Michigan Medicine

Matching Inventory and Demand of Call Rooms

Final Report

Submitted to:Hilary King, MS, RN, Administrative Director, Hospital Operations

Coordinators: Olivia DeTroyer, Industrial Engineer, University of Michigan Health System

Orlando Gonzalez, Junior Management Engineer, University of Michigan Health System

Supervising Instructor: Mark P. Van Oyen

Submitted by:IOE 481 Project Team #8

Mr. Evan BreenMs. Lane Tobin

Mr. Michael BrownMs. Pheebe Hsu

(18W8-Final Report)

Date Submitted: April 17, 2018

Table of Contents

EXECUTIVE SUMMARY...........................................................................................................1Background and Key Issues.................................................................................................1Data......................................................................................................................................1Methods...............................................................................................................................2Findings and Conclusions....................................................................................................2Design Methods, Requirements, Constraints and Standards...............................................2Recommendations................................................................................................................3Expected Impact..................................................................................................................3Next Steps and Future Analysis...........................................................................................3

INTRODUCTION.........................................................................................................................4BACKGROUND............................................................................................................................4

Key Issues............................................................................................................................5Goals and objectives............................................................................................................5Project Scope.......................................................................................................................5

DATA AND METHODS...............................................................................................................5Data......................................................................................................................................5Methods...............................................................................................................................6

FINDINGS AND CONCLUSIONS..............................................................................................6Superior On-Call Room Reservation Systems....................................................................6On-Call Room Accessibility and Supply.............................................................................7Demand for On-Call Rooms is Greater than Supply...........................................................8Verifying Demand with Payroll Logs..................................................................................9Simulation Findings...........................................................................................................13

DESIGN METHODS, REQUIREMENTS, CONSTRAINTS, AND STANDARDS.............14Design Requirements.........................................................................................................14Pugh Selection Matrix.......................................................................................................14Mock On-Call Room Reservation System........................................................................15Design Constraints.............................................................................................................16Design Standards...............................................................................................................17

RECOMMENDATIONS............................................................................................................17Minor changes...................................................................................................................17Major changes....................................................................................................................18

EXPECTED IMPACT................................................................................................................19NEXT STEPS AND FUTURE ANALYSIS...............................................................................20REFERENCES............................................................................................................................21APPENDIX A: Simulation Design.............................................................................................22APPENDIX B: Design Requirements........................................................................................26APPENDIX C: Design Constraints and Standards Matrix.....................................................27

APPENDIX D: Data Processing.................................................................................................29APPENDIX E: Reservation System Access Methods Pugh Matrix........................................30

List of Tables and Figures

Table 1: On-Call Room Classification……………………….…………………………….....… 8Table 2: Average On-Call Professionals by Days of the Week ………………...………....…... 9

Figure 1: Demand by Month …....…………………...……………….………………….....….. 10Figure 2: OR On-Call Room Demand…....…………………...…………………………....….. 11Figure 3: IR On-Call Room Demand…....…………………...………………..…………....….. 12Figure 4: Year Over Year Demand……………………..…....…………………...………....…. 13Figure 5: Call Room Assignment Methods Pugh Matrix…………………………………...…. 15

EXECUTIVE SUMMARY

Michigan Medicine provides beds for on-call professionals scheduled daily. However, the current bed capacity for on-call professionals is constrained. These professionals are not formally on duty, but may be contacted if their services are needed. On-call professionals who need to stay overnight or sleep during the day due to fatigue from duty may choose to stay at the hospital, but can only sleep in on-call rooms that belong to their department. As a result, some departments have empty on-call rooms, while other departments do not have enough. With this poor utilization of on-call rooms, the Administrative Director of Hospital Operations asked the IOE 481 Project Team from the University of Michigan to observe the current reservation system in 2 departments: (1) Operating Room and (2) Interventional Radiology and determine if there is a discrepancy between the number of on-call rooms available and the number of professionals who require rooms.

After examining the current reservation system in these 2 departments through benchmarking, interviewing, analyzing payroll logs, and performing simulations, the team has developed recommendations to design a framework for an alternative reservation system that communicates across OR and IR departments.

Background and Key Issues Currently, the OR and IR departments manage their own set of on-call rooms for their professionals. Departments do not share on-call rooms, leading to poor utilization of all on-call rooms. As a result, on-call professionals do not have a proper place to rest and are dissatisfied with the current on-call room reservation system. In addition, an inconsistency exists between the number of on-call professionals each night stated by the OR and IR managers and the number of professionals receiving on-call pay each night. Therefore, the number of on-call rooms required each night is unknown.

Goals and Objectives The goal of this project is to determine the utilization of on-call rooms in the OR and IRdepartments and design a framework for an alternative reservation system across these twodepartments to assess on-call room availability. To achieve this goal, the team has identified current usage and availability of on-call rooms in these 2 departments. The team has also developed recommendations to decrease the number of professionals without a place to rest and eliminate communication confusion of scheduling on-call rooms across these 2 departments.

Project Scope The scope of this project focuses on examining the number, utilization, and scheduling of all current on-call rooms in OR and IR departments at Michigan Medicine. It also focuses on developing recommendations for a new on-call room reservation scheduling system across these 2 departments.

DataThe team collected data from 3 sources: benchmarking, interviews, and payroll logs. The team contacted 3 hospitals: (1) Beth Israel Deaconess Medical Center in Boston, MA (2) Houston Methodist Hospital in Houston, TX and (3) University of Florida Health Hospital in Gainesville,

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FL. The team conducted 10 interviews with key personnel. The Manager of Nursing information Services provided payroll logs for on-call professionals over the past 2 years.

MethodsThe team inspected all on-call rooms in the OR and IR and used the demand gathered from the data above to design a simulation to test future scenarios of on-call room reservation system.

Findings and Conclusions Through collecting data in benchmarking, interviews, payroll logs, and simulation, the team has discovered significant findings.

