Literature DB >> 28938242

Clinical Data Warehouse: An Effective Tool to Create Intelligence in Disease Management.

Mahtab Karami1, Azin Rahimi, Ali Hosseini Shahmirzadi.   

Abstract

Clinical business intelligence tools such as clinical data warehouse enable health care organizations to objectively assess the disease management programs that affect the quality of patients' life and well-being in public. The purpose of these programs is to reduce disease occurrence, improve patient care, and decrease health care costs. Therefore, applying clinical data warehouse can be effective in generating useful information about aspects of patient care to facilitate budgeting, planning, research, process improvement, external reporting, benchmarking, and trend analysis, as well as to enable the decisions needed to prevent the progression or appearance of the illness aligning with maintaining the health of the population. The aim of this review article is to describe the benefits of clinical data warehouse applications in creating intelligence for disease management programs.

Entities:  

Mesh:

Year:  2017        PMID: 28938242     DOI: 10.1097/HCM.0000000000000113

Source DB:  PubMed          Journal:  Health Care Manag (Frederick)        ISSN: 1525-5794


  8 in total

1.  Public Reporting of Cardiac Outcomes for Patients With Acute Myocardial Infarction: A Systematic Review of the Evidence.

Authors:  Pamela B de Cordova; Mary L Johansen; Kathryn A Riman; Jeannette Rogowski
Journal:  J Cardiovasc Nurs       Date:  2019 Mar/Apr       Impact factor: 2.083

2.  Applying Data Warehousing to a Phase III Clinical Trial From the Fondazione Italiana Linfomi Ensures Superior Data Quality and Improved Assessment of Clinical Outcomes.

Authors:  Gian Maria Zaccaria; Simone Ferrero; Samanta Rosati; Marco Ghislieri; Elisa Genuardi; Andrea Evangelista; Rebecca Sandrone; Cristina Castagneri; Daniela Barbero; Mariella Lo Schirico; Luca Arcaini; Anna Lia Molinari; Filippo Ballerini; Andres Ferreri; Paola Omedè; Alberto Zamò; Gabriella Balestra; Mario Boccadoro; Sergio Cortelazzo; Marco Ladetto
Journal:  JCO Clin Cancer Inform       Date:  2019-10

Review 3.  Semantic Web Technologies for Sharing Clinical Information in Health Care Systems.

Authors:  Mahtab Karami; Azin Rahimi
Journal:  Acta Inform Med       Date:  2019-03

4.  Real-time autOmatically updated data warehOuse in healThcare (ROOT): an innovative and automated data collection system.

Authors:  Hyun Ae Jung; Oksoon Jeong; Dong Kyung Chang; Sehhoon Park; Jong-Mu Sun; Se-Hoon Lee; Jin Seok Ahn; Myung-Ju Ahn; Keunchil Park
Journal:  Transl Lung Cancer Res       Date:  2021-10

5.  Evaluation of Doc'EDS: a French semantic search tool to query health documents from a clinical data warehouse.

Authors:  Thibaut Pressat-Laffouilhère; Pierre Balayé; Badisse Dahamna; Romain Lelong; Kévin Billey; Stéfan J Darmoni; Julien Grosjean
Journal:  BMC Med Inform Decis Mak       Date:  2022-02-08       Impact factor: 3.298

6.  Data warehouse and medical research.

Authors:  Thiago Gonçalves Dos Santos Martins; Flavia de Souza Rangel
Journal:  Einstein (Sao Paulo)       Date:  2022-03-07

7.  Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study.

Authors:  James V Lacey; Nadia T Chung; Paul Hughes; Jennifer L Benbow; Christine Duffy; Kristen E Savage; Emma S Spielfogel; Sophia S Wang; Maria Elena Martinez; Sandeep Chandra
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-02-12       Impact factor: 4.254

8.  Research Integrated Network of Systems (RINS): a virtual data warehouse for the acceleration of translational research.

Authors:  Wenjun He; Katie G Kirchoff; Royce R Sampson; Kimberly K McGhee; Andrew M Cates; Jihad S Obeid; Leslie A Lenert
Journal:  J Am Med Inform Assoc       Date:  2021-07-14       Impact factor: 4.497

  8 in total

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