10 Change Healthcare SQL Interview Questions (Updated 2024)
Change Healthcare employees use SQL to analyze patient data trends, helping them find patterns in treatment outcomes and patient demographics. it is also used to manage healthcare databases effectively, ensuring that information is easy to retrieve and report on when needed, this is why why Change Healthcare evaluates jobseekers with SQL query questions during interviews for Data Science, Analytics, and Data Engineering positions.
Thus, to help you prepare for the Change Healthcare SQL interview, we'll cover 10 Change Healthcare SQL interview questions in this article.
10 Change Healthcare SQL Interview Questions
SQL Question 1: Calculate Average Claim Processing Time
Change Healthcare deals with processing health insurance claims. You are given a dataset that contains unique claim IDs, claim submission dates, and claim processed dates. Your task is to write a SQL query to calculate the average processing time (in days) of the claims, categorized by month of submission, using SQL window functions.
Example Input:
| claim_id | submission_date | processed_date |
|---|---|---|
| 01 | 2022-01-01 | 2022-02-01 |
| 02 | 2022-01-03 | 2022-01-31 |
| 03 | 2022-01-10 | 2022-01-20 |
| 04 | 2022-02-01 | 2022-02-15 |
| 05 | 2022-02-10 | 2022-02-28 |
| 06 | 2022-02-15 | 2022-03-02 |
Example Output:
| month_of_submission | avg_processing_time |
|---|---|
| 1 | 27.00 |
| 2 | 14.67 |
Answer:
What this query does is it first extracts the month from the for each claim. It then calculates the processing time (in days) by subtracting the from the . The average of these processing times is then calculated for each month using the function. Finally, the results are grouped by the to provide the desired output.
Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur
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SQL Question 2: Employees Earning More Than Managers
Suppose there was a table of Change Healthcare employee salaries. Write a SQL query to find the employees who earn more than their own manager.
Change Healthcare Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.
Try this interview question and run your code right