Literature DB >> 24867195

Electronically implemented clinical indicators based on a data warehouse in a tertiary hospital: its clinical benefit and effectiveness.

Sooyoung Yoo1, Seok Kim1, Kee-Hyuck Lee1, Chang Wook Jeong2, Sang Woong Youn3, Kyoung Un Park4, So Young Moon5, Hee Hwang6.   

Abstract

OBJECTIVE: Assessing and monitoring care and service using clinical indicators (CIs) can allow the measurement of and lead to improvements in the quality of care. However, the management and maintenance of CI data has been shown to be difficult because the data are usually collected and provided manually. In this study, for the purpose of efficient managing quality indicators, a data warehouse (DW)-based CI monitoring system was developed. The clinical effectiveness and efficiency of a DW-based CI monitoring was investigated through several case studies of the system's operation at a tertiary hospital.
METHODS: This study analyzed the CIs that have been developed over the past 8 years at a 1340-bed tertiary general university hospital in South Korea to improve and monitor the quality of care and patient safety. The hospital was opened as a fully digital hospital in 2003, and the CIs were computerized in 2005 by implementing a DW-based CI monitoring system. We classified the computerized CIs and evaluated the monitoring results for several representative CIs, such as the optimal prescribing of preventive antibiotics, the average length of stay, the mortality rate, and the rehospitalization rate.
RESULTS: During the development of the system in 2005, 12 of 19 CIs were computerized, and this number gradually increased until 299 of 335 CIs were computerized by 2012. In addition, among the CIs built computationally through the CI task force team, focal CIs subject to monitoring were selected annually, and the results of this monitoring were shared with all of the staff or the related department and its staff. By providing some examples of our CI monitoring results, we showed the feasibility of improving the quality of care, and maintaining the optimum level of patient care with less labor.
CONCLUSIONS: The results of this study provide evidence regarding the clinical effectiveness and efficiency as well as the systems operation experience of a DW-based CI monitoring system. These findings may aid medical institutions that plan on computerizing CIs with respect to decision and policy making regarding their systems development and operations.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Data warehouse; Health information management; Hospital information systems; Integrated advanced information management systems; Quality of care

Mesh:

Year:  2014        PMID: 24867195     DOI: 10.1016/j.ijmedinf.2014.04.001

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  6 in total

Review 1.  Hospital information systems: experience at the fully digitized Seoul National University Bundang Hospital.

Authors:  Sooyoung Yoo; Hee Hwang; Sanghoon Jheon
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Authors:  Soo-Yong Shin; Yu Rang Park; Yongdon Shin; Hyo Joung Choi; Jihyun Park; Yongman Lyu; Moo-Song Lee; Chang-Min Choi; Woo-Sung Kim; Jae Ho Lee
Journal:  J Korean Med Sci       Date:  2014-12-23       Impact factor: 2.153

3.  Prediction of neoadjuvant radiation chemotherapy response and survival using pretreatment [(18)F]FDG PET/CT scans in locally advanced rectal cancer.

Authors:  Ji-In Bang; Seunggyun Ha; Sung-Bum Kang; Keun-Wook Lee; Hye-Seung Lee; Jae-Sung Kim; Heung-Kwon Oh; Ho-Young Lee; Sang Eun Kim
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-09-04       Impact factor: 9.236

4.  ACE: the Advanced Cohort Engine for searching longitudinal patient records.

Authors:  Alison Callahan; Vladimir Polony; José D Posada; Juan M Banda; Saurabh Gombar; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2021-07-14       Impact factor: 4.497

5.  Perspectives of Patients, Health Care Professionals, and Developers Toward Blockchain-Based Health Information Exchange: Qualitative Study.

Authors:  Keehyuck Lee; Kahyun Lim; Se Young Jung; Hyerim Ji; Kyungpyo Hong; Hee Hwang; Ho-Young Lee
Journal:  J Med Internet Res       Date:  2020-11-13       Impact factor: 5.428

6.  Identifying Unmet Treatment Needs for Patients With Osteoporotic Fracture: Feasibility Study for an Electronic Clinical Surveillance System.

Authors:  Fong-Ci Lin; Chen-Yu Wang; Rung Ji Shang; Fei-Yuan Hsiao; Mei-Shu Lin; Kuan-Yu Hung; Jui Wang; Zhen-Fang Lin; Feipei Lai; Li-Jiuan Shen; Chih-Fen Huang
Journal:  J Med Internet Res       Date:  2018-04-24       Impact factor: 5.428

  6 in total

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