Data Science for Healthcare Claims Data from Udemy

The most commonly available and widely used type of data in healthcare is claims data. Claims data is sometimes also called billing data, insurance data or administrative data. The reason why claims data is the most large scale, reliable and complete type of big data in healthcare is rather straightforward. It has to do with reimbursement, that is, the payment of health care goods and services depends on claims data. Healthcare providers may not always find the time to fill in all required paperwork in healthcare, but they will always do that part of their administration on which their income depends. Thus, in many cases, analyzing healthcare claims data is a much more pragmatic alternative for extracting valuable insights.

Claims data allows for the analysis of many non-biological elements pertaining to the organization of health care, such as patient referral patterns, patient registration, waiting times, therapy adherence, health care financing, patient pathways, fraud detection and budget monitoring. Claims data also allows for some inferences about biological facts, but these are limited when compared to medical records.

By following this course, students will gain a solid theoretical understanding of the purpose of healthcare claims data. Moreover, a significant portion of this course is dedicated to the application of data science and health information technology (Healthcare IT) to obtain meaningful insights from raw healthcare claims data.

This course is for professionals that (want to) work in health care organizations (providers and payers) that need to generate actionable insights out of the large volume of claims data generated by these organizations. In other words, people that need to apply data science and data mining techniques to healthcare claims data.

Examples of such people are: financial controllers and planners, quality of care managers, medical coding specialists, medical billing specialists, healthcare or public health researchers, certified electronic health records specialist, health information technology or health informatics personnel, medical personnel tasked with policy, personnel at procurement departments and fraud investigators. Finally, this course will also be very useful for data scientists and consultants that lack domain knowledge about the organization of healthcare, but somehow got pulled into a healthcare claims data project.

The instructor of this course is Dennis Arrindell, MSc., MBA. Dennis has a bachelor’s degree in Public Health, a master’s degree in Health Economics and a Master’s degree in Business Administration.

Upon completion of this course, students will be able to contribute significantly towards making healthcare organizations (providers and payers) more data driven.

What this course is NOT about:

- Although we will be applying some important statistics and machine learning concepts, this course is NOT about statistics or machine learning as a topic on itself.

- Although we will be using multiple software tools and programming languages for the practical parts of this course, this course is NOT about any of these tools (Excel, SQL, Python, Celonis for process mining) as topics on themselves.

What's inside

Learning objective

In this course, you will learn and practice, how to transform raw healthcare claims data into valuable knowledge and actionable insights.

Syllabus

Introduction

Welcome to the course

Claims Data Defined

Why analyze healthcare claims data

Test your knowledge about healthcare systems by taking this quiz!

take this quiz and test your knowledge about healthcare provider payment systems!

Test your knowledge about this section by taking this quiz

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides a solid theoretical understanding of healthcare claims data, which is essential for professionals in healthcare organizations

Covers the application of data science and health information technology to extract meaningful insights from healthcare claims data

Explores patient referral patterns, waiting times, therapy adherence, healthcare financing, patient pathways, fraud detection, and budget monitoring

Uses tools such as Excel, SQL, Python, and Celonis for process mining, which are standard tools in the data science field

Requires learners to use Celonis, which may require a subscription or entail costs for some learners

Focuses on applying statistics and machine learning concepts to healthcare claims data, rather than teaching statistics or machine learning as a topic on itself

Reviews summary

Data science for healthcare claims analysis

According to learners, this course offers a solid foundation in understanding and applying data science techniques to healthcare claims data. Students found the course highly relevant for professionals working in healthcare finance, IT, and analytics roles. Key strengths include the practical application of concepts using real-world data and tools like Excel, SQL, and Celonis. The course provides a good balance of theoretical background and hands-on exercises. Some reviewers noted that the sections on specific tools, particularly Celonis, could sometimes be slightly outdated due to software updates, but the core principles taught remain valuable and applicable. Overall, it's seen as a valuable resource for gaining domain knowledge in healthcare claims data analysis.

Instructor has strong domain knowledge.

"The instructor clearly understands the healthcare claims domain deeply."

"Liked that the instructor had practical experience in healthcare and data."

"His explanations on healthcare systems and payment models were very informative."

Balances foundational concepts with exercises.

