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.
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.
- Making progress in the near term, “Principles for evolutionary change”:
- 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.
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.