years, I have advocated that the city of Portland and state of Oregon have the necessary ingredients to develop an industry cluster in health and biomedical information technology (IT). I expounded this vision in an Op-Ed piece in the Oregonian in 2008 and in the Silicon Forest blog in 2009.

Some recent happenings in the area make this vision more compelling. First comes news that is not directly related to biomedical informatics but is relevant to the currently beleaguered Oregon economy. This is the plan announced by Intel, one of our major local high-tech employers, to invest several billion dollars in renovating existing production centers and building a new research and development center. This is good news for the local economy due to the promise of high-skill, high-paying jobs. This is synergistic with other local development efforts, including those led by the Portland Development Commission to advance software as one of the four areas it identifies as a key cluster for economic development.

There are also specific instances of highly visible health IT companies, such as Kyrptiq, which just received some investment from the large national e-prescribing company, Surescripts. Oregon also has the cache of a strong open-source software community and the surrounding business activity to make it sustainable, not only generally but also specifically in health and healthcare. A local company that exemplifies this approach is the Collaborative Software Initiative, with its focus on public health.

I have always argued that Oregon is a potential hub for health and biomedical IT because of the confluence of strong industry, innovation in the healthcare delivery sector (Oregon is one of those "high quality, low cost" states), and the presence of a world-class academic program in biomedical and health informatics. I believe that these attributes can combine synergistically to foster economic development, improve the quality of people's health, and provide leadership and innovation in health and biomedical IT.

One encouraging recent happening is the publication of a draft report for comments calling for Portland State University (PSU) and Oregon Health & Science University (OHSU) to expand their collaboration by developing a formal strategic alliance. The report explicitly calls out the potential for developing joint programs in biomedical and health informatics.

There are other cities and regions that aspire to leadership in this area. The city of Atlanta recently published a gloss on its being an "epicenter" of health IT. The larger healthcare entrepreneurship scene in Nashville also includes a component of health IT. I hope the leaders in Portland and Oregon will share this vision.

The Health IT Holding Pattern (or Calm Before the Storm?)

Despite all the frenzy over HITECH, a large part of the health IT community seems to be in a holding pattern. Maybe it is the calm before the storm. Hospitals and physician practices are waiting for the final criteria for meaningful use now that the comment period has ended. (More on those in a moment.) Researchers and innovators are waiting to hear respectively about their SHARP and Beacon proposals, while educators are waiting to hear about their workforce development proposals.

For those interested in workforce-related issues, such as certification, the press has not been quiet. A recent article by Joseph Conn described where things with a focus on physician certification, while another article by Bruce Bollag describes the ONC workforce funding initiatives in more detail.

In the meantime, a number of groups have put forth thoughtful critiques of the interim rules for meaningful use. The entirety of comments can be seen at Regulations.gov. It will be interesting to see how ONC and CMS take these into account and what modifications they make. Here are some published letters from some of the more prominent organizations:

• A group of 96 physician associations
  
• American Medical Informatics Association (AMIA) comments on the CMS NPRM and ONC IFR
• American Health Information Management Association (AHIMA)
  
• Association of American Medical Colleges (AAMC) comments on the CMS NPRM and ONC IFR
  
• Consumer Partnership for eHealth
• eHealth Initiative
  
• American Hospital Association
  
• American Academy of Family Physicians
  
• Premier (insurance group purchaser)
• Medical Group Management Association
• HIMSS EHR (Vendor) Association comments on the CMS NPRM and ONC IFR
• Combined comments from the Markle Foundation, the Center for American Progress, and the Engelberg Center for Healthcare Reform of the Brookings Institute on the CMS NPRM and the ONC IFR
  

Fortunately the wheels of educational opportunity are not standing still. AMIA has announced three offerings of the OHSU 10x10 course. Two are oriented to specific professional groups, while the other is oriented to the usual general clinical informatics audience. More information for each can be found at the following links:

• General clinical informatics
• Emergency medicine physicians (in partnership with the American College of Emergency Physicians)
  
• Dietitians (in partnership with the American Dietetic Association)
  

Section 3016 Has Arrived!

The long-anticipated Funding Opportunity Announcements (FOAs) for health information technology (HIT) workforce development, as specified in Section 3016 of the American Recovery and Reinvestment Act (ARRA), have been released by the Office of the National Coordinator for Health IT (ONC). These FOAs reveal the overall plans of ONC for quickly ramping up the workforce to meet the ARRA electronic health record (EHR) adoption goals. This will be done by two specific FOAs, one that funds development of five regional consortia of community colleges around the country, who in turn will implement curricula developed by the other FOA that funds five national curriculum development centers.

