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Journal articles on the topic 'Health data warehousing evaluation'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Miller, Steven D., Phillip Stablein, Jay Syed, Valerie Smothers, Emily Marx, Peter Greene, Harold Lehmann, and Paul G. Nagy. "Evaluation of a Training Program to Improve Organizational Capacity for Health Systems Analytics." Applied Clinical Informatics 10, no. 04 (August 2019): 634–42. http://dx.doi.org/10.1055/s-0039-1694965.

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Objective The Leadership in Analytics and Data Science (LEADS) course was evaluated for effectiveness. LEADS was a 6-month program for working biomedical and health informatics (BMHI) professionals designed to improve analytics skills, knowledge of enterprise applications, data stewardship, and to foster an analytics community of practice through lectures, hands-on skill building workshops, networking events, and small group projects. Methods The effectiveness of the LEADS course was evaluated using the Kirkpatrick Model by assessing pre- and postcourse knowledge, analytics capabilities, goals, practice, class lecture reaction, and change in the size of participant professional networks. Differences in pre- and postcourse responses were analyzed with a Wilcoxon signed rank test to determine significance, and effect sizes were computed using a z-statistic. Results Twenty-nine students completed the course with 96% of respondents reporting that they were “very” or “extremely” likely to recommend the course. Participants reported improvement in several analytics capabilities including Epic data warehousing (p = 0.017), institutional review board policy (p = 0.005), and data stewardship (p = 0.007). Changes in practice patterns mirrored those in self-reported capability. On average, the participant professional network doubled. Conclusion LEADS was the first course targeted to working BMHI professional at a large academic medical center to have a formal effectiveness evaluation be published in the literature. The course achieved the goals of expansion of BMHI knowledge, skills, and professional networks. The LEADS course provides a template for continuing education of working BMHI professionals.

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Mahoney, Terrence. "Data warehousing and CI: An evaluation." Competitive Intelligence Review 9, no. 1 (January 1998): 38–43. http://dx.doi.org/10.1002/(sici)1520-6386(199801/03)9:1<38::aid-cir7>3.0.co;2-2.

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Spengler, Helmut, Claudia Lang, Tanmaya Mahapatra, Ingrid Gatz, Klaus A. Kuhn, and Fabian Prasser. "Enabling Agile Clinical and Translational Data Warehousing: Platform Development and Evaluation." JMIR Medical Informatics 8, no. 7 (July 21, 2020): e15918. http://dx.doi.org/10.2196/15918.

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Background Modern data-driven medical research provides new insights into the development and course of diseases and enables novel methods of clinical decision support. Clinical and translational data warehouses, such as Informatics for Integrating Biology and the Bedside (i2b2) and tranSMART, are important infrastructure components that provide users with unified access to the large heterogeneous data sets needed to realize this and support use cases such as cohort selection, hypothesis generation, and ad hoc data analysis. Objective Often, different warehousing platforms are needed to support different use cases and different types of data. Moreover, to achieve an optimal data representation within the target systems, specific domain knowledge is needed when designing data-loading processes. Consequently, informaticians need to work closely with clinicians and researchers in short iterations. This is a challenging task as installing and maintaining warehousing platforms can be complex and time consuming. Furthermore, data loading typically requires significant effort in terms of data preprocessing, cleansing, and restructuring. The platform described in this study aims to address these challenges. Methods We formulated system requirements to achieve agility in terms of platform management and data loading. The derived system architecture includes a cloud infrastructure with unified management interfaces for multiple warehouse platforms and a data-loading pipeline with a declarative configuration paradigm and meta-loading approach. The latter compiles data and configuration files into forms required by existing loading tools, thereby automating a wide range of data restructuring and cleansing tasks. We demonstrated the fulfillment of the requirements and the originality of our approach by an experimental evaluation and a comparison with previous work. Results The platform supports both i2b2 and tranSMART with built-in security. Our experiments showed that the loading pipeline accepts input data that cannot be loaded with existing tools without preprocessing. Moreover, it lowered efforts significantly, reducing the size of configuration files required by factors of up to 22 for tranSMART and 1135 for i2b2. The time required to perform the compilation process was roughly equivalent to the time required for actual data loading. Comparison with other tools showed that our solution was the only tool fulfilling all requirements. Conclusions Our platform significantly reduces the efforts required for managing clinical and translational warehouses and for loading data in various formats and structures, such as complex entity-attribute-value structures often found in laboratory data. Moreover, it facilitates the iterative refinement of data representations in the target platforms, as the required configuration files are very compact. The quantitative measurements presented are consistent with our experiences of significantly reduced efforts for building warehousing platforms in close cooperation with medical researchers. Both the cloud-based hosting infrastructure and the data-loading pipeline are available to the community as open source software with comprehensive documentation.

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Nicholson, Scott, Lynn Silipigni Connaway, and Bob Molyneux. "Using context to improve data-based library evaluation through data warehousing, data mining and visualization." Proceedings of the American Society for Information Science and Technology 43, no. 1 (October 10, 2007): 1–6. http://dx.doi.org/10.1002/meet.1450430164.