Superior On-Call Room Reservation SystemsBeth Israel Deaconess Medical Center provides on-call rooms for professionals living a certain distance from the hospital and reservations can be made on the day the room is required. It also has a 24-hour desk attendant. Houston Methodist Hospital has implemented a modified hotel system. Each on-call room has a cipher lock, a telephone, and a private lockable bathroom. Passwords to the cipher locks can be obtained from their managers. The hospital also provides nap rooms for professionals who need a short rest. At the University of Florida Health Hospital, professionals are allowed to use the on-call rooms within their departments anytime. All on-call rooms have bunk beds and two professionals share a room.

On-Call Room Accessibility and SupplyInterviews with hospital professionals lead to 2 conclusions: (1) All interviewees assert that it is the hospital’s responsibility to provide adequate sleep rooms for their professionals and (2) The demand for on-call rooms is greater than the supply.

Verifying Demand with Payroll LogsPayroll logs data were analyzed in 3 ways: by day, month, and location. The demand in the IR and OR was confirmed to be 4 and around 8 during weekdays. The OR demand increased to 25 on weekends.

Simulation Findings The team discovered 2 findings from the simulation. First, OR and IR departments do not have enough on-call rooms to accommodate the demand. Second, a centralized allocation system improves the utilization of current number of on-call rooms as well as with additional on-call rooms.

Design Methods, Requirements, Constraints and StandardsThe team utilized the findings from the interviews, benchmarking, and data to design the optimal framework for an alternative on-call room reservation system.

Design RequirementsThe team identified 18 design requirements by which the alternative designs were evaluated.

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Pugh Selection Matrix The team used a Pugh Selection Matrix, Call Room Assignment Methods, to determine the best way to distribute on-call room among the 3 assignment methods. The 2 alternative methods were created by the team using findings gained from benchmarking against similar sized teaching hospitals. The Pugh Matrix indicates that the centralized assignment method has the highest total sums and therefore is the most favorable call room assignment method.

Mock FrameworkThe team created a mock framework to both (1) display the functionality of the future on-call reservation system and (2) illustrate what the system would look like from an on-call professional’s point of view.

Design Constraints The team identified 4 design constraints that are restricted for the final design.

Design Standards The Team abided by OSHA regulations, MLearning policy, and the University of Michigan Policy.

Recommendations With the findings, the team was able to make recommendations for the framework design for the alternative on-call room reservation system.

Minor ChangesFour minor changes can be implemented into the current on-call room reservation system: (1) Tracking On-Call Room Availability, (2) Increase Number of On-call Rooms, (3) Share on-call rooms between Departments, and (4) Inspect Weekend On-Call Schedules.

Major Changes The major changes involve complete renovations of the entire process from start to finish. The team recommends a centralized reservation system using a mobile application, single on-call rooms, and nap rooms for professionals who need a temporary rest.

Expected Impact The recommendations will result in 3 impactful changes. First, they will assess if the supply matches the demand. Next, more professionals will have a proper place to rest. Lastly, communications across OR and IR departments will be clear and efficient.

Next Steps and Future Analysis The on-call room reservation system will take 3 months to create and implement using the requirements listed in the system framework. Meanwhile, all departments should track on-call room usage and survey all on-call rooms.

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INTRODUCTIONMichigan Medicine provides beds for on-call professionals scheduled daily. However, the current bed capacity for on-call professionals is constrained. These professionals are not formally on duty, but may be contacted if their services are needed. On-call professionals who need to stay overnight or sleep during the day due to fatigue from duty may choose to stay at the hospital, but can only sleep in on-call rooms that belong to their department. As a result, some departments have empty on-call rooms, while other departments do not have enough. The Administrative Director of Hospital Operations would like suggestions for scheduling professionals to on-call rooms. The IOE 481 Project Team has been asked to observe the current reservation system in 2 departments: (1) Operating Room and (2) Interventional Radiology and determine if there is a discrepancy between the number of on-call rooms available and the number of professionals who require rooms. Based on the findings, the IOE 481 Project Team will design a framework for an alternative reservation system that communicates across these two departments. The purpose of this final report is to present the findings and conclusions, which include data collection and analysis, design methods, and expected impact.

BACKGROUND Currently, the OR and IR departments manage their own set of on-call rooms for their professionals. Since the departments do not communicate and share on-call rooms, the OR department has empty on-call rooms, while the IR department does not have enough. Professionals without an on-call room are sleeping in areas not designated as on-call rooms or sleeping in their car, causing poor sleep, which affects the quality of their work. Professionals report that they are dissatisfied with the current reservation process as shown below:

1. Contact on-call reservation manager within their department2. Request room for a specific day and time3. Wait to hear from reservation manager4. Obtain key or code from reservation manager if room is available5. Access room 6. Otherwise, find alternative place to sleep

The OR department manages 7 on-call rooms while the IR department manages 1. The Operations Manager in the OR and the Director of Clinical Operations and Nursing in the IR state that at least 6 professionals per department are on-call each night. The team also contacted the Manager of Nursing Information Services to confirm number of on-call professionals. The team analyzed 2 years of on-call payroll logs in the OR and IR departments and discovered that the average number of professionals receiving on-call pay during the weekdays in the OR and IR departments are 9 and 5. During the weekends, the number of on-call professionals receiving on-call pay increases to 38 and 13 in the OR and IR departments. The team concludes an inconsistency exists between the number of on-call professionals each night stated by the OR and IR managers and the number of professionals receiving on-call pay each night.Given the issues in the current state, the IOE 481 Project Team will determine the utilization of on-call rooms and design a framework for an alternative reservation system across in the OR and IR departments that assesses on-call room availability.

