Protocol for stepped wedge cluster randomized trial to evaluate the effects of SurgeCon: A quality improvement emergency department surge management platform (Preprint)

2021 ◽  
Author(s):  
Hensley Mariathas ◽  
Shabnam Asghari ◽  
Oliver Hurley ◽  
Nahid Anaraki ◽  
Christina Young ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Patient Satisfaction ◽  
Health System ◽  
Wait Time ◽  
Cluster Randomized Trial ◽  
Wait Times ◽  
Hybrid Design ◽  
Stepped Wedge ◽  
Patient Reported ◽  
Cluster Randomized

BACKGROUND Despite many efforts, long wait time and overcrowding at Emergency Departments (EDs) have remained a significant health system issue in Canada. For several years, Canada has had one of the longest wait times among Organisation for Economic Co-operation and Development OECD countries. From the patient’s perspective, the challenge has been described as “patients wait in pain or discomfort for hours before being seen at EDs”. In this study, we propose an innovative quality-improvement intervention called SurgeCon that includes a protocol-driven software platform and several other initiatives to reduce wait times and improve the sustainability of health systems without significant workforce changes. We piloted SurgeCon at an ED in Carbonear, Newfoundland and Labrador (NL) and found there was a 32% reduction in ED wait time. OBJECTIVE Our primary objectives of the trial are to evaluate the effects of SurgeCon on ED performance based on length of stay (LOS), time to physician’s initial assessment (PIA), and the number of patients leaving the ED without being seen by a physician (LWBS), patient satisfaction and patient-reported experience with ED wait times. The ultimate goal of this study is to create better value care by reducing the per-patient cost of delivering ED services. METHODS This study will investigate the effects of SurgeCon on health system key performance outcomes and patient-reported experience and satisfaction. The study uses a comparative effectiveness-implementation hybrid design. This type of hybrid design has been recommended to help achieve rapid translational gains that can hasten the movement of interventions from research to practice to public health impact. In our hybrid design, we will use a pragmatic stepped wedge cluster randomized trial (SW-CRT) design that enrols four 24/7 on-site ED physician support (category A) hospitals into a 30-month trial. All clusters (hospitals) start with a baseline period of “usual care” and are randomized to determine the order and timing of transitioning to “intervention care” until all hospitals are exposed to the intervention condition for the remainder of the study. RESULTS Data collection for this study is ongoing. To date, 15 randomly selected patients have participated in telephone interviews concerning patient-reported experiences and patient satisfaction with ED wait times. CONCLUSIONS By evaluating the mechanisms behind the use of SurgeCon, we hope to be able to improve wait times and create better value ED care in this healthcare context. CLINICALTRIAL This study is registered in ClinicalTrials.gov NCT04789902

Time stamps used to measure the patient's clinic experience.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 150-150 ◽  
Author(s):  
Terry Jensen ◽  
Roy Brown ◽  
Gay Riegel ◽  
Lalan S. Wilfong ◽  
John Russell Hoverman
Keyword(s):  
Patient Satisfaction ◽  
Wait Time ◽  
Office Visit ◽  
Site Quality ◽  
Satisfaction Survey ◽  
Wait Times ◽  
Time Stamp ◽  
Patient Satisfaction Survey ◽  
Patient Reported ◽  
Time Stamps

150 Background: In 2013, a patient reported satisfaction survey indicated 19% of patients waited 20-40 minutes, 8% 40-60 minutes and 4% over 1 hour. We initiated a project to objectively quantify the components of wait times to investigate opportunities for improvement. Methods: Utilizing existing technology in the practice management system, clinic staff use the Day List feature to capture time stamps as patients move through the clinic. We focused on provider appointments but these visits could also include business office, labs, infusion and diagnostics. It was important to define where the wait(s) occurred. The Time Stamp durations measured are as follows: Arrival to Depart – duration of each appointment; Arrival to site to Exam Start – duration of activity until ready to be seen by the provider, includes rooming, labs and business office activity. Used to compare to the patient satisfaction survey responses; Exam Start to Depart – the provider portion of the office visit, includes patient wait plus exam time. Three reports are generated: Time Stamp Error Report indicating the completeness of data collection; Average Wait Times Report with appointment counts by physician by site and average durations; Provider Wait Times Report with office visit counts, Wait Time Category counts ( < 10 min, 10-20, 20-40, 40-60, and > 1 hour ) and average durations. Results: There was a correlation calculation to the patient satisfaction survey of .779, with long wait times more likely to be underreported by patients. Site and physician data were available for review at site Quality Committees. The data can be used by the site to improve processes, such as lab and infusion room scheduling. Time stamps are used to communicate patient readiness for next steps in the office visit. The time stamps provide objective data to discuss patient complaints with staff. Conclusions: Patient wait times are a valued measure of patient satisfaction and quality. Full utilization of the Day List and supporting technology allows us to objectively monitor and improve this aspect of patient care. Table 1: Sample Provider Report [Table: see text]