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Muntjir, Mohd. "Novice Evaluation and Comparative Survey on Database Management System, Data Warehousing and Data Mining." International Journal of Computer Applications 136, no. 10 (February 17, 2016): 39–45. http://dx.doi.org/10.5120/ijca2016908613.

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Berrar, Daniel, Frederic Stahl, Candida Silva, J. Rui Rodrigues, Rui M. M. Brito, and Werner Dubitzky. "Towards Data Warehousing and Mining of Protein Unfolding Simulation Data." Journal of Clinical Monitoring and Computing 19, no. 4-5 (October 2005): 307–17. http://dx.doi.org/10.1007/s10877-005-0676-z.

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Mattei, Michael D., and Stephen Hellebusch. "Simplified Data Analytics for the Accurate Evaluation of a New Venture's Market Potential." New England Journal of Entrepreneurship 9, no. 2 (March 1, 2006): 9–17. http://dx.doi.org/10.1108/neje-09-02-2006-b001.

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This article examines the creation of an accurate market projection designed with easy-to-use, cost-effective data analytic techniques. Many of the techniques explored are derived from the subdisciplines of decision support and data warehousing found in the information technology arena. Two significant contributions are presented: a simple mathematical technique that eliminates the need for heuristics, and the simplification of the process to the point where no computer or sophisticated statistical analysis is needed.

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Blatt, Robin J. R. "Banking Biological Collections: Data Warehousing, Data Mining, and Data Dilemmas in Genomics and Global Health Policy." Public Health Genomics 3, no. 4 (2000): 204–11. http://dx.doi.org/10.1159/000051140.

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Jaramillo, Alejandro. "Data Warehousing Solutions and Internet Initiatives in the Disease Management Era." Disease Management and Health Outcomes 9, no. 1 (2001): 1–9. http://dx.doi.org/10.2165/00115677-200109010-00001.

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Cifci, Mehmet Akif, and Sadiq Hussain. "Data Mining Usage and Applications in Health Services." JOIV : International Journal on Informatics Visualization 2, no. 4 (June 27, 2018): 225. http://dx.doi.org/10.30630/joiv.2.4.148.

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Data Mining (DM), used to extract large amounts of hidden, valuable, useful information in large quantities and to provide strategic decision support, has created a new perspective on the use of health data. It has become a rapidly growing method of responding to problematic areas of data in large quantities in almost all sections. Although in health services it seems to be slow, a major leap has come to the scene. The aim of this study is to provide a new perspective on decision-making processes by creating an infrastructure for the health data and to provide examples for healthcare workers in the healthcare industry using DM techniques. Forasmuch as, the conceptual framework of data discovery in databases, Data Warehousing, DM, Business Intelligence (BI) has been given. DM applications and usages are given as examples of priority issues and problem areas in the health sector.

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Di, Tria, Ezio Lefons, and Filippo Tangorra. "Academic data warehouse design using a hybrid methodology." Computer Science and Information Systems 12, no. 1 (2015): 135–60. http://dx.doi.org/10.2298/csis140325087d.

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In the last years, data warehousing has got attention from Universities which are now adopting business intelligence solutions in order to analyze crucial aspects of the academic context. In this paper, we present the architecture of a Business Intelligence system for academic organizations. Then, we illustrate the design process of the data warehouse devoted to the analysis of the main factors affecting the importance and the quality level of every University, such as the evaluation of the Research and the Didactics. The design process we describe is based on a hybrid methodology that is largely automatic and relies on an ontological approach for the integration of the different data sources.

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Tan, Joseph, and Fuchung Wang. "Non-Traditional Data Mining Applications in Taiwan National Health Insurance (NHI) Databases." International Journal of Healthcare Information Systems and Informatics 12, no. 4 (October 2017): 31–51. http://dx.doi.org/10.4018/ijhisi.2017100103.

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This study examines time-sensitive applications of data mining methods to facilitate claims review processing and provide policy information for insurance decision-making vis-à-vis the Taiwan National Health Insurance (NHI) databases. In order to obtain the best payment management, a hybrid mining (HM) approach, which has been grounded on the extant knowledge of data mining projects and health insurance domain knowledge, is proposed. Through the integration of data warehousing, online analytic processing, data mining techniques and traditional data analysis in the healthcare field, an easy-to-use decision support platform, which will assist in directing the health insurance decision-making process, is built. Drawing from lessons learned within a case study setting, results showed that not only is HM approach a reliable, powerful, and user-friendly platform for diversified payment decision support, but that it also has great relevance for the practice and acceptance of evidence-based medicine. Essentially, HM approach can provide a critical boost to health insurance decision support; hence, future researchers should develop and improve the approach combined with their own application systems.

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Irshad, Omer, and Muhammad Usman Ghani Khan. "Integration and Querying of Heterogeneous Omics Semantic Annotations for Biomedical and Biomolecular Knowledge Discovery." Current Bioinformatics 15, no. 1 (February 6, 2020): 41–58. http://dx.doi.org/10.2174/1574893614666190409112025.

