Industrial and Operations Engineering 481 Project Team #10 SWAT Patient Flow and Personnel Workload - Final Presentation Industrial and Operations Engineering 481 Project Team #10 Presented by: Nicole Bartecki, Jack Jasper, Rishi Shah, & Emily Sweet December 13, 2016 Hi, my name is Emily Sweet and my group members consist of…. We are here today to present our final presentation on our project regarding SWAT Patient Flow and Personnel Workload. 1500 E. Medical Center Drive Ann Arbor, MI 48109 1

OVERVIEW Introduction Key Issues Goals and Objectives Methods Findings & Conclusions Recommendations Expected Impact Emily 2 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

INTRODUCTION SWAT: Specialized Workforce for Acute Transport Transport high/moderate-risk patients Policy change June 1, 2016 Broadened criteria for high/moderate-risk patients Increased “turf” rate Emily SWAT stands for the Specialized Workforce for Acute Transport and they are responsible for transporting high-risk and moderate-risk patients to different procedural areas around the hospital. SWAT is needed because these patients need to be specially monitored in case an emergency occurs. In the event of an emergency, SWAT is specially trained to better handle these situations versus the bedside nurse. In June of 2016, the hospital introduced a transportation policy which requires SWAT to transport moderate-risk patients in addition to high-risk patients to an added number of procedural areas. Prior to this policy change, SWAT was only in charge of transporting high-risk patients to a fewer number of procedural areas. The key indicator of SWAT’s insufficiency in meeting demand has been the “turf” rate: this is the percentage of transports SWAT says they will accommodate, but then have to cancel because they don’t have time or staff. Historically, the turf rate fell between 6-8%, but since the policy change it is now around 18%. Introduction Introduction Key Issues Key Issues Goals and Objectives Goals and Objectives Methods Methods Findings and Conclusions Findings and Conclusions Recommendations Recommendations Expected Impact Expected Impact

KEY ISSUES Increased turf rate Increased number of patient transportation and procedure requests Inefficient scheduling procedure Perceived shortage of SWAT personnel Emily Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

GOALS AND OBJECTIVES Goals Objectives Increase the efficiency of the SWAT team and address SWAT employee workload Objectives Decrease turf rate Streamline scheduling process to reduce workload on schedulers Increase visibility in scheduling to simplify the scheduling process Determine optimal SWAT staffing levels in order to achieve an acceptable turf rate, a maximum of 8% Emily Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

METHODS On-Site Observations Time Studies 183 transport timesheets over 13 days 79 scheduling timesheets over 16 days Statistical Analysis Emily Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

METHODS Value Stream Mapping Literature Search Emily Introduction Key Issues Key Issues Goals and Objectives Goals and Objectives Methods Methods Findings and Conclusions Findings and Conclusions Recommendations Recommendations Expected Impact Expected Impact