The next generation of quality improvement at MSK: Turning chemotherapy process delays into chemo express.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18230-e18230
Author(s):  
Jennifer Tota ◽  
Kathleen Levine ◽  
Jeanine Gordon ◽  
Abigail Baldwin ◽  
Jodi Wald ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Patient Satisfaction ◽  
Patient Experience ◽  
Wait Time ◽  
Wait Times ◽  
Pilot Program ◽  
Treatment Results ◽  
Average Wait Time ◽  
Major Bottleneck ◽  
Work Done

e18230 Background: Chemotherapy wait times can dramatically affect patient experience. MSK’s largest outpatient facility has 76 infusion spaces and 250-300 daily visits. A retrospective review of the facility’s infusion area wait times suggested that the lab (where all patients go to get their vitals and blood drawn) was a major bottleneck leading to process delays in infusion. Methods: We conducted a pilot program using a multi-pronged approach. Our goal was to decrease wait time from 40 minutes to an average of 15 minutes. Our initiative was defined as follows: (1) to redefine lab parameters that are relevant for toxicity and to only consider drawing those necessary labs; additionally, we created guidelines for timing of the labs prior to infusion treatment, (2) to introduce a program known as “ChemoExpress” which offers patients the opportunity to get blood work done prior to the day of their infusion appointment. After the labs result, the outpatient RN calls the patient, assesses symptoms and “clears them” for treatment cueing the pharmacy to prepare and “premix” the drug on the day of treatment. Results: 150 patients have enrolled in ChemoExpress. Patient satisfaction was high based on patient satisfaction surveys (n = 20). Average wait time was 9 minutes (76% less) in ChemoExpress participants as compared to an average wait of 39 minutes for those who did not participate in ChemoExpress. Conclusions: Implementing a process that enables patients to have their bloodwork drawn prior to the day of treatment and drugs prepared in advance of their treatment appointment results in greater efficiency in the overall workflow. It also offers the patient a lower wait time and a more efficient and satisfying experience.

Improving Outpatient Infusion Clinic Wait Times at a Comprehensive Cancer Center

2021 ◽  
pp. OP.21.00118
Author(s):  
Neda Hashemi-Sadraei ◽  
Shenthol Sasankan ◽  
Nick Crozier ◽  
Bernard Tawfik ◽  
Ronald Kittson ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Patient Satisfaction ◽  
Working Group ◽  
Outcome Measure ◽  
Wait Time ◽  
Comprehensive Cancer Center ◽  
Secondary Outcome ◽  
Cancer Center ◽  
Wait Times ◽  
Patient Wait Time

PURPOSE: Many factors contribute to long wait times for patients on the day of their chemotherapy infusion appointments. Longer wait time leads to nonoptimal care, increased costs, and decreased patient satisfaction. We conducted a quality improvement project to reduce the infusion wait times at a Comprehensive Cancer Center. METHODS: A multidisciplinary working group of physicians, infusion center nurses, pharmacists, information technology analysts, the Chief Medical Officer, and patient advocates formed a working group. Wait times were analyzed, and the contributing factors to long wait time were identified. Plan-Do-Study-Act cycles were implemented and included labeling patients ready to treat earlier, loading premedications into the medication dispensing system, increasing the number of pharmacy staff, and improving communication using a secure messaging system. The outcome measure was time from patient appointment to initiation of first drug at the infusion center. The secondary outcome measure was patient wait time satisfaction on the basis of Press Ganey score. RESULTS: Postintervention, the mean time from appointment to initiation of first drug decreased 17.6 minutes ( P < .001; 95% CI, 16.3 to 18.9), from 58.1 minutes to 40.5 minutes (43.5% decrease). Patient wait time satisfaction score increased 8.9 points ( P < .001; 95% CI, 6.0 to 11.82), from 76.2 to 85.1 (11.7% increase). CONCLUSION: Exploring real-time data and using a classic quality improvement methodology allowed a Comprehensive Cancer Center to identify deficiencies and prevent delays in chemotherapy initiation. This significantly improved patient wait time and patient satisfaction.

Digital Adherence Technology for Tuberculosis Treatment Supervision: A Stepped-Wedge Cluster Randomized Trial

2020 ◽  
Author(s):  
Adithya Cattamanchi ◽  
Rebecca R. Crowder ◽  
Alex Kityamuwesi ◽  
Noah Kiwanuka ◽  
Maureen Lamunu ◽  
...  
Keyword(s):  
Randomized Trial ◽  
Cluster Randomized Trial ◽  
Tuberculosis Treatment ◽  
Stepped Wedge ◽  
Cluster Randomized
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