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Background:Exploring various functional aspects of a biological cell system has been a focused research trend for last many decades. Biologists, scientists and researchers are continuously striving for unveiling the mysteries of these functional aspects to improve the health standards of life. For getting such understanding, astronomically growing, heterogeneous and geographically dispersed omics data needs to be critically analyzed. Currently, omics data is available in different types and formats through various data access interfaces. Applications which require offline and integrated data encounter a lot of data heterogeneity and global dispersion issues.Objective:For facilitating especially such applications, heterogeneous data must be collected, integrated and warehoused in such a loosely coupled way so that each molecular entity can computationally be understood independently or in association with other entities within or across the various cellular aspects.Methods:In this paper, we propose an omics data integration schema and its corresponding data warehouse system for integrating, warehousing and presenting heterogeneous and geographically dispersed omics entities according to the cellular functional aspects.Results & Conclusion:Such aspect-oriented data integration, warehousing and data access interfacing through graphical search, web services and application programing interfaces make our proposed integrated data schema and warehouse system better and useful than other contemporary ones.

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Solodovnikova, Darja, Laila Niedrite, and Aivars Niedritis. "Architecture Enabling Adaptation of Data Integration Processes for a Research Information System." Foundations of Computing and Decision Sciences 43, no. 2 (June 1, 2018): 129–49. http://dx.doi.org/10.1515/fcds-2018-0008.

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Abstract Today, many efforts have been made to implement information systems for supporting research evaluation activities. To produce a good framework for research evaluation, the selection of appropriate measures is important. Quality aspects of the systems’ implementation should also not be overlooked. Incomplete or faulty data should not be used and metric computation formulas should be discussed and valid. Correctly integrated data from different information sources provide a complete picture of the scientific activity of an institution. Knowledge from the data integration field can be adapted in research information management. In this paper, we propose a research information system for bibliometric indicator analysis that is incorporated into the adaptive integration architecture based on ideas from the data warehousing framework for change support. A data model of the integrated dataset is also presented. This paper also provides a change management solution as a part of the data integration framework to keep the data integration process up to date. This framework is applied for the implementation of a publication data integration system for excellence-based research analysis at the University of Latvia.

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Rado, Ratsimbazafy, and Omar Boussaid. "Multiple Decisional Query Optimization in Big Data Warehouse." International Journal of Data Warehousing and Mining 14, no. 3 (July 2018): 22–43. http://dx.doi.org/10.4018/ijdwm.2018070102.

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Data warehousing (DW) area has always motivated a plethora of hard optimization problem that cannot be solved in polynomial time. Those optimization problems are more complex and interesting when it comes to multiple OLAP queries. In this article, the authors explore the potential of distributed environment for an established data warehouse, database-related optimization problem, the problem of Multiple Query Optimization (MQO). In traditional DW materializing views is an optimization technic to solve such problem by storing pre-computed join or frequently asked queries. In this era of big data this kind of view materialization is not suitable due to the data size. In this article, the authors tackle the problem of MQO on distributed DW by using a multiple, small, shared and easy to maintain shared data. The evaluation shows that, compared to available default execution engine, the authors' approach consumes on average 20% less memory in the Map-scan task and it is 12% faster regarding the execution time of interactive and reporting queries from TPC-DS.

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Ganslandt, T., and H. U. Prokosch. "Perspectives for Medical Informatics." Methods of Information in Medicine 48, no. 01 (2009): 38–44. http://dx.doi.org/10.3414/me9132.

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Summary Objectives: Even though today most university hospitals have already implemented commercial hospital information systems and started to build up comprehensive electronic medical records, reuse of such data for data warehousing and research purposes is still very rare. Given this situation, the focus of this paper is to present an overview on exemplary projects, which have already tackled this challenge, reflect on current initiatives within the United States of America and the European Union to establish IT infrastructures for clinical and translational research, and draw attention to new challenges in this area. Methods: This paper does not intend to provide a fully comprehensive review on all the issues of clinical routine data reuse. It is based, however, on a presentation of a large variety of historical, but also most recent activities in data warehousing, data retrieval and linking medical informatics with translational research. Results: The article presents an overview of the various international approaches to this issue and illustrates concepts and solutions which have been published, thus giving an impression of activities pursued in this field of medical informatics. Further, problems and open questions, which have also been named in the literature, are presented and three challenges (to establish comprehensive clinical data warehouses, to establish professional IT infrastructure applications supporting clinical trial data capture and to integrate medical record systems and clinical trial databases) related to this area of medical informatics are identified and presented. Conclusions: Translational biomedical research with the aim “to integrate bedside and biology” and to bridge the gap between clinical care and medical research today and in the years to come, provides a large and interesting field for medical informatics researchers. Especially the need for integrating clinical research projects with data repositories built up during documentation of routine clinical care, today still leaves many open questions and research challenges. Consideration of regulatory requirements, data privacy issues, data standards as well as people/organizational issues are prerequisites in order to vanquish existing obstacles.

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Lyu, Yongle, Zhuo Pang, Chuang Zhou, and Peng Zhao. "Prognostics and health management technology for radar system." MATEC Web of Conferences 309 (2020): 04009. http://dx.doi.org/10.1051/matecconf/202030904009.

