title: Automatic time-motion study of a multistep preoperative process.
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.
authors.affiliation: Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Meyer
authors.forename: Andreas R
authors.initials: AR
authors.lastname: Seim
authors.forename: Pamela
authors.initials: P
authors.lastname: Fairbrother
authors.forename: Marie T
authors.initials: MT
authors.lastname: Egan
authors.forename: Warren S
authors.initials: WS
authors.lastname: Sandberg
mesh_terms: D001707:Biopsy, Needle; D001943:Breast Neoplasms / Q000473:pathology*; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D001330:Electronic Data Processing / Q000379:methods / Q000706:statistics & numerical data; D005260:Female; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006801:Humans; D008404:Massachusetts; D010044:Outpatient Clinics, Hospital / Q000706:statistics & numerical data; D010045:Outpatients / Q000706:statistics & numerical data*; D010355:Patient Identification Systems / Q000379:methods / Q000706:statistics & numerical data; D011300:Preoperative Care / Q000379:methods*; D017064:Process Assessment, Health Care / Q000379:methods / Q000706:statistics & numerical data*; D011872:Radiology Department, Hospital / Q000706:statistics & numerical data; D012985:Software Design; D013996:Time and Motion Studies