Effectiveness of Automated Notification and Customer Service Call Centers for Timely and Accurate Reporting of Critical Values: A Laboratory Medicine Best Practices Systematic Review and Meta-Analysis

Liebow, Edward B.; Derzon, James H.; Fontanesi, John; Favoretto, Alessandra M.; Baetz, Rich Ann; Shaw, Colleen; Thompson, Pamela; Mass, Diana; Christenson, Robert; Epner, Paul; Snyder, Susan R.

doi:10.1016/j.clinbiochem.2012.06.023

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Effectiveness of Automated Notification and Customer Service Call Centers for Timely and Accurate Reporting of Critical Values: A Laboratory Medicine Best Practices Systematic Review and Meta-Analysis

Published Date:

Jun 29 2012

Publisher's site:

http://dx.doi.org/10.1016/j.clinbiochem.2012.06.023 New Site Icon

Source:

Clin Biochem. 45(0):979-987

Language:

English

[PDF-1.00 MB]

Details:

Personal Authors:

Liebow, Edward B. ; Derzon, James H. ; Fontanesi, John ; Favoretto, Alessandra M. ; Baetz, Rich Ann ; ... More ▼

Keywords:

[+]

Pubmed ID:

22750773

Pubmed Central ID:

PMC4518392

Description:

Objective

To conduct a systematic review of automatic notification methods and consider evidence-based recommendations for best practices in improving the timeliness and accuracy of critical value reporting.

Results

196 bibliographic records were identified, with nine meeting review inclusion criteria. Four studies examined automated notification systems and five assessed call center performance. Average improvement from implementing automated notification systems is d = 0.42 (95% CI = 0.2 – 0.62) while the average odds ratio for call centers is OR = 22.1 (95% CI = 17.1 – 28.6).

Conclusions

The evidence, though suggestive, is not sufficient to make a recommendation for or against using automated notification systems as a best practice to improve the timeliness and accuracy of critical value reporting in an in-patient care setting. Call centers, however, are effective in improving the timeliness and accuracy of critical value reporting in an in-patient care setting, and are recommended as an “evidence-based best practice.”

Document Type:

Journal Article

Collection(s):

CDC Public Access

Funding:

CC999999/Intramural CDC HHS/United States

Supporting Files:

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