Literature DB >> 16255327

Critical laboratory value notification: a failure mode effects and criticality analysis.

Sunita Saxena1, Raymond Kempf, Susan Wilcox, Ira A Shulman, Louise Wong, Glenn Cunningham, Elaine Vega, Stephanie Hall.   

Abstract

BACKGROUND: The Failure Mode Effects and Criticality Analysis (FMECA) was applied to improve the timeliness of reporting and the timeliness of receipt by the responsible licensed caregiver of critical laboratory values (CLVs) for outpatients and non-critical care inpatients.
METHODS: Through a risk prioritization process, the most important areas for improvement, including contacting the provider, assisting the provider in contacting the patient, and educating the provider in follow-up options available during off hours, were identified. ACTIONS TAKEN: A variety of systemic improvements were made; for example, the CLV notification process was centralized in the customer service center, with databases to help providers select options and make arrangements for follow-up care and an electronic abstract form to document the CLV notification process. Review of documentation and appropriateness of CLV follow-up care was integrated into the quality monitoring process to detect any variations or problems.
RESULTS: The average CLV notification time for the month steadily declined during an eight-month period. Compliance was 100% for the "read-back" requirement and documentation in patient's health record. DISCUSSION: This proactive risk assessment project successfully modified the CLV notification program from a high- to a low-risk process, identified activities to further improve the process, and helped ensure compliance with a variety of requirements.

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Mesh:

Year:  2005        PMID: 16255327     DOI: 10.1016/s1553-7250(05)31064-6

Source DB:  PubMed          Journal:  Jt Comm J Qual Patient Saf        ISSN: 1553-7250


  7 in total

Review 1.  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.

Authors:  Edward B Liebow; James H Derzon; John Fontanesi; Alessandra M Favoretto; Rich Ann Baetz; Colleen Shaw; Pamela Thompson; Diana Mass; Robert Christenson; Paul Epner; Susan R Snyder
Journal:  Clin Biochem       Date:  2012-06-29       Impact factor: 3.281

Review 2.  Laboratory results that should be ignored.

Authors:  Dirk M Elston
Journal:  MedGenMed       Date:  2006-10-11

3.  Computerized Provider Order Entry with Pager Notification Improves Efficiency in STAT Radiographic Studies and Respiratory Treatments.

Authors:  Brian R Jacobs; Eric Crotty; Ed Conway; Kim Ward Hart; Craig Dietrich; Scott Pettinichi; John Racadio
Journal:  Appl Clin Inform       Date:  2010-02-12       Impact factor: 2.342

Review 4.  The safety implications of missed test results for hospitalised patients: a systematic review.

Authors:  Joanne Callen; Andrew Georgiou; Julie Li; Johanna I Westbrook
Journal:  BMJ Qual Saf       Date:  2011-02-07       Impact factor: 7.035

5.  Analysis of factors influencing the generation of unqualified clinical samples and measures to prevent this generation.

Authors:  Xiaofei Lai; Ping Yang; Yuhong Zhang; Ju Cao; Liping Zhang
Journal:  Ann Lab Med       Date:  2012-04-18       Impact factor: 3.464

6.  Application of a proactive risk analysis to emergency department sickle cell care.

Authors:  Victoria L Thornton; Jane L Holl; David M Cline; Caroline E Freiermuth; Dori T Sullivan; Paula Tanabe
Journal:  West J Emerg Med       Date:  2014-07

7.  Benefits of VISION Max automated cross-matching in comparison with manual cross-matching: A multidimensional analysis.

Authors:  Hee-Jung Chung; Mina Hur; Sang Gyeu Choi; Hyun-Kyung Lee; Seungho Lee; Hanah Kim; Hee-Won Moon; Yeo-Min Yun
Journal:  PLoS One       Date:  2019-12-23       Impact factor: 3.240

  7 in total

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