New NRC Report Finds “Health Care IT Chasm,” Seeks New Course Toward Quality Improvement and Cost Savings

Like the Institute of Medicine’s

(IOM) 2001 counterpart report, “Crossing the Quality Chasm,” a new
report from the National Research Council of the National Academies
is complex, full of new ideas assembled from multiple disciplines, and
is likely to have seminal importance in framing public policy from now
on. “Computational Technology for Effective Health Care:  Immediate Steps and Strategic Directions
was released last Friday, January 9, 2009 in draft, but there is so
much to comment on that I think it’s wise to begin with a quote from
the committee that sums up the central conclusion:

In short, the nation faces a health care IT chasm that is analogous to the quality chasm highlighted by the IOM over the past decade. In the quality domain, various improvement efforts have failed to improve health care outcomes, and sometimes even done more harm than good. Similarly, based on an examination of the multiple sources of evidence described above and viewing them through the lens of the committee’s judgment, the committee believes that the nation faces the same risk with health care IT—that current efforts aimed at the nationwide deployment of health care IT will not be sufficient to achieve the vision of 21st century health care, and may even set back the cause if these efforts continue wholly without change from their present course. Success in this regard will require greater emphasis on the goal of improving health care by providing cognitive support for health care providers and even for patients and family caregivers on the part of computer science and health/biomedical informatics researchers. Vendors, health care organizations, and government, too, will also have to pay greater attention to cognitive support. This point is the central conclusion articulated in this report. (emphasis added)

It would be difficult to find a more sober indictment of US health care IT policy
and implementation over the past decade than what is contained here.
The report is the result of many meetings and site visits beginning in
April 2007. It was written by a committee chaired by William W. Stead,
MD, Director of the prestigious Informatics Center at Vanderbilt
University Medical Center, and includes not only some of the nation’s
top academic computer scientists and health IT engineers, but
representatives from the private sector (Google and Intel) as well.

The report recommends that governmental institutions – especially the
federal government – should explicitly embrace measurable health care
quality improvement as the driving rationale for its health care IT
adoption efforts, and should shun programs that promote specific
clinical applications or products.

Although the report’s language
is sometimes almost impenetrable, the Committee’s major criticism of
today’s health IT is that the systems in use do not support the
clinical decision making processes that are foundational to the
practice of quality medicine, lacking what the authors refer to as
“cognitive support.” Nor do they adequately support the data collection
and aggregation necessary to analyze, report, and improve care.  Again,
in the words of the report:

The committee also
saw little cognitive support for data interpretation, planning, or
collaboration. For example, even in situations where different members
of the care team were physically gathered at the entrance to a
patient’s room and looking at different aspects of a patient’s case on
their individual computers, collaborative interactions took place via
verbal discussion, not directly supported in any way by the computer
systems, and the discussions were not captured back into the system or
record (i.e., the valuable high-level abstractions and integration were
neither supported nor retained for future use).



Instead, committee members repeatedly observed health care IT focused
on individual transactions (e.g., medication X is given to the patient
at 9:42 p.m., laboratory result Y is returned to the physician, and so
on) and virtually no attention being paid to helping the clinician
understand how the voluminous data collected could relate to the
overall health care status of any individual patient. Care providers
spent a great deal of time in electronically documenting what they did
for patients, but these providers often said that they were entering
the information to comply with regulations or to defend against
lawsuits, rather than because they expected someone to use it to
improve clinical care.

And I found it
refreshingly honest that the report compares the human interfacing of
health care software with software used in other information-intense
environments, and not favorably:

A
reviewer of this report in draft form noted the non-intuitive behavior
of most health care IT systems and the training requirements that
result from that behavior. Hospitals often require 3- or 4-hour
training sessions for physicians before they can get the user names and
passwords for access to new clinical systems. Yet much of the computing
software that these people use in other settings (e.g., office
software) adopts a consistent interface metaphor across applications
and adheres to prevailing design/interface norms. As a result, there is
much less need for training, and the user manual need only be consulted
when special questions arise. In contrast, health care IT lacks these
characteristics of conventional software packages—a fact that reflects
the failure of these systems to address some basic human interface
considerations.

