Skip Navigation
Skip to contents

J Korean Acad Nurs : Journal of Korean Academy of Nursing

Search
Advanced Search
OPEN ACCESS
mobile search button mobile menu button

Articles

Page Path
HOME > J Korean Acad Nurs > Volume 42(4); 2012 > Article
Original Article
Medication Error Management Climate and Perception for System Use according to Construction of Medication Error Prevention System
Myoung Soo Kim
Journal of Korean Academy of Nursing 2012;42(4):568-578.
DOI: https://doi.org/10.4040/jkan.2012.42.4.568
Published online: August 12, 2012

Department of Nursing, Pukyong National University, Busan, Korea

Department of Nursing, Pukyong National University, Busan, Korea

Address reprint requests to : Kim, Myoung Soo Department of Nursing, Pukyong National University, 599-1 Daeyeon 3-dong, Nam-gu, Busan 608-737, Korea Tel: +82-51-629-5782 Fax: +82-51-629-7906 E-mail: kanosa@pknu.ac.kr
• Received: October 18, 2011   • Revised: October 31, 2011   • Accepted: July 24, 2012

Copyright © 2012 Korean Society of Nursing Science

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 8 Views
  • 0 Download
prev next
Full Article

Download PDF Download PDF

  • Purpose
    The purpose of this cross-sectional study was to examine current status of IT-based medication error prevention system construction and the relationships among system construction, medication error management climate and perception for system use.
  • Methods
    The participants were 124 patient safety chief managers working for 124 hospitals with over 300 beds in Korea. The characteristics of the participants, construction status and perception of systems (electric pharmacopoeia, electric drug dosage calculation system, computer-based patient safety reporting and bar-code system) and medication error management climate were measured in this study. The data were collected between June and August 2011. Descriptive statistics, partial Pearson correlation and MANCOVA were used for data analysis.
  • Results
    Electric pharmacopoeia were constructed in 67.7% of participating hospitals, computer-based patient safety reporting systems were constructed in 50.8%, electric drug dosage calculation systems were in use in 32.3%. Bar-code systems showed up the lowest construction rate at 16.1% of Korean hospitals. Higher rates of construction of IT-based medication error prevention systems resulted in greater safety and a more positive error management climate prevailed.
  • Conclusion
    The supportive strategies for improving perception for use of IT-based systems would add to system construction, and positive error management climate would be more easily promoted.
  • Keywords: Medication errors; Safety management; Culture; Perception
Table 1.
Demographic and Hospital related Characteristics of Participants (N=124)
Characteristics Categories n (%) M±SD
Gender Male 8 (6.5)
Female 116 (93.5)
Age (yr) 22-29 5 (4.0) 41.28±7.43
30-39 42 (33.9)
40-49 60 (48.4)
≥50 17 (13.7)
Marital status Married 101 (81.5)
Single 23 (18.5)
Educational status Diploma 13 (10.5)
BSN 54 (43.5)
MSN 48 (38.7)
Doctoral course or higher 9 (7.3)
Total clinical experience (yr) < 5 23 (18.5) 13.12±7.71
5 -< 10 21 (16.9)
10 -< 15 27 (21.8)
≥15 53 (42.7)
Clinical experience in current position (yr) < 3 62 (50.0) 4.49±4.40
3 -< 5 18 (14.5)
5 -< 10 32 (25.8)
10 -< 15 7 (5.6)
≥15 5 (4.0)
Number of beds < 300 18 (14.5)
300 -< 500 47 (37.9)
500 -< 700 26 (21.0)
700 -< 1,000 27 (21.8)
≥1,000 6 (4.8)
Hospital type Secondary 97 (78.2)
Third 27 (21.8)

BSN=Bachelor of science in nursing; MSN=Master of science in nursing.