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Information-based war in the future has a higher requirement to the maintenance and support ability of radar system. Prognostics and Health Management(PHM) technology represents the research hotspot of maintenance system, and following key techniques need to be resolved to research on the radar PHM technology such as the acquirement and selection of health information and fault signs of a radar’s electronical components, mass data warehousing and mining, fusion of multi-source test data and multi-field characteristic information, failure model building and forecasting, automatic decision-making on maintenance, and at the same time improving the self built-in test abilities of radar’s components based on the optimization of Design For Testability(DFT). The radar PHM technology has the trend of “built-in to integrate”, “together with DFT” and “long-distance and distributed”. However, subjected to radar’s complexity and current PHM technique level, radar PHM engineering still meets many challenges, but has bright future.

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McKenna, Thomas M., Gagandeep Bawa, Kamal Kumar, and Jaques Reifman. "The physiology analysis system: An integrated approach for warehousing, management and analysis of time-series physiology data." Computer Methods and Programs in Biomedicine 86, no. 1 (April 2007): 62–72. http://dx.doi.org/10.1016/j.cmpb.2007.01.003.

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Rabinovich, Boris, and Mark Last. "A Scalable Algorithm for One-to-One, Onto, and Partial Schema Matching with Uninterpreted Column Names and Column Values." Journal of Database Management 25, no. 4 (October 2014): 1–16. http://dx.doi.org/10.4018/jdm.2014100101.

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In this paper, the authors propose a five-step approach to the problem of identifying semantic correspondences between attributes of two database schemas. It is one of the key challenges in many database applications such as data integration and data warehousing. The authors' research is focused on uninterpreted schema matching, where the column names and column values are uninterpreted or unreliable. The approach implements Bayesian networks, Pearson's correlation and mutual information to identify inter-attribute dependencies. Additionally, the authors propose an extension to their algorithm that allows the user to manually enter the known mappings to improve the automated matching results. The five-step approach also allows data privacy preservation. The authors' evaluation experiments show that the proposed approach enhances the current set of schema matching techniques.

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Artoli, Abdelmonim M., Hassan I. Mathkour, and Alaaeldin M. Hafez. "A Proposed Quality Assurance Intelligent Model for Higher Education Institutions in Saudi Arabia." Journal of Quality in Education 3, no. 3 (November 1, 2012): 7. http://dx.doi.org/10.37870/joqie.v3i3.92.

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Recent growth and demands for dealing with increasing complexity in management, evaluation, and accreditation of higher educational institutions have led keynote academic institutions and higher education authorities to adopt and try nonconventional solutions known to business firms to account for massive data management. The development in new practices and merging technology for analytics and information management have offered different solutions such as data warehousing, big data, and business intelligence. Such solutions are gradually being installed in a number of renown universities. Due to the difference between the two firms (higher education and business industry) in nature and aims, tailor-made solutions are needed. This paper shares authors' experience in designing and implementing an educational information system in the College of Computers and Information systems at King Saud University, Saudi Arabia. The paper also highlights differences between educational intelligence and business intelligence systems. Higher education implementation aspects ensuring suitable data query service to ease the running of high educational institutions are discussed and recognized.

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Raymond, Mark R. "Missing Data in Evaluation Research." Evaluation & the Health Professions 9, no. 4 (December 1986): 395–420. http://dx.doi.org/10.1177/016327878600900401.

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He, Wenjun, Katie G. Kirchoff, Royce R. Sampson, Kimberly K. McGhee, Andrew M. Cates, Jihad S. Obeid, and Leslie A. Lenert. "Research Integrated Network of Systems (RINS): a virtual data warehouse for the acceleration of translational research." Journal of the American Medical Informatics Association 28, no. 7 (March 17, 2021): 1440–50. http://dx.doi.org/10.1093/jamia/ocab023.

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Abstract Objective Integrated, real-time data are crucial to evaluate translational efforts to accelerate innovation into care. Too often, however, needed data are fragmented in disparate systems. The South Carolina Clinical & Translational Research Institute at the Medical University of South Carolina (MUSC) developed and implemented a universal study identifier—the Research Master Identifier (RMID)—for tracking research studies across disparate systems and a data warehouse-inspired model—the Research Integrated Network of Systems (RINS)—for integrating data from those systems. Materials and Methods In 2017, MUSC began requiring the use of RMIDs in informatics systems that support human subject studies. We developed a web-based tool to create RMIDs and application programming interfaces to synchronize research records and visualize linkages to protocols across systems. Selected data from these disparate systems were extracted and merged nightly into an enterprise data mart, and performance dashboards were created to monitor key translational processes. Results Within 4 years, 5513 RMIDs were created. Among these were 726 (13%) bridged systems needed to evaluate research study performance, and 982 (18%) linked to the electronic health records, enabling patient-level reporting. Discussion Barriers posed by data fragmentation to assessment of program impact have largely been eliminated at MUSC through the requirement for an RMID, its distribution via RINS to disparate systems, and mapping of system-level data to a single integrated data mart. Conclusion By applying data warehousing principles to federate data at the “study” level, the RINS project reduced data fragmentation and promoted research systems integration.

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Owad, William P. "Using drug-use evaluation data in medical staff evaluation." American Journal of Health-System Pharmacy 46, no. 6 (June 1, 1989): 1120–22. http://dx.doi.org/10.1093/ajhp/46.6.1120.