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Key IssuesThe following key issues are driving the need for this project:

● Departments do not share on-call rooms, leading to poor utilization of all on-call rooms● Professionals do not have a proper place to rest, affecting their work● Professionals are dissatisfied with current reservation system● Number of on-call rooms required each night is unknown

Goals and objectivesThe goal of this project is to determine the utilization of on-call rooms in the OR and IRdepartments and design a framework for an alternative reservation system across these twodepartments to assess on-call room availability. To achieve this goal, the IOE 481 Project Teamis addressing the following objectives:

● Identify current usage and availability of on-call rooms in OR and IR● Decrease the number of professionals without a place to rest● Eliminate communication confusion of scheduling on-call rooms across OR and IR

Project ScopeThe scope of this project will include examining the number, utilization, and scheduling of all current on-call rooms in OR and IR departments at Michigan Medicine. It will also include recommendations for a new on-call room reservation scheduling system across these 2 departments. The scope of this project will not include on-call rooms for house officers. It will also not consider layout of on-call rooms except number of beds.

DATA AND METHODSThe team collected data from 3 sources and used the data to design a simulation in order to test future scenarios.

DataThe team collected data from 3 sources: benchmarking, interviews, and payroll logs.

Benchmarking To gain a better understanding of how other teaching hospitals assign on-call professionals to rooms, the team contacted 3 hospitals: (1) Beth Israel Deaconess Medical Center in Boston, MA (2) Houston Methodist Hospital in Houston, TX and (3) University of Florida Health Hospital in Gainesville, FL.

InterviewsThe team conducted 10 interviews with key hospital staff, including the: Associate Chief Nursing Officer, OR Operations Manager, IR Director of Clinical Operations and Nursing, CVC Director of Nursing and Patient Care Services, Director of Patient Care Services, Manager of Nursing Information, Med-inn Hotel General Manager, Environmental Services Administrative manager, HHC Space Data Coordinator, and OR Nurses. The interviews help the team understand the current on-call room reservation system from employees’ perspectives.

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Payroll LogsIn addition to the interviews, the team also utilized payroll logs data to assess the demand of on-call rooms. The Manager of Nursing Information Services provided payroll logs for on-call professionals over the past two years. Professionals are paid a certain amount to stand on-call and are coded as such in the system. The team obtained the exact number of professionals paid as on-call over the past two years in the OR and IR departments. MethodsThe team inspected all on-call rooms in the OR and IR and used the demand gathered from the data above to design a simulation to test future scenarios of on-call room reservation system.

On-Call Room InspectionThe team surveyed all on-call rooms owned by the OR and IR. The team took pictures of each room and documented the room number, number of beds in the room, and if there was a computer in the room.

Simulation DesignThe goal of the IOE 481 Project Team’s simulation is not to find the optimal solution, but to provide an interface to highlights strengths and weaknesses of different methods of room assignment implemented in ProModel. The simulation simplifies the current hospital reservation system and utilizes discrete event simulation, as suggested by Gunal [1]. ProModel has the capability to test multiple scenarios, which allows for comparisons between the current state, department owned on-call rooms, to potential future states, department shared on-call rooms. For this simulation, the model was run using data from the OR and IR departments; however, it has the capability to be expanded to additional departments. For a detailed description of the simulation design including entities, and locations. See Appendix A.

FINDINGS AND CONCLUSIONSThrough collecting data in benchmarking, interviews, payroll logs, and simulation, the team has discovered significant findings as shown below.

Superior On-Call Room Reservation SystemsThe hospital outreach provides advantageous insight on how to run a hospital wide on-call room reservation system. The IOE 481 Project Team considered these techniques while designing the framework for an alternative on-call room reservation system across OR and IR departments. The team benchmarked by reaching out to 3 academic hospitals of similar size to Michigan Medicine to learn how they schedule on-call rooms.

Beth Israel Deaconess Medical Center Boston, MABeth Israel manages 671 licensed beds, which is comparable to the 1000 licensed beds Michigan Medicines manages. Beth Israel on-call room reservation system includes the following:

● On-call rooms are accessible to professionals living a certain distance from the hospital● On-call reservations are made via phone or in person on the day the room is required● A 24-hour working reservation desk attendant● Single on-call rooms are distributed first, then shared rooms

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● On-call rooms are accessible with a key card● Key cards are picked up and returned to the reservation desk or drop box

Houston Methodist Hospital, Houston, TXHouston Methodist Hospital has implemented a modified hotel system to assign sleep rooms to professionals. They own a total of 42 on-call rooms, in which 13 of them are specifically for residents. Their on-call room reservation system includes the following:

● On-call rooms are accessible to professionals in certain programs● Five of the on-call rooms can be used as overflow rooms for any staff or fellow ● Each on-call room has a telephone and a private lockable bathroom ● All on-call rooms have cipher locks and on-call professionals can obtain passwords from

their manager● On-call professionals are allowed to make gender preferences

In addition to on-call rooms, Houston Methodist Hospital also provides nap rooms for professionals who need rest up to 2 hours. The nap rooms are available Monday through Friday from 8 AM to 4 PM. All rooms have a single bed with no window or TV because they were specifically designed for sleeping. In order to get a nap room, professionals go to a specific building, show their badges, and a staff will escort them to the room. Professionals are also allowed to leave their electronics at the front desk for safekeeping and avoiding disturbances during sleep.

University of Florida Health Hospital, Gainesville, FLUniversity of Florida Health Hospital owns a total of 80 on-call rooms and has never run out of on-call rooms except during severe weather. The on-call rooms were assigned to departments back when they were building the hospital. Their on-call room reservation system includes the following:

● Professionals are allowed to use the on-call rooms within their departments anytime● All on-call rooms have bunk beds ● Two professionals share a room ● Professionals cannot make gender preferences

On-Call Room Accessibility and SupplyThe team inspected all 8 on-call rooms in the OR and IR. The on-call rooms are accessible via keys which are distributed by department. Each department has two keys for each room and EVS has a master key for all on-call rooms. On-call rooms are not allowed to lock from the inside. Professionals complain that they feel unsafe in the on-call rooms because multiple people have access.