"Appreciated the theoretical intro before diving into the practical exercises with data."

"The mix of explaining healthcare systems and then showing how to manipulate claims data was great."

"Good balance, although some theory parts were a bit less engaging than the hands-on work."

Introduces key tools for claims analysis.

"The sections on using SQL for claims data extraction were very useful."

"Introduced Celonis for process mining, which was a new and interesting tool for me."

"Covered basic Excel techniques which were a good refresher before more complex tools."

Target audience found the course useful.

"Perfectly suited for those of us working with claims data in hospitals or insurance."

"As a data scientist new to healthcare, this provided essential domain context."

"Recommended for anyone involved in healthcare billing, coding, or finance."

Directly applicable to jobs in healthcare.

"This course is incredibly practical and directly relevant to my work in healthcare analytics."

"I immediately applied some of the data cleaning and merging techniques to my projects."

"It gave me actionable insights into analyzing claims data that I use daily."

Some tool interfaces may differ from course.

"The Celonis interface shown in the videos was slightly different from the current version, which caused some minor confusion."

"Had to figure out some steps myself because the Big Query interface update wasn't fully reflected in the videos."

"Updates to the software tools mean some visual elements don't match exactly, but the concepts are the same."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Science for Healthcare Claims Data with these activities:

Review Healthcare System Fundamentals

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Reinforce your understanding of healthcare systems to better contextualize claims data analysis.

Browse courses on Healthcare Systems

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Review the four functions of a healthcare system.
Identify the three key actors in claims data.
Understand vertical integration in healthcare.

Review: 'Understanding Health Insurance: A Guide to Billing and Reimbursement'

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Gain a deeper understanding of the billing and reimbursement processes that generate claims data.

View Putting Knowledge to Work on Amazon

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Read chapters on claim submission and processing.
Study the different types of insurance plans.
Familiarize yourself with common billing codes.

Excel Pivot Table Exercises

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Sharpen your Excel skills to efficiently explore and summarize healthcare claims data.

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Practice creating pivot tables with different aggregations.
Experiment with grouping data by date and category.
Create charts from pivot tables to visualize trends.

Five other activities

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Show all eight activities

Claims Data Glossary

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Solidify your understanding of claims data terminology by creating a glossary of key terms.

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Identify key terms related to healthcare claims data.
Define each term in a clear and concise manner.
Organize the terms alphabetically for easy reference.

SQL Tutorial for Data Extraction

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Enhance your SQL skills to efficiently extract and manipulate healthcare claims data from databases.

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Complete a SQL tutorial focusing on SELECT, WHERE, and JOIN clauses.
Practice writing SQL queries to extract specific data elements.
Experiment with different SQL functions for data manipulation.

Mini-Project: Claims Data Analysis Report

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Apply your knowledge to analyze a sample claims dataset and generate a report with key findings.

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Select a specific area of focus for your analysis.
Extract and clean the relevant data from the dataset.
Perform exploratory data analysis using Excel or SQL.
Summarize your findings in a concise report with visualizations.

Review: 'Healthcare Data Analytics'

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Deepen your understanding of data analytics techniques applicable to healthcare claims data.

View Putting Knowledge to Work on Amazon

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Read chapters on data mining and machine learning applications.
Study case studies of healthcare data analytics projects.
Explore different statistical methods for analyzing claims data.

Claims Data Visualization Dashboard

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Create an interactive dashboard to visualize key trends and patterns in healthcare claims data.

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Choose a data visualization tool (e.g., Tableau, Power BI).
Connect to a claims data source and select relevant metrics.
Design interactive visualizations to explore the data.
Create a dashboard with filters and drill-down capabilities.

Career center

Learners who complete Data Science for Healthcare Claims Data will develop knowledge and skills that may be useful to these careers:

Healthcare Data Analyst

A Healthcare Data Analyst uses data to improve healthcare operations and patient outcomes. This role involves working with large datasets, often including claims data, to identify trends, patterns, and areas for improvement. This course will be particularly useful for anyone in this role because it covers the core concepts of working with healthcare claims data. This course will help anyone learn to extract, clean, merge, and analyze data, as well as produce visualizations. Specifically, this course's focus on merging data, using tools like SQL and Excel to perform these data tasks, combined with its focus on using pivot tables and charting will be useful in this role. The course's practical applications of data science techniques to healthcare claims data are directly applicable to the responsibilities of a Healthcare Data Analyst.