Table 2.
Current Status on Construction of Medication Error Prevention System (N=124)
System Characteristics Categories n (%)
Electric pharmacopoeia Knowledge Yes 105 (84.7)
No 19 (15.3)
Construct or use Yes 84 (67.7)
No 40 (32.3)
Type (n=84) KIMS 51 (41.1)
Developed by own hospital 23 (18.5)
Bit drug info 10 (8.0)
Reason for inability Deficiency in information 28 (33.3)
to establish Deficiency in personal needs 24 (28.6)
Deficiency in orientation/training 20 (23.8)
Deficiency in hospital support 12 (14.3)
Patient safety Knowledge Yes 113 (91.1)
reporting system No 11 (8.9)
Construct Yes 98 (79.0)
No 26 (21.0)
Type (n=98) Computer-based only* 42 (33.9)
Computer-based+Paper-based*† 13 (10.5)
Computer-based +Verbal-based*‡ 3 (2.4)
All of the above* 5 (4.0)
Paper-based only† 46 (37.1)
Paper-based+Verbal-based only†‡ 6 (4.8)
Verbal-based only‡ 9 (7.3)
Anonymity ⓐ Real-name use 56 (45.2)
ⓑ Anonymity guaranteed 37 (29.8)
ⓒ Anonymity guaranteed but revealed real name 11 (8.9)
ⓐ+ⓒ 13 (10.5)
ⓐ+ⓑ 4 (3.2)
ⓑ+ⓒ 2 (1.6)
ⓐ+ⓑ+ⓒ 1 (0.8)
Reason for inability Deficiency in information 6 (23.0)
to establish (n=26) Deficiency in institutional need 6 (23.0)
Deficiency in orientation/training 6 (23.0)
Staff shortage/Overload 5 (19.0)
Institutional cultural trait 2 (8.0)
Deficiency of personal needs 1 (4.0)
Electric drug dosage Knowledge Yes 65 (52.4)
calculation system No 59 (47.6)
Construct Yes 40 (32.3)
No 84 (67.7)
Type (n=40) Unit based developed program 8 (20.0)
EMR based 32 (80.0)
Reason for inability Deficiency in institutional needs 26 (31.0)
to establish (n=84) Deficiency in economic support 22 (26.2)
Deficiency in information 18 (21.4)
Deficiency in orientation/training 5 (6.0)
Delayed construction 5 (6.0)
Deficiency in personal need 2 (2.4)
Institutional cultural trait 3 (3.6)
Staff shortage/Overload 1 (1.2)
Communication problem 1 (1.2)
Others 1 (1.2)
Barcode system Knowledge Yes 104 (83.9)
No 20 (16.1)
Construct Yes 20 (16.1)
No 104 (83.9)
Type (n=20) Unit based developed program 3 (15.0)
Link to the EMR 17 (85.0)
Reason for inability Deficiency in economic support 59 (56.7)
to establish (n=104) Deficiency in institutional needs 25 (24.0)
Institutional cultural trait 7 (6.7)
Delayed constructing 6 (5.8)
Deficiency in information 3 (2.9)
Staff shortage/Overload 2 (1.9)
Deficiency in orientation/training 2 (1.9)

KIMS=Korean index of medical specialties; EMR=Electronic medical record. *Computer-based reporting system=50.8 %;

†Paper-based reporting system=54.9 %;

‡Verbal-based reporting system=14.5 %.

