University of Michigan Health System
Materiel Services Center
Implementation of Proximity to Care Model for Inventory Improvement
Final Report
Submitted to:
Ms. Kristine Komives
Associate Director of Supply Chain/Materiel Services
Mr. Adam Haab
Supply Chain Analyst - Michigan Medicine
Mr. Ab Bustillo
Warehouse Supervisor - Michigan Medicine
Mr. Tim Bates
Nurse/Supply Room Support - Michigan Medicine
Mr. Arnold Yin
Industrial Engineer Supply Chain Specialist - Quality Improvement
Ms. Yuting Ding
Industrial Engineer Fellow - Quality Improvement
Dr. Mark Van Oyen
IOE 481 Professor
Submitted by:
IOE 481 Project Team #6,
Ms. Andrea Fungueirino
Mr. Orlando Gonzalez
Ms. Jessica Sirias
Date Submitted: December 12th, 2017
EXECUTIVE SUMMARY
Background
Key Issues
Methodology
Nurse Observations
Nurse Interviews
Order Data
Time Studies
Linear Program
Findings and Conclusions
Literature Review
Nurse Observations
Nurse Interviews
Order Data
Linear Program
Time Studies
Recommendations
INTRODUCTION
BACKGROUND
Previous 5th Floor State
Current State
Proximity to Care Model
KEY ISSUES
GOALS AND OBJECTIVES
PROJECT SCOPE
METHODS
Literature Search
Nurse Observations
Nurse Interviews
Order Data
Time Studies
Linear Program
FINDINGS AND CONCLUSIONS
Literature Search
Nurse Observations
Nurse Interviews
Order Data
Linear Program
Time Studies
Recommendations
Location of Items
Proximity to Care Model Improvements
Future Work in Implementing Proximity to Care Model
Expected Impact
Methods and Constraints
Standards
EXECUTIVE SUMMARY
Background
The 5th floor of the University of Michigan Hospital is composed of 4 units: A, B, C and D. Units 5-A, 5-B, and 5-C are acute care units, and unit 5-D is an intensive care unit.Prior to the recent change in patient population, the University of Michigan Hospital 5th floor patient population was general surgery patients. On September 19, 2017 patient population of the 5th floor University of Michigan Hospital changed to optimize patient flow. Currently, units 5-A, 5-B and 5-C house urology surgery patients, urology patients, and colorectal patients. The units are also being used for overflow patients. Each of the units holds 32 patient beds, and about 160 nurses are staffed daily to all three acute care units combined.
Proximity to Care Model
The proximity to care model was created by the University Hospital to improve the management of medical supplies [1]. There are five main criteria to determine supply locations: the urgency/criticalness of the supply, the frequency of use, the medical event, the variability of patient, and other factors such asmobile clinical functions like phlebotomy that carry their supplies in their own carts. Those five criteria determine the location of the supplies.
Key Issues
The following key issues are driving the need for this project.
●UMHS has not applied a standard approach determining where supplies should be located such as the proximity to care model
●UMHS currently lacks the resources to gather and analyze data on the new patient population operation and how those changes affect the medical supplies
Methodology
The team conducted a literature search, completed nurse interviews, performed observations of nurse supply usage, analyzed order data, conducted time studies and created a linear program.
Nurse Observations
Nurse observations were performed from October 9th to November 10th, 2017 between the hours of 7 am and 7 pm. The data collected gave information on the Usage Frequency for each supply which is a criteria the team members added in the Proximity to Care Model.
Nurse Interviews
To determine Criticality, Medical Event, Frequency and Variability per Patient of the Proximity to Care Model, the team carried out a series of nurse interviews. The nurse interviews were developed using the historical order data from the month of October. The obtained the top 100 items for each unit. For each item, the team asked the nurse to report the criticality of the supply, the frequency on patients, whether the supply was used for an unknown or a known medical event, and the variability per patient.
Order Data
The team members gathered historical data from the hospital database starting from before May 2017 to August 2017, but only use data from October 2017. This data helped determine the order frequency which is correlated to the usage frequency.
Time Studies
To show how moving a medical supply from the clean room to the nurse server would save travel time for nurses; the team decided to perform a time study. The team ran a time study of 100 trials to determine how long it takes a nurse to walk a foot per minute. During observations nurses didn’t always walk to their destination right away and there was no way of gauging how much distance was travel that is why this trial was conducted.
Linear Program
A linear program was created that inputted the data from the nurse interviews as well as order data and nurse observation data and produced the supplies that should be placed into the nurse server. The model considered constraints such as the capacity and what would be allowed in the nurse server.