ONC has also provided its own analysis and plan for the workforce. Both FOAs state a need to train 51,000 workers to implement the ARRA HIT agenda. They list specifically six job roles for this workforce, noting that preparation for any them will typically require six months of intense training for individuals with appropriate backgrounds. These individuals could work for a variety of entities, including health care organizations, regional extension centers, government organizations, vendors, and others. (It would be great for those of us with an interest in workforce research and education to see their data and analysis of the workforce needs. I hope they release it at some point.)

Four of the job roles are "mobile adoption support positions" and involve personnel who carry out the initial EHR implementation at a site and then move on to the next one. The specific roles for these positions are:

• Practice workflow and information management redesign specialists
• Clinician/practitioner consultants
• Implementation support specialists
• Implementation managers

The other two job roles are "permanent staff of healthcare delivery and public health sites" and provide ongoing support after implementation. The specific roles for these positions include:

• Technical/software support staff
• Trainers

Although this process presents a coherent and specific plan to quickly ramp up the workforce, an approach with which I concur, I also hope it also raises the visibility of clinical informatics as an important component of EHR adoption and a career option for people who aspire to work professionally (and academically) in HIT. I am somewhat disappointed that the programs developed will not have pathways that articulate with more formal degree programs (e.g., baccalaureate and master's degrees, or even associate degrees for that matter). I do hope that educators who participate will be given the option to find ways to make further articulation and career enhancement happen. In addition, while I know that community colleges have historically risen to the challenge of quickly implementing skills-based training, I also wonder whether those with no experience or expertise teaching this content will be able to ramp up quickly enough. Where, for example, will they find faculty with sufficient expertise to do more than just deliver a packaged curriculum?

One also has to wonder whether those with short-term training will have the complex array of knowledge and skills in areas like healthcare workflow, change management, quality measurement, and oral and written communication (among even more) that are so essential for successful EHR implementation in complicated entities like healthcare organizations. We will no doubt be witnessing a great workforce and education "experiment" (just like, I suppose, all of the ARRA EHR agenda). I look forward to being a "subject" in that experiment.

On to the details. The first FOA (EP-HIT-10-001) is entitled, Community College Consortia to Educate Health Information Technology Professionals in Health Care Program. This FOA divides the country into five regions, each of which will have one consortium. Each consortium has a target amount of funding, number of students, and number of institutions. (Oregon is in Region A, the smallest of the five regions in terms of population served.) The overall allocation is $70 million.

Each consortium will have a lead organization and targeted number of member community colleges (varying from 5-8 in Region A to 17-23 in Region E in the Northeast). Each will have an expected minimum number of students each year, with the overall goal of training 10,500 students annually. Programs will not award degrees, but instead award a six-month certificate. It is assumed many students will have some background in healthcare and/or IT, and will need to flexibly learn more of what they do not know. Each member institution does not have to offer training for all six job roles, but each consortium as a whole must cover all the roles. The number of institutions must be within the specified range (unless an exemption is given), though each member does not need to train an equal numbers of students. Training must be commence by September 30, 2010.

Funding is for two years. The FOA does not address sustainability, either as requiring it in the plan or its being assessed in evaluation of proposals. It does say that the funding is a one-time opportunity. Up to $1M per consortium can be budgeted for consortium expenses. Up to 8% indirect (F&A) costs will be awarded to the lead institution and any others that have federal F&A agreements. My reading of the FOA is that any institution of higher learning, including a university, that offers HIT training (e.g., OHSU) can be a lead institution. The amount of funding works out to about $3,000-$4,000 per student trained (depending on the region and how much is allocated for consortium expenses).

The second FOA (EP-HIT-10-003) is entitled, Curriculum Development Centers Program. The goal of this FOA is to develop curricula that will be deployed by the community college consortia formed in the other FOA to train HIT professionals in 20 topics the cover the six specific job roles.

This FOA will fund five centers to develop materials in some number (applicants need to specify 7-10 where they have expertise) of areas from a list of 20. They are required to be academic training programs in informatics, HIT, or HIM, and engage both community college educators as well as instructional design experts. One center will also be designated the National Training and Dissemination Center, and additionally carry out training as well as establishing the repository for download of materials.