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The majority of the on-call rooms are singles, but there are a 2 shared rooms. Professionals prefer single rooms to shared rooms. The team classified the 8 on-call rooms into 2 categories: on-call rooms and consult rooms. Throughout the paper, all 8 will be referred to as on-call rooms, but it is important to note the distinctions.

Table 1: On-Call Room Classification

Classification On-Call Room Consult Room

Quantity 4 4

Picture

The room must have an adjoining bathroom to be classified as ant on-call room. The OR has 3 legitimate on-call rooms. Once these rooms are full, professionals sleep on the couches in the consult rooms that double as a bed at night. These rooms are not ideal because consults begin at 6 AM and the professionals must leave the room beforehand. Lastly, the IR only maintains 1 on-call room.

Demand for On-Call Rooms is Greater than SupplyInterviews with hospital professionals lead to 2 conclusions: (1) All interviewees assert that it is the hospital’s responsibility to provide adequate sleep rooms for their professionals and (2) The demand for on-call rooms is greater than the supply.

According to the Director of Nursing and Patient Care Services in the Cardiovascular Center and Internal Medicine, the lack of on-call rooms for nurses and technicians is a national problem, especially for academic hospitals due to the expensive housing market within close proximity to the hospital [2]. To further confirm this statement, the team researched housing prices near universities and found there is a significant correlation between housing costs and distance to a University [3].

Because of the expensive housing market, hospital professionals are forced to commute further to work. One OR nurse commutes upwards of 1.5 hours. With a response time of 30 minutes, professionals are unable to return home while on-call, leading to a higher demand for on-call rooms. After speaking with professionals who use the on-call rooms, the team concluded that the professionals are unsatisfied with the current on-call room reservation system because they cannot easily access an available room.

Interviews with Director of Clinical Operations and Nursing in IR provided insight into the demand for on-call rooms in the IR. She stated that the IR department does not maintain records of on-call room usage. However, each night, she schedules 3 to 4 teams, which equates to 6 to 8

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professionals, to be on-call. In comparison, the OR has sign in sheets, but they are not monitored or enforced leading to inaccurate data, according to the OR manager. She also stated that there are 6 professionals on-call each night in the OR. Six professionals constitute the minimum demand for the IR and OR department. Minimum demand is the smallest number of professionals that must be on-call each night, which will be used in the ProModel simulation.

These in-person interviews confirm that the minimum demand for on-call rooms is higher than the supply and there is a need for a better on-call room reservation system. The interviews have also provided insight for designing an alternative on-call room reservation system, which will decrease the number of professionals without a place to rest and eliminate communication confusion when scheduling on-call rooms.

Verifying Demand with Payroll LogsThe demand found from analyzing the payroll log data conflicts with the demand found from interviews. The team analyzed the payroll data to determine the demand distribution by day of week and by month. The results were broken down by department and individual driving distance.

Demand by DayThe average on-call professionals in the OR and IR departments by days of the week are seen in Table 2. The IR department has a constant demand of 4 throughout the week. In comparison, the OR department’s demand peaks to about 25 during the weekends, but is constant at 8 during the weekdays.

Table 2: Average On-Call Professionals by Days of the Week

Sunday Monday Tuesday Wednesday Thursday Friday Saturday

OR 25 9 8 7 8 7 26

IR 4 4 4 5 5 4 5

Demand by MonthThe team investigated the seasonality of on-call room schedules to determine which season has the highest demand. As shown in Figure 1 below, December had the highest combined average daily demand of 18.0. In comparison, May has the lowest combined demand of 14.6. The team decided to focus on the in winter months, with the highest demand, to ensure sufficient on-call rooms are available year round.

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Figure 1: Demand by Month

Demand by LocationThe payroll log data provide the number of professionals paid as on-call. However, the data do not specify where the professionals are physically located during their on-call shift, meaning that the professionals may choose to sleep in an on-call room during their shift or at home. The team is only concerned with on-call professionals sleeping in on-call rooms.

The payroll data also include professionals’ home zip codes, which can be used to estimate how many on-call professionals are using on-call rooms. The team mapped the driving distances using an average speed of 40 miles per hour from the Taubman Medical Center to all zip codes listed using Free Map Tool [4]. The team sorted the demand for on-call rooms into 3 scenarios:

1. Best Case: On-call professionals that live further than 25 minutes from the hospital will sleep in on-call rooms.

2. Medium Case: On-call professionals that live further than 15 minutes from the hospital will sleep in on-call rooms.

3. Worst Case: All on-call professionals will sleep in on-call rooms.

The 3 demand scenarios for the OR and IR departments can be found on the following pages, in Figures 2 and 3.

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Figure 2: OR On-Call Room Demand

The OR department has the highest number of professionals on-call during the weekends, up to 38 professionals with 10 occurrences in the Worst Case Scenario. The data conflict with information from OR Operations Manager that 6 to 10 professionals are on-call each night. During the weekdays, 6 to 10 professionals are on-call each night, but during the weekends, the number of paid on-call professionals increases significantly.

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Figure 3: IR On-Call Room Demand

As shown in Figure 3, the number of professionals on-call increases as the IR demand scenarios change from Best Case to Worse Case. In the Best Case scenario, only 4 professionals require an on-call room. In the Worst Case scenario, 7 professionals require an on-call room. As stated in the Findings and Conclusions, the IR Director of Clinical Operations and Nursing stated that 6 professionals are on-call each night. The payroll log data validate that statement.

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Demand by YearThe team also analyzed the combined daily demand for on-call rooms in the OR and IR from year to year, as seen in Figure 4 below.

Figure 4: Year Over Year Demand

All months’ on-call room demand, besides March, due to having partial month’s data, was compared to the same month in the following year. The demand in Year 2 (2017 for Apr.-Dec. and 2018 for Jan.-Feb.) was higher than the demand in Year 1 for all months. Therefore, the team concluded that a growing demand of on-call rooms can cause troubles in the future if the supply of rooms stays the same and the demand continues to grow.

