Frederick G. Sayward

Hints on Test Data Selection: Help for the Practicing Programmer

In many cases tests of a program that uncover simple errors are also effective in uncovering much more complex errors. This so-called coupling effect can be used to save work during the testing process.

Maintaining and incrementally revalidating a computer-based clinical guideline: a case study.

The paper explores the issues involved in maintaining the logic within a complex computer-based clinical guideline, using as a case study IMM/Serve, an operational guideline whose domain is childhood immunization. For a period of more than a year and a half, we have maintained a log of (1) the national changes to the immunization recommendations, (2) the local customizations of IMM/Serves logic, and (3) certain logic problems that arose in the process of accommodating these changes and customizations. We describe the nature of these changes, customizations, and problems. We also discuss how different types of domain knowledge might assist in the automated process of validating successive versions of the logic. The papers goal is to use the immunization domain to provide specific examples of the issues and problems that arise in maintaining a computer-based clinical guideline.

Issues in computer-based decision support in public health illustrated using projects involving childhood immunization.

The article discusses issues that arise in implementing computer-based decision support using childhood immunization as a source of examples. The examples include (1) IMM/Serve, a program that provides patient-specific recommendations, (2) informatics tools developed to help validate IMM/Serves knowledge and functionality, and (3) tools developed to explore how computers can help ensure immunization data quality. Issues discussed include the complexity of creating computer-based decision support, the need for a continuing process of revision and testing as the health field evolves over time, and the potential value of computer-based tools to assist in this process.

IMM/SCRUB: A domain-specific tool for the deduplication of vaccination history records in childhood immunization registries

IMM/Scrub is a pilot tool developed to assist in the deduplication of vaccination history records in childhood immunization registries. This problem is complicated by a number of factors including that fact that: (1) some doses are numbered and some are not, (2) doses may have different dose numbers, (3) doses may specify different preparations within a vaccine series, (4) one dose may indicate a combination vaccine and the other dose may specify one component of that combination, (5) two doses may have slightly different dates, and (6) combinations of any of these problems may occur together. IMM/Scrub is designed to help detect 10 different types of vaccination dose duplicates and also allows the user to specify flexibly the conditions in which a duplicate dose might be automatically eliminated. In addition, IMM/Scrub is linked to the IMM/Serve immunization forecasting program, which can provide additional assistance in the data cleaning process. The paper describes (1) the design of the current pilot implementation of IMM/Scrub, (2) the lessons learned during its implementation, and (3) our preliminary experience applying it to data from three immunization databases, from a state, a metropolitan area, and an academic medical center.

Can Statistical Methods Help Solve Problems in Software Measurement

The study of software metrics involves the creation and analysis of quantitative indices of merit which can be assigned to software, either existing or proposed. These measurements of software provide informational aids to be used in making software lifecycle decisions.