See salaries and explore the career path for Healthcare Data Analyst

Health Informatics Specialist

A Health Informatics Specialist manages and analyzes health information systems to improve healthcare delivery. They often work with electronic health records and claims data, aiming to optimize processes and data-driven decisions. This course provides a solid foundation for Health Informatics Specialists, especially concerning the use of data science and health information technology to extract meaningful insights from healthcare claims data. The course content is a good fit because it covers the practical application of data science techniques to healthcare data, which is essential for this role. The course covers a variety of concepts that would be used by a Health Informatics Specialist, such as working with relational database schema. Additionally, the instruction helps learners understand how to merge healthcare claims data and perform higher-level categorizations, all of which directly relates to this job.

See salaries and explore the career path for Health Informatics Specialist

Healthcare Researcher

A Healthcare Researcher conducts studies to improve healthcare practices and outcomes, often working with complex datasets such as claims data. This course will be very helpful to a Healthcare Researcher, particularly those that do not have a background in healthcare. This course's focus is on building an understanding of claims data, how it is generated, and how it can be analyzed. The focus of this course is on applying data science to healthcare claims data to understand patient pathways, provider payment systems, and other areas. In particular, the course provides practical experience in working with claims data using various tools and techniques, including SQL and process mining. This is valuable for conducting research using this type of data.

See salaries and explore the career path for Healthcare Researcher

Fraud Investigator

A Fraud Investigator in healthcare investigates potential fraudulent activities related to healthcare claims. This course will be helpful for a Fraud Investigator because it offers an understanding of the healthcare claims data ecosystem. This includes an understanding of how claims data is generated, stored, and used within healthcare organizations. The course covers techniques for data analysis, such as filtering, aggregation, and visualization, which are techniques used to identify patterns of fraudulent claims. The course also covers topics such as process mining, which will help detect anomalies in the data and find fraudulent behaviors.

See salaries and explore the career path for Fraud Investigator

Healthcare Consultant

Healthcare Consultants advise healthcare organizations on various issues, including operational efficiency, financial performance, and data-driven strategy. This course will be helpful for a Healthcare Consultant, particularly those involved in projects requiring analysis of healthcare claims data. It may be useful because it introduces the specific challenges and opportunities in healthcare claims data analysis, including how to derive actionable insights from complex datasets. The course's emphasis on understanding the purpose of claims data and its use in analyzing aspects of healthcare operations, such as patient pathways and provider payment systems, will be particularly beneficial. This course also guides learners through the process of data mining, which is a crucial skill for any Healthcare Consultant. This course may help those consultants that have limited domain knowledge of healthcare systems.

See salaries and explore the career path for Healthcare Consultant

Financial Analyst

A Financial Analyst working in the healthcare sector analyzes financial data, including claims data, to inform financial planning, budgeting, and cost management for healthcare organizations. This course will be useful for a Financial Analyst as it offers a comprehensive approach to understanding and analyzing healthcare claims data. The course provides a crucial understanding of the purposes of claims data and how it reflects various aspects of healthcare organization and payment systems. Through instruction on data merging, higher level categorizations, and basic exploration and visualization, this course can help prepare anyone for working with claims data in a financial context. In particular, this course guides the learner through the use of pivot tables and vertical lookups, all valuable to the role of Financial Analyst.

See salaries and explore the career path for Financial Analyst

Process Improvement Analyst

A Process Improvement Analyst analyzes business processes to improve efficiency and effectiveness. This course may be helpful for a process improvement analyst due to its specific emphasis on process mining. The course provides a theoretical understanding of how process mining works and shows how it can be used to identify bottlenecks and areas for improvement in healthcare. It also provides hands-on experience with Celonis, a process mining tool, which can help a Process Improvement Analyst to apply the techniques they learned from the course. The course also provides a detailed introduction to extracting data using SQL, which may be useful in analyzing data related to a business process.

