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

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

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

Reducing patient wait time with computer simulation modeling

2017 ◽  
Vol 145 ◽  
pp. 152
Author(s):  
C.M. Niemi ◽  
B.R. Krueger ◽  
K.J. Bluske ◽  
R. Spencer ◽  
M.F. Peterson ◽  
...  
Keyword(s):  
Computer Simulation ◽  
Simulation Modeling ◽  
Wait Time ◽  
Patient Wait Time

Measuring chemotherapy appointment duration and variation utilizing real-time location systems (RTLS).

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 154-154
Author(s):  
Constance Barysauskas ◽  
Gina Hudgins ◽  
Katie Kupferberg Gill ◽  
Kristen Camuso ◽  
Janet Bagley ◽  
...  
Keyword(s):  
Chemotherapy Regimen ◽  
Wait Time ◽  
Consensus Method ◽  
Scarce Resources ◽  
Staffing Ratios ◽  
Increase Patient Satisfaction ◽  
Dana Farber Cancer Institute ◽  
Patient Wait Time ◽  
Almost All ◽  
Utilization Cost

154 Background: Clinical schedules drive resource utilization, cost, and patient wait time. Accurate appointment durations ensure appropriate staffing ratios to the daily caseload and maximizes scarce resources. Dana-Farber Cancer Institute (DFCI) adjusts infusion appointment durations for each chemotherapy regimen using a consensus method of experts including pharmacists, nurses, and administrators. Utilizing RTLS, we examined the accuracy of appointment duration compared to suggested duration. Methods: Appointment duration was calculated using RTLS in three disease centers at DFCI between August 1st and September 30th, 2013. Duration was defined as the amount of time a patient occupied an infusion chair. The top 10 administered infusion regimens were statistically investigated (n=805). Results: All median observed appointment durations were statistically different than the suggested durations. Appointment duration was shorter than scheduled 98% [C], 95% [I], and 75% [F] of the time and longer than scheduled 77% [A] and 76% [G] of the time. Almost all C and I appointments were more than 30 minutes shorter than scheduled. Among A appointments longer than scheduled, 56% were more than 30 minutes longer than scheduled. Conclusions: RTLS provides reliable and unbiased data to improve schedule accuracy. Replacing consensus with system-based data may improve clinic flow, relieve staff stress, and increase patient satisfaction. Further investigations should elucidate factors that cause variation in appointment duration. [Table: see text]

Increase in the patient wait-time and delays in the clinic workflow post-implementation of the electronic health record.

2017 ◽  
Vol 35 (8_suppl) ◽  
pp. 194-194
Author(s):  
Meyyammai Narayanan ◽  
Xiao Zhou ◽  
Shawn J Janarthanan ◽  
Mary Daniel ◽  
Maria Olmedo ◽  
...  
Keyword(s):  
Wait Time ◽  
Total Sample ◽  
Health Records ◽  
Exam Room ◽  
Patient Wait Time ◽  
Electronic Health ◽  
The Impact ◽  
Implementation Of Ehr ◽  
New System

194 Background: Growth in patient (pt) volume and limited clinic capacity can lead to long wait-times and pt/provider dissatisfaction. We have previously shown that the room pooling model, can reduce pt wait-time in the exam room, improve room utilization, and pt/providers satisfaction (ASCO 2016, Abstract 6595). One of the important goals of adopting electronic health records (EHR) is also to increase the clinical efficiencies, productivity and quality of care. The purpose of this study was to evaluate the impact of implementation of EHR on pt wait-time in the exam room and satisfaction in the Sarcoma Center. Methods: The time studies and pt and provider wait-time satisfaction surveys were carried out over 2 weeks prior to (baseline) and 6 months after the implementation of EHR. All times of when pts, mid-level providers, and doctors (MD) entered and exited the exam rooms were collected for a total sample size of 578 pts (300 before, 278 after) seen during the clinic hours and analyzed using JMP and SAS. Results: The proportion of pts seen within 30 minutes (Min) by MDs from the time pts roomed into exam room decreased by about 32% [from 53% (148/280) to 36% (94/259), p = 0.0001] post implementation of EHR. The median time for pts in the exam room waiting for MD increased (p = 0.0001) from 30 min (range: 0-126 min) to 40 min (range: 0-121 min). Although, the pt satisfaction did not significantly change [increase from 8% (23/278) to 12% (31/267) in the number of pts that were not satisfied to little-satisfied, and decrease from 92% (255/278) to 88% (236/267) in pts that were moderately to very-satisfied], the number of times MD had to wait for an open exam room increased from 8% (5/65) to 24% (14/59, p = 0.01). The delays to see MDs were associated with longer time spent with the nurse (from median 4 to 7 min), followed by delays in seeing Mid-level provider (from 11 to 18 min). Conclusions: These findings indicate that in the initial stages of implementation of EHR, the increase in pt wait-time and reduced clinical efficiencies can be related to the learning of and adapting to the new system. Attempts targeted to the areas of delays (such as training and redesigning workflow) may reduce the pt wait-time and improve the clinical efficiency.

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