Simulation Findings The team discovered 2 findings from the simulation. First, OR and IR departments do not have enough on-call rooms to accommodate the demand. Second, a centralized allocation system improves the utilization of current number of on-call rooms as well as with additional on-call rooms.

The team determined that the OR and IR departments do not have enough on-call rooms to match the demand from the interviews and payroll data. The current reservation system and the centralized allocation system do not accommodate all professionals. However, a centralized allocation system reduces the number of professionals who required alternative sleep space. On average, 1 additional professional will have an on-call room each day.

The centralized allocation system also increases on-call room utilization. The team added 1 on-call room to each department. The team tested the maximum combined demand scenario, 31 professionals on-call, in the simulation and compared the average numbers of professionals without a place to sleep under current conditions and with an additional on-call room. Department based allocation reduces the average number of professionals without a place to sleep from 26.1 to 23.6, which is a decrease of 2.5. In contrast, a centralized allocation system reduces the average number of professionals without a place to sleep from 23.6 to 19.9, which is a decrease of 3.7. Both numbers are lower for the centralized system, and when an additional

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room is added to each department, the reduction is larger, meaning the system better utilizes the on-call rooms.

Finally, in order to illustrate how these results would expand to additional departments, a simulation was run with 2 mock IRs and 2 mock ORs (using only weekday demand) and 3 different allocation systems. The fist had all departments only using their own on-call rooms, the second had the IRs and ORs sharing internally, and the third had a fully centralized allocation system. The simulation ran for 1,000 iterations. The average daily need for alternative sleep space was 6.4 when all 4 departments do not share, 5.35 when departments share internally, and 4.41 with a fully centralized allocation. The fully centralized allocation system performs the best. Also, when more departments are added, the centralized system utilizes the on-call rooms better than the first two options.

DESIGN METHODS, REQUIREMENTS, CONSTRAINTS, AND STANDARDSThe team utilized the findings from the interviews, benchmarking, and data to design the optimal framework for an alternative on-call room reservation system.

Design RequirementsThe design requirements by which the alternative designs were evaluated are shown below and the tags with links to Appendix C are shown in Appendix B:

1. Time and effort required for nurses/technicians to get an on-call room 2. Time and effort required for desk manager to get an on-call room3. Ease of tracking room availability4. Department Acceptance of approach 5. Proximity of reserved room to department 6. Ability to select who the nurse/technician rooms with 7. Ability for nurse/technician to find an open room 8. Maximize utilization of call rooms/minimize need of alternate sleep space 9. Safety Concerns 10. Ease of use for nurses/technicians 11. Ease of developing for client 12. Ease of maintaining and updating 13. Ease of accessing method/platform for nurses/technicians14. Cost to develop simulation15. Cost of labor required to implement16. Reliability of method/platform17. Ability for expansion18. Number of professionals that do not have a place to sleep

Pugh Selection Matrix The team used a Pugh Selection Matrix, Call Room Assignment Methods, to determine the best way to distribute on-call room among the 3 assignment methods as seen below in Figure 5. The 2 alternative methods were created by the team using findings gained from benchmarking against similar sized teaching hospitals.

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Figure 5: Call Room Assignment Methods Pugh Matrix

The Call Room Assignment Method Pugh Matrix looks at 3 assignment methods that are explained below:

● Current state system: on-calls rooms are owned and utilized by individual departments.● Shared room system: professionals may contact other departments to use their on-call

rooms if their own on-call rooms are occupied.● Centralized desk system: professionals go to a centralized location to obtain on-call

rooms owned by the hospital, not individually owned by department The Pugh Matrix indicates that the centralized assignment method has the highest total sums and therefore is the most favorable call room assignment method. Mock On-Call Room Reservation SystemThe team created a mock framework to both (1) display the functionality of the future on-call reservation system and (2) illustrate what the system would look like from an on-call professional’s point of view.

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System Functionality FrameworkImportant functions of a potential on-call room reservation system were documented. Required functions of the system must include the following:

● Restricting access to the system● Checking for room availability● Confirming and viewing current reservations● Preventing double reservations● Allowing for cancellations● Incorporating backup/alternate sleep space

Mock SystemThe team utilized VBA within Microsoft Excel to create the mock reservation system. The future state reservation system will be a web application. To demonstrate what the web application would look like and how it would function, the team designed a mock system in Microsoft Excel. The functions mentioned above in the System Functionality Framework were incorporated into the mock system. See below for the steps of the mock system.

1. The mock system begins with the users inputting their personal information such as: name, department, and title. The users also select the date that they are searching for an on-call room for, in addition to indicating whether they are willing to sleep with a roommate or in a bunk bed.

2. When the users search for a room, the system checks the room database, which includes room name, number of beds, and room location. The system also checks the room database reservations to determine which rooms are available.

3. Next, the system illustrates the available rooms based on the on-call professionals’ criteria. The users select which available room they would like to reserve and make the reservation. If no room is available, the users will find an alternative sleep space.

4. The users will receive a notification via email or text on the day of the reservation, whether that is the day the reservation is made or three days down the line.

In addition, the mock system includes 2 alerts:

1. Invalid Position - Only non-house officers should be allowed to use this system. If a professional with a different title tries to access the system, he/she will be denied.

