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This case study explored 1) how much online clinical data is required to obtain patient-specific recommendations from a computer-based clinical practice guideline, 2) whether the availability of increasing amounts of online clinical data might allow a higher specificity of those recommendations, and 3) whether that increased specificity is necessarily desirable. The "quick reference guide" version of the guideline for acute postoperative pain management in adults, developed by the Agency for Health Care Policy and Research, was analyzed. Patient-specific data items that might be used to tailor the computer's output for a particular case were grouped into rough categories depending on how likely they were to be available online and how readily they might be determined from online clinical data. The patient-specific recommendations were analyzed to determine to what degree the amount of text produced depended on the online availability of different categories of data. An examination of example recommendations, however, illustrated that high specificity may not always be desirable. The study provides a concrete illustration of how the richness of online clinical data can affect patient-specific recommendations, and describes a number of related design trade-offs in converting a clinical guideline into an interactive, computer-based form. [ABSTRACT FROM AUTHOR]

We devised an algorithm for integrating similar clinical research data collection instruments to create a common measurement instrument. We tested this algorithm using questions from several similar surveys. We encountered differing levels of granularity among questions and responses across surveys resulting in either the loss of granularity or data. This algorithm may make survey integration more systematic and efficient.

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.

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.

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.

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.

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.

Objective: To evaluate use of information resources during the first year of IAIMS implementation at the Yale-New Haven Medical Center. The evaluation asked: (1) Which information resources are being used? (2) Who uses information resources? (3) Where are information resources used? (4) Are multiple sources of information being integrated?, Design: Measures included monthly usage data for resources delivered network-wide, in the Medical Library, and in the Hospital; online surveys of library workstation users; an annual survey of a random, stratified sample of Medical Center faculty, postdoctoral trainees, students, nurses, residents, and managerial and professional staff; and user comments., Results: Eighty-three percent of the Medical Center community use networked information resources, and use of resources is increasing. Both status (faculty, student, nurse, etc.) and mission (teaching, research, patient care) affect use of individual resources. Eighty-eight percent of people use computers in more than one location, and increases in usage of traditional library resources such as MEDLINE are due to increased access from outside the Library. Both survey and usage data suggest that people are using multiple resources during the same information seeking session., Conclusions: Almost all of the Medical Center community is using networked information resources in more settings. It is necessary to support increased demand for information access from remote locations and to specific populations, such as nurses. People are integrating information from multiple sources, but true integration within information systems is just beginning. Other institutions are advised to incorporate pragmatic evaluation into their IAIMS activities and to share evaluation results with decision-makers.

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.

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.

Objective: To explore the software design issues involved in implementing an operational information sources map (ISM) knowledge base (KB) and system of navigational tools that can help medical users access network-based information sources relevant to a biomedical question., Design: A pilot biomedical ISM KB and associated client-server software (ISM/Explorer) have been developed to help students, clinicians, researchers, and staff access network-based information sources, as part of the National Library of Medicine's (NLM) multi-institutional Unified Medical Language System (UMLS) project. The system allows the user to specify and constrain a search for a biomedical question of interest. The system then returns a list of sources matching the search. At this point the user may request 1) further information about a source, 2) that the list of sources be regrouped by different criteria to allow the user to get a better overall appreciation of the set of retrieved sources as a whole, or 3) automatic connection to a source., Results: The pilot system operates in client-server mode and currently contains coded information for 121 sources. It is in routine use from approximately 40 workstations at the Yale School of Medicine. The lessons that have been learned are that: 1) it is important to make access to different versions of a source as seamless as possible, 2) achieving seamless, cross-platform access to heterogeneous sources is difficult, 3) significant differences exist between coding the subject content of an electronic information resource versus that of an article or a book, 4) customizing the ISM to multiple institutions entails significant complexities, and 5) there are many design trade-offs between specifying searches and viewing sets of retrieved sources that must be taken into consideration., Conclusion: An ISM KB and navigational tools have been constructed. In the process, much has been learned about the complexities of development and evaluation in this new environment, which are different from those for Gopher, wide area information servers (WAIS), World-Wide-Web (WWW), and MOSAIC resources.

The Database of Data Sets (DB/DS) for Health Services Research will be an online searchable directory of data sets which are available, often with restrictions and confidentiality safeguards, for use by health care researchers. The DB/DS project is aimed at a wide audience, and intends to include a very broad range of health care data sets, ranging from state hospital discharge data bases, to national registries and health survey data sets, to institutional clinical databases. The intended users are the same community of researchers, policy-makers, administrators and practitioners who are served by the National Library of Medicine's current bibliographic databases. This paper describes a pilot phase of the DB/DS project in which the issues involved in creating such a database were explored with an initial set of 20 representative data sets.