Hi Community members, A solution to last week’s challenge can be found here. This challenge was submitted by Erin Miller, @Erin . Thank you, Erin, for your submission! You are a data analyst reviewing independent medical review outcomes. Your objective is to identify patterns that influence whether a health plan's decision is upheld or overturned. Use the dataset to analyze trends and answer the following questions. * For each diagnosis category, calculate the percentage of cases where the health plan’s decision was upheld and where it was overturned. Exclude any records with missing diagnosis categories. * For each gender (male or female), identify the age range most commonly associated with overturned decisions. * Determine which diagnosis and treatment categories have the highest number of overturned decisions. * Create a graph/chart showing how the percentage of overturned decisions has changed over time, broken down by year. Once you have completed your challenge, include your solution file and a screenshot of your workflow as attachments to your comment. Good Luck! The Academy Team Source: https://www.kaggle.com/datasets/prasad22/ca-independent-medical-review Challenge 492_solution_file.yxzp Challenge 492_start_file.yxzp

Here is my solution. Challenge 492_solution_file.yxmd

My Solution Report.bmp Challenge492.bmp Challenge 492_Solution.yxmd

Here is my solution Challenge 492_start_file.yxmd

Challenge #492: Trends in Medical Review Decisions

AYXAcademy

Full Width - WC banner.svg Hi Community members,

A solution to last week’s challenge can be found here.

This challenge was submitted by Erin Miller, @Erin . Thank you, Erin, for your submission!

You are a data analyst reviewing independent medical review outcomes. Your objective is to identify patterns that influence whether a health plan's decision is upheld or overturned.

Use the dataset to analyze trends and answer the following questions.

For each diagnosis category, calculate the percentage of cases where the health plan’s decision was upheld and where it was overturned. Exclude any records with missing diagnosis categories.
For each gender (male or female), identify the age range most commonly associated with overturned decisions.
Determine which diagnosis and treatment categories have the highest number of overturned decisions.
Create a graph/chart showing how the percentage of overturned decisions has changed over time, broken down by year.

Once you have completed your challenge, include your solution file and a screenshot of your workflow as attachments to your comment.

Good Luck!

The Academy Team

Source: https://www.kaggle.com/datasets/prasad22/ca-independent-medical-review

Challenge 492_solution_file.yxzp

Challenge 492_start_file.yxzp

Data Preparation

Core

Basic

Accepted answers

All comments

AkimasaKajitani

My solution!

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Challenge 492_start_file_AK.yxzp

Bobbyt23

Nice challenge.

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Weekly Challenge 492 25-09-25.yxzp

TurboToad

Fun Challenge. Had some slight variations on a few answers based on filter criteria.

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TT_Challenge 492_solution_file.yxzp

Hub119

My answer to task 1 was slightly different as I rounded everything to one decimal place, but otherwise matches up nicely.

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Challenge 492 - CH Solved.yxzp

binu_acs

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Challenge 492_soultion_BV.yxmd

revac

My solution!

Challenge_492_Solution.yxzp

mattnason1

Practice with charts which I need!

Challenge 492_start_file_mn.yxmd

sethwood11

Charts!

Challenge 492_start_file.yxmd

EKasminsky

Nice challenge!

Challenge 492_ek.yxmd

Erin

Thanks @AYXAcademy for using my challenge submission!

Looks like I might have been a little lazy on rounding numbers.....woopsie doodles.

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challenge_492_submission_EM.yxzp

SamanthaW

AlteryxUser1

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AlteryxUser1 Challenge 492.yxzp

olga_strubbe

Thank you, Erin, @Erin for a neat challenge and an interesting topic to explore.

FYI - I swapped the colors of the Overturned/Upheld lines to be a bit more in alignment with their meanings to call out overturned decisions in orange.