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Optimizing Patient Throughput Baylor University Medical Center Katy Moffett Carolyn Trimble Jessica Trimmer Ashley VanMeter.

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Presentation on theme: "Optimizing Patient Throughput Baylor University Medical Center Katy Moffett Carolyn Trimble Jessica Trimmer Ashley VanMeter."— Presentation transcript:

1 Optimizing Patient Throughput Baylor University Medical Center Katy Moffett Carolyn Trimble Jessica Trimmer Ashley VanMeter

2 Background of Problem Baylor Task Force Connie Bowling, Baylor Engineering Management John Dixon, head of Nursing Management and Nursing Research Jamey Koontz, Baylor Engineering Management

3 Problem Emergency Department’s admissions process was in need of a more streamlined flow and the elimination of bottlenecks Average wait time in Emergency Department is 6 hours Description of Problem

4 Baylor’s Overall Goal Reduce Emergency Department wait time by 20% This would be an average wait time of 4 and ¾ hours instead of 6 hours

5 Initial Investigation Due to the Emergency Department’s very complicated process, the realm of our project needed to be narrowed to the bed placement Further Investigation We discovered the underlying problem for bed placement was the patient discharge process Final Decision We decided that the discharge process was a feasible and rewarding project. Focus turned to 2 Johnson and 2 Intensive Care Unit Background/Description of Problem

6 Main Baylor Correspondents Marcella Owens, 2 Jonsson Clinical Manager Charlotte Farris, 2 Intensive Care Unit Clinical Manager Nathan Thompson, Manager of Environmental Services Description of Problem

7 Our Team Goal Map out flow analysis of every possible situation encountered Collect relevant corresponding data Observe the process and make alterations Analyze the data and make subsequent suggestions Description of Problem

8 Questions Addressed What are the bottlenecks for the discharge process? What are the roles of each person involved? How long does each action take? What are the prerequisites for each step? What is the order of hierarchy among Baylor employees?

9 Decisions Made What exact data needs to be collected? Who are the relevant people to contact about the processes? Description of Problem

10 Analysis of the Situation Observed detailed discharge and transfer process for all types of patients Ordered the specific steps into separate flow charts Included completion times for steps when available Examined flow chart and average procedure times to find bottlenecks General Approach to the Problem

11 Types of Patients Discharged to Home (2 ICU) Transferring Cardiac Patient (2 ICU) Transferring Medicine Patient (2 ICU) Expired Patients (2 ICU) Against Medical Advice (2 ICU) Discharged to Home (2 Jonsson) Against Medical Advice (2 Jonsson) Analysis of the Situation

12 Model Assumptions Discharge procedures are accurate Task times recorded are accurate All patient types are covered within the given discharge processes All nurses follow a similar procedure Analysis of the Situation

13 Technical Description of Model Process is very patient-specific After Medical Doctor writes order or transfer, there are many different scenarios We created flow charts for each type of patient No patient is ever the same

14 Technical Description of Model Variables & Constraints Linear Variables of Patient Flow Each required step of the patient flow process Illustrated in flow chart Integer Variables in Patient Flow Time of the completion of each step Constraints The steps in process that have to be completed in order to continue

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17 Analysis of Data

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19 Conclusions General Solutions Type instructions to cut down on time spent interpreting handwriting Admissions Solutions Implement a real-time bed display system Solutions for 2 ICU Combine steps during periods of down time

20 Conclusions Solutions for 2 Jonsson Doctors should keep nurses updated through instructions in patient charts Implement a discharged patient waiting room Offer alternate transportation Mandatory discharge check-out time


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