2. Invalid Date - Reservations can only be made in the future. Design Constraints The design constraints that are restricted for the final design with tags to the Design constraints and Standards Matrix in Appendix C are shown below:

1. Physical space: number of on-call rooms are fixed. If the demand is higher than the supply, it is not an option to add more rooms. (C-E-1)

2. Response time: response time for on-call professionals is fixed at thirty minutes. The pugh matrix cannot include a requirement that increases the response time. (C-F-1)

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3. No tracking of supply usage: IR department does not have tracking of their on-call room usage. OR department has a tracking system, but is not enforced properly. (C-G-1)

4. On-call rooms widely distributed: since on-call rooms are scattered throughout each department and across the hospital, the team does not have the manpower to get detailed information from each department. (C-G-2)

Design Standards The design standards that the team includes are from OSHA and the University of Michigan Policy shown below:

OSHA (Occupational Safety & Health Administration) standards:● Consultation Agreements (1908.6 Conduct of a visit) (S-2-1)

The team completed online MLearning modules before the onsite visit to Michigan Medicine to ensure all members understand the rules and policies at the hospital. The team also conducted online research to learn about the hospital’s operations before the onsite visit.

University of Michigan Policy: The names of all professionals that the team has conducted interviews with are kept confidential (S-1-1). The team did not reveal the professionals’ names in documentations and during client and coordinator meetings. In addition, the hospital layout plans and on-call room locations are kept confidential (S-1-2). All maps are kept on Mbox drive and the team does not access them from personal computers.

The team searched the websites for Design Standards on March 11th, 2017 6-9 PM with keywords sleep, rooms, nurses, but found no relevant standards from HIPPA, ASTM, ANSI, SAE, or Mil-Specs.

RECOMMENDATIONS The team divided the recommendations section into 2 portions: Minor and Major changes. Minor changes are able to be implemented into the current on-call room reservation system and major changes involve complete renovations of the entire process from start to finish.

Minor changesFour minor changes can be implemented into the current on-call room reservation system, including tracking on-call rooms availability, increase number of on-call rooms, department sharing, and further inspections of weekend on-call schedules.

Tracking On-call Rooms AvailabilityAccording to the interview with IR and OR managers, the IR department does not track on-call room usage at all and the OR department has sign-in sheets, but are not enforced, leading to inaccurate records. In addition, the payroll data show only the number of professionals on-call,

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not the number of professionals who stay at the hospital and sleep in the on-call rooms. Therefore, the team suggests that the IR and OR departments implement a sign-in sign-out protocol for all on-call professionals using the computers in the on-call rooms.

Increase Number of On-Call Rooms Based on the payroll data, the IR department has 6 on-call professionals daily. However, the IR department only has 1 on-call room that sleeps 2 professionals. The team has determined a need for additional on-call rooms in the IR department because 4 on-call professionals do not have a proper place to rest every day. The team recommends that the IR department either increases on-call rooms from 1 to 3 or switches to department sharing with the OR department.

Department Sharing Since the OR and IR departments own a total of 8 on-call rooms only, the team recommends that the 2 departments share their on-call rooms. The simulation shows that sharing on call rooms reduces the number of professionals without a place to rest by an average of 7.8 each week. Therefore, department sharing will improve overall utilization of all on-call rooms and more professionals have a proper place to rest.

Further Inspections of Weekend On-call SchedulesThe payroll data identify that the OR department staffs over 30 on-call professionals on weekends as shown in Table 2. See Appendix D for the SQL relational database and queries. The high demand conflicts the demand of 6 on-call professionals each night stated by the OR manager. The team recommends inspecting further into the weekend on-call schedules to determine the reason that the number of on-call professionals is particularly high on weekends.

Major changesThe 3 major changes involve complete renovations of the entire process from start to finish, including a centralized reservation system using a mobile application, single on-call rooms, and nap rooms for professionals who need a temporary rest.

Centralized Reservation System The team recommends implementing a centralized reservation system across the hospital for 3 reasons: (1) Track on-call room availability and increase utilization (2) Increase safety (3) Implement restrictions on who can use the on-call rooms.

First, the centralized reservation system will track which on-call rooms are occupied and prevent double reservations. Based on the Pugh Selection Matrix in Appendix E, the team compared the current state, phone call, web application, and mobile application reservation systems. The team determined that a mobile application is the best system for reserving on-call rooms with the highest total of weighted sums. In a mobile application, the room availability will be updated constantly as professionals reserve on-call rooms. With the constant updates of room availability,

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once a professional signs out of the on-call room, other professionals can easily see the room is no longer occupied and reserve instantly on their mobile device. The overall on-call room utilization will increase through tracking and continuous mobile updates.

Second, in the current system, each department maintains duplicate keys for each on-call room and EVS has a master key. From the interviews with the OR nurses, the nurses do not feel safe sleeping in the on-call rooms because the rooms are not secure. The team recommends implementing a key card system. The key cards will be picked up and dropped off at a central location. Once a professional signs out of a room, the key card will deactivate. Professionals will feel safer sleeping because no one can access the room.

Third, the centralized reservation system will restrict access for professionals that live within a certain distance from the hospital. It will prioritize professionals that live further away due to limited number of on-call rooms and response time of 30 minutes for on-call professionals.

Single On-call RoomsAccording to interviews with nurses, the team concludes that most professionals prefer to sleep in single on-call rooms to eliminate disturbances, gender preferences, and safety concerns. Professionals utilizing an on-call room are exhausted and do not want to be disturbed by a roommate. Some professionals also stated that they do not feel comfortable sleeping with the opposite gender. Michigan Medicine policy states that departments are not permitted to ask professionals to reveal their gender. It is not feasible to design a system that accommodates for all gender preferences without asking for gender. Due to professionals’ preferences to sleep individually and the Michigan Medicine’s gender policy, the team recommends only building single on-call rooms in the future.

Nap Rooms From the data analysis through benchmarking, the team recommends providing nap rooms for professionals who need a temporary rest similar to the Houston Methodist Hospital. The nap rooms will have 2 main impacts. First, they will decrease the number of on-call rooms requested each night if professionals are able to have enough rest during the temporary stay. Second, professionals who need rest due to any reason are allowed to stay. A nap room will allow for a quiet and short stay without occupying an entire on-call room.

