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.

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 National Comprehensive Cancer Network Infusion Efficiency Workgroup Study: Optimizing Patient Flow in Infusion Centers

2019 ◽  
Vol 15 (5) ◽  
pp. e458-e466 ◽  
Author(s):  
Jessica M. Sugalski ◽  
Timothy Kubal ◽  
Daniel L. Mulkerin ◽  
Rebecca L. Caires ◽  
Penny J. Moore ◽  
...  
Keyword(s):  
National Comprehensive Cancer Network ◽  
Patient Flow ◽  
Wait Time ◽  
Cancer Centers ◽  
Administration Routes ◽  
Chemotherapy Drugs ◽  
Average Patient ◽  
Patient Wait Time ◽  
Standard Practices ◽  
Cancer Network

PURPOSE: The National Comprehensive Cancer Network (NCCN) formed an Infusion Efficiency Workgroup to determine best practices for operating efficient and effective infusion centers. METHODS: The Workgroup conducted three surveys that were distributed to NCCN member institutions regarding average patient wait time, chemotherapy premixing practices, infusion chair use, and premedication protocols. To assess chair use, the Workgroup identified and defined five components of chair time. RESULTS: The average patient wait time in infusion centers ranged from 25 to 102 minutes (n = 23; mean, 58 minutes). Five of 26 cancer centers (19%) routinely mix chemotherapy drugs before patient arrival for patients meeting specified criteria. Total planned chair time for subsequent doses of the same drug regimens for the same diseases varied greatly among centers, as follows: Administration of doxorubicin and cyclophosphamide ranged from 85 to 240 minutes (n = 22); of FOLFIRINOX (folinic acid, fluorouracil, irinotecan hydrochloride, and oxaliplation) ranged from 270 to 420 minutes (n = 22); of rituximab ranged from 120 to 350 minutes (n = 21); of paclitaxel plus carboplatin ranged from 255 to 380 minutes (n = 21); and of zoledronic acid ranged from 30 to 150 minutes (n = 22) for planned total chair time. Cancer centers were found to use different premedication regimens with varying administration routes that ranged in administration times from zero to 60 minutes. CONCLUSION: There is a high degree of variation among cancer centers in regard to planned chair time for the same chemotherapy regimens, providing opportunities for improved efficiency, increased revenue, and more standardization across centers. The NCCN Workgroup demonstrates potential revenue impact and provides recommendations for cancer centers to move toward more efficient and more standard practices.

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 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.

Management of patients brought in by ambulance to the emergency department: role of the Advanced Musculoskeletal Physiotherapist

2018 ◽  
Vol 42 (3) ◽  
pp. 309 ◽  
Author(s):  
Rita Kinsella ◽  
Tom Collins ◽  
Bridget Shaw ◽  
James Sayer ◽  
Belinda Cary ◽  
...  
Keyword(s):  
Emergency Department ◽  
Positive Impact ◽  
Patient Flow ◽  
Quality Care ◽  
Wait Time ◽  
The Body ◽  
Musculoskeletal Complaints ◽  
Musculoskeletal Conditions ◽  
Improve Patient

Objective The aim of the present study was to evaluate the role of the Advanced Musculoskeletal Physiotherapist (AMP) in managing patients brought in by ambulance to the emergency department (ED). Methods This study was a dual-centre observational study. Patients brought in by ambulance to two Melbourne hospitals over a 12-month period and seen by an AMP were compared with a matched group seen by other ED staff. Primary outcome measures were wait time and length of stay (LOS) in the ED. Results Data from 1441 patients within the Australasian Triage Scale (ATS) Categories 3–5 with musculoskeletal complaints were included in the analysis. Subgroup analysis of 825 patients aged ≤65 years demonstrated that for Category 4 (semi-urgent) patients, the median wait time to see the AMP was 9.5 min (interquartile range (IQR) 3.25–18.00 min) compared with 25 min (IQR 10.00–56.00 min) to see other ED staff (P ≤ 0.05). LOS analysis was undertaken on patients discharged home and demonstrated that there was a 1.20 greater probability (95% confidence interval 1.07–1.35) that ATS Category 4 patients managed by the AMP were discharged within the 4-hour public hospital target compared with patients managed by other ED staff: 87.04% (94/108) of patients managed by the AMPs met this standard compared with 72.35% (123/170) of patients managed by other ED staff (P = 0.002). Conclusions Patients aged ≤65 years with musculoskeletal complaints brought in by ambulance to the ED and triaged to ATS Category 4 are likely to wait less time to be seen and are discharged home more quickly when managed by an AMP. This study has added to the evidence that AMPs improve patient flow in the ED, freeing up time for other ED staff to see higher-acuity, more complex patients. What is known about the topic? There is a growing body of evidence establishing that AMPs improve the flow of patients presenting with musculoskeletal conditions to the ED through reduced wait times and LOS and, at the same time, providing good-quality care and enhanced patient satisfaction. What does this paper add? Within their primary contact capacity, AMPs also manage patients who are brought in by ambulance presenting with musculoskeletal conditions. To the authors’ knowledge, there is currently no available literature documenting the performance of AMPs in the management of this cohort of patients. What are the implications for practitioners? This study has added to the body of evidence that AMPs improve patient flow in the ED and illustrates that AMPs, by seeing patients brought in by ambulance, are able to have a positive impact on the pressures increasingly facing the Victorian Ambulance Service and emergency hospital 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 Improving patient flow and timeliness in the diagnosis and management of breast abnormalities: the impact of a rapid diagnostic unit

