| Decreasing extremes in patient waiting time. | |
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MedLine Citation:
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PMID: 20351538 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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Lynn J Groome; E J Mayeaux |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Quality management in health care Volume: 19 ISSN: 1550-5154 ISO Abbreviation: Qual Manag Health Care Publication Date: 2010 Apr-Jun |
Date Detail:
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Created Date: 2010-03-30 Completed Date: 2010-06-28 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9306156 Medline TA: Qual Manag Health Care Country: United States |
Other Details:
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Languages: eng Pagination: 117-28 Citation Subset: H |
Affiliation:
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Department of Obstetrics and Gynecology, Louisiana State University Health Sciences Center, Shreveport, LA 71130, USA. lgroom@lsuhsc.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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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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