Findings & Conclusions HISTORICAL DATA Month Number Turfed Calls Total Calls Turf Rate June 269 1273 0.211 July 281 1298 0.216 August 196 1131 0.173 October 92 674 0.136 November 210 1342 0.156 Average 209.6 1143.6 0.178 1 Full-Time-Employee goes on 43 Transports/month Need 3.5 additional FTEs to reduce turf rate from ~18% to 8% RISHI 8 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions ON-SITE OBSERVATIONS Inefficient Current Scheduling Tool RISHI 9 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions ON-SITE OBSERVATIONS Visual difficulties in scheduling Scheduler uses intuition for transport run estimation Turf calls that otherwise could have been picked up Busiest time period 0730 - 0930 Need for a new, more user- friendly scheduling tool Conduct time studies between 0730 - 0930 RISHI Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions TIME STUDIES Stratifying by Patient Risk Level Patient Risk Level Mean Transportation Time Std. Dev. of Transportation Time Moderate 63.56 112.85 High 71.41 87.97 183 Samples Data Collected from 10/17/16 - 11/1/16 RISHI Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions TIME STUDIES Stratifying by Patient Risk Level Patient Risk Level Mean Transportation Time Std. Dev. of Transportation Time Moderate 63.56 112.85 High 71.41 87.97 Stratifying by Risk Level leads to unreliable estimates 183 Samples Data Collected from 10/17/16 - 11/1/16 RISHI Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions TIME STUDIES Stratifying by Procedure Type Procedure Mean Time (min) Std. Dev. of Time (min) Bedside Sedation 96.67 16.82 CT 47.65 12.57 CPU Return 32.83 6.08 Echo PET Scan 78.80 141.80 19.35 15.20 MRI 119.00 34.30 Radiology 47.23 16.80 Scheduling Deliverable: Estimated Time Per Procedure 183 Samples Data Collected from 10/17/16 - 11/1/16 RISHI Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions STATISTICAL ANALYSIS Distributions of Run Length Difficult to fit distribution to each run type Capture at least 75% for estimated time 183 Samples Data Collected from 10/17/16 - 11/1/16 RISHI 14 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions STATISTICAL ANALYSIS 7 Procedure Types Account for 71.10% of all transports 183 Samples Data Collected from 10/17/16 - 11/1/16 RISHI 15 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions STATISTICAL ANALYSIS Procedure Estimated Time (min.) Percentage Captured Radiology 50 75 CT 75.68 Echo 90 80 MRI 125 Bedside Sedation 110 100 CPU Return 35 PET Scan 155 Times Used in Scheduling Tool 183 Samples Data Collected from 10/17/16 - 11/1/16 RISHI 16 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions VALUE STREAM MAPPING Total Time: 21.07 min Value-Add Time: 7.40 min - 35.12% Non-Value Add Time: 13.67 min - 64.88% 79 scheduling timesheets collected over 16 days Jack --- Mention non-value added boxes Percentage of value added time Define value-added/non value-added In order to determine if SWAT needed a more streamlined scheduling process, we created a current state value stream map of the scheduling process, which you can see on the screen. To explain, the scheduling process begins when the charge nurse in charge of the patient contacts SWAT. If the schedulers are contacted by a page, then they schedule the patient and then call the charge nurse to confirm. If the schedulers are contacted by a call, then they simply talk with the nurse on the line to schedule the patient at an OK time. So far, the time taken is almost 4 minutes. Next, the schedulers make up to two additional calls back to nurses to get more information on the patient, or to procedural units, like MRI units or XRay unit, to find availability for patients. Once this is done, the schedulers update the Excel sheet with transportation information and fill out paperwork on the patient. The additional calls, updating the Excel sheet, and the paperwork take around 13 and a half minutes, and we identified this time as non-value added time. Finally, the nurses confirm the transport with the charge nurse by calling the nurse, completing the scheduling procedure. To draw out the most important insight - in the scheduling process we saw that almost 65% of the time was non-value added. Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions VALUE STREAM MAPPING Total Time: 8.40 min Value-Add Time: 7.40 min - 88.10% Non-Value Add Time: 1 min - 11.90% Jack -- We’ll mention SOP later We created a future state value stream map, which is shown on the screen. You’ll see that we eliminated the additional calls with standard operating procedures, which we’ll talk about later in the presentation, and we eliminated manual paperwork with automated paperwork, cutting non-value added time down to just 1 minute, or under 12% of the total time in the scheduling process. We also created a new scheduling tool, which we’ll also talk about later in the presentation. 18 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions VALUE STREAM MAPPING Paperwork Additional calls ~ 6.03 minutes 12.67 minutes saved per call 6.64 minutes ~ 60% Time Reduction Jack Cutting out the additional calls and reducing paperwork time saves more than 12 and a half minutes per call, which reduces total time in the scheduling process by 60% 19 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions LITERATURE SEARCH Rules for schedulers: augment intuition with standardization [1] Objectives for intra-hospital transport [1] Recommends additional staffing during exceptionally busy hours [2] Staffing can be altered throughout a shift based on need [3] [1] T. Hanne, T, Melo, S. Nickel, (2009) Bringing Robustness to Patient Flow Management Through Optimized Patient Transports in Hospitals. Interfaces 39(3):241-255. http://dx.doi.org/10.1287/inte.1080.0379 [2] M. Blasco, M. Brennan, and L. Soderstrom, (2006) Nursing SWAT Patient Transport Analysis Regarding Workload and Tasks. Ann Arbor, MI: University of Michigan, Industrial and Operations Engineering Department [3] K. Wilson, (2009) Fire Department Staffing: A Need, Not a Want. Fire Engineering. http://www.fireengineering.com/articles/print/volume-162/issue-8/features/fire-department-staffing-a-need-not-a-want.html