Table 3.
Error Management Climate, Perception on Medication Error Prevention System (MEPS) Use according to MEPS Construction (N=124)
Categories n (%) Error management climate
 Perception on program use
Learn from medication errors
 Thinking about medication errors
 Medication error competence
 Medication error communication
M±SD M±SD M±SD M±SD M±SD
EP Yes 84 (67.7) 4.32±.056 4.17±0.53 3.59±0.56 4.04±0.58 7.20±1.11
No 40(32.3) 4.08±0.52 3.85±0.83 3.56±0.61 3.62±0.82 6.87±1.59
t (p) 2.29 (.024) 2.25 (.028) 2.13 (.035) 2.89 (.005) 0.92 (.368)
PSRS Yes 98 (79.0) 4.28±0.53 4.10±0.58 3.50±0.55 3.92±0.64 7.10±1.26
No 26 (21.0) 4.12±0.64 3.97±0.89 3.57±0.71 3.84±0.85 7.56±0.50
t (p) 1.33 (.185) 0.65 (.518) −0.50 (.618) 0.52 (.601) −2.15 (.047)
DDCS Yes 40 (32.3) 4.39±0.49 4.18±0.58 3.59±0.53 4.08±0.57 7.25±1.11
No 84 (67.7) 4.18±0.57 4.02±0.69 3.48±0.61 3.82±0.73 7.06±1.29
t (p) 2.01 (.037) 1.23 (.222) 1.02 (.311) 1.96 (.053) 0.74 (.459)
BS Yes 20 (16.1) 4.30±0.48 4.25±0.55 3.60±0.46 4.16±0.59 7.44±1.07
No 104 (83.9) 4.23±0.57 4.04±0.67 3.50±0.61 3.85±0.70 7.06±1.25
t (p) 0.49 (.624) 1.34 (.183) 0.70 (.487) 1.85 (.067) 1.26 (.211)

EP=Electric pharmacopoeia; PSRS=Patient safety reporting system; DDCS=Drug dosage calculation system; BS=Barcode system.

Table 4.
Partial Correlation among Research Variables (N=124)
Variables MEPS construction
 EMC 1
 EMC 2
 EMC 3
 EMC 4
 Total EMC
r (p) r (p) r (p) r (p) r (p) r (p)
MEPS construction 1.00
EMC 1-learn from medication errors .28 (.005) 1.00
EMC 2-thinking about medication errors .37 (< .001) .46 (< .001) 1.00
EMC 3-medication error competence .13 (.201) .36 (< .001) .71 (< .001) 1.00
EMC 4-medication error communication .20 (.042) .14 (.150) .62 (< .001) .52 (< .001) 1.00
Total EMC .34 (.001) .63 (< .001) .93 (< .001) .81 (< .001) .74 (< .001) 1.00
Perception on MEPS use .13 (.182) .27 (.005) .30 (.003) .29 (.003) .30 (.002) .37 (< .001)

MEPS=Medication error prevention system; EMC=Error management climate.

Table 5.
Differences in Error Management Climate and Perception on Medication Error Prevention System Use according to MEPS Construction (N=106)
Variables Categories Pillai trace (p) F df sig. eta2
Covariate Gender Learn from medication errors .35 (.88) 1.48 1 .227 .02
Thinking about medication errors 0.01 1 .999 .00
Medication error competence 0.01 1 .937 .00
Medication error communication 0.04 1 .837 .00
Perception on MEPS use 0.02 1 .879 .00
Age (yr) Learn from medication errors 1.54(.19) 0.05 1 .822 .00
Thinking about medication errors 3.15 1 .079 .03
Medication error competence 0.20 1 .655 .00
Medication error communication 0.01 1 .917 .00
Perception on MEPS use 0.17 1 .680 .00
Education Learn from medication errors 1.34 (.26) 4.05 1 .047 .04
Thinking about medication errors 2.52 1 .115 .03
Medication error competence 0.57 1 .451 .00
Medication error communication 2.64 1 .108 .03
Perception on MEPS use 0.69 1 .407 .01
Nursing experience Learn from medication errors 1.44 (.22) 0.80 1 .374 .01
Thinking about medication errors 0.01 1 .945 .00
Medication error competence 0.15 1 .703 .00
Medication error communication 2.11 1 .150 .02
Perception on MEPS use 0.56 1 .458 .01
Independent variable MEPS Learn from medication errors 1.79 (.04) 2.99 3 .035 .08
construction Thinking about medication errors 6.21 3 .001 .16
Medication error competence 0.74 3 .533 .02
Medication error communication 1.77 3 .157 .05
Perception on MEPS use 0.82 3 .486 .02

MEPS=Medication error prevention system.

