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Kotsilieris T. An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications. Healthcare (Basel) 2021; 9:322. [PMID: 33805721 PMCID: PMC8000069 DOI: 10.3390/healthcare9030322] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/10/2021] [Accepted: 03/11/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND As medical knowledge is continuously expanding and diversely located, Health Information Technology (HIT) applications are proposed as a good prospect for improving not only the efficiency and the effectiveness but also the quality of healthcare services delivery. The technologies expected to shape such innovative HIT architectures include: Mobile agents (Mas) and NoSQL technologies. Mobile agents provide an inherent way of tackling distributed problems of accessing heterogeneous and spatially diverse data sources. NoSQL technology gains ground for the development of scalable applications with non-static and open data schema from complex and diverse sources. METHODS AND DESIGN This paper conducts a twofold study: It attempts a literature review of the applications based on the mobile agent (MA) and NoSQL technologies for healthcare support services. Subsequently, a pilot system evaluates the NoSQL technology against the relational one within a distributed environment based on mobile agents for information retrieval. Its objective is to study the feasibility of developing systems that will employ ontological data representation and task implementation through mobile agents towards flexible and transparent health data monitoring. RESULTS AND DISCUSSION The articles studied focus on applying mobile agents for patient support and healthcare services provision thus as to make a positive contribution to the treatment of chronic diseases. In addition, attention is put on the design of platform neutral techniques for clinical data gathering and dissemination over NoSQL. The experimental environment was based on the Apache Jena Fuseki NoSQL server and the JAVA Agent DEvelopment Framework -JADE agent platform. The results reveal that the NoSQL implementation outperforms the standard relational one.
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Affiliation(s)
- Theodore Kotsilieris
- Department of Business and Organizations Administration, University of the Peloponnese, 24100 Kalamata, Greece
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Norton L, Ciervo J, Lobanov VS, Agrafiotis DK. Xcellerate Investigator Portal: A New Web-Based Tool for Online Delivery of Central Laboratory Data, Reports, and Communications to Clinical Sites. SLAS Technol 2020; 25:427-435. [PMID: 32726559 PMCID: PMC7509614 DOI: 10.1177/2472630320942200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Covance Drug Development produces more than 55 million test results via its central laboratory services, requiring the delivery of more than 10 million reports annually to investigators at 35,000 sites in 89 countries. Historically, most of these data were delivered via fax or electronic data transfers in delimited text or SAS transport file format. Here, we present a new web portal that allows secure online delivery of laboratory results, reports, manuals, and training materials, and enables collaboration with investigational sites through alerts, announcements, and communications. By leveraging a three-tier architecture composed of preexisting data warehouses augmented with an application-specific relational database to store configuration data and materialized views for performance optimizations, a RESTful web application programming interface (API), and a browser-based single-page application for user access, the system offers greatly improved capabilities and user experience without requiring any changes to the underlying acquisition systems and data stores. Following a 3-month controlled rollout with 6,500 users at early-adopter sites, the Xcellerate Investigator Portal was deployed to all 240,000 of Covance’s Central Laboratory Services’ existing users, gaining widespread acceptance and pointing to significant benefits in productivity, convenience, and user experience.
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Affiliation(s)
- Louis Norton
- Covance, the Drug Development Division of LabCorp, Princeton, NJ, USA
| | - Joseph Ciervo
- Covance, the Drug Development Division of LabCorp, Princeton, NJ, USA
| | - Victor S Lobanov
- Covance, the Drug Development Division of LabCorp, Princeton, NJ, USA
| | - Dimitris K Agrafiotis
- Covance, the Drug Development Division of LabCorp, Princeton, NJ, USA.,Novartis Institutes for Biomedical Research, Cambridge, MA, USA
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Farnum MA, Mohanty L, Ashok M, Konstant P, Ciervo J, Lobanov VS, Agrafiotis DK. A dimensional warehouse for integrating operational data from clinical trials. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2019; 2019:5425677. [PMID: 30942863 PMCID: PMC6446529 DOI: 10.1093/database/baz039] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 03/02/2019] [Accepted: 03/05/2019] [Indexed: 11/16/2022]
Abstract
Timely, consistent and integrated access to clinical trial data remains one of the pharmaceutical industry’s most pressing needs. As part of a comprehensive clinical data repository, we have developed a data warehouse that can integrate operational data from any source, conform it to a canonical data model and make it accessible to study teams in a timely, secure and contextualized manner to support operational oversight, proactive risk management and other analytic and reporting needs. Our solution consists of a dimensional relational data warehouse, a set of extraction, transformation and loading processes to coordinate data ingestion and mapping, a generalizable metrics engine to enable the computation of operational metrics and key performance, quality and risk indicators and a set of graphical user interfaces to facilitate configuration, management and administration. When combined with the appropriate data visualization tools, the warehouse enables convenient access to raw operational data and derived metrics to help track study conduct and performance, identify and mitigate risks, monitor and improve operational processes, manage resource allocation, strengthen investigator and sponsor relationships and other purposes.