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Ziminski, Timoteus B., Steven A. Demurjian, Eugene Sanzi, Mohammed Baihan, and Thomas Agresta. "An Architectural Solution for Health Information Exchange." International Journal of User-Driven Healthcare 6, no. 1 (January 2016): 65–103. http://dx.doi.org/10.4018/ijudh.2016010104.

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Health information technology (HIT) systems including electronic health records (EHRs) have a market saturation nearing 92% at individual institutions but are still unsuited for cross-institutional collaboration of stakeholders (e.g., medical providers such as physicians, hospitals, clinics, labs, etc.) in support of health information exchange (HIE) of different HIT systems in geographically separate locations. In the computer science field, software architectures such as service-oriented architecture, grid computing, publish/subscribe paradigm, and data warehousing are well-established approaches for interoperation. However, the application of these software architectures to support HIE has not been significantly explored. To address this issue, this paper proposes an architectural solution for HIE that leverages established software architectural styles in conjunction with the emergent HL7 standard Fast Healthcare Interoperability Resources (FHIR). FHIR models healthcare data with XML or JSON schemas using a set of 93 resources to track a patient's clinical findings, problems, allergies, adverse events, history, suggested physician orders, care planning, etc. For each resource, a FHIR CRUD RESTful Application Program Interface (API) is defined to share data in a common format for each of the HITs that can then be easily accessible by mobile applications. This paper details an architectural solution for HIE using software architectural styles in conjunction with FHIR to allow HIT systems of stakeholders to be integrated to facilitate collaboration among medical providers. To demonstrate the feasibility and utility of HHIEA, a realistic regional healthcare scenario is introduced that illustrates the interactions of stakeholders across an integrated collection of HIT systems.

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Dush, David M. "Standardizing outcome data in program evaluation." Community Mental Health Journal 21, no. 1 (1985): 52–57. http://dx.doi.org/10.1007/bf00754706.

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Eisemann, N. "Routine health data in skin cancer screening evaluation." British Journal of Dermatology 175, no. 5 (October 28, 2016): 862. http://dx.doi.org/10.1111/bjd.14881.

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Chen, Tingqiang, Shuaibin Wang, Lei Pei, and Jining Wang. "Assessment of Dairy Product Safety Supervision in Sales Link: A Fuzzy-ANP Comprehensive Evaluation Method." Journal of Food Quality 2018 (June 25, 2018): 1–16. http://dx.doi.org/10.1155/2018/1389879.

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An evaluation index system is developed to assess food safety supervision in the sales links of dairy products. Evaluation research is conducted using the fuzzy-ANP comprehensive evaluation model to assess the product safety supervision of dairy products in the sales link based on 307,705 survey data acquired from 1,501 online and offline dairy businesses in China. Evaluation results show that (1) the overall situation of dairy product safety supervision in the sales link is encumbered by the fact that the online situation of dairy product safety supervision in the sales link is general. It does not achieve a relatively good level; (2) the investment in food safety supervision of dairy products in the sales link is insufficient for the online e-commerce platforms. Especially, the processes of reviewing and approving relevant business sales qualification must be improved; (3) online business types do not directly determine the situation of dairy product safety supervision in the sales link, but the operating environment, sales staff quality, and warehousing management are common regulatory weaknesses; and (4) for offline provinces, the level of economic development can affect the situation of dairy product safety supervision in the sales link. Aside from emphasizing sales qualifications, economically backward provinces should improve the supervision of the operating environment, sales equipment, sanitary status of workers, and other aspects.

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HARPER, S. L., V. L. EDGE, C. J. SCHUSTER-WALLACE, M. AR-RUSHDI, and S. A. McEWEN. "Improving Aboriginal health data capture: evidence from a health registry evaluation." Epidemiology and Infection 139, no. 11 (December 7, 2010): 1774–83. http://dx.doi.org/10.1017/s095026881000275x.

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SUMMARYThe lack of high-quality health information for accurately estimating burdens of disease in some Aboriginal populations is a challenge for developing effective and relevant public health programmes and for health research. We evaluated data from a health registry system that captured patient consultations, provided by Labrador Grenfell Health (Labrador, Canada). The goal was to evaluate the registry's utility and attributes using modified CDC guidelines for evaluating surveillance systems. Infectious gastrointestinal illness data were used as a reference syndrome to determine various aspects of data collection and quality. Key-informant interviews were conducted to provide information about system utility. The study uncovered limitations in data quality and accessibility, resulting in region-specific recommendations including conversion to an electronic system. More generally, this study emphasized how a systematic and standardized evaluation of health registry systems can help address challenges to obtaining quality health data in often remote areas where many Aboriginal communities are found.

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Akter, Mst Farzana, Tanjila Islam, Kaniz Fatema Trisha, and Mohammad Ohid Ullah. "An overview of data mining in medical informatics: Bangladesh perspective." Asian Journal of Medical and Biological Research 5, no. 4 (February 3, 2020): 258–64. http://dx.doi.org/10.3329/ajmbr.v5i4.45262.

