Delivering Patient Value by Using Process Improvement Tools to Decrease Patient Wait Time in an Outpatient Oncology Infusion Unit

2016 ◽  
Vol 12 (1) ◽  
pp. e95-e100 ◽  
Author(s):  
Lauren N. Gjolaj ◽  
Gloria G. Campos ◽  
Angela I. Olier-Pino ◽  
Gustavo L. Fernandez
Keyword(s):  
Patient Care ◽  
Process Improvement ◽  
Wait Time ◽  
Patient Wait Time ◽  
Patient Value

By using the systematic PDCA tool, the authors were able to identify opportunities to reduce waste in the system and streamline patient care.

scholarly journals Using quality improvement methodology and tools to reduce patient wait time in a paediatric subspecialty rheumatology clinic

2021 ◽  
Vol 10 (4) ◽  
pp. e001550
Author(s):  
Bayardo Garay ◽  
Denise Erlanson ◽  
Bryce A Binstadt ◽  
Colleen K Correll ◽  
Nora Fitzsimmons ◽  
...  
Keyword(s):  
Process Improvement ◽  
Patient Flow ◽  
Wait Time ◽  
Time Of Day ◽  
The Body ◽  
Ambulatory Setting ◽  
Rheumatology Clinic ◽  
Physician Contact ◽  
Day Of The Week ◽  
Patient Wait Time

Our paediatric rheumatology clinic has experienced inefficient patient flow. Our aim was to reduce mean wait time and minimise variation for patients. Baseline data showed that most waiting occurs after a patient has been roomed, while waiting for the physician. Wait time was not associated with a patient’s age, time of day, day of the week or individual physician. We implemented a checkout sheet and staggered start times. After a series of plan–do–study–act cycles, we observed an initial 26% reduction in the variation of wait time and a final 17% reduction in the mean wait time. There was no impact on patient–physician contact time. Overall, we demonstrate how process improvement methodology and tools were used to reduce patient wait time in our clinic, adding to the body of literature on process improvement in an ambulatory setting.

scholarly journals Decreasing Laboratory Turnaround Time and Patient Wait Time by Implementing Process Improvement Methodologies in an Outpatient Oncology Infusion Unit

2014 ◽  
Vol 10 (6) ◽  
pp. 380-382 ◽  
Author(s):  
Lauren N. Gjolaj ◽  
Gloria A. Gari ◽  
Angela I. Olier-Pino ◽  
Juan D. Garcia ◽  
Gustavo L. Fernandez
Keyword(s):  
Process Improvement ◽  
Wait Time ◽  
Turnaround Time ◽  
Comprehensive Treatment ◽  
Treatment Unit ◽  
Patient Wait Time ◽  
Improvement Methodologies

Streamlining workflows and placing a phlebotomy station inside of the Comprehensive Treatment Unit (CTU) decreased laboratory turnaround times by 53% for patients who required same-day laboratory and CTU services.

scholarly journals Behind the clock: elucidating factors contributing to longer clinic appointment duration and patient wait time

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Daniel Jonathan Kagedan ◽  
Stephen B. Edge ◽  
Kazuaki Takabe
Keyword(s):  
Wait Time ◽  
High Volume ◽  
Advanced Practice ◽  
Single Institution ◽  
Clinic Appointment ◽  
Nurse Assessment ◽  
Patient Wait Time ◽  
Encounter Time ◽  
Examination Room

Abstract Background Longer wait time in ambulatory clinics can disrupt schedules and decrease satisfaction. We investigated factors associated with patient wait time (WT, check-in to examination room placement), approximate clinician time (ACT, completion of nurse assessment to check-out), and total appointment length (TAL, check-in to check-out). Methods A single-institution retrospective study was conducted of breast surgery clinic patients, 2017–2019, using actual encounter times. A before/after analysis compared a five-day 8 hour/day (from a four-day 10 hour/day) advanced practice provider (APP) work-week. Non-parametric tests were used, and medians with interquartile ranges (IQRs) reported. Results 15,265 encounters were identified. Overall WT was 15.0 minutes (IQR:6.0–32.0), ACT 49.0 minutes (IQR:31.0–79.0) and TAL 84.0 minutes (IQR:57.0-124.0). Trainees were associated with 30.0 minutes longer ACT (p < 0.0001); this increased time was greatest for follow-up appointments, least for new patients. Patients arriving > 5 minutes late (versus on-time) experienced shorter WT (11.0 vs. 15.0 minutes, p < 0.0001) and ACT (43.0 vs. 53.0 minutes, p < 0.0001). Busier days (higher encounter volume:APP ratios) demonstrated increased encounter times. After transitioning to a five-day APP work-week, ACT decreased. Conclusions High-volume clinics and trainee involvement prolong ambulatory encounters. Increasing APP assistance, altering work schedules, and assigning follow-up appointments to non-trainees may decrease encounter time.

