PROJECT NAME: SUSTAINING REDUCED WAIT TIMES FOR OUTPATIENT BLOOD DRAWS Institution: The University of Texas M D Anderson Cancer Center Primary Author: Ron Phipps Secondary Author: Han Le Project Category: Sustained CS&E Projects Choose most appropriate category: 1) Patient Safety, 2) Patient Centered Care, 3) Timeliness, 4) Efficiency, 5) Effectiveness, 6) CS & E Projects Implemented at a New Site, 7) General Quality Improvements or 8)Sustained CS & E Projects Overview The Clark and Mays Diagnostic Centers are the top two highest volume outpatient centers that provide lab services for MD Anderson Cancer Center These centers are operated by phlebotomists, patient Service Coordinators and one Medical Technologist The Clark Clinic sees 500 to 900 patients per day, and the Mays Clinic sees 300 to 600 patients per day For most patients, their blood draw appointment is their first appointment of the day Due to patient complaints about long wait time and congested waiting rooms, we started a project in 2010 to decrease the wait times in our out patient diagnostic center located in the Mays and Clark Clinics Our goal was to improve the turn around time from patient arrival to specimen collection so that 95% of our patients were seen within 20 minutes of arriving at the outpatient centers This project is aligned with the institutional value of Caring, and the Institutional Strategic Goal for Patient Care (including Strategy 1.2, "We will increase the quality, safety and value of our clinical care" and Strategy 1.5, "We will enhance productivity, access and efficiency by strengthening our infrastructure and support systems." This project is also directly aligned with the “Every Minute Counts” initiative for Clinical Operations and the impact it has on Press-Gayney patient satisfaction scores Aim Statement (max points 150): The process improvement project started in 2010 improved the turnaround times in Mays and Clark clinics dramatically, but did not meet our goal We continue to work with the Clark and Mays Clinics to improve the time patients wait to have a blood specimen collected Mays Clinic: Baseline from Feb 2010: • Average time of 26 minutes • 44% of patients were collected within 20 minutes • 18% were seen within 10 minutes Phase I improvement July 2010 • Average time of 18 minutes (a 30% improvement) • 65% of patients were collected within 20 minutes ( a 48% improvement) • 35% were seen within 10 minutes (a 94% improvement) Clark Clinic: Baseline from Feb 2010: • Average time of 15 minutes • 74% of patients were collected within 20 minutes • 40% were seen within 10 minutes Phase I improvement July 2010 • Average time of 14 minutes (7% improvement) • 82% of patients were collected within 20 minutes ( 11% improvement) • 47% were seen within 10 minutes (18% improvement) Measures of Success: We monitor and trend the turnaround time with daily graphs that are available for review by the supervisor and phlebotomists The graph is posted on a bulletin board for the staff to view The staff was also taught how to interpret the graph The measure is based on raw data from the Laboratory Information System, using the time points from the CARE patient arrival time to the blood collection time, which is based on the collection time written on the chemistry specimen We also monitor the Press Ganey Outpatient survey results to see if we are meeting our patients’ expectations Use of Quality Tools (max points 250): We used a value stream map to better understand the process and brainstorm the following possible causes for delays: • Peak volume days / times o Phlebotomy staffing levels / schedules • Supply Shortages o Draw stations / supplies not standardized • Differences in Phlebotomist Productivity o Analysis of variation between work flows o Removal of ‘waste’ in phlebotomist cycle time • Impact of scheduling on Wait times • Developed Phlebotomy Staffing algorithm o Used to determine staffing needs • Patient volumes, arrival patterns & draw times per patient o Used to optimize mix of personnel to staff at each clinic by half hour o Used to determine hours of operation We used an Issue Prioritization matrix to identify issues that needed to be addressed in the PSC work area We used the following graph (which includes previous months’ overall trends and the current month’s daily trends) to monitor the process daily and to identify outlier times We also monitored the results of the Press Ganey patient survey