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Recently using information technology in the health care system is an important issue. Medical informatics is the combination of information science, computer science, and health care. As population is increasing rapidly, it is obvious to use medical informatics to save human lives and to treat people in efficient way. Therefore, we tried to explore an overview of the necessities and practical uses of data mining in administrative, clinical, research as well as educational aspects of medical informatics in Bangladesh. It is one the most populous countries in the world and the health care system including data mining in medical informatics is not so handy. Besides, for the effect of monsoon weather people of this country are affected by various diseases but poor investment and weak implementation make these diseases a burden. The study focuses on the needs of clinical data warehousing and the practice of examining these databases in order to improve various aspects of medical informatics in Bangladesh. The study suggests that government and private health care organizations need to take account to store their data and create a research wing in every hospital in Bangladesh as well as other developing countries in the world so that researchers and doctors may be able to find out the solution of their problems. For the greater benefits of the people, more research on medical informatics is essential and implementation of the research outputs must be done in medical treatment. Asian J. Med. Biol. Res. June 2019, 5(4): 258-264

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Magruder, Steven, and James Sari. "Evaluation of potential data sources for surveillance." Journal of Urban Health 80, S1 (March 2003): i139. http://dx.doi.org/10.1007/bf02416935.

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Card, Josefina J., James L. Peterson, Starr Niego, and Claire Brindis. "The Prevention Minimum Evaluation Data Set (PMEDS)." Evaluation & the Health Professions 21, no. 3 (September 1998): 377–94. http://dx.doi.org/10.1177/016327879802100305.

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Cai, Xing Quan, Qian Qian Shi, and Li Na Duan. "Acquiring Evaluation Data of Health Habits and its Application." Advanced Materials Research 739 (August 2013): 446–49. http://dx.doi.org/10.4028/www.scientific.net/amr.739.446.

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In this paper, we present one method of acquiring the evaluation data of health habits using FitBit sensor. After registering in Fitbit.com, we create a customer client based on OAuth protocol and obtain the authorization of operational resources. Then we access to health habits assessment data, and complete data visualization. Finally, we provide the experiments results. The experiments results prove our method is feasible and valid. Our method has been used in our practical application.

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Yale, Andrew, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, and Kristin P. Bennett. "Generation and evaluation of privacy preserving synthetic health data." Neurocomputing 416 (November 2020): 244–55. http://dx.doi.org/10.1016/j.neucom.2019.12.136.

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Scott, John W., Todd A. Schwartz, and Justin B. Dimick. "Practical Guide to Health Policy Evaluation Using Observational Data." JAMA Surgery 155, no. 4 (April 1, 2020): 353. http://dx.doi.org/10.1001/jamasurg.2019.4398.

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Fang, Ziwei, Shuli Liu, and Yanming Zhao. "Health Evaluation Method of Supercapacitor Based on Data Mining." Journal of Physics: Conference Series 1861, no. 1 (March 1, 2021): 012006. http://dx.doi.org/10.1088/1742-6596/1861/1/012006.

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Lee, Myung Kyung, Hyeoun-Ae Park, Yul Ha Min, Younglan Kim, Hyo Ki Min, and Sung Woo Ham. "Evaluation of the Clinical Data Dictionary (CiDD)." Healthcare Informatics Research 16, no. 2 (2010): 82. http://dx.doi.org/10.4258/hir.2010.16.2.82.

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Ubaid, Ayesha, Farookh Hussain, and Muhammad Saqib. "Container Shipment Demand Forecasting in the Australian Shipping Industry: A Case Study of Asia–Oceania Trade Lane." Journal of Marine Science and Engineering 9, no. 9 (September 6, 2021): 968. http://dx.doi.org/10.3390/jmse9090968.

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Demand forecasting has a pivotal role in making informed business decisions by predicting future sales using historical data. Traditionally, demand forecasting has been widely used in the management of production, staffing and warehousing for sales and marketing data. However, the use of demand forecasting has little been studied in the container shipping industry. Improved visibility into the demand for container shipments has been a long-held objective of industry stakeholders. This paper addresses the shortcomings of both short-term and long-term shipment demand forecasting for the Australian container shipping industry. In this study, we compare three forecasting models, namely, the seasonal auto-regressive integrated moving average (SARIMA), Holt–Winters’ seasonal method and Facebook’s Prophet, to find the best fitting model for short-term and long-term import demand forecasting in the Australian shipping industry. Demand data from three years, i.e., 2016–2018, is used for the Asia–Oceania trade lane. The mean absolute percentage error (MAPE), root mean squared error (RMSE) and 2-fold walk-forward cross-validation are used for the model evaluation. The experiment results observed from the selected metrics suggest that Prophet outperforms the other models in its comparison for container shipment demand forecasting.

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MIZUSHIMA, Shunsaku, Nozomi MORIKAWA, Hitoshi FUJII, and Tetsuji YOKOYAMA. "Evaluation of Health Promotion Programs Using Health Checkup Data and Medical Receipts." Nippon Eiseigaku Zasshi (Japanese Journal of Hygiene) 67, no. 1 (2012): 44–49. http://dx.doi.org/10.1265/jjh.67.44.

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Xia, H. Amy, and Qi Jiang. "Statistical Evaluation of Drug Safety Data." Therapeutic Innovation & Regulatory Science 48, no. 1 (January 2014): 109–20. http://dx.doi.org/10.1177/2168479013510917.

