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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/Serve's 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.

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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/Serve's 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 paper's 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.

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Duplicate patient records pose a major problem for many immunization registries, as well as for many electronic patient record systems. This paper reports two complementary studies exploring the deduplication of immunization registry records. One study explores the utility of different demographic data elements, singly and in combination, to assist in the deduplication process. The second study explores how clinical patient data (vaccination history data) might assist in this process. To assess the utility of demographic data elements, data were used from three registries after duplicates had been identified. A computer program, IMM/Scan, was written to count the number of true-positive (TP) matches and false-positive (FP) matches found when using different Boolean combinations of demographic data elements. In this study, a strategy of "ORing high value ANDed pairs of data elements" appeared to be most powerful. To assess the utility of vaccination history data, record pairs were drawn from 440,000 patient records. Two metrics on patient history were tested: (1) the number of identical doses shared by two records, and (2) the number of "extra" doses in the combined history of two records. In this study, sample findings include: (1) for pairs of nonduplicate records, 93% had no identical doses and 90.6% had "extra" doses, and (2) for pairs of duplicate records, 83.8% had one or more identical doses and 82% contained no "extra" doses. These studies demonstrate potentially useful approaches to using demographic data and patient history data to assist the automated deduplication of immunization patient records.

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IMM/Serve is a computer-based guideline that provides patient-specific recommendations regarding childhood immunization. IMM/Serve is currently installed at an estimated 75 sites within the US Indian Health Service (IHS), with plans to extend its use to roughly 150 additional sites nationwide by the end of the year 2000. The dissemination of IMM/Serve within the IHS provides a case study with concrete examples that illustrate the diverse informatics issues that arise in the widespread dissemination of a computer-based clinical guideline.

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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.

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A significant problem faced by immunization registries is that the dates of a patient's previous vaccinations may not be known. These incomplete histories can pose a problem when attempting to use a computer-based guideline to produce patient-specific immunization recommendations automatically. This paper describes an overall approach, together with 3 specific strategies, developed to help deal with this problem. The paper then describes our experience applying the approach to a database containing over 400,000 immunization histories. The paper also discusses a number of the issues raised in adapting a computer-based guideline to accommodate incomplete patient data of this sort.

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IMM/Test is a prototype software tool built to generate test cases that can be used to help test and verify the internal logic of an immunization forecasting program. A forecasting program takes as input a child's immunization history and produces recommendations as to which vaccinations are due and which should be scheduled next. IMM/Test was developed to test a specific immunization forecasting program, IMM/Serve. In addition, IMM/Test has been incorporated into a broader Web-based tool, IMM/Web, which allows the user (e.g., a member of an immunization registry staff) to customize the parameters used for immunization forecasting (e.g., the minimum ages for each dose and the minimum wait intervals between doses) to reflect local practice. IMM/Web then generates a customized set of test cases that may be used to test the user's immunization forecasting program. The user may also request that the test cases be automatically passed to IMM/Serve to analyze using the newly defined parameters. The paper describes the internal design of IMM/Test and IMM/Web and discusses certain lessons learned in the implementation of the two programs.

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ACT/DB is a client-server database application for storing clinical trials and outcomes data, which is currently undergoing initial pilot use. It stores most of its data in entity-attribute-value form. Such data are segregated according to data type to allow indexing by value when possible, and binary large object data are managed in the same way as other data. ACT/DB lets an investigator design a study rapidly by defining the parameters (or attributes) that are to be gathered, as well as their logical grouping for purposes of display and data entry. ACT/DB generates customizable data entry. The data can be viewed through several standard reports as well as exported as text to external analysis programs. ACT/DB is designed to encourage reuse of parameters across multiple studies and has facilities for dictionary search and maintenance. It uses a Microsoft Access client running on Windows 95 machines, which communicates with an Oracle server running on a UNIX platform. ACT/DB is being used to manage the data for seven studies in its initial deployment.

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As clinical practice guidelines are increasingly implemented in computer-based form, a major challenge will be to maintain their domain knowledge as new national recommendations are developed and as local customization is required. This maintenance may also need to be performed for any computer-based tools developed to help in the guideline knowledge maintenance process itself. This paper uses the domain of childhood immunization to explore certain issues involved. It describes 1) two recent changes to the national recommendations dealing with the DTP and Polio vaccine series, and 2) several customizations requested by the immunization registries of the State of Oregon and the US Indian Health Service. It then describes how these guideline practice variations are currently handled in three computer-based tools, IMM/Serve, IMM/Def, and IMM/Test. Finally, it discusses how the use of these tools can provide one approach to characterizing the complexity of guideline variations.

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IMM/Serve is a computer program which implements the clinical guidelines for childhood immunization. IMM/Serve accepts as input a child's immunization history. It then indicates which vaccinations are due and which vaccinations should be scheduled next. The clinical guidelines for immunization are quite complex and are modified quite frequently. As a result, it is important that IMM/Serve's knowledge be represented in a format that facilitates the maintenance of that knowledge as the field evolves over time. To achieve this goal, IMM/Serve uses four representations for different parts of its knowledge base: (1) Immunization forecasting parameters that specify the minimum ages and wait-intervals for each dose are stored in tabular form. (2) The clinical logic that determines which set of forecasting parameters applies for a particular patient in each vaccine series is represented using if-then rules. (3) The temporal logic that combines dates, ages, and intervals to calculate recommended dates, is expressed procedurally. (4) The screening logic that checks each previous dose for validity is performed using a decision table that combines minimum ages and wait intervals with a small amount of clinical logic. A knowledge maintenance tool, IMM/Def, has been developed to help maintain the rule-based logic. The paper describes the design of IMM/Serve and the rationale and role of the different forms of knowledge used.

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IMM/Web is a prototype Web site designed to assist in the maintenance of the knowledge required to perform computer-based forecasting for childhood immunization. IMM/Web operates in conjunction with IMM/Serve, a immunization forecasting program that takes a child's immunization history and produces recommendations as to which vaccinations are due, and which should be scheduled next. IMM/Serve's domain knowledge is expressed in both tabular and rule-based form. Using IMM/Web, the various tabular forecasting parameters can be modified via the Web. Test cases can then be generated automatically which can be used to help verify the new version of logic. Finally, the test cases can be automatically passed for IMM/Serve to analyze using the newly defined parameters. The IMM/Web project is exploring how the process of updating, customizing, and testing new versions of a computer-based clinical guideline might be performed and guided in an organized fashion via the World-Wide Web.

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A rule-based program, IMM/Serve, is being developed to help guide childhood immunization for initial use, within Oregon. The program is designed primarily for automated use with an online immunization registry, but can also be used interactively by a single user. The paper describes IMM/Serve and discusses 1) the sources of complexity in immunization logic, 2) the potential advantages of a rule-based approach for representing that logic, and 3) the potential advantage of such a program evolving to become the standard of care. Related projects include 1) a computer-based tool to help verify the completeness of the logic, 2) a tool that allows a central part of the logic to be generated automatically, and 3) an approach that allows visualization of the logic graphically.

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