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Affiliation(s)
- Michael A Farnum
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
| | - Lalit Mohanty
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
| | - Mathangi Ashok
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
| | - Paul Konstant
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
| | - Joseph Ciervo
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
| | - Victor S Lobanov
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
| | - Dimitris K Agrafiotis
- Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA
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Ciervo J, Shen SC, Stallcup K, Thomas A, Farnum MA, Lobanov VS, Agrafiotis DK. A new risk and issue management system to improve productivity, quality, and compliance in clinical trials. JAMIA Open 2019; 2:216-221. [PMID: 31984356 PMCID: PMC6951877 DOI: 10.1093/jamiaopen/ooz006] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 01/07/2019] [Accepted: 03/01/2019] [Indexed: 11/14/2022] Open
Abstract
Objective We present a new system to track, manage, and report on all risks and issues encountered during a clinical trial. Materials and Methods Our solution utilizes JIRA, a popular issue and project tracking tool for software development, augmented by third-party and custom-built plugins to provide the additional functionality missing from the core product. Results The new system integrates all issue types under a single tracking tool and offers a range of capabilities, including configurable issue management workflows, seamless integration with other clinical systems, extensive history, reporting, and trending, and an intuitive web interface. Discussion and Conclusion By preserving the linkage between risks, issues, actions, decisions, and outcomes, the system allows study teams to assess the impact and effectiveness of their risk management strategies and present a coherent account of how the trial was conducted. Since the tool was put in production, we have observed an increase in the number of reported issues and a decrease in the median issue resolution time which, along with the positive user feedback, point to marked improvements in quality, transparency, productivity, and teamwork.
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Affiliation(s)
- Joseph Ciervo
- Covance, the Drug Development Division of LabCorp, Princeton, New Jersey, USA
| | - Shih Chuan Shen
- Covance, the Drug Development Division of LabCorp, Princeton, New Jersey, USA
| | - Kristin Stallcup
- Covance, the Drug Development Division of LabCorp, Princeton, New Jersey, USA
| | - Abraham Thomas
- Covance, the Drug Development Division of LabCorp, Princeton, New Jersey, USA
| | - Michael A Farnum
- Covance, the Drug Development Division of LabCorp, Princeton, New Jersey, USA
| | - Victor S Lobanov
- Covance, the Drug Development Division of LabCorp, Princeton, New Jersey, USA
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Farnum MA, Ashok M, Kowalski D, Du F, Mohanty L, Konstant P, Ciervo J, Lobanov VS, Agrafiotis DK. A cross-source, system-agnostic solution for clinical data review. Database (Oxford) 2019; 2019:baz017. [PMID: 30773591 PMCID: PMC6378235 DOI: 10.1093/database/baz017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Revised: 12/24/2018] [Accepted: 01/19/2019] [Indexed: 01/23/2023]
Abstract
Assembly of complete and error-free clinical trial data sets for statistical analysis and regulatory submission requires extensive effort and communication among investigational sites, central laboratories, pharmaceutical sponsors, contract research organizations and other entities. Traditionally, this data is captured, cleaned and reconciled through multiple disjointed systems and processes, which is resource intensive and error prone. Here, we introduce a new system for clinical data review that helps data managers identify missing, erroneous and inconsistent data and manage queries in a unified, system-agnostic and efficient way. Our solution enables timely and integrated access to all study data regardless of source, facilitates the review of validation and discrepancy checks and the management of the resulting queries, tracks the status of page review, verification and locking activities, monitors subject data cleanliness and readiness for database lock and provides extensive configuration options to meet any study's needs, automation for regular updates and fit-for-purpose user interfaces for global oversight and problem detection.
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Affiliation(s)
- Michael A Farnum
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Mathangi Ashok
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Daniel Kowalski
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Fang Du
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Lalit Mohanty
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Paul Konstant
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Joseph Ciervo
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Victor S Lobanov
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
| | - Dimitris K Agrafiotis
- Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA
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