EXPECTED IMPACTThe team’s recommendations will result in 3 impactful changes. First, identifying the current usage of all the on-call rooms in OR and IR departments will assess if the supply matches the demand. Next, more professionals will have a proper place to rest, allowing professionals to perform work responsibilities attentively. Lastly, communication across these two departments concerning on-call room scheduling will be clear and efficient, enabling professionals to quickly access on-call rooms when required.

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NEXT STEPS AND FUTURE ANALYSISTo implement the IOE 481 Team’s recommendations, the on-call reservation system should first be built. This should be completed using the requirements for the system listed in the system framework. Based on the team’s estimations, the system should take around three months to create and implement.

While the system is being developed, all departments throughout the hospital should be surveyed in order to determine the total non-house officer on-call room supply. These rooms should be surveyed in order to determine the room properties for the database that the reservation system utilizes. Departments should also begin to document and track not only the workers that are on-call, but also the frequency of the workers requiring an on-call room. This documentation will be helpful to enable a more accurate demand to be calculated with the addition of more and more departments. Finally, departments should open up their on-call rooms to allow professionals from other departments to utilize them, when necessary.

Once the on-call room reservation system is created and ready for roll out, all departments should be notified of new on-call room procedures. Nurses and technicians that will utilize the on-call rooms should also be notified of how to access the system.

Finally, the on-call room reservation system can then be implemented for house officers and future hospital expansion. However, another analysis should be conducted to determine if the supply of rooms for house officers matches the supply of the on-call rooms.

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REFERENCES

[1] Günal, M.M.  2012. “A Guide for Building Hospital Simulation Models,” Operational Research Society, vol. 1, pp. 17-25.

[2] S. MacDonald, ‘Director of Nursing and Patient Care Services in the Cardiovascular Center and Internal Medicine’, University of Michigan Health Systems, 2018.

[3] Aikman, Misha-von-Derek, (2014, May). “Does Living Near a University Boost Home Prices? Duke and Durham As a Case Study.” Duke University. [Online]

Available at: https://sites.duke.edu/urbaneconomics/?p=1102

[4] “Free Map Tools,” Free Map Tools. [Online].

Available at: https://www.freemaptools.com/.

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APPENDIX A: Simulation Design

Simulation Text File w/ ExplinationsLocations

Name Cap Units Stats Rules CostCentral_Desk_IR 1 1 Time Series Oldest, ,

Central_Desk_IR_q INF 1 Time Series Oldest, FIFO,

Central_Desk_OR 1 1 Time Series Oldest, ,

Central_Desk_OR_q INF 1 Time Series Oldest, FIFO,

Centralized_Allocation 1 1 Time Series Oldest, ,

Call_Room_IR IR_Room_count 1 Time Series Oldest, , FIRST

Call_Room_OR OR_Room_count 1 Time Series Oldest, , FIRST

Alternative_Sleep_Space INF 1 Time Series Oldest, ,

The number capacity at each routing location is 1 so they may only be used one at a time. The queue capacity is infinite to allow for unlimited arrivals. The number of call rooms available are set by macros which can be changed by scenario. The alternative sleep space capacity is infinite to serve as overflow.

EntitiesName Speed (fpm) Stats Cost

IR_Nurse 150 Time Series

OR_Nurse 150 Time Series

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Separate entities for the nurses / techs from each department. This allows for easier tracking

For model 1, routing is simple. Nurses arrive at their respective queues then move to their central desk. If their department has a call room available, they move there to rest and if not they move to alternative sleep space to rest.

For model 2, nurses are routed from their respective queues to central allocation. From there they are routed to a bed with a priority on their home department, using alternative sleep space if neither department has beds available.

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ProcessingProcess RoutingEntity Location Operation Blk Output Destination Rule Move LogicALL Central_Desk_IR_q Wait 5 min

If Model_ID = 1 Then Route 1If Model_ID = 2 Then Route 2

1 ALL Central_Desk_IR FIRST 12 ALL Centralized_Allocation FIRST 1

ALL Central_Desk_OR_q Wait 5 minIf Model_ID = 1 Then Route 1If Model_ID = 2 Then Route 2

1 ALL Central_Desk_OR FIRST 12 ALL Centralized_Allocation FIRST 1

ALL Central_Desk_IR Wait 51 ALL Call_Room_IR FIRST 1 Moving

ALL Alternative_Sleep_Space FIRST 1 MovingALL Central_Desk_OR Wait 5

1 ALL Call_Room_OR FIRST 1 MovingALL Alternative_Sleep_Space FIRST 1 Moving

ALL Centralized_Allocation Wait 5If department = 1 Then Route 1If department = 2 Then Route 2

1 ALL Call_Room_IR FULL 1 MovingALL Call_Room_OR FULL MovingALL Alternative_Sleep_Space ALT Moving

2 ALL Call_Room_OR FULL 1 MovingALL Call_Room_IR FULL MovingALL Alternative_Sleep_Space ALT Moving

ALL Call_Room_IR Use_Room1 ALL EXIT FIRST 1

ALL Call_Room_OR Use_Room1 ALL EXIT FIRST 1

ALL Alternative_Sleep_Space Inc Alt_SleepUse_Room

1 ALL EXIT FIRST 1

Arrivals

Entity Location Qty EachFirst Time Occurrences Frequency Logic

IR_NurseCentral_Desk_IR_q

P(IR_avg_demand); Daily_Request_Timing 12 hr INF 24 hr

department = 1

OR_NurseCentral_Desk_OR_q

P(OR_avg_demand); Daily_Request_Timing 12 hr INF 24 hr

department = 2

OR_NurseCentral_Desk_OR_q

P(OR_weekend_demand); Weekend_Request_Timing 3 day INF 7 day

department = 2

OR_NurseCentral_Desk_OR_q

P(OR_weekend_demand); Weekend_Request_Timing 4 day INF 7 day

department = 2

Arrival frequency is based on the distributions found in the payroll data. There was a steady base daily demand for both the IR and the OR. As the model begins on a Wednesday at 12 am, the demand distribution begins 12 hours later at noon and repeats each day. The OR also had additional weekend demand which is modeled separately for Saturday and Sunday. These demand distributions begin 3 and 4 days after the model beings on Saturday at 12 am and Sunday at 12 am.A poisson distribution was used to model the variability in demand. While the distribution does not fit the precisely, it is close and easy to understand and work with.