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Gabetta, M., G. Milani, M. Bucalo, F. Mulas, A. Nuzzo, V. Favalli, E. Arbustini, R. Bellazzi, and C. Larizza. "Supporting Translational Research on Inherited Cardiomyopathies through Information Technology." Methods of Information in Medicine 52, no. 02 (2013): 137–47. http://dx.doi.org/10.3414/me12-01-0046.

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SummaryObjectives: The INHERITANCE project, funded by the European Commission, is aimed at studying genetic or inherited Dilated cardiomyopathies (DCM) and at understanding the impact and management of the disease within families that suffer from heart conditions that are caused by DCMs. The biomedical informatics research activity of the project aims at implementing information technology solutions to support the project team in the different phases of their research, in particular in genes screening prioritization and new gene-disease association discovery.Methods: In order to manage the huge quantity of scientific, clinical and patient data generated by the project several advanced biomedical informatics tools have been developed. The paper describes a layer of software instruments to support translation of the results of the project in clinical practice as well as to support the scientific discovery process. This layer includes data warehousing, intelligent querying of the phenotype data, integrated search of biological data and knowledge repositories, text mining of the relevant literature, and case based reasoning.Results: At the moment, a set of 1,394 patients and 9,784 observations has been stored into the INHERITANCE data warehouse. The literature database contains more than 1,100,000 articles retrieved from the Pubmed and generically related to cardiac diseases, already analyzed for extracting medical concepts and genes.Conclusions: After two years of project the data warehouse has been completely set up and the text mining tools for automatic literature analysis have been implemented and tested. A first prototype of the decision support tool for knowledge discovery and gene prioritization is available, but a more complete release is still under development.

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Wilson, Daniel Lawrence, Kendra N. Williams, and Ajay Pillarisetti. "An Integrated Sensor Data Logging, Survey, and Analytics Platform for Field Research and Its Application in HAPIN, a Multi-Center Household Energy Intervention Trial." Sustainability 12, no. 5 (February 28, 2020): 1805. http://dx.doi.org/10.3390/su12051805.

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Researchers rely on sensor-derived data to gain insights on numerous human behaviors and environmental characteristics. While commercially available data-logging sensors can be deployed for a range of measurements, there have been limited resources for integrated hardware, software, and analysis platforms targeting field researcher use cases. In this paper, we describe Geocene, an integrated sensor data logging, survey, and analytics platform for field research. We provide an example of Geocene’s ongoing use in the Household Air Pollution Intervention Network (HAPIN). HAPIN is a large, multi-center, randomized controlled trial evaluating the impacts of a clean cooking fuel and stove intervention in Guatemala, India, Peru, and Rwanda. The platform includes Bluetooth-enabled, data-logging temperature sensors; a mobile application to survey participants, provision sensors, download sensor data, and tag sensor missions with metadata; and a cloud-based application for data warehousing, visualization, and analysis. Our experience deploying the Geocene platform within HAPIN suggests that the platform may have broad applicability to facilitate sensor-based monitoring and evaluation efforts and projects. This data platform can unmask heterogeneity in study participant behavior by using sensors that capture both compliance with and utilization of the intervention. Platforms like this could help researchers measure adoption of technology, collect more robust intervention and covariate data, and improve study design and impact assessments.

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Sahu, Nitin Kumar, Saurav Datta, and Siba Sankar Mahapatra. "Fuzzy based appraisement module for 3PL evaluation and selection." Benchmarking: An International Journal 22, no. 3 (April 7, 2015): 354–92. http://dx.doi.org/10.1108/bij-01-2013-0002.

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Purpose – In today’s’ highly competitive market, outsourcing logistic activities have become a global trend as it offers wide range of services including transportation, distribution, packaging, labeling, warehousing, freight forwarding and order fulfillment. The demand of third-party logistics (3PL) provider becomes an increasingly important issue for corporate seeking improved customer service, operational efficiency, logistics costs as well as capital expenditure reduction. However, choosing a proper 3PL provider is a kind of multi-criteria decision making problem under consideration of complicated criteria hierarchy. Therefore, it seems necessary to develop an efficient appraisement module towards performance evaluation as well as selecting the best 3PL provider. The paper aims to discuss these issues. Design/methodology/approach – The present paper proposes a fuzzy based appraisement platform for evaluation and selection of 3PL providers. The theory behind interval-valued fuzzy numbers (IVFNs) has been utilized to aid the said decision-modeling. Based on two appraisement modules for 3PL evaluation; empirical data have been analyzed to validate case application. Findings – The proposed method has been found efficient for solving the group decision-making problem under uncertain environment due to vagueness, ambiguity associated with decision-makers’ subjective judgment. The proposed appraisement platform has been explored by an Indian automobile part manufacturing company at eastern part of India. 3PL providers have been evaluated individually to check their performance level with respect to various evaluation attributes. Apart from estimating overall performance metric, the model presented here can identify ill-performing areas which necessitate future attention. Originality/value – The major contributions of this work have been summarized as follows: First, development and implementation of an efficient decision-making procedural hierarchy to support 3PL evaluation and selection. Second, an overall performance metric has been introduced. Third, concept of IVFNs has been efficiently explored to facilitate such a appraisement cum selection decision making. Final, the appraisement index system has been extended with the capability to search ill-performing areas which require future progress.

