Literature DB >> 18497613

Automatic time-motion study of a multistep preoperative process.

Mark A Meyer1, Andreas R Seim, Pamela Fairbrother, Marie T Egan, Warren S Sandberg.   

Abstract

BACKGROUND: Hospitals use time-motion studies to monitor process effectiveness and patient waiting. Manual tracking is labor-intensive and potentially influences system performance. New technology known as indoor positioning systems (IPS) may allow automatic monitoring of patient waiting and progress. The authors tested whether an IPS can track patients through a multistep preoperative process.
METHODS: The authors used an IPS between October 14, 2005, and June 13, 2006, to track patients in a multistep ambulatory preoperative process: needle localization and excisional biopsy of a breast lesion. The process was distributed across the ambulatory surgery and radiology departments of a large academic hospital. Direct observation of the process was used to develop a workflow template. The authors then developed software to convert the IPS data into usable time-motion data suitable for monitoring process efficiency over time.
RESULTS: The authors assigned tags to 306 patients during the study period. Eighty patients never underwent the procedure or never had their tag affixed. One hundred seventy-seven (78%) of the remaining 226 patients successfully matched the workflow template. Process time stamps were automatically extracted from the successful matches, measuring time before radiology (mean +/- SD, 77 +/- 35 min), time in radiology (105 +/- 35 min), and time between radiology and operating room (80 +/- 60 min), which summed to total preoperative time (261 +/- 67 min).
CONCLUSIONS: The authors have demonstrated that it is possible to use a combination of IPS technology and sequence alignment pattern matching software to automate the time-motion study of patients in a multidepartment, multistep process with the only day-of-surgery intervention being the application of a tag when the patient arrives.

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Year:  2008        PMID: 18497613     DOI: 10.1097/ALN.0b013e31817302ca

Source DB:  PubMed          Journal:  Anesthesiology        ISSN: 0003-3022            Impact factor:   7.892


  2 in total

1.  Modeling the impact of changing patient transportation systems on peri-operative process performance in a large hospital: insights from a computer simulation study.

Authors:  Danny Segev; Retsef Levi; Peter F Dunn; Warren S Sandberg
Journal:  Health Care Manag Sci       Date:  2012-02-14

2.  Time-motion analysis of research nurse activities in a lung transplant home monitoring study.

Authors:  Ruth Lindquist; Arin VanWormer; Bruce Lindgren; Kathleen MacMahon; William Robiner; Stanley Finkelstein
Journal:  Prog Transplant       Date:  2011-09       Impact factor: 1.065

  2 in total

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