AttributesID Type Classification

Department Integer Entity

Used in the routing logic

Variables (global)ID Type Initial value Stats

Alt_Sleep Integer 0 Time Series

Used to track the total number of people using alternative sleep space

MacrosID Text

Model_Id 1

Use_Room Wait 8 hr

Moving Move For 10 min

IR_Room_Count 2

OR_Room_Count 6

IR_avg_demand 5.5

OR_avg_demand 10

OR_weekend_demand 22

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The Use_Room and Moving macros are to standardize those processes across multiple processing statements. The rest are used to adjust the parameters in order to analyze different scenarios

Arrival CyclesID Quantity / % Cumulative Time (Hours) Value

Daily_Request_Timing Percent No 2 5

4 10

6 20

8 30

10 25

12 10

Weekend_Request_Timing Percent No 4 20

4 20

4 20

4 20

4 20

The arrival cycles were used to space out the arrival of professionals throughout the day instead of all arriving at one time. This was done to better match the findings from our interviews where it was stated that some people came to check out the keys for rooms early in the day if they were around but most checked them out in the evenings, closer to when they would be using the on-call rooms.

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APPENDIX B: Design Requirements

The design requirements by which the alternative designs were evaluated with tags to the Design constraints and standards matrix in Appendix C are shown below:

1. Time and effort required for nurses/technicians to get an on-call room (R-H-1)2. Time and effort required for desk manager to get an on-call room (R-H-2)3. Ease of tracking room availability (R-F-1)4. Department Acceptance of approach (R-A-1)5. Proximity of reserved room to department (R-E-1)6. Ability to select who the nurse/technician rooms with (R-C-1)7. Ability for nurse/technician to find an open room (R-F-2)8. Maximize utilization of call rooms/minimize need of alternate sleep space (R-D-1)9. Safety Concerns (R-C-2)10. Ease of use for nurses/technicians (R-F-3)11. Ease of developing for client (R-I-1)12. Ease of maintaining and updating (R-I-2)13. Ease of accessing method/platform for nurses/technicians (R-E-2)14. Cost to develop simulation (R-D-2)15. Cost of labor required to implement (R-D-3)16. Reliability of method/platform (R-E-3)17. Ability for expansion (R-I-3)18. Number of professionals that do not have a place to sleep (R-A-2)

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APPENDIX C: Design Constraints and Standards Matrix

Below is the constraints and standards matrix that the team organized based on categories:

Entry # 1 2 3

Requirements

R-A. Organizational Policy (R-A-1) (R-A-2)

R-B. Ethical N.A.

R-C. Health & Safety (R-C-1) (R-C-2)

R-D. Economic (R-D-1) (R-D-2) (R-D-3)

R-E. Implementability (R-E-1) (R-E-2) (R-E-3)

R-F. User Acceptance (R-F-1) (R-F-2) (R-F-3)

R-G. Patient Acceptance N.A.

R-H. Time Limitations (R-H-1) (R-H-2)

R-I. Client Requirements (R-I-1) (R-I-2) (R-I-3)

Entry # 1 2 3

Constraints C-A. Organizational Policy N.A.

C-B. Ethical N.A.

C-C. Health & Safety N.A.

C-D. Economic N.A.

C-E. Implementability (C-E-1)

C-F. Task Duration (C-F-1)

C-G. Team Constraints (C-G-1) (C-G-2)

Entry # 1 2 3

Standards S-1. Organization's Std. (S-1-1) (S-1-2)

S-2. OSHA (S-2-1)

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Standards that are not of consequence

HIPPA,ANSI, IEEE

NIOSH, ASTM

SAE, Mil-Specs

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APPENDIX D: Data Processing

Relational Database:

SQL Queries:

IR Distinct by Day, Best CaseSELECT O.Date, MIN(O.DOW) AS DOW, MIN(O.DOW_ID) AS DOW_ID, COUNT(O.Name)

AS Distinct_Count, MIN(O.Month_ID) AS Month_ID, MIN(O.Year_ID) AS Year_IDFROM (SELECT DISTINCT P.Zip, O.Name, O.Date, O.DOW,

O.DOW_ID, O.Div_CC, O.Month_ID, O.Year_IDFROM Zips AS Z INNER JOIN

(People AS P INNER JOIN (Div AS D RIGHT JOIN Oncall AS O ON D.Div_Code = O.Div_CC) ON P.Name = O.Name)

ON Z.Zip = P.ZipWHERE D.IR = Yes AND Z.Dist_cat > 1) AS O

GROUP BY O.DateORDER BY O.Date;

IR MonthlySELECT O.Month_ID, O.Year_ID,

ROUND(AVG(O.Monthly_Distinct)) AS AVG_Monthly_DistinctFROM (SELECT Month_ID, Year_ID, SUM(Distinct_Count) AS Monthly_Distinct

FROM IR_Distinct_dailyWHERE Date > #4/1/2016# AND Date < #3/1/2018#GROUP BY Month_ID, Year_ID) AS O

GROUP BY Month_IDORDER BY Month_ID, Year_ID;

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APPENDIX E: Reservation System Access Methods Pugh Matrix

The Reservation System Access Methods Pugh Matrix looks at different characteristics such as ease of usage, cost of labor, speed of making reservation, reliability of platform, and ability for expansion for Current System, Phone Call, Web Application, and Mobile Application. The Pugh Matrix indicates that the Mobile Application is the best reservation system access method with the highest total sums.

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