Instance-based Matching Research Articles

Rebuilding the Standing Prescription Renewal Orders

Managing prescription renewal requests is a labor-intensive challenge in ambulatory care. In 2009, Vanderbilt University Medical Center developed clinic-specific standing prescription renewal orders that allowed nurses, under specific conditions, to authorize renewal requests. Formulary and authorization changes made maintaining these documents very challenging. This article aims to review, standardize, and restructure legacy standing prescription renewal orders into a modular, scalable, and easier to manage format for conversion and use in a new electronic health record (EHR). We created an enterprise-wide renewal domain model using modular subgroups within the main institutional standing renewal order policy by extracting metadata, medication group names, medication ingredient names, and renewal criteria from approved legacy standing renewal orders. Instance-based matching compared medication groups in a pairwise manner to calculate a similarity score between medication groups. We grouped and standardized medication groups with high similarity by mapping them to medication classes from a medication terminology vendor and filtering them by intended route (e.g., oral, subcutaneous, inhalation). After standardizing the renewal criteria to a short list of reusable criteria, the Pharmacy and Therapeutics (P&T) committee reviewed and approved candidate medication groups and corresponding renewal criteria. Seventy-eight legacy standing prescription renewal orders covered 135 clinics (some applied to multiple clinics). Several standing orders were perfectly congruent, listing identical medications for renewal. We consolidated 870 distinct medication classes to 164 subgroups and assigned renewal criteria. We consolidated 379 distinct legacy renewal criteria to 21 criteria. After approval by the P&T committee, we built subgroups in a structured and consistent format in the new EHR, where they facilitated chart review and standing order adherence by nurses. Additionally, clinicians could search an autogenerated document of the standing order content from the EHR data warehouse. We describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.

An integrated heterogeneous web service retrieval via combination of instance- and metadata-based schema matching method

Schema matching is a critical step in the integration of heterogeneous web service, which contains various types of web services and multi-version services of the same type. Mapping loss or mismatch usually occurs due to schema differences in structure and content and the variety in concept definition and organization. Current instance schema matching methods are not mature enough for heterogeneous web service because they cannot deal with the instance data in web service domain and capture all the semantics, especially metadata semantics. The metadata-based and the instance-based matching methods, in the case of being employed individually, are not efficient to determine the concept relationships, which are crucial for finding high-quality matches between schema attributes. In this paper, we propose an improved schema matching method, based on the combination of instance and metadata (CIM) matcher. The main method of our approach is to utilize schema structure, element labels, and the corresponding instance data information. The matching process is divided into two phases. In the first phase, the metadata-based matchers are used to compute the element label similarity of multi-version open geospatial consortium web service schema, and the generated matching results are raw mappings, which will be reused in the next instance matching phase. In the second phase, the designed instance matching algorithms are employed to the instance data of the raw mappings and fine mappings are generated. Finally, the raw mappings and the fine mappings are combined, and the final mappings are obtained. Our experiments are executed on different versions of web coverage service and web feature service instance data deployed in Geoserver. The results indicate that, the CIM method can obtain more accurate matching results and is flexible enough to handle the web service instance data.

Utilizing WordNet and Regular Expressions for Instance-based Schema Matching

Instance-based matching is the process of finding the correspondence of schema elements by comparing the data from different data sources. It is used as an alternative option when the match between schema elements fails. Instance-based matching is applied in many application areas such as website creation and management, schema evolution and migration, data warehousing, database design and data integration. Sometimes the schema information such as (element name, description, data type, etc.) is unavailable or is unable to get the correct match especially when the element name is abbreviation, therefore, if the schema matching failed, the next step is to focus on values stored in the schemas. For these reasons, many recent approaches focus on instance-based matching. In this study, we propose an approach that combines the strength of pattern recognition utilizing regular expressions for numerical domain as well with WordNet for string domain by getting the similarity coefficient in the range of (0,1). In previous approach, the regular expression is achieved with a good accuracy for numerical instances only and is not implemented on string instances because we need to know the meaning of string to decide if there is a match or not. The using of WordNet-based measures for string instances should guarantee to improve the effectiveness in terms of Precision (P), Recall (R) and F-measure (F). This approach is evaluated with real dataset and the results are found better than using just equality measure for string especially if the schemas are disjoint. The approach achieved 95.3% F-measure (F).