  • Ambrisko T. D., Nemeth, T. 2004;A computer program for calculation of doses and prices of injectable medications based on body weight or body surface area. Canadian Journal of Veterinary Research. 68:62–65.PubMedPMC
  • Cigularov K. P., Chen P. Y., Rosecrance, J. 2010;The effects of error management climate and safety communication on safety: A multilevel study. Accident Analysis & Prevention. 42:1498–1506. http://dx.doi.org/10.1016/j.aap.2010.01.003Article
  • Crespin D. J., Modi A. V., Wei D., Williams C. E., Greene S. B., Pierson S., et al. 2010;Repeat medication errors in nursing homes: Contributing factors and their association with patient harm. The American Journal of Geriatric Pharmacotherapy. 8:258–270. http://dx.doi.org/10.1016/j.amjopharm.2010.05.005ArticlePubMed
  • Dilles T., Elseviers M. M., Van Rompaey B., Van Bortel L. M., Stichele R.R. 2011;Barriers for nurses to safe medication management in nursing homes. Journal of Nursing Scholarship. 43:171–180. http://dx.doi.org/10.1111/j.1547-5069.2011.01386.xArticlePubMed
  • Elder N. C., Graham D., Brandt E., Hickner, J. 2007;Barriers and mo-tivators for making error reports from family medicine offices: A report from the American Academy of Family Physicians National Research Network (AAFP NRN). Journal of the American Board of Family Medicine. 20:115–123. http://dx.doi.org/10.3122/jabfm.2007.02.060081ArticlePubMed
  • Force M. V., Deering L., Hubbe J., Andersen M., Hagemann B., Cooper-Hahn M., et al. 2006;Effective strategies to increase reporting of medication errors in hospitals. The Journal of Nursing Administration. 36:34–41.ArticlePubMed
  • Haw C., Stubbs J., Yorston, G. 2008;Antipsychotics for BPSD: An audit of prescribing practice in a specialist psychiatric inpatient unit. International Psychogeriatrics. 20:790–799. http://dx.doi.org/10.1017/S1041610208006819ArticlePubMed
  • Heard G. C., Sanderson P. M., Thomas R.D. 2012;Barriers to adverse event and error reporting in anesthesia. Anesthesia and Analgesia. 114:604–614. http://dx.doi.org/10.1213/ANE.0b013e31822649e8ArticlePubMed
  • Hoddinott S. N., Bass M.J. 1986;The dillman total design survey method. Canadian Family Physician Médecin De Famille Cana-dien. 32:2366–2368.
  • Homsma G. J., Van Dyck C., De Gilder D., Koopman P. L., Elfring, T. 2009;Learning from error: The influence of error incident characteristics. Journal of Business Research. 62:115–122. http://dx.doi.org/10.1016/j.jbusres.2007.12.003Article
  • Khajouei R., Wierenga P. C., Hasman A., Jaspers M. W.M. 2011;Clinicians satisfaction with CPOE ease of use and effect on clinicians' workflow, efficiency and medication safety. International Journal of Medical Informatics. 80:297–309. http://dx.doi.org/10.1016/j.ijmedinf.2011.02.009ArticlePubMed
  • Kim C. H., Kim, M. 2009;Defining reported errors on web-based reporting system using ICPS from nine units in a Korean university hospital. Asian Nursing Research. 3:167–176. http://dx.doi.org/10.1016/S1976-1317(09)60028-1ArticlePubMed
  • Kim J., Bates D.W. 2006;Results of a survey on medical error reporting systems in Korean hospitals. International Journal of Medical Informatics. 75:148–155. http://dx.doi.org/10.1016/j.ijmedinf.2005.06.005ArticlePubMed
  • Kim J.K. 2011;May 25. Construction rate of EMR, hospital 66%, clinic 52%. Korea Healthlog. Retrieved September 21, 2011, from. http://doc3.koreahealthlog.com/46751
  • Kim K. S., Kwon S. H., Kim J. A., Cho S.H. 2011;Nurses' perceptions of medication errors and their contributing factors in South Korea. Journal of Nursing Management. 19:346–353. http://dx.doi.org/10.1111/j.1365-2834.2011.01249.xArticlePubMed
