The Adoption of Electronic Medical Records and Decision Support Systems in Korea

Objectives To examine the current status of hospital information systems (HIS), analyze the effects of Electronic Medical Records (EMR) and Clinical Decision Support Systems (CDSS) have upon hospital performance, and examine how management issues change over time according to various growth stages. Methods Data taken from the 2010 survey on the HIS status and management issues for 44 tertiary hospitals and 2009 survey on hospital performance appraisal were used. A chi-square test was used to analyze the association between the EMR and CDSS characteristics. A t-test was used to analyze the effects of EMR and CDSS on hospital performance. Results Hospital size and top management support were significantly associated with the adoption of EMR. Unlike the EMR results, however, only the standardization characteristic was significantly associated with CDSS adoption. Both EMR and CDSS were associated with the improvement of hospital performance. The EMR adoption rates and outsourcing consistently increased as the growth stage increased. The CDSS, Knowledge Management System, standardization, and user training adoption rates for Stage 3 hospitals were higher than those found for Stage 2 hospitals. Conclusions Both EMR and CDSS influenced the improvement of hospital performance. As hospitals advanced to Stage 3, i.e. have more experience with information systems, they adopted EMRs and realized the importance of each management issue.

[1]  Jonathan A. Zlabek,et al.  Early cost and safety benefits of an inpatient electronic health record , 2011, J. Am. Medical Informatics Assoc..

[2]  Joon S. Kim,et al.  Does the physician order-entry system increase the revenue of a general hospital? , 2003, Int. J. Medical Informatics.

[3]  Petter Gottschalk,et al.  Toward a Model of Growth Stages for Knowledge Management Technology in Law Firms , 2002, Informing Sci. Int. J. an Emerg. Transdiscipl..

[4]  Michael J. Earl,et al.  Evolving the E-Business , 2000 .

[5]  Ferdinand T. Velasco,et al.  Improving Outcomes with Clinical Decision Support: An Implementer's Guide , 2012 .

[6]  Il Ryu,et al.  An Empirical Study on the Success Factors and Performance Model of Hospital Information Systems , 2002 .

[7]  Andrew P. McAfee,et al.  The state of regional health information organizations: current activities and financing. , 2007, Health affairs.

[8]  Jiajie Zhang,et al.  Performance factors of mobile rich media job aids for community health workers , 2011, J. Am. Medical Informatics Assoc..

[9]  D. Bates,et al.  Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. , 1998, JAMA.

[10]  R. Nolan,et al.  Managing the Four Stages of EDP Growth , 1974 .

[11]  Rainu Kaushal,et al.  Bmc Medical Informatics and Decision Making Assessing the Level of Healthcare Information Technology Adoption in the United States: a Snapshot , 2005 .

[12]  Jane Robles.  The Effect of the Electronic Medical Record on Nurses’ Work , 2009, Creative Nursing.

[13]  G. J. Kuperman,et al.  Bates DW, Leape LL, Cullen DJ, Laird N, Petersen LA, Teich JM, Burdick E, HicSheakey M, Kleefield SB, Vander Vliet M, Seger DL, Effect of computerized physician order entry and a team intervention on prevention of serious medication errors , 1999, Journal of Clinical Monitoring and Computing.

[14]  I. Sim,et al.  Physicians' use of electronic medical records: barriers and solutions. , 2004, Health affairs.