Each center will be funded up to $1.82M over two years ($910,000 per year), including indirect costs. The National Training and Dissemination Center will receive an additional $900,000 ($450,000 per year), including indirect costs.

Like the other FOA, there is a great amount of prescriptive detail provided. The 20 curricular areas from which to choose include:

• Introduction to Health Care and Public Health in the U.S
• The Culture of Health Care
• Terminology in Health Care and Public Health Settings
• Introduction to Information and Computer Science
• History of Health Information Technology in the U.S.
• Health Management Information Systems
• Working with Health IT Systems
• Installation and Maintenance of Health IT systems
• Networking and Health Information Exchange
• Fundamentals of Health Workflow Process Analysis & Redesign
• Configuring EHRs
• Quality Improvement
• Public Health IT
• Special Topics Course on Vendor-Specific Systems
• Usability and Human Factors
• Professionalism/Customer Service in the Health Environment
• Working in Teams
• Planning, Management and Leadership for Health IT
• Introduction to Project Management
• Training and Instructional Design

This whole approach is not without risk, but as I said above, it is a great plan for quickly ramping up the workforce. I do hope that it will allow for professional growth and development for those undertake the training and want to work as professionals in this extremely important component of improving healthcare. I also hope that the process will be evaluated well, so we can make corrections to the process when we find areas it does not work. In any case, I will stop writing now and get back to working on my proposals!

Informatics Education: A Final Common Pathway

As readers of this blog know from my other writings, the field of biomedical and health informatics is heterogeneous and diverse. The types of jobs performed by informaticians range from the highly technical to those that are more people and organizational in nature. The entire spectrum is vitally important. A unifying common element of these jobs is that they are somehow related to the use of information, often aided by technology, to improve individual health, health care, public health, and biomedical research.

I am also delighted to report that US News & World Report still considers informatics be one of its "ahead of the curve" careers. There is a Web page devoted to it, where I recently posted a comment.

• http://www.usnews.com/articles/business/best-careers/2008/12/11/ahead-of-the-curve-health-informatics-specialist-2009.html
• http://www.usnews.com/articles/business/best-careers/2008/12/11/ahead-of-the-curve-health-informatics-specialist-2009/comments/

As any director of an informatics education program can tell you, teaching informatics is a challenge. You have physicians, other health care professionals, computer scientists, health information managers, and many others sitting (virtually and in classrooms) alongside each other. Furthermore, many are adult learners, already having completed their primary education and often having substantial work experience.

Of course, educating such a diverse group can also be a real joy. Most of these individuals are very smart and highly motivated. I learn a great deal from them, and they require me to keep a step ahead in my knowledge.

Because of all this, I think of informatics education as a "final common pathway" for many individuals who bring diverse backgrounds, interests, and talents to the field. Such individuals will be uniquely qualified to develop, implement, and lead health IT, especially in the coming years.

It is hard to fathom this education not taking place at the graduate level. I recognize there are growing numbers of community college and undergraduate programs in informatics, but I tend to view these as one of the many pathways leading to that final common one. Most of the associate and baccalaureate programs in informatics are really IT programs with some health-related content added. This does not mean they cannot be of value to individuals or make contributions in health care settings, but such individuals are not likely to "practice" informatics as we normally define it.

I suspect that the informatics profession and its education will become more standardized in the coming years, especially as we see certification of individuals, with the commensurate accreditation of programs.

Learning about Informatics and Health IT at OHSU

The interest in health IT and biomedical informatics continues to grow, fueled no doubt by federal policy efforts and the economic stimulus plan. One result is that many people have inquired to me about opportunities to learn more about the biomedical informatics field at OHSU. To that end, I am going to describe the options in this posting. If you have further questions, feel free to contact me individually.

OHSU's programs are open to people of all career backgrounds. Our programs have served a wide diversity of people over the years, including those with backgrounds in health care (e.g., medicine, nursing, hospital administration, etc.), IT (e.g., computer scientists, IT professionals, etc.), and many other areas (e.g., health administration, business, public health, law, etc.). There is room for everyone in the big tent of informatics!

While our certificate and degree programs are at the graduate level (i.e., you need to have a bachelor's degree), our 10x10 ("ten by ten") course is open to anyone, even those who do not have a bachelor's degree.

An excellent way to get a broad-based introduction to the field is our on-line introductory biomedical informatics course. This course is offered in a number of flavors, and there are upcoming opportunities for you to enroll. Whatever path you take through the course, you can (assuming you are eligible for graduate study) get credit in our graduate program and be eligible to take more courses in our program if you are interested.