  • Kim M. S., Kim J. S., Jung I. S., Kim Y. H., Kim H.J. 2007;The effectiveness of the error reporting promoting program on the nursing error incidence rate in Korean operating rooms. Journal of Korean Academy of Nursing. 37:185–191.ArticlePubMedPDF
  • Mekhjian H. S., Bentley T. D., Ahmad A., Marsh, G. 2004;Development of a web-based event reporting system in an academic environment. Journal of the American Medical Informatics Association. 11:11–18. http://dx.doi.org/10.1197/jamia.M1349ArticlePubMedPMC
  • Milch C. E., Salem D. N., Pauker S. G., Lundquist T. G., Kumar S., Chen, J. 2006;Voluntary electronic reporting of medical errors and adverse events. An analysis of 92,547 reports from 26 acute care hospitals. Journal of General Internal Medicine. 21:165–170. http://dx.doi.org/10.1111/j.1525-1497.2006.00322.xArticlePubMedPMC
  • Poon E. G., Keohane C. A., Yoon C. S., Ditmore M., Bane A., Levtzion-Korach O., et al. 2010;Effect of bar-code technology on the safety of medication administration. The New England Journal of Medicine. 362:1698–1707. http://dx.doi.org/10.1056/NEJMsa0907115ArticlePubMed
  • Reason, J. 2004;Beyond the organisational accident: The need for "error wisdom" on the frontline. Quality & Safety in Health Care. 13:ii28–ii33. http://dx.doi.org/10.1136/qshc.2003.009548Article
  • Simpson J.B. 2001;A unique approach for reducing specimen labeling errors: Combining marketing techniques with performance improvement. Clinical Leadership & Management Review: The Journal of CLMA. 15:401–405.
  • Southard, K. 2005;Bar coding medication administration: Preparing the culture for change. Nurse Leader. 3(3):53–55. http://dx.doi.org/10.1016/j.mnl.2005.02.009Article
  • Tabachnick B. G., Fidell L.S. 2001.Using multivariate statistics. 4th ed.Boston, MA: Allyn & Bacon.
  • Thomsen L. A., Winterstein A. G., Søndergaard B., Haugbølle L. S., Melander, A. 2007;Systematic review of the incidence and characteristics of preventable adverse drug events in ambulatory care. The Annals of Pharmacotherapy. 41:1411–1426. http://dx.doi.org/10.1345/aph.1H658ArticlePubMedPDF
  • Tsai S. L., Sun Y. C., Taur F.M. 2010;Comparing the working time between bar-code medication administration system and traditional medication administration system: An observational study. International Journal of Medical Informatics. 79:681–689. http://dx.doi.org/10.1016/j.ijmedinf.2010.07.002ArticlePubMed
  • van Dyck C., Frese M., Baer M., Sonnentag, S. 2005;Organizational error management culture and its impact on performance: A two-study replication. Journal of Applied Psychology. 90:1228–1240. http://dx.doi.org/10.1037/0021-9010.90.6.1228ArticlePubMed
  • Wideman M. V., Whittler M. E., Anderson T.M. 2005.Barcode medication administration: Lessons learned from an intensive care unit implementation. In: Henriksen K., Battles J.B., Marks E.S., Lewin D.I., editors. Advances in patient safety: From research to implementation (volume 3: Implementation issues). Rockville, MD: Agency for Healthcare Research and Quality.
  • Wright A. A., Katz I.T. 2005;Bar coding for patient safety. The New England Journal of Medicine. 353:329–331. http://dx.doi.org/10.1056/NEJMp058101ArticlePubMed
  • Wulff K., Cummings G. G., Marck P., Yurtseven, O. 2011;Medication administration technologies and patient safety: A mixed-method systematic review. Journal of Advanced Nursing. 67:2080–2095. http://dx.doi.org/10.1111/j.1365-2648.2011.05676.xArticlePubMed
  • Yamamoto L., Kanemori, J. 2010;Comparing errors in ED computer-assisted vs conventional pediatric drug dosing and administration. American Journal of Emergency Medicine. 28:588–592. http://dx.doi.org/10.1016/j.ajem.2009.02.009ArticlePubMed

