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

Appointment standardization evaluation in a primary care facility

2016 ◽  
Vol 29 (6) ◽  
pp. 675-686 ◽  
Author(s):  
Yu-Li Huang
Keyword(s):  
Primary Care ◽  
Access To Care ◽  
Wait Time ◽  
Idle Time ◽  
Urgent Care ◽  
Content Type ◽  
Finish Time ◽  
Number Of Patients ◽  
Patient Wait Time ◽  
The Impact

Purpose – The purpose of this paper is to evaluate the performance on standardizing appointment slot length in a primary care clinic to understand the impact of providers’ preferences and practice differences. Design/methodology/approach – The treatment time data were collected for each provider. There were six patient types: emergency/urgent care (ER/UC), follow-up patient (FU), new patient, office visit (OV), physical exam, and well-child care. Simulation model was developed to capture patient flow and measure patient wait time, provider idle time, cost, overtime, finish time, and the number of patients scheduled. Four scheduling scenarios were compared: scheduled all patients at 20 minutes; scheduled ER/UC, FU, OV at 20 minutes and others at 40 minutes; scheduled patient types on individual provider preference; and scheduled patient types on combined provider preference. Findings – Standardized scheduling among providers increase cost by 57 per cent, patient wait time by 83 per cent, provider idle time by five minutes per patient, overtime by 22 minutes, finish time by 30 minutes, and decrease patient access to care by approximately 11 per cent. An individualized scheduling approach could save as much as 14 per cent on cost and schedule 1.5 more patients. The combined preference method could save about 8 per cent while the number of patients scheduled remained the same. Research limitations/implications – The challenge is to actually disseminate the findings to medical providers and adjust scheduling systems accordingly. Originality/value – This paper concluded standardization of providers’ clinic preference and practice negatively impact clinic service quality and access to care.

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.

scholarly journals Online Ratings of Primary Care Physicians: Comparison of Gender, Training, and Specialty

2021 ◽  
Vol 8 ◽  
pp. 237437352110077
Author(s):  
Daliah Wachs ◽  
Victoria Lorah ◽  
Allison Boynton ◽  
Amanda Hertzler ◽  
Brandon Nichols ◽  
...  
Keyword(s):  
Primary Care ◽  
Primary Care Physicians ◽  
Waiting Times ◽  
Wait Time ◽  
Primary Care Providers ◽  
Wait Times ◽  
Care Providers ◽  
Female Physicians ◽  
Online Ratings ◽  
And Gender

The purpose of this study was to explore patient perceptions of primary care providers and their offices relative to their physician’s philosophy (medical degree [MD] vs doctorate in osteopathic medicine [DO]), specialty (internal medicine vs family medicine), US region, and gender (male vs female). Using the Healthgrades website, the average satisfaction rating for the physician, office parameters, and wait time were collected and analyzed for 1267 physicians. We found female doctors tended to have lower ratings in the Midwest, and staff friendliness of female physicians were rated lower in the northwest. In the northeast, male and female MDs were rated more highly than DOs. Wait times varied regionally, with northeast and northwest regions having the shortest wait times. Overall satisfaction was generally high for most physicians. Regional differences in perception of a physician based on gender or degree may have roots in local culture, including proximity to a DO school, comfort with female physicians, and expectations for waiting times.

scholarly journals Patient-centred method to evaluate the spatial accessibility of primary health care in a case study in Shanghai

2020 ◽  
Vol 26 (4) ◽  
pp. 344
Author(s):  
Xuechen Xiong ◽  
Li Luo
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Primary Health Care ◽  
Waiting Times ◽  
Care Facility ◽  
Wait Time ◽  
Spatial Accessibility ◽  
Quantitative Methodology ◽  
Time Cost ◽  
Primary Health

Quantitative methodology investigating medical resource accessibility does not incorporate patients’ feelings about the adequacy and fairness of primary health care (PHC). In this study we quantified the spatial accessibility of PHC from the patient perspective. The main obstacles regarding access to PHC services are: (1) distance from the medical facility; and (2) waiting times after reaching the facility. The total time cost to access PHC is calculated as the sum of the time cost to access the PHC facility and the time cost waiting to receive health care; the total time cost was used in this study to reflect the potential spatial accessibility (i.e. probable entry into the healthcare system) of PHC. In Shanghai, it took residents approximately 13min to reach the nearest primary care facility, with an approximate 23min wait time after arriving at the facility. Thus, the spatial accessibility of PHC in Shanghai is approximately 36min. The method of assessing the spatial accessibility of PHC from the perspective of patients is more explanatory and easier to interpret. In the case of Shanghai, the regional accessibility of PHC is much better than its regional availability. Relevant managers should focus on increasing the resource supply capacity of existing facilities providing primary care in the suburbs of Shanghai.

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
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