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Operator Case Study Problem

The document outlines a case study challenge for RCM Data Analysts involving two datasets: Closed Encounters from a client's EHR and Imported Closed Encounters. The primary tasks are to identify missing encounters from the EHR dataset that are not in the imported dataset and to investigate potential reasons for their absence. Analysts are encouraged to use various tools for data analysis and are required to deliver a list of missing encounters along with an analysis of associated factors.

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navidalazim09
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101 views2 pages

Operator Case Study Problem

The document outlines a case study challenge for RCM Data Analysts involving two datasets: Closed Encounters from a client's EHR and Imported Closed Encounters. The primary tasks are to identify missing encounters from the EHR dataset that are not in the imported dataset and to investigate potential reasons for their absence. Analysts are encouraged to use various tools for data analysis and are required to deliver a list of missing encounters along with an analysis of associated factors.

Uploaded by

navidalazim09
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Operator Case Study Problem


RCM Data Analyst Challenge: Closed Encounters Analysis

Background:

Ops Case Study Dataset - Sample DB Data.csv

Ops Case Study Dataset - Sample EHR Data.csv

You have been provided with two datasets (linked above) in CSV format:

1. Closed Encounters from the Client’s EHR: A list of encounters that have been
closed in the client's electronic health record (EHR).

2. Imported Closed Encounters: A list of closed encounters that have been


successfully imported into Normandy.

Each dataset contains information about Patient Name, Date of Service, and
Rendering Provider, which together form a unique id for an encounter, alongside
procedure-level details.

Some encounters in the client’s EHR may not be present in our database, and
your task is to identify these missing encounters and come to a conclusion as to
why the encounters weren’t imported.

Instructions:
1. Task 1: Identifying Missing Encounters

Operator Case Study Problem 1


Compare the two datasets and identify which encounters from the Client
EHR Closed Encounters file are not found in the Imported Closed
Encounters file.

Provide a list of these missing encounters in the form of the unique ID


mentioned above (Patient Name, Date of Service, and Rendering Provider)

2. Task 2: Investigating the Cause

Analyze the missing encounters and identify any patterns or reasons why
they might not have been imported into our database.

Summarize your findings and explain why certain encounters were not
imported.

Hints:
Identify trends within the imported encounters vs the encounters that weren’t
imported

You can use any tools you're comfortable with (e.g., Excel, SQL, Python) to
analyze the data and answer these questions.

Deliverables:
A list of missing encounters and their associated details.

Some analysis into the associated factors with these missing encounters, with
the goal of identifying potential reasons for why these encounters weren’t
imported into our database.

Operator Case Study Problem 2

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