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Spoth, Richard, and Virginia Molgaard. "Consumer-Focused Data Collection in Prevention Program Evaluation." Evaluation & the Health Professions 16, no. 3 (September 1993): 278–94. http://dx.doi.org/10.1177/016327879301600302.

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Okada, Y., Y. Haruki, and Y. Ogushi. "Evaluation of an encrypted database for patient data." Journal of Telemedicine and Telecare 6, no. 1_suppl (February 2000): 204. http://dx.doi.org/10.1258/1357633001934816.

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Koehoorn, M., L. Tamburic, CB McLeod, PA Demers, L. Lynd, and SM Kennedy. "Population-based surveillance of asthma among workers in British Columbia, Canada." Chronic Diseases and Injuries in Canada 33, no. 2 (March 2013): 88–94. http://dx.doi.org/10.24095/hpcdp.33.2.05.

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Introduction Population-based health databases were used for the surveillance of asthma among workers in British Columbia for the period 1999 to 2003. The purpose was to identify high-risk groups of workers with asthma for further investigation, education and prevention. Methods Workers were identified using an employer-paid health premium field in the provincial health registry, and were linked to their physician visit, hospitalization, workers' compensation and pharmaceutical records; asthma cases were defined by the presence of an asthma diagnosis (International Classification of Diseases [ICD]-9-493) in these health records. Workers were assigned to an ''at-risk'' exposure group based on their industry of employment. Results For males, significantly higher asthma rates were observed for workers in the Utilities, Transport/Warehousing, Wood and Paper Manufacturing (Sawmills), Health Care/Social Assistance and Education industries. For females, significantly higher rates were found for those working in the Waste Management/Remediation and Health Care/ Social Assistance industries. Conclusion The data confirm a high prevalence of active asthma in the working population of British Columbia, and in particular, higher rates among females compared to males and in industries with known respiratory sensitizers such as dust and chemical exposures.

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McLean, C., J. Ransom, and A. Galaznik. "PCN432 EVALUATION OF MISSING DATA IMPUTATION STRATEGIES IN CLINICAL TRIAL AND EMR DATA USING STANDARDIZED DATA MODELS." Value in Health 22 (November 2019): S520. http://dx.doi.org/10.1016/j.jval.2019.09.625.

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Boler, A. "PMD8 TRENDS IN DATA SOURCES USED FOR ECONOMIC EVALUATION." Value in Health 5, no. 6 (November 2002): 531–32. http://dx.doi.org/10.1016/s1098-3015(10)61406-4.

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Sinha, Hari Om Sharan. "Enhancement of “Technique for Order Preference by Similarity to Ideal Solution” Approach for Evaluating the Web Sources to Select as External Source for Web Warehousing." International Journal of Natural Computing Research 6, no. 1 (January 2017): 1–16. http://dx.doi.org/10.4018/ijncr.2017010101.

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The main concern of this paper is to evaluate the web sources, which are to be selected as external data sources for web warehousing. In order to identify the web sources, they are evaluated on the ground of their multiple features. For it, Multi Criteria Decision Making (MCDM) approach has been used. Here, among all the MCDM approach, the focus is on “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) approach and proposing an enhancement in this method. The conventional TOPSIS approach uses Euclidean Distance to measure the similarity. Here, Jeffrey Divergence has been proposed to measure the similarity instead of Euclidean Distance which includes all the symmetric distances during computation. The Euclidean Distance only measures unidirectional distance whereas the Jeffrey Divergence includes multidirectional distances. Unidirectional distance includes only distance in one dimension but multidirectional distances includes differences, so more relevant in web sources evaluation. Experimental analysis for both the variations of TOPSIS approach have been conducted and the result shows the enhancement in the selection of web sources.

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Li, Qing, Qiyuan Peng, Rengkui Liu, Ling Liu, and Lei Bai. "Track grid health index for grid-based, data-driven railway track health evaluation." Advances in Mechanical Engineering 11, no. 11 (November 2019): 168781401988976. http://dx.doi.org/10.1177/1687814019889768.

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Railway managers must have accurate assessments of railway track health to optimize maintenance and replacement scheduling and allocate resources reasonably. A model for railway track health evaluation, in which a continuous track line is divided into adjacent segments of the same length, referred to as track grids, is proposed in this study. A condition-evaluation index system for track grids was established, and deep autoencoder networks were used to reduce the dimensions of data on multiple condition measures. The set of all possible health features of the track grids was obtained using the hybrid hierarchical k-means clustering method. The tree-augmented naïve Bayes algorithm was employed to obtain the track grid health index and evaluate the overall health of the track grids. The proposed model was verified using measurement data from the Lanxin Railway in China. The proposed model was found to be superior to conventional health evaluation methods used in railway management in China. These results will enhance railway management knowledge and enable accurate determination of track health on a smaller spatial scale.

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Shen, Zhengguang, Qi Wang, and Fengyu Zhu. "Data-driven Health Evaluation of Multifunctional Self-validating Sensor Using Health Reliability Degree." Information Technology Journal 11, no. 11 (October 15, 2012): 1597–604. http://dx.doi.org/10.3923/itj.2012.1597.1604.

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