Figure & Data

REFERENCES

    Citations

    Citations to this article as recorded by  

      • Cite
        CITE
        export Copy Download
        Close
        Download Citation
        Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.
        Format:
        • RIS — For EndNote, ProCite, RefWorks, and most other reference management software
        • BibTeX — For JabRef, BibDesk, and other BibTeX-specific software
        Include:
        • Citation for the content below
        Medication Error Management Climate and Perception for System Use according to Construction of Medication Error Prevention System
        J Korean Acad Nurs. 2012;42(4):568-578.   Published online August 12, 2012
        DOI: https://doi.org/10.4040/jkan.2012.42.4.568
        Close
      • XML DownloadXML Download
      We recommend
      Medication Error Management Climate and Perception for System Use according to Construction of Medication Error Prevention System
      Medication Error Management Climate and Perception for System Use according to Construction of Medication Error Prevention System
      Characteristics Categories n (%) M±SD
      Gender Male 8 (6.5)
      Female 116 (93.5)
      Age (yr) 22-29 5 (4.0) 41.28±7.43
      30-39 42 (33.9)
      40-49 60 (48.4)
      ≥50 17 (13.7)
      Marital status Married 101 (81.5)
      Single 23 (18.5)
      Educational status Diploma 13 (10.5)
      BSN 54 (43.5)
      MSN 48 (38.7)
      Doctoral course or higher 9 (7.3)
      Total clinical experience (yr) < 5 23 (18.5) 13.12±7.71
      5 -< 10 21 (16.9)
      10 -< 15 27 (21.8)
      ≥15 53 (42.7)
      Clinical experience in current position (yr) < 3 62 (50.0) 4.49±4.40
      3 -< 5 18 (14.5)
      5 -< 10 32 (25.8)
      10 -< 15 7 (5.6)
      ≥15 5 (4.0)
      Number of beds < 300 18 (14.5)
      300 -< 500 47 (37.9)
      500 -< 700 26 (21.0)
      700 -< 1,000 27 (21.8)
      ≥1,000 6 (4.8)
      Hospital type Secondary 97 (78.2)
      Third 27 (21.8)
      System Characteristics Categories n (%)
      Electric pharmacopoeia Knowledge Yes 105 (84.7)
      No 19 (15.3)
      Construct or use Yes 84 (67.7)
      No 40 (32.3)
      Type (n=84) KIMS 51 (41.1)
      Developed by own hospital 23 (18.5)
      Bit drug info 10 (8.0)
      Reason for inability Deficiency in information 28 (33.3)
      to establish Deficiency in personal needs 24 (28.6)
      Deficiency in orientation/training 20 (23.8)
      Deficiency in hospital support 12 (14.3)
      Patient safety Knowledge Yes 113 (91.1)
      reporting system No 11 (8.9)
      Construct Yes 98 (79.0)
      No 26 (21.0)
      Type (n=98) Computer-based only* 42 (33.9)
      Computer-based+Paper-based*† 13 (10.5)
      Computer-based +Verbal-based*‡ 3 (2.4)
      All of the above* 5 (4.0)
      Paper-based only† 46 (37.1)
      Paper-based+Verbal-based only†‡ 6 (4.8)
      Verbal-based only‡ 9 (7.3)
      Anonymity ⓐ Real-name use 56 (45.2)
      ⓑ Anonymity guaranteed 37 (29.8)
      ⓒ Anonymity guaranteed but revealed real name 11 (8.9)
      ⓐ+ⓒ 13 (10.5)
      ⓐ+ⓑ 4 (3.2)
