Document Detail


Decreasing extremes in patient waiting time.
MedLine Citation:
PMID:  20351538     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
INTRODUCTION: We present a conceptual framework for approaching reducing excessive patient wait time in an outpatient setting. We hypothesized that statistical process control techniques can be used to identify extremes in waiting time; root cause analysis can be used to identify specific delay causes; and minimizing the contribution of the root causes will lead to an improvement in system performance. SUBJECT AND METHOD: We conducted a prospective study of waiting times in a private outpatient clinic providing high-risk obstetrical care. The baseline period consisted of 55 clinic sessions, and the intervention period consisted of 101 clinic sessions. RESULTS: Mean waiting time was prolonged during 9 (16.4%) baseline clinic sessions. The root cause analysis determined that appointment schedule, physician tardiness, and patient complexity contributed to clinic delays. After making changes to minimize root causes, there was a significant reduction in prolonged waiting times (16.4% vs 4.9%, Yates chi(2) = 4.37, P = .037); a significant decrease in mean waiting time (32.7 +/- 23.6 minutes vs 29.3 +/- 21.2 minutes, t = 3.42, P < .001); and a significant improvement in the waiting time distribution (Kruskal-Wallis test of homogeneity, P = .003). CONCLUSIONS: Our methodology was successful in identifying and reducing factors associated with prolonged wait times. However, although system operation was improved, as defined by a decrease in the occurrence of excessive clinic delays, effecting a large and sustained decrease in patient waiting times was challenging.
Authors:
Lynn J Groome; E J Mayeaux
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Quality management in health care     Volume:  19     ISSN:  1550-5154     ISO Abbreviation:  Qual Manag Health Care     Publication Date:    2010 Apr-Jun
Date Detail:
Created Date:  2010-03-30     Completed Date:  2010-06-28     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9306156     Medline TA:  Qual Manag Health Care     Country:  United States    
Other Details:
Languages:  eng     Pagination:  117-28     Citation Subset:  H    
Affiliation:
Department of Obstetrics and Gynecology, Louisiana State University Health Sciences Center, Shreveport, LA 71130, USA. lgroom@lsuhsc.edu
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Ambulatory Care Facilities / organization & administration*
Causality
Efficiency, Organizational*
Female
Humans
Obstetrics
Pregnancy
Prospective Studies
Time Factors
Waiting Lists*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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