This information was being used to monitor how we were meeting our patient expectations and to help us make changes to better meet their needs (See graphs in Interventions) Interventions (max points 150 includes points for innovation): Our improvements from the previous and current projects included: • 5S pilot in ACB (01/11) • Installed Redesigned Sign-in tables (02/11) • Phlebotomist workflow enhancements (3/11) • Roll out 5S projects in Clark Clinic completed (4/11) • Front Desk Standardization (4/11) • Departmental Super Star board in Clark Clinic (5/11) • Roll out 5S projects in Mays Clinic (11/11) • Changed Hours of Operation (12/2011) o Mays: M-F 6:30a - 7p == 6a - 6p o Clark: M-F 6a – 8:30p == 6a – 7p o Rotary: Sun-T 5p – 8:30p == 3:30p – 8:00p • Minimized patients waiting before clinic opened (12/11) • Provided more coverage earlier in the day • Optimized staffing during busier hours • Promotion of Regional Care Centers We continue monitoring and posting the daily TAT graph for all staff to view This information sharing has encouraged the staff to aim for the goal and continue to provide excellent care for our patients Furthermore, the supervisor uses the data from the next day’s patient appointment load to ensure proper staffing We continue to monitor the turn around time in the Mays and Clark Clinics daily and upload the graphs to an intranet site for review by all team members This helps with trending of patient arrival times and allows the staff to monitor exception days for special causes The staffing levels are monitored daily and adjustments are made as needed The tool below is available to the staff for assessing the best way to allocate the available personnel in the clinics Results (max points 250): We have continued to monitor the turnaround times on a daily basis and have seen a continual decrease in the wait times of our patients at Mays Clinic We can now proudly announce to our Administrators that our goal has been met: The Mays Clinic has achieved: July 2010 vs July 2012 = 95% of patients were collected within 20 minutes vs 70% baseline from July 2010 (36% improvement) = 70% of patients were collected within 10 minutes vs 33.2% baseline from July 2010 (112% improvement) July 2012 vs Feb 2010 = 95% of patients were collected within 20 minutes vs 44% Feb 2010 (116% improvement) = 70% of patients were collected within 10 minutes vs 18% Feb 2010 (289% improvement) Also, the Clark Clinic has sustained and improved upon their improvement results, as noted in the following graph: The Clark Clinic has achieved: July 2010 vs July 2012 = 87% of patients were collected within 20 minutes vs 82% baseline from July 2010 (6% improvement) = 62% of patients were collected within 10 minutes vs.47% baseline from July 2010 (32% improvement) July 2012 vs Feb 2010 = 87% of patients were collected within 20 minutes vs 74% 2010 (18% improvement) = 62% of patients were collected within 10 minutes vs 40% 2010 (55% improvement) The total hours per week of patient wait time saved from both clinics (using the difference in the average times) is 344 hours per week Press Ganey results supported the improvements made thru out the project Revenue Enhancement /Cost Avoidance / Generalizability (max points 200): Soft Savings: • Outlier patients in Mays Clinic with more than 40 minutes from Arrival to Collect dropped from 4.1% in the baseline to 2% in 2012 (53 patients per week given their volume of 2,500 patients per week) • Outlier patients in Clark Clinic with more than 40 minutes from Arrival to Collect dropped from 1.9% in the baseline to 1.0% in 2012 (a difference of 38 patients per week given their volume of 3,750 patients per week) • Therefore, 91 fewer patients per week had wait times more than 40 minutes Conservatively assuming that only 20% of the combined clinics’ difference of 91 patients with more than a 40 minute wait per week had a cost avoidance of $100 per patient (from a combination of missed / delayed downstream appointments, utilization of affected equipment, poor productivity of personnel, overtime from personnel, etc.): • The soft savings total would be over $94,000 per year Conclusions and Next Steps: We continue to monitor and post daily TAT graph Our future goals include modifying the process to support and leverage arm-banding, the Sorian system, bar-coding of patients at check-in, positive patient ID during collection, and an automated kiosk for patient self check-in