      ⓑ+ⓒ 2 (1.6)
      ⓐ+ⓑ+ⓒ 1 (0.8)
      Reason for inability Deficiency in information 6 (23.0)
      to establish (n=26) Deficiency in institutional need 6 (23.0)
      Deficiency in orientation/training 6 (23.0)
      Staff shortage/Overload 5 (19.0)
      Institutional cultural trait 2 (8.0)
      Deficiency of personal needs 1 (4.0)
      Electric drug dosage Knowledge Yes 65 (52.4)
      calculation system No 59 (47.6)
      Construct Yes 40 (32.3)
      No 84 (67.7)
      Type (n=40) Unit based developed program 8 (20.0)
      EMR based 32 (80.0)
      Reason for inability Deficiency in institutional needs 26 (31.0)
      to establish (n=84) Deficiency in economic support 22 (26.2)
      Deficiency in information 18 (21.4)
      Deficiency in orientation/training 5 (6.0)
      Delayed construction 5 (6.0)
      Deficiency in personal need 2 (2.4)
      Institutional cultural trait 3 (3.6)
      Staff shortage/Overload 1 (1.2)
      Communication problem 1 (1.2)
      Others 1 (1.2)
      Barcode system Knowledge Yes 104 (83.9)
      No 20 (16.1)
      Construct Yes 20 (16.1)
      No 104 (83.9)
      Type (n=20) Unit based developed program 3 (15.0)
      Link to the EMR 17 (85.0)
      Reason for inability Deficiency in economic support 59 (56.7)
      to establish (n=104) Deficiency in institutional needs 25 (24.0)
      Institutional cultural trait 7 (6.7)
      Delayed constructing 6 (5.8)
      Deficiency in information 3 (2.9)
      Staff shortage/Overload 2 (1.9)
      Deficiency in orientation/training 2 (1.9)
      Categories n (%) Error management climate
      		 Perception on program use
      Learn from medication errors
      		 Thinking about medication errors
      		 Medication error competence
      		 Medication error communication
      M±SD M±SD M±SD M±SD M±SD
      EP Yes 84 (67.7) 4.32±.056 4.17±0.53 3.59±0.56 4.04±0.58 7.20±1.11
      No 40(32.3) 4.08±0.52 3.85±0.83 3.56±0.61 3.62±0.82 6.87±1.59
      t (p) 2.29 (.024) 2.25 (.028) 2.13 (.035) 2.89 (.005) 0.92 (.368)
      PSRS Yes 98 (79.0) 4.28±0.53 4.10±0.58 3.50±0.55 3.92±0.64 7.10±1.26
      No 26 (21.0) 4.12±0.64 3.97±0.89 3.57±0.71 3.84±0.85 7.56±0.50
      t (p) 1.33 (.185) 0.65 (.518) −0.50 (.618) 0.52 (.601) −2.15 (.047)
      DDCS Yes 40 (32.3) 4.39±0.49 4.18±0.58 3.59±0.53 4.08±0.57 7.25±1.11
      No 84 (67.7) 4.18±0.57 4.02±0.69 3.48±0.61 3.82±0.73 7.06±1.29
      t (p) 2.01 (.037) 1.23 (.222) 1.02 (.311) 1.96 (.053) 0.74 (.459)
      BS Yes 20 (16.1) 4.30±0.48 4.25±0.55 3.60±0.46 4.16±0.59 7.44±1.07
      No 104 (83.9) 4.23±0.57 4.04±0.67 3.50±0.61 3.85±0.70 7.06±1.25
      t (p) 0.49 (.624) 1.34 (.183) 0.70 (.487) 1.85 (.067) 1.26 (.211)
      Variables MEPS construction
      		 EMC 1
      		 EMC 2
      		 EMC 3
      		 EMC 4
      		 Total EMC
      r (p) r (p) r (p) r (p) r (p) r (p)
      MEPS construction 1.00
      EMC 1-learn from medication errors .28 (.005) 1.00
      EMC 2-thinking about medication errors .37 (< .001) .46 (< .001) 1.00
      EMC 3-medication error competence .13 (.201) .36 (< .001) .71 (< .001) 1.00
