The Case of the Belated Lab Tests
Performance Improvement Opportunity – Part 2
CAHIIM Competency Assessed:
Subdomain III.H. Information Integrity and Data Quality
3. Apply quality management tools
Subdomain VI.C. Work Design and Process Improvement
- Analyze workflow processes and responsibilities to meet organizational needs (Blooms 4)
- Construct performance management measures (Blooms 6)
- Demonstrate workflow concepts (Blooms 3)
Part 1: Create a flowchart (See Lesson) of the process that was discussed in the first meeting (see packet 1) to illustrate the workflow that is currently being used. This will help the team decide where there may be problems in the current workflow.
The following information was extracted from the floor secretary logs from the past week.
- A total of 3622 tests were done and 589 were over the standards for turnaround time
- The breakdown by urgency is as follows:
- Of 459 STATs, 77 were over standard
- Of 1042 Urgents, 334 were over standard
- Of 2121 Routines, 178 were over standard
You want to bring a graph of this data for the next team meeting.
NOTE: Your Excel table might look something like this in order to make a graph that will be valuable.
Number > Standard
% of Total > Standard
Cumulative % of Total
- Create a graph, using Excel, depicting the data above. Analyze this data once your graph is made. What conclusions can be drawn? Write a short summary of what the graph is telling you.
Decide! Does the team have enough data? Brainstorm a list of the data you would like to have. Where would you get that data? Submit a short list of your brainstorm ideas and explain what you would discuss with the team regarding gathering more
Expert Solution Preview
In this assignment, we will be discussing the Case of the Belated Lab Tests. The aim is to apply quality management tools and workflow concepts to analyze the workflow processes, identify areas of improvement, and construct performance management measures to meet organizational needs. We will be creating a graph using Excel depicting the extracted data from the floor secretary logs and analyzing the same to draw conclusions. Additionally, we will brainstorm a list of data that we would like to have and explain our ideas on gathering more data.
To complete Part 2 of the assignment, we need to create a graph using Excel to depict the data extracted from the floor secretary logs from the past week. The data shows that a total of 3622 tests were done, out of which 589 tests were over the standards for turnaround time. The breakdown by urgency reveals that of 459 STATs, 77 were over standard, of 1042 Urgents, 334 were over standard, and of 2121 Routines, 178 were over standard.
To create a graph in Excel, we need to use the data provided in the table. We can create a stacked bar graph that shows the breakdown of tests by urgency and highlights the number and percentage of tests that were over the standard turnaround time. The graph will show three bars, one each for STATs, Urgents, and Routines, with different colors for the tests that were completed within and over the standard turnaround time. The percentage of tests completed within and over the standard turnaround time can also be depicted as labels on the graph.
After creating the graph, we need to analyze the data to draw conclusions. The graph shows that out of all the tests, the maximum number of tests that were over the standard turnaround time were Urgents, followed by Routines and STATs. The percentage of tests completed over the standard turnaround time was the highest for Urgents at 57%, followed by Routines at 30% and STATs at 13%. This indicates that Urgents need more attention in terms of process improvement measures.
Regarding the team having enough data, we can brainstorm more data we would like to have, such as the reasons for the delay in completing tests over the standard turnaround time, patient details, laboratory technician details, etc. The data can be gathered from various sources such as patient charts, laboratory equipment, and test reports. We can discuss the need for further data and how it can assist in the process improvement measures with the team.