Hickam 2000: the maturation of, and linkages between, medical informatics and bioinformatics

I have always been infatuated with computers and convinced of their potential for solving problems in biologic research and clinical care. In the 1960s I thought we could use the computer to predict the shape of macromolecules from their chemical formulas and fundamental physical chemical principles. However, with the computers of the 1960s that was a fantasy. So I focused on the use of computers to manage medical record content and to assist with clinical care. The Electronic Medical Record (EMR) we began developing in 1972 with 33 diabetes patients now carries nearly 300 million separate results for more than 3 million patients. The data include lab and other diagnostic studies, dictated notes, orders, encounter records, radiology images, electrocardiograph tracings, and motion cardiac echoes, and the care provider at Indiana University and Wishard Hospital is accessed 10 million times per year. We have also agitated for standards to make the collection of these data easier. This work has become part of a field called medical informatics. In the meantime, the application of computers to biology has rapidly matured into a field called bioinformatics, and researchers in this field now provide annotated databases for many categories of molecules, programs for "matching" newly discovered genomic sequences with previously studied sequences, and systems for storing and processing massive amounts of genomic and molemic data. They have developed sophisticated methods for predicting the shape of biologic macromolecules and other important insights about biology and evolution. Medical informatics and bioinformatics intersect at many points. The most important intersection is between electronic medical records and the human specimen databases that can link genotype to the phenotype, as needed, to unravel polygenetic disease causality. The National Cancer Institute is embarking on an intriguing effort to use EMRs (phenotype) to link to paraffin blocks (genotype) in pathology laboratories where opportunities for cancer genomic discovery are open. We will participate in this effort and look forward to bending the EMR we developed for clinical use to bioinformatics uses as well.