Jack In addition to the value stream mapping, we conducted a literature search on intra-hospital transport and staffing. The four most important takeaways are shown on the screen: First, in schedulers like the ones in SWAT need to augment their intuition in scheduling patients with standardization in order to be schedule the most amount of patients with their limited staff resources. Second, the objectives in intra-hospital transport should be to minimize a transporter’s earliness to a call, minimize a transporter’s lateness to a call, and to maximize the use of all nurses. Third, extra staffing may be needed during the most busy periods of the day, but this does not mean that extra staffing is needed throughout the entire day. Fourth, staff should switch roles depending on where staff are needed most. In SWAT’s case, this would mean shifting schedulers to transporters or vice versa depending on need. 20 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Findings & Conclusions SUMMARY The scheduling tool needs to be updated to assist schedulers in optimally scheduling transports The paperwork portion of the scheduling process can and should be automated to increase efficiency The scheduling process should be streamlined to increase efficiency Jack To summarize our findings and conclusions, we found that The scheduling tool needs to be updated; otherwise schedulers will not be optimally scheduling transports. The paperwork portion of the scheduling process can and should be automated. The scheduling process had lots of room for improvement to be streamlined for maximum efficiency. 21 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Recommendations NEW SCHEDULING TOOL Nikki Time on the left, Name on the top Buttons above with the most common types of runs as well as an other button Cell selected here shows a run that transporter 3 is going on at 9am Still have colors from previous sheet as well as the key data in the top left 22 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Recommendations NEW SCHEDULING TOOL Nikki When clicking on a button the form seen here on the left appears - an example is filled out All the same data as on the old scheduling sheet When clicking Okay, the cells are colored in grey for the amount of time that captured at least 75% of that type of run based on our transport time studies. also, the data you entered in the form is populated in the cells as you can see on the right. note that this time includes the walking time to and from the SWAT office, so the scheduler might want to schedule a run for 850 if the transporter needs to be at the patient’s bedside by 9 This makes it easy for schedulers to see which transporters are gone and when they are expected to come back 23 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Recommendations NEW SCHEDULING TOOL Other Button Form: When Overlapping Transports: Nikki When clicking the other button, the form on the left appears allowing the scheduler to input any time from 20-200 minutes. When clicking okay on this form, the patient information form, seen on the previous slide appears. If at any point a scheduler tries to schedule a run that overlaps with another run, the warning message on the right will appear, and the scheduler will not be able to input this run. 24 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Recommendations STREAMLINE SCHEDULING PROCESS Utilize Standard Operating Procedures Eliminate Additional Calls Utilize MiChart Printing Feature Eliminate Handwriting Paperwork Free up one scheduler to join transporters after 0930 Nikki In order to streamline the scheduling process, we recommend utilizing standard operating procedures as well as the MiChart printing feature. These recommendations stem from the creation of the future state map where the team could see which processes were not adding value to the scheduling process and needed to be eliminated A standard operating procedure is a set of step-by-step instructions compiled to help workers carry out routine operations We believe that a checklist of all of the necessary information should be created by the SWAT schedulers and used on each call in order to eliminate additional calls We also believe that using the MiChart print off would be much more efficient than handwriting paperwork on each run and recommend that the SWAT team uses this feature. In streamlining the scheduling process and using the new scheduling tool, we believe that one scheduler can join the transport team after the busiest time of the day 730-930 25 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Recommendations ADD PERSONNEL New scheduling tool allows ~40 additional runs/ month Streamlined scheduling process provides additional transporter Hire 1.5 additional FTE Meet acceptable turf rate of 8% Nikki In freeing up the scheduler as mentioned on the last slide, the SWAT team will gain additional transportation personnel, however this is still not enough to meet the acceptable turf rate of 8% In order to meet the acceptable turf rate, SWAT must hire an additional 1.5 personnel 26 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

Cumulative Decrease in Turf Rate EXPECTED IMPACT Recommendation Decrease in Turf Rate Cumulative Decrease in Turf Rate Expected Turf Rate Utilize Scheduling Tool 2.85% 15.03% Move Scheduler to Transporter 2.30% 5.15% 12.73% Add 1.5 Full-Time Employees 4.60% 9.75% 8.13% Nikki The expected impact of our recommendations are as follows In utilizing the scheduling tool, the team found that additional runs can be made which will decrease the turf rate by 2.85% In moving the scheduler to a transporter after 930, the turf rate will decrease by 2.3% In adding 1.5 FTEs to the SWAT team, the turf rate will decrease by 4.6% With all of these recommendations in place, the turf rate is expected to drop to 8.13% - an acceptable level 27 Introduction Key Issues Goals and Objectives Methods Findings and Conclusions Recommendations Expected Impact

??? QUESTIONS? NIKKI Thank you for listening and participating in our discussion about our status update. At this time we will be taking any additional questions you may have.