Findings and Conclusions
Literature Review
The article The management of the supply chain for hospital pharmacies: A focus on inventory management practices helped the team understand common inventory practices in the hospital industry as well as learn of different factors that affect inventory levels to see how to improve the proximity to care model. The second article Optimal inventory policy within hospital space constraints helped the team members develop the linear program.
Nurse Observations
The top supplies used in unit 5-A were Medicine Cups, Gauze Sponges, and Lubricant Jelly. The most frequently used supplies in unit 5-B were ABD Pads, Blue Pads and Medicine Cups. Lastly, Saline Flushes, ABD Pads and Luer-lok Syringes were the most frequently used supplies in unit 5-C. The supplies with the high usage frequency were more likely to be added to the nurse server.
Nurse Interviews
The critical supplies in 5A include chemo-sensicare gloves and gauze sponges while some supplies that are not critical include baby wipes and medicine cups. For 5B, the supplies that are most critical include blood test strips and urinary while some supplies that are not critical include beige slippers and ice packs. Lastly, for 5C, all-purpose sponges and saline bags are considered critical whereas items such as stethoscopes and facial tissues are considered non-critical. Among other factors, the more critical supplies were placed in the nurse server.
Order Data
As shown by the order data, Unit 5A’s highest ordered supplies were Abdominal Pads, 3-mL LuerLok Syringes, and Blue Absorbent Underpads. 5B’s highest ordered supplies were Abdominal Pads, Isolation Gowns, and LuerLok Caps. Lastly 5C’s highest ordered supplies were Abdominal Pads, and Drain Sponges.
Linear Program
A list of 30 supplies was created that maximize unit frequency, order frequency, usage frequency and criticality for each unit. Appendix 7 displays the results for the linear program.
Time Studies
For Unit A on average nurses will waste anywhere between 5 hours to 32 minutes retrieving medical supplies daily. For Unit B it can be seen that on average nurses will waste anywhere between 8 hours to 50 minutes retrieving medical supplies daily. For Unit C it can be seen that on average a nurse will waste anywhere between 29 to 3 minutes daily retrieving items. For a thorough analysis reference Appendix 8.
Recommendations
Considering all of the findings from the nurse surveys, nurse observations, order data and the linear program, the team created recommendations for the supplies that should be added to the clean room and nurse server for 5A, 5B and 5C can be found in Appendix 7.
To improve the proximity to care model, the team identified 4 recommendations. One recommendation is that there should be an option to not include all factors depending on if the unit is for acute versus intensive. The second recommendation is that the model should have a factor with what is allowed in the nurse server. The third recommendation is that it should be standard for the proximity to care model to include order frequency and unit frequency to make sure the model takes into account how many supplies have been used over a period of time. Lastly, the definitions for each factor and the measures used to describe them are vaguely defined. The factors should be defined quantitatively in order for the proximity to care model to be standardized.
For future work in implementing the proximity to care model for other units or the same unit, the team has a few recommendations on what can be reused and what could be improved. For the nurse surveys, the team recommends to continue the same format, but to pass out the survey to more nurses per unit. The team also recommends using barcode scanning to track the usage of the supply and thought incorporating usage and order data into the model made the model more robust. Lastly, the linear program is a good baseline to use for all units, however changes in the weights of the objective function may be necessary as well as addition of constraints as more guidelines are discovered.
INTRODUCTION
The fifth floor of the University of Michigan Hospital previously provided care to general surgery patients. As of September 19, 2017, the patient population of the fifth floor University of Michigan Hospital was changed to urology surgical, urology, colorectal, and general overflow to optimize patient flow. Due to this change in patient population, the supplies required for patient care in the units 5-A, 5-B, and 5-C must also change. There is currently no standard approach that has been implemented to manage supplies. To improve the management of medical supplies on the 5th floor, the University Hospital Supply Chain and Materiel Services staff want to apply the newly developed proximity to care model, a model that provides criteria on where supplies should be located based on frequency, criticality, medical event, variability per patient and other. However, Materiel Services lack the resources to gather and analyze data on supply usage to determine optimal locations for each of the supplies relative to patients’ bedside. Therefore, the Associate Director of Supply Chain and Materiel Services has asked an IOE 481 student team from the University of Michigan to observe the three units, collect data on the usage of supplies by nurses, and recommend for where each supply should be located. The purpose of this report is to present the team’s findings, conclusion and recommendations.
BACKGROUND
The 5th floor of the University of Michigan Hospital is composed of 4 units: A, B, C and D. Units 5-A, 5-B, and 5-C are acute care units, and unit 5-D is an intensive care unit.
