The single greatest impediment to the successful leveraging of computer-based patient records (CPRs) is the difficulty of creating and maintaining comparable patient descriptions. Specifically, it will be hard to justify the investment required to deploy CPRs widely if the patient descriptions they store are not comparable across successive releases of controlled health-care vocabularies. Thus, it is necessary to solve the controlled health-care vocabulary update problem for CPRs before the comparability of patient descriptions can be sustained. What may seem to be a narrow technical problem of interest only to maintainers of health-care enterprise systems is, instead, a central problem of medical informatics. Cimino's "Formal descriptions and adaptive mechanisms for changes in controlled medical vocabularies" describes a classification of the changes appearing in the 1994 Edition of the International Classification of Diseases (ICD-9-CM). His paper describes the conversion of differences detected between the 1993 and 1994 releases of ICD-9-CM and a conversion of the elements of the classification into the required formal changes to the Medical Entities Dictionary (MED), part of the CPR in use at Columbia Presbyterian Medical Center. Because the process of detecting differences begins with an empirical analysis of the ASCII representations of the 1993 and 1994 releases of ICD-9-CM, it is impossible for a computer program to infer the intent of the changes that caused the differences; instead, a content expert must infer the intent and then update the MED accordingly. A typical task is to infer whether a change in naming also reflects a change in the meaning named. While Cimino's methods and their execution are exemplary in every respect, they nevertheless constitute a kind of "reverse engineering"-an ad hoc attempt to infer intent from details. Reverse engineering of changes to controlled medical vocabularies is a poor precedent. Such methods should be viewed as necessary short-term expedients only, and all parties concerned should work toward an incremental plan by which the intent of changes to controlled health-care vocabularies can be made both explicit and machine processible. Only then can the comparability of patient descriptions be sustained.
