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Through his visionary leadership as Director of the U.S. National Library of Medicine (NLM), Donald A.B. Lindberg M.D. influenced future generations of informatics professionals and the field of biomedical informatics itself. This chapter describes Dr. Lindberg's role in sponsoring and shaping the NLM's Institutional T15 training programs.

At the 2011 American College of Medical Informatics (ACMI) Winter Symposium we studied the overlap between health IT and economics and what leading healthcare delivery organizations are achieving today using IT that might offer paths for the nation to follow for using health IT in healthcare reform. We recognized that health IT by itself can improve health value, but its main contribution to health value may be that it can make possible new care delivery models to achieve much larger value. Health IT is a critically important enabler to fundamental healthcare system changes that may be a way out of our current, severe problem of rising costs and national deficit. We review the current state of healthcare costs, federal health IT stimulus programs, and experiences of several leading organizations, and offer a model for how health IT fits into our health economic future.

Objective: This study presents a conceptual model to investigate the healthcare technology management (HTM) competency required by healthcare IS professionals and the impact of such competency in gaining strategic advantages through information technology (IT) by development of partnerships with people from different divisions of healthcare organizations., Methods: First, a scale to measure HTM competency was developed and validated, then it was used to collect the large-scale survey data. Second, the partial least squares (PLS) method was used to empirically test the conceptual model and hypotheses through the large-scale survey data collected., Results: The empirical results support the proposed structure for HTM competency encompassing the four skills/knowledge domains: healthcare organization overview, external knowledge networking, healthcare technology integration, and management and interpersonal. The findings indicate that HTM competency positively influences the attitudes of information system (IS) professionals towards their willingness to develop partnerships with healthcare professionals., Conclusions: The findings improve our understanding of the concept of HTM competency and its influence on IT-healthcare partnerships. The conceptual model of HTM is of particular value to those concerned with skills/knowledge training and competency development for IS professionals in healthcare organizations. Healthcare organizations can develop HTM profiles for individual IS professionals in accordance with their own organization contexts. Executive management can take advantage of such HTM profiles to assist in making succession-planning decisions by evaluating the competency levels and development needs of their employees.

Central problems in health care involve availability, access, quality, and cost. A major part of a health care strategy also involves disease prevention and promotion of healthy lifestyles, which go well beyond the purview of the health care system itself. Implementing any strategy involves health policy, finance, and management expertise. What then is the role of informatics? We take the position here that informatics is a key enabler both for addressing availability, access, quality, and cost, and also for supporting the work of health policy, finance, and management experts. Informatics provides the necessary information technology (IT) infrastructure, standards, tools, and data to be able to address these key topics and for carrying out the work of the experts. In that sense, we regard informatics as a means for social engineering--the availability of these capabilities brings stakeholders to the table who might otherwise not have reason to or be able to work together.

Attempts to predict the future are typically off the mark. Beyond the challenges of forecasting the stock market or the weather, dramatic instances of notoriously inaccurate prognostications have been those by the US patent office in the late 1800s about the future of inventions, by Thomas Watson in the 1930s about the market for large computers, and by Bill Gates in the early 1990s about the significance of the Internet. When one seeks to make predictions about health care, one finds that, beyond the usual uncertainties regarding the future, additional impediments to forecasting are the discontinuities introduced by advances in biomedical science and technology, the impact of information technology, and the reorganizations and realignments attending various approaches to health care delivery and finance. Changes in all three contributing areas themselves can be measured in "PSPYs", or paradigm shifts per year. Despite these risks in forecasting, I believe that certain trends are sufficiently clear that I am willing to venture a few predictions. Further, the predictions I wish to make suggest a goal for the future that can be achieved, if we can align the prevailing political, financial, biomedical, and technical forces toward that end. Thus, in a sense this is a call to action, to shape the future rather than just let it happen. This chapter seeks to lay out the direction we are heading in knowledge management and decision support, and to delineate an information technology framework that appears desirable. I believe the framework to be discussed is of importance to the health care-related knowledge management and decision making activities of the consumer and patient, the health care provider, and health care delivery organizations and insurers. The approach is also relevant to the other dimensions of academic health care institution activities, notably the conduct of research and the processes of education and learning.

Through his visionary leadership as Director of the U.S. National Library of Medicine (NLM), Donald A. B. Lindberg M.D. influenced future generations of informatics professionals and the field of biomedical informatics itself. This chapter describes Dr. Lindberg's role in sponsoring and shaping the NLM's Institutional T15 training programs. [ABSTRACT FROM AUTHOR]

Medical educators are interested in approaches to making selected relevant knowledge available in the context of problem-based care. This is of value both during the process of care and as a means of organizing information for offline self-study . Four trends in health information technology are relevant to achieving the goal and can be expected to play a growing role in the future. First, health care enterprises are developing approaches for access to information resources related to the care of a patient, including clinical data and images but also communication tools, referral and other logistic tools, decision support, and educational materials. Second, information for patients and methods for patient-doctor interaction and decision making are becoming available. Third, computer-based methods for representation of practice guidelines are being developed to support applications that can incorporate their logic. Finally, considering patients as being in particular "clinical management states" (or CMSs) for specific problems, approaches are being developed to use guidelines as a kind of "predictive" framework to enable development of interfaces for problem-based clinical encounters. The guidelines for a CMS can be used to identify the kinds of resources specifically needed for clinical encounters of that type. As the above trends converge to produce problem-specific environments, professional specialty organizations and continuing medical education course designers will need to focus energies on organizing and updating medical knowledge to make it available in CMS-specific contexts. [ABSTRACT FROM AUTHOR]

Describes the evolving field of medical informatics in the U.S. Definition of medical informatics; Fundamental research problems; Academic units of medical informatics; Planning and policy issues regarding its role in the healthcare institution; Career paths for professionals.

Representation of clinical practice guidelines in a computer-interpretable format is a critical issue for guideline development, implementation, and evaluation. We studied 11 types of guideline representation models that can be used to encode guidelines in computer-interpretable formats. We have consistently found in all reviewed models that primitives for representation of actions and decisions are necessary components of a guideline representation model. Patient states and execution states are important concepts that closely relate to each other. Scheduling constraints on representation primitives can be modeled as sequences, concurrences, alternatives, and loops in a guideline''s application process. Nesting of guidelines provides multiple views to a guideline with different granularities. Integration of guidelines with electronic medical records can be facilitated by the introduction of a formal model for patient data. Data collection, decision, patient state, and intervention constitute four basic types of primitives in a guideline''s logic flow. Decisions clarify our understanding on a patient''s clinical state, while interventions lead to the change from one patient state to another. [Copyright &y& Elsevier]