Dose banding of chemotherapy doses at the Juravinski Cancer Centre

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6099-6099 ◽  
Author(s):  
H. W. Hirte ◽  
S. Kagoma ◽  
L. Zhong ◽  
I. Collins ◽  
D. Burns ◽  
...  
Keyword(s):  
Standard Dose ◽  
Waiting Times ◽  
Wait Time ◽  
Phase Iii ◽  
Time Study ◽  
Post Dose ◽  
Drug Dispensing ◽  
Average Patient ◽  
Patient Wait Time ◽  
Selection Of

6099 Background: As the number and complexity of chemotherapy regimens increase, the demands on pharmacy services to reduce chemotherapy preparation and checking times continues to increase. Dose banding, a system whereby doses of intravenous cytotoxic drugs calculated on an individual basis are rounded up or down to predetermined standard doses (the maximum variation of the adjustment between standard dose and doses constituting each band is 5% or less) was identified as a strategy that could be used to address some of the issues around time pressures to help reduce patient waiting times for treatment. Methods: The project consisted of 3 phases; Phase I - literature review to identify dose banding publications; Phase II - selection of drugs to be banded for the pilot. The two drugs selected were 5FU and leukovorin, and Phase III - Time studies pre-, interim and post dose banding implementation to determine drug dispensing time and patients’ wait time for pharmacy related procedures. This occurred for a 2 week period (10 working days) either prior to implementation (pre- 819 patients studied), 4 days after implementation (interim - 854 patients studied) and 4 weeks after implementation (post - 785 patients studied). Results: Drug dispensing time did not decrease with dose banding (pre- 7.9 min, interim - 7.6 min and post - 9.4 min). However, the average patient wait time decreased after piloting the dose banding project (pre - 31.6 min, interim 23.7 min, and post - 27.8 min). The percentage of doses that were banded were 37.8% in the interim time study and 58.2% in the post time study. Conclusions: Although dose banding did not reduce dispensing time in this study, likely because the preparation for dispensing 5FU and leukovorin syringes is normally very simple and quick, patient’s wait time for pharmacy related procedures did decrease. This was probably due to contributions of other factors in the pharmacy process. A reduction in dispensing time could likely be achieved if more complex regimens were considered for dose banding. Dose banding could be used to increase capacity within the chemotherapy suite on the day of administration. It also allows for a better work schedule and increases efficiencies within the chemotherapy preparation and administration areas. (Sponsored by funds from Cancer Care Ontario) No significant financial relationships to disclose.

Improving patient wait-time and patient/provider wait-time satisfaction by the room pooling model.

2016 ◽  
Vol 34 (15_suppl) ◽  
pp. 6595-6595
Author(s):  
Shawn J Janarthanan ◽  
Xiao Zhou ◽  
Mary Daniel ◽  
Colleen Jernigan ◽  
Shreyaskumar Patel ◽  
...  
Keyword(s):  
Wait Time ◽  
Patient Wait Time

Reducing infusion wait time: Redesigning medication order verification workflow at a comprehensive cancer center.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 129-129
Author(s):  
Michael D Kearney ◽  
Rachel A Wolfberg ◽  
Mark Sudol ◽  
Shital Shukla ◽  
Barbara Fine ◽  
...  
Keyword(s):  
Process Improvement ◽  
Patient Flow ◽  
Wait Time ◽  
Comprehensive Cancer Center ◽  
Cancer Center ◽  
Drug Preparation ◽  
Medication Order ◽  
Throughput Time ◽  
Reduced Order ◽  
Dana Farber Cancer Institute

129 Background: Many factors contribute to long wait times for cancer patients on the day of their infusion. At Dana-Farber Cancer Institute (DFCI), a contributing factor is patient flow between exam and infusion. Order verification affects patient flow and begins when the following two criteria are met: provider signed an order and the patient’s scheduled infusion appointment arrives. Patients often check-in to infusion before their scheduled infusion appointment. Order verification has three sequential steps: nurse verification, pharmacist 1 verify (V1), and pharmacist 2 verify (V2). Methods: A team of pharmacists, nurses, providers, and process improvement leads designed a pilot in which V1 moved before nurse verification, concurrent with patient check-in to infusion. Further, V1 began as soon as an order was signed; the pharmacist did not wait for a patient’s scheduled infusion appointment. Nurse verification and V2 occurred in sequence after V1. Timestamp data were extracted from Epic and analyzed via Tableau to assess reduction in verification throughput, defined as time between infusion check-in and V2. Fourteen providers and one pharmacist joined a 6-week pilot to adopt the redesigned workflow beginning 4/23/18. Results: At baseline, time between check-in and V2 was consistent for pilot and non-pilot orders. During the pilot, time between check-in and V2 was shorter for pilot orders, showing a sustained decrease of approximately 10 minutes. The table below provides time in minutes between infusion check-in and V2 for pilot and non-pilot orders at baseline (3/12/18-4/20/18) and following workflow redesign (4/23/18-6/1/18). Conclusions: Implementing the pilot workflow reduced order verification throughput time and enabled drug preparation to begin sooner. Expanding this workflow to all medication orders can decrease infusion wait time at DFCI.[Table: see text]

scholarly journals Willing to wait?: The influence of patient wait time on satisfaction with primary care

2007 ◽  
Vol 7 (1) ◽  
Author(s):  
Roger T Anderson ◽  
Fabian T Camacho ◽  
Rajesh Balkrishnan
Keyword(s):  
Primary Care ◽  
Wait Time ◽  
Patient Wait Time

800 - Econsultations to Hepatologists Reduce Patient Wait Time for Clinical Visits and Improve Provider Communication

2018 ◽  
Vol 154 (6) ◽  
pp. S-1106
Author(s):  
Indira Bhavsar ◽  
Jennifer Wang ◽  
Kimberly Dowdell ◽  
Rachel A. Hays ◽  
Nicolas Intagliata
Keyword(s):  
Wait Time ◽  
Provider Communication ◽  
Patient Wait Time
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