Seite - v - in Applied Interdisciplinary Theory in Health Informatics - Knowledge Base for Practitioners

Foreword Charles P. FRIEDMAN a,1 a Josiah Macy Jr. Professor of Medical Education Chair, Department of Learning Health Sciences, Medical School Professor of Information and Public Health University of Michigan Editor-in-Chief: Learning Health Systems This volume is an enormously important step, in a vital direction, for the field of health informatics. Few would argue with a statement that health informatics (HI) is an applied science. Given almost universal consensus around that assertion, HI researchers can approach their work from three positions. The first is what might be called pure empiricism, hold- ing to the premise that HI does not need theories. Knowledge in the field can cumulate through results of empirical studies, grounded in real world experiences, that reference and build upon each other. The second position is what might be called theoretical de- rivativism. As an applied field, HI does not require theories of its own, and it suffices to borrow theories from the widely acknowledged basic sciences such as mathematics, computer science, philosophy, psychology, and sociology. Supporters of the second po- sition would also assert that HI could borrow theory from more mature, but also applied, fields such as policy science, information science, and decision science. The third posi- tion – the most radical and, to me, most appealing – is that HI could, over time, evolve its own theoretical bases and assume a place alongside other, more mature applied sci- ences. This volume importantly and emphatically reveals the inadequacy of the first posi- tion, argues elegantly for and enables the second, and stimulates us to contemplate the third. It accomplishes this by describing in depth a strong candidate set of theories that do, could, or should underpin research in HI. These contributions support a statement that HI must be evidence-based and, perhaps more important, a statement that HI should also be prediction-based. Prediction-based HI research studies are grounded in models of the world that exist at higher levels of abstraction than the measures used in the study itself. These abstract models are then applied to describe expected study results, in ad- vance of any data collection and without resort to the results of other studies. In the pages that follow, the reader will experience an invaluable catalog of perspectives that can achieve not only evidence-based informatics but also prediction-based informatics. And peeking over the horizon, using the perspectives offered in this volume, every- one in the field, can begin to visualize what a theoretical basis unique to health informat- ics might be. Will this take the form of a synthesis of the fields described herein, or will some new perspectives, perhaps suggested by what is not included in this finite volume, 1 Corresponding Author: Prof Charles Friedman, E-mail: cpfried@umich.edu v