Categories
Health Information Ethics

“Exploring Coder Productivity: A Tableau Presentation and Analysis of AHIMA’s 2018 Study on the Impact of ICD-10 Implementation” “Coding Productivity Assessment”

In this activity, you will manipulate data from an Excel spreadsheet to create a Tableau presentation with reports, charts, graphs and dashboard information related to coder productivity. 
Let’s first discuss some background information on what coding productivity is, how productivity standards are established, and how managers utilize productivity standards.
Managers base coding productivity on the amount and type of information being coded as well as the risk complexity of the cases. Coding productivity standards are usually described by a certain number of charts/encounters coded per hour or day of work. However, other factors must be identified prior to setting specific coding productivity standards such as whether the coder has other tasks to complete in the job (abstracting, answering telephones, communicating with providers and other staff) as well as the kind of record/encounter for which the coder is responsible (e.g., cardiology, obstetrics, emergency department encounters).
There are several methods that can be utilized to set standards for coder productivity, but all must begin with data collection regarding the task itself. Regardless of the method used, productivity should never be assessed without regard to the quality of the production, i.e. the accuracy with which the codes are being assigned.
Productivity standards can be utilized to determine appropriate staffing levels. Information on discharges or encounters also need to be utilized to analyze and correctly forecast staffing. For example, productivity may need to be calculated with a weighted formula to account for certain factors such as length of stay (i.e., longer lengths of stay might mean greater volume of documentation to review and increased complexity of coding). Using this information to our best advantage, appropriate work standards for coding professionals can be achieved.
This activity is designed to help you locate, display and analyze decisions based on data. This type of process helps us to make decisions based on information as described above. First, we will work with a spreadsheet of raw, complete data collected during a 2018 study conducted by AHIMA. You will practice breaking down a large dataset into a smaller subset for the purposes of data visualization.
We will then work with a condensed dataset from a fictional pool of coding professionals that provide support nationally for outsourced physician office setting visits/encounters. The goal will be to determine if the implementation of ICD-10 has affected our coder productivity and/or accuracy.
While the data we are using in Part 1 of this activity was collected in early 2018, the work in this area started with a study conducted by the AHIMA Foundation in 2016. A PDF copy of the 2016 study results can be downloaded using the following link Perceived Effects of ICD-10 Coding Productivity and Accuracy Among Coding Professionals
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. Reading this whitepaper provides background information into why the productivity data was collected. The data illustrates how various factors, such as coder characteristics (e.g., education, experience) can impact the perception of how productive coders are, comparing two different points in time, before ICD-10 implementation and after. Consider the following quote found therein:
“With the implementation of ICD-10, the number of diagnosis codes for healthcare services has increased from 13,000 to 68,000, and the number of procedure codes has also increased. While the new codes allow for greater specificity of reporting diagnoses and care delivered, has the new code set resulted in disadvantages related to training, loss of productivity and system changes and updates? Findings from this study will provide valuable insight into the perceived impact of ICD-10 implementation on productivity and accuracy for coding professionals.” (Rudman et al, 2016, pg 3)
Important! To successfully complete this activity, you must download and save the following Excel files before beginning the assessment. Make sure to save them to a drive location you will have access to for easy retrieval:
2018 Coding Productivity Results Download 2018 Coding Productivity Results – This file will be used in Part 1 to practice breaking a large dataset down into a smaller subset for use in data visualization software such as Tableau.
Coder Productivity Perceptions Download Coder Productivity Perceptions – This is a condensed dataset from a fictional pool of coding professionals that will be used for data visualization in Tableau for Part 2 of this activity.
Download the Coding Productivity instructions 
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before completing the directions. 
Submit the completed dashboard as a PowerPoint file here. 
Rubric
Coding Productivity
Coding Productivity
Criteria Ratings Pts
This criterion is linked to a Learning OutcomeTableau
25 pts
Complete
The student submits the Tableau Dashboard of the Coding Productivity activity. The Dashboard is correct. The assignment is submitted as a PowerPoint file
0 pts
Incomplete
The student submits the Coding Productivity assignment but has more than one error and/or the assignment is not submitted as a PowerPoint file.
25 pts
Total Points: 25