2016 ◽  
Vol 23 (3) ◽  
pp. 260 ◽  
Author(s):  
J.M. Racz ◽  
C.M.B. Holloway ◽  
W. Huang ◽  
N.J. Look Hong
Keyword(s):  
Care Delivery ◽  
Patient Flow ◽  
Wait Time ◽  
Definitive Treatment ◽  
Wait Times ◽  
Fisher Exact Test ◽  
Patient Anxiety ◽  
Diagnostic Unit ◽  
Clinical Investigations ◽  
The Impact

Background Efforts to streamline the diagnosis and treatment of breast abnormalities are necessary to limit patient anxiety and expedite care. In the present study, we examined the effect of a rapid diagnostic unit (RDU) on wait times to clinical investigations and definitive treatment.Methods A retrospective before–after series, each considering a 1-year period, examined consecutive patients with suspicious breast lesions before and after initiation of the RDU. Patient consultations, clinical investigations, and lesion characteristics were captured from time of patient referral to initiation of definitive treatment. Outcomes included time (days) to clinical investigations, to delivery of diagnosis, and to management. Groups were compared using the Fisher exact test or Student t-test.Results The non-RDU group included 287 patients with 164 invasive breast carcinomas. The RDU group included 260 patients with 154 invasive carcinomas. The RDU patients had more single visits for biopsy (92% RDU vs. 78% non-RDU, p < 0.0001). The RDU group also had a significantly shorter wait time from initial consultation to delivery of diagnosis (mean: 2.1 days vs. 16.7 days, p = 0.0001) and a greater chance of receiving neoadjuvant chemotherapy (37% vs. 24%, p = 0.0106). Overall time from referral to management remained statistically unchanged (mean: 53 days with the RDU vs. 50 days without the RDU, p = 0.3806).Conclusions Introduction of a RDU appears to reduce wait times to definitive diagnosis, but not to treatment initiation, suggesting that obstacles to care delivery can occur at several points along the diagnostic trajectory. Multipronged efforts to reduce system-related delays to definitive treatment are needed.

scholarly journals The system analysis and mathematical modeling road accidents in the metropolis

2019 ◽  
pp. 4-8
Author(s):  
A. G. Davidovsky ◽  
A. M. Linnik
Keyword(s):  
Mathematical Modeling ◽  
Traffic Safety ◽  
System Analysis ◽  
Safety Management ◽  
Road Traffic ◽  
Time Of Day ◽  
Road Accidents ◽  
Traffic Incidents ◽  
Day Of The Week ◽  
Pedestrian Collisions

The article presents the results of correlation analysis of the causes of road accidents in such a modern metropolis as Minsk. Has been identified the most frequent causes of road accidents, including pedestrian collisions caused by drivers, collisions at intersections, incidents at controlled and unregulated pedestrian crossings, as well as on the roadway. The dependence of transport incidents on the time of day, day of the week and month of the year was investigated. Shows the periods when road traffic incidents occur from 3.00 to 6.00 h, from 15.00 to 18.00 and from 21.00 to 24.00 on Monday, Friday and Sunday in January, March, June, September, October and November. Methods of correlation and multiple regression analysis can be the basis of preventive traffic safety management in a modern metropolis.

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