      EMC 4-medication error communication .20 (.042) .14 (.150) .62 (< .001) .52 (< .001) 1.00
      Total EMC .34 (.001) .63 (< .001) .93 (< .001) .81 (< .001) .74 (< .001) 1.00
      Perception on MEPS use .13 (.182) .27 (.005) .30 (.003) .29 (.003) .30 (.002) .37 (< .001)
      Variables Categories Pillai trace (p) F df sig. eta2
      Covariate Gender Learn from medication errors .35 (.88) 1.48 1 .227 .02
      Thinking about medication errors 0.01 1 .999 .00
      Medication error competence 0.01 1 .937 .00
      Medication error communication 0.04 1 .837 .00
      Perception on MEPS use 0.02 1 .879 .00
      Age (yr) Learn from medication errors 1.54(.19) 0.05 1 .822 .00
      Thinking about medication errors 3.15 1 .079 .03
      Medication error competence 0.20 1 .655 .00
      Medication error communication 0.01 1 .917 .00
      Perception on MEPS use 0.17 1 .680 .00
      Education Learn from medication errors 1.34 (.26) 4.05 1 .047 .04
      Thinking about medication errors 2.52 1 .115 .03
      Medication error competence 0.57 1 .451 .00
      Medication error communication 2.64 1 .108 .03
      Perception on MEPS use 0.69 1 .407 .01
      Nursing experience Learn from medication errors 1.44 (.22) 0.80 1 .374 .01
      Thinking about medication errors 0.01 1 .945 .00
      Medication error competence 0.15 1 .703 .00
      Medication error communication 2.11 1 .150 .02
      Perception on MEPS use 0.56 1 .458 .01
      Independent variable MEPS Learn from medication errors 1.79 (.04) 2.99 3 .035 .08
      construction Thinking about medication errors 6.21 3 .001 .16
      Medication error competence 0.74 3 .533 .02
      Medication error communication 1.77 3 .157 .05
      Perception on MEPS use 0.82 3 .486 .02
      Table 1. Demographic and Hospital related Characteristics of Participants (N=124)

      BSN=Bachelor of science in nursing; MSN=Master of science in nursing.

      Table 2. Current Status on Construction of Medication Error Prevention System (N=124)

      KIMS=Korean index of medical specialties; EMR=Electronic medical record. *Computer-based reporting system=50.8 %;

      Paper-based reporting system=54.9 %;

      Verbal-based reporting system=14.5 %.

      Table 3. Error Management Climate, Perception on Medication Error Prevention System (MEPS) Use according to MEPS Construction (N=124)

      EP=Electric pharmacopoeia; PSRS=Patient safety reporting system; DDCS=Drug dosage calculation system; BS=Barcode system.

      Table 4. Partial Correlation among Research Variables (N=124)

      MEPS=Medication error prevention system; EMC=Error management climate.

      Table 5. Differences in Error Management Climate and Perception on Medication Error Prevention System Use according to MEPS Construction (N=106)

      MEPS=Medication error prevention system.

      Table 1.

      Table 2.

      Table 3.

      Table 4.

      Table 5.

      J Korean Acad Nurs : Journal of Korean Academy of Nursing
      © Korean Society of Nursing Science.
      Close layer
      TOP