The introductory course is completely on-line and has been completed by about 1000 individuals in the last decade. It covers all the major aspects of biomedical and health informatics, with a focus on informatics applied to health care. It is offered using a variety of asynchronous distance learning teaching modalities, so you do not need to be present on-line at any specific time, although you do need to keep up with the work during the academic term.

One way to take the course is through our regular graduate program. OHSU is on an academic quarter system. Due to continued demand, the introductory course has been offered every academic quarter. The next offering is over the summer quarter, which runs from June 22 to September 11. The course will be offered again in the fall quarter, which runs from September 28 to December 13. To take the course by this pathway, you need to enroll in the OHSU Graduate Certificate program, which is open to anyone with a bachelor's degree. For more information, follow this link to our department Web site and click on the link to the Prospective Students Portal on the lower right:
http://www.ohsu.edu/dmice/

Another option to take essentially the same course is via the AMIA 10x10 program. This version of the course is offered in partnership with the American Medical Informatics Association (AMIA). The course is taught in the same on-line, asynchronous manner. It is offered over a slightly longer time period (decompressed with some "off" weeks) and adds an in-person session at the AMIA Annual Symposium, where all the students come together to meet and engage in additional learning. The AMIA Annual Symposium is one of the leading health IT meetings and will be held this year in San Francisco from November 14-18. Registration is already open for the next offering of the 10x10 course, which begins on July 30th and runs until the AMIA meeting. For more information, visit:
http://www.amia.org/10x10/partners/ohsu/
Or:
http://www.billhersh.info/10x10-2009.html

If you successfully complete the 10x10 course (and are eligible for graduate study), you can then get credit for the BMI 510 course in our graduate program. Once you are enrolled in the program, you can take additional courses. There is also a relatively easy pathway to advance beyond our Graduate Certificate into our master's degree program (and even the PhD program).

Here is a detailed outline of the introductory course content:

1. Overview of Field and Problems Motivating It
1.1 What is Health/Bio/Medical Informatics?
1.2 A Discipline Whose Time Has Come
1.3 Who Does Biomedical Informatics?
1.4 Problems in Health Care Motivating Biomedical Informatics
1.4 Seminal Documents and Reports
1.5 Resources for Field - Organizations, Information, Education

2. Biomedical Computing
2.1 Types of Computers
2.2 Data Storage in Computers
2.3 Computer Hardware and Software
2.4 Computer Networks
2.5 Software Engineering
2.6 Challenges for Biomedical Computing

3. Electronic Health Records
3.1 Clinical Data
3.2 History and Perspective of the Health (Medical) Record
3.3 Potential Benefits of the Electronic Health Record
3.4 Definitions and Key Attributes of the EHR
3.5 EHR Examples
3.6 Nursing Informatics

4. Clinical Decision Support; EHR Implementation
4.1 Historical Perspectives and Approaches
4.2 Medical Errors and Patient Safety
4.3 Reminders and Alerts
4.4 Computerized Provider Order Entry (CPOE)
4.5 Implementing the EHR
4.6 Use and Outcomes of the EHR
4.7 Cost-Benefit of the EHR

5. Standards and Interoperability; Privacy, Confidentiality, and Security
5.1 Standards: Basic Concepts
5.2 Identifier and Transaction Standards
5.3 Message Exchange Standards
5.4 Terminology Standards
5.5 Privacy, Confidentiality, and Security: Basic Concepts
5.6 HIPAA Privacy and Security Regulations

6. Secondary Use of Clinical Data: Personal Health Records, Health Information Exchange, Public Health, Health Care Quality, Clinical Research
6.1 Personal Health Records
6.2 Health Information Exchange
6.3 Public Health Informatics
6.4 Health Care Quality
6.5 Clinical Research Informatics

7. Evidence-Based Medicine and Medical Decision Making
7.1 Definitions and Application of EBM
7.2 Interventions
7.3 Diagnosis
7.4 Harm and Prognosis
7.5 Summarizing Evidence
7.6 Putting Evidence into Practice
7.7 Limitations of EBM

8. Information Retrieval and Digital Libraries
8.1 Information Retrieval
8.2 Knowledge-based Information
8.3 Content
8.4 Indexing
8.5 Retrieval
8.6 Evaluation
8.7 Digital Libraries