Previous 5th Floor State
Prior to the recent change in patient population, the University of Michigan Hospital’s 5th floor patient population was general surgery patients.
Current State
On September 19, 2017 patient population of the 5th floor University of Michigan Hospital changed to optimize patient flow. Currently, units 5-A, 5-B and 5-C house urology surgery patients, urology patients, and colorectal patients. The units are also being used for overflow patients. Each of the units holds 32 patient beds, and about 160 nurses are staffed daily to all three acute care units combined.
Due to the change in patient population, the supplies needed for patient care must also change. Patient care supplies could be in one of four locations:
- Point of care (nurse server)
- Intermediate (8 nurse carts per unit)
- Central location in unit (unit clean room)
- Outside of the unit (warehouse)
Nurse servers are the locker-like storage compartments outside of each patient room. The supplies currently located in the nurse server are shown in Appendix 1. Intermediate carts are small carts located throughout the unit. For this project, the team focused on the supplies in the nurse servers and unit clean rooms.
With the change in patient population in place, the UH Supply Chain and Materiel Services staff has the opportunity to improve the management of medical supplies on the 5th floor by applying a proximity to care model which has a set of criteria to determine where medical supplies should be located relative to the patient bedside.
Proximity to Care Model
The proximity to care model was created by the University Hospital to improve the management of medical supplies [1]. It has a standard criteria on the time sensitivity and frequency of use of each supply that are used to determine where they should be located relative to patient bedside. The framework for the proximity care model can be seen in Figure 1.
As seen in Figure 1, there are five main criteria used to determine a supply’s location: the urgency/criticalness of the supply, the frequency of use, the medical event, the variability of patient, and other factors such asmobile clinical functions like phlebotomy that carry their supplies in their own carts. The possible locations for the supplies are outside the unit, central location in the unit, intermediate (8 nurse carts per unit), and point of care (patient bedside). Outside the unit would pertain to the warehouse. The central location in the unit is the clean room located in each corresponding unit. The intermediate location refers to the eight mobile carts outside certain patient rooms. Finally, the point of care locations are the nurse servers right outside each patient room. In the model, each location is denoted by a different color and shape to represent the locations respective layout. For example, point of care or the nurse servers are locker-like storage outside the patient room which is why on the model the graphic looks like a locker.
KEY ISSUES
The following key issues are driving the need for this project.
●UMHS has not applied a standard approach determining where supplies should be located such as the proximity to care model
●UMHS currently lacks the resources to gather and analyze data on the new patient population operation and how those changes affect medical supply usage.
GOALS AND OBJECTIVES
To determine the optimal location for each medical supply relative to the patient bedside, the team accomplished the following tasks:
●Observed nurses taking supplies during their shift to obtain data for the usage of medical supplies, time sensitivity and criticality
●Analyzed the data to determine frequency of use of each product
●Compared the time it takes nurses to pick out supplies from the nurse servers as opposed to the unit clean room.
With this information the team designed recommendations for:
●Where to locate each type of supply
●How to implement the proximity to care model
PROJECT SCOPE
This project includes only University of Michigan Hospital fifth floor units 5-A, 5-B, and 5-C. The team focused on two of the four areas of supply storage: the nurse servers outside patient rooms, and the clean room in each unit.
This project did not include any data collection or analysis of the intensive care unit 5-D. The team also did not consider any other storage facility other than the unit clean room and the nurse servers.
METHODS
To complete the project, the team conducted a literature search, completed nurse interviews, performed observations of nurse supply usage, analyzed order data data, conducted time studies and created a linear program. In order to accurately determine the best location for each supply, the team decided to add two factors to the Proximity to Care Model: usage frequency and order frequency. These two additional factors described below will provide a more holistic representation of how often each medical supply is used. For further information on the reasoning behind the analysis tools we used, reference Appendix 2 which provides the design documentation.
Literature Search
The team members conducted a literature search on two articles related to past work on medical supplies and managing inventory. The first article was called The management of the supply chain for hospital pharmacies: A focus on inventory management practices by F. J. Beier which discusses the logistics of determining where to locate pharmaceutical supplies in a hospital. The goal of reading the article was to understand common inventory practices in the hospital industry as well as learn of different factors that affect inventory levels to see how to improve the proximity to care model. The second article was called Optimal inventory policy within hospital space constraints by James Little and Brian Coughlan which discusses creating a mathematical model for inventory decision making. The goal of reading the article was to learn how to take a general model like the proximity to care model and transform it into a standard quantitative tool.