See salaries and explore the career path for Process Improvement Analyst

Quality Improvement Specialist

A Quality Improvement Specialist in healthcare uses data to identify areas for improvement in patient care, safety, and operational efficiency. They often analyze healthcare claims data to track outcomes and identify opportunities for enhancements in quality. This course may be useful to a Quality Improvement Specialist because it covers the application of data science techniques to healthcare claims data, specifically with an eye toward generating meaningful insights. This course guides learners through a variety of means to analyze data, including filtering, pivot tables, data merging and visualization. This is highly relevant to the tasks of a Quality Improvement Specialist, like identifying areas of improvement in patient pathways.

See salaries and explore the career path for Quality Improvement Specialist

Medical Coder

A Medical Coder assigns standardized codes to medical procedures and diagnoses for billing and data analysis purposes. While a Medical Coder's primary focus is on the accuracy of coding itself, this course will be useful to a Medical Coder. The course provides a broader understanding of how claims data is used for analysis, particularly in the context of healthcare organization and reimbursement. This course covers topics that will help build a more wholistic understanding of the use of codes. Examples include working with data dictionaries, understanding the logic behind code systems, and also categorizing and merging healthcare data. Further, this learning also will allow a medical coder to understand the implications of their work in the broader healthcare system.

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Health Policy Analyst

A Health Policy Analyst develops and evaluates health policies using data and research. These roles often involve working with a variety of healthcare data, including claims data, in order to understand how these policies affect patients. This course may be useful to a Health Policy Analyst because it provides insights into how data is used to understand healthcare systems. The course covers topics such as patient pathways, provider payment systems, and healthcare system functions. This detailed understanding would help a policy analyst evaluate the effects of public policy changes. The course also covers techniques of data analysis, data visualization, and process mining.

See salaries and explore the career path for Health Policy Analyst

Business Intelligence Analyst

A Business Intelligence Analyst uses data analytics to optimize business performance. This course may be useful to a Business Intelligence Analyst who works within a healthcare organization, or who may be working on a consulting basis within healthcare. The course covers a variety of ways to analyze and visualize data. This includes hands-on practice with SQL, Excel, and using pivot tables. These are all skills that are directly related to a Business Intelligence Analyst. Additionally, the domain knowledge of healthcare systems, claims data, and patient pathways will provide helpful context for any business intelligence analysis of a healthcare organization.

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Medical Billing Specialist

A Medical Billing Specialist manages the billing process for healthcare services. This course may be useful for a Medical Billing Specialist because this role will help this specialist understand how the data they manage is used for analysis. The course may provide a broader view of how claims data is used to find trends, understand patient pathways, and optimize workflows. While Medical Billing Specialists work with the data on a daily basis, this course offers a way to look at that data, which may help improve how they work. For example, the course covers both relational data schemas and also data merging, which are topics central to the medical billing process.

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Healthcare Administrator

A Healthcare Administrator manages the day-to-day operations of healthcare facilities. This course may be helpful for a Healthcare Administrator because it provides a detailed understanding of healthcare claims data and its potential uses. While a Healthcare Administrator may not directly work with claims data on a daily basis, they will be responsible for making decisions based on the data that others have analyzed. Specifically, by learning how to analyze claims data, this specialist may better understand their organization's performance. Topics such as provider payment systems, patient pathways, and data analysis covered in the course will be useful.

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Actuary

An Actuary uses statistical and mathematical methods to assess and manage risk. While this role is usually associated with finance and insurance, an Actuary within healthcare may use healthcare claims data. This course may be helpful to an Actuary, particularly one that is newer to the field of healthcare, due to its emphasis on analyzing and understanding healthcare systems. In particular, this course covers areas such as patient pathways, provider payment systems, and also includes several lessons on performing calculations, comparisons, and applying logic in SQL and Excel, which are all relevant to this role.

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Clinical Data Manager

A Clinical Data Manager oversees clinical data and systems. While this role usually focuses on data associated with clinical trials, it may also involve working with claims data. This course may be helpful to a Clinical Data Manager by providing them with a better understanding of the healthcare data landscape. While the Clinical Data manager typically uses different data, this course may improve their abilities with data analysis by applying data science techniques to healthcare. Specifically this course guides users through using SQL, Excel, and other tools to merge, clean, and analyze data.

See salaries and explore the career path for Clinical Data Manager

Data Science for Healthcare Claims Data

What's inside

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Data science for healthcare claims analysis

Activities

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