Paula A Newman-Casey1,2, John A Musser1, Leslie M Niziol1, Michele M Heisler3,4,5, Shivani S Kamat1, Manjool M Shah1, Nish Patel1, Amy M Cohn2,3. 1. Departments of Ophthalmology and Visual Sciences. 2. Institute for Healthcare Policy and Innovation. 3. Department of Industrial and Operations Engineering, University of Michigan. 4. Internal Medicine, University of Michigan Medical School. 5. Veterans Affairs Center for Practice Management and Outcomes Research, Veterans Affairs Healthcare System, Ann Arbor, MI.
Abstract
PURPOSE: The main purpose of this study was to use Lean analysis to identify how often and when wait times occur during a glaucoma visit to identify opportunities for additional patient engagement. METHODS: This prospective observational time-motion study measured process and wait times for 77 patient visits from 12 ophthalmologists at an academic glaucoma clinic over a 3-month period. Value stream maps visually diagramed the process of a clinical visit from the patient's perspective. Descriptive statistics were calculated for process times, wait times, and the frequency of 10+ minute wait times during each part of the visit. Key stakeholders participated in a root cause analysis to identify reasons for long wait times. The main outcome measure was average times (hours: minutes: seconds) for process times and wait times. RESULTS: Twenty-nine new visit (NV) patients and 48 return visit (RV) patients were included. Total time in clinic was 187.1±44.5 (mean±SD) minutes for NV patients and 102.0±44.7 minutes for RV patients. Wait time for NV patients was 63.7±33.4 minutes (33.1% of total appointment time) and for RV patients was 52.6±31.6 minutes (49.4% of the total appointment time). All NV patients and 87.5% of RV patients had at least one 10+ minute wait time during their clinic visit and the majority (75.9% NV, 60.4% RV) had >1. CONCLUSIONS: Currently, sufficient wait time exists during the visit for key portions of glaucoma education such as teaching eye drop instillation.
PURPOSE: The main purpose of this study was to use Lean analysis to identify how often and when wait times occur during a glaucoma visit to identify opportunities for additional patient engagement. METHODS: This prospective observational time-motion study measured process and wait times for 77 patient visits from 12 ophthalmologists at an academic glaucoma clinic over a 3-month period. Value stream maps visually diagramed the process of a clinical visit from the patient's perspective. Descriptive statistics were calculated for process times, wait times, and the frequency of 10+ minute wait times during each part of the visit. Key stakeholders participated in a root cause analysis to identify reasons for long wait times. The main outcome measure was average times (hours: minutes: seconds) for process times and wait times. RESULTS: Twenty-nine new visit (NV) patients and 48 return visit (RV) patients were included. Total time in clinic was 187.1±44.5 (mean±SD) minutes for NV patients and 102.0±44.7 minutes for RV patients. Wait time for NV patients was 63.7±33.4 minutes (33.1% of total appointment time) and for RV patients was 52.6±31.6 minutes (49.4% of the total appointment time). All NV patients and 87.5% of RV patients had at least one 10+ minute wait time during their clinic visit and the majority (75.9% NV, 60.4% RV) had >1. CONCLUSIONS: Currently, sufficient wait time exists during the visit for key portions of glaucoma education such as teaching eye drop instillation.
Authors: David S Friedman; Roger C W Wolfs; Benita J O'Colmain; Barbara E Klein; Hugh R Taylor; Shelia West; M Cristina Leske; Paul Mitchell; Nathan Congdon; John Kempen Journal: Arch Ophthalmol Date: 2004-04
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