Not all criticism
But
the new “Health Care IT Chasm” report is not just criticism.  It
suggests a number of ways to think about the challenges going forward,
posits principles that can achieve a vision of patient-centered
decision support, and makes clear cut recommendations aimed at the
government, health care provider organizations, the IT vendor
community, and researchers.    Here are a few highlights that caught my
immediate attention:

  • Motivated
    by a presentation from Intermountain Healthcare’s Marc Probst, the
    Committee found it useful to categorize health care information
    technology (IT) into four domains: automation; connectivity; decision support; and data-mining.

    The report comments that there is currently an “imbalance” in which
    most IT efforts have been focused on automation, and not enough on the
    other three domains.

  • The
    report suggests two sets of principles to guide governmental policy on
    health care IT, one for making progress in the near term, and one for
    the longer term.

    • Making progress in the near term, “Principles for evolutionary change”:
      •    Focus on improvements in care – technology is secondary.
      •    Seek incremental gain from incremental effort.
      •    Record available data so that today’s biomedical knowledge can be
      used to interpret the data to drive care, process improvement, and
      research.
      •    Design for human and organizational factors so that social and
      institutional processes will not pose barriers to appropriately taking
      advantage of technology.
      •    Support the cognitive functions of all caregivers, including health professionals, patients, and their families.

    • While preparing for the long term, “Principles for radical change”:
      •    Architect information and workflow systems to accommodate disruptive change.
      •    Archive data for subsequent re-interpretation, that is, in
      anticipation of future advances in biomedical knowledge that may change
      today’s interpretation of data and advances in computer science that
      may provide new ways extracting meaningful and useful knowledge from
      existing data stores.
      •    Seek and develop technologies that identify and eliminate ineffective work processes.
      •    Seek and develop technologies that clarify the context of data.
  • The report calls for increasing the development of IT tools for patients and consumers, not just doctors and nurses:
A final and significant benefit for the committee’s vision of patient-centered cognitive support is that patients themselves should be able to make use of tools designed with such support in mind. That is, entirely apart from being useful for clinicians, tools and technologies for patient-centered cognitive support should also be able to provide value for patients who wish to understand their own medical conditions more completely and thoroughly. Obviously, different interfaces would be required (e.g., interfaces that translate medical jargon into lay language)—but the underlying tools for medical data integration, modeling, and abstraction designed for patient-centered cognitive support are likely to be the same in any system for lay end users (i.e., patients).
  • The report recommends that health care organizations and their leaders:
Insist
that vendors supply IT that permits the separation of data from
applications and facilitates data transfers to and from other non-vendor
applications in shareable and generally useful formats.

Notice the wording here doesn’t mention standards, but only shareable and generally useful formats. To
discuss the separation of data from software applications de-mystifies
that awful term interoperability, and gets more directly at the heart
of the matter of sharing data.

  • The
    section of the report on Research Challenges provides readers with a
    high level diagram of what the committee calls the “virtual patient” —
    which they define as “a conceptual model of the patient reflecting
    their [the clinician’s] understanding of interacting physiological,
    psychological, societal, and other dimensions.”  The diagram
    illustrates where they believe health IT is currently, and where it
    needs to go in the future.

Ebm_practice

Bound to spark controversy
As
readers of this review will certainly know, there is currently an
on-going debate occasioned by President-elect Obama’s pledge to spend
$50 billion on health IT as part of the economic recovery package,
about how the new administration should parse these investments in
health IT over the next few years.  One group favors massive
expenditure on existing products and services, such as EHRs, and the
other recommends an approach that would also support incremental and
less disruptive IT adoption while re-designing clinical software and
communications technology to be more affordable and directly
contributory to better care outcomes.  The timing of the Health Care IT
Chasm report, therefore, could not be, well, more timely.

There is probably something in this report to help reinforce the
arguments of both the “EHRs are good enough” camp as well as the “don’t
spend bad money after good” group. But I find it predominantly a
cautionary tale, told by a group of scientists who have carefully
considered the present course of IT investment and have found it
needing a re-direction.  Because many of the committee members are or
have been leaders of the present course, the report is by definition courageously self-critical.
It is also commendable that this committee took the time and effort to
actually survey health care institutions, talk with doctors, nurses,
and patients, and examine first hand the social, organizational, and
technical interactions of the IT systems they criticize in this
report.  This is not just a report by the experts.  It is a report by
experts who are also stewards and witnesses.

David C. Kibbe MD MBA
is a Family Physician and Senior Advisor to the American Academy of
Family Physicians who consults on health care professional and consumer
technologies.

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