9. Imaging Informatics and Telemedicine
9.1 Imaging in Health Care
9.2 Modalities of Imaging
9.3 Digital Imaging
9.4 Telemedicine: Definitions, Uses, and Barriers
9.5 Efficacy of Telemedicine

10. Translational Bioinformatics
10.1 Translational Bioinformatics - The Big Picture
10.2 Overview of Basic Molecular Biology
10.3 Important Biotechnologies Driving Bioinformatics
10.4 Clinical Genetics and Genomics
10.5 Bioinformatics Information Resources
10.6 Translational Bioinformatics Challenges and Opportunities

11. Organizational and Management Issues in Informatics
11.1 Organizational Behavior
11.2 Organizational Issues in Failure and Success of Informatics Projects
11.3 Change Management

Health IT provisions of American Recovery and Reinvestment Act of 2009

There is a great deal of excitement in the biomedical informatics field due to the health IT provisions of American Recovery and Reinvestment Act of 2009, also known as the economic stimulus package. There are two main health IT provisions in the economic stimulus package: incentives for “meaningful use” of electronic health records (EHRs) by physicians and hospitals ($17B) and direct grants administered by federal agencies ($2B). No grant programs have been announced yet, but an encouraging sign is the recent appointment of a new National Coordinator for HIT, Dr. David Blumenthal. The are also provisions in other areas of legislation that pertinent to health IT in other areas of the stimulus package, including comparative effectiveness research, NIH and other science funding, and broadband and other infrastructure funding.

The incentives for “meaningful use” of EHRs will be implemented through increased Medicare or Medicaid reimbursement starting in 2011. Non-hospital-based physicians will receive incentives based on Medicare or Medicaid charges, up to $64K. Hospitals will have an incentive base amount of $2M, which is adjusted by the hospital’s number of discharges, Medicare/Medicaid patient mix, up to $9M, and phased down over four years. After 2016, physicians and hospitals begin to have reimbursement penalties for not using EHRs.“Meaningful use” is likely to include CCHIT certification, e-prescribing capability, interoperability standards, and other features.

There are opportunities in this space for software vendors, consultants, health care organizations with existing EHR systems. There are also opportunities for educational programs to train users, implementers, and others.

The stimulus package contains a variety of other funding initiatives that will be led by the Office of National Coordinator for Health IT (ONC) now under the leadership of Dr. Blumenthal. A total of $2B will be distributed to a variety of programs. The legislation does not allocate specific dollar amounts of the specific programs. The ones most pertinent to our program include:

• Sec. 13201 – Establishment of multidisciplinary Centers for Health Care Information Enterprise Integration, led by NIST, but involving other federal agencies, and funding research projects
• Sec. 3012 – Health Information Technology Implementation Assistance, providing matching funds for Regional Health IT Extension Centers
• Sec. 3013 – State Grants to Promote Health Information Technology, providing funding to states to facilitate and expand health information exchange
• Sec. 3015 – Demonstration Program to Integrate IT into Clinical Education, providing grants to develop academic curricula integrating EHRs into clinical education of health professionals
• Sec. 3016 – Information Technology Professionals on Health Care, providing funding for short-term (re-)training in informatics for IT and health care professionals in established educational programs

(A disclaimer about 3016: I wrote some of the words in it, and can honestly claim to have inserted the word "informatics" into the stimulus bill. Thanks to the staffs of Rep. David Wu and Sen. Ron Wyden for allowing me to help them draft the text. Naturally, OHSU's educational program is "shovel-ready" to train and re-train people for the jobs in health IT!)

The legislation provides other monies for health IT, some of which will fund biomedical research. There is $8.4 billion for National Institutes of Health for biomedical research. Some of this money is already being allocated, such as the newly announced NIH Challenge Grants program. Most of the money will be funneled to the 30 or so Institutes of the NIH, including the National Library of Medicine (NLM), which funds research and education in biomedical informatics. OHSU is already seeing some of this money in the expansion of our biomedical informatics training grant that will also provide funding for summer internships for both college students and non-research college faculty (e.g., community college and high school teachers).

The legislation also allocates $1.1B for comparative effectiveness research, which it defines as “research studies that compare one or more diagnostic or treatment options to evaluate effectiveness, safety or outcomes.” This money will be distributed by a variety of agencies, not only NIH but also the Agency for Healthcare Research & Quality and the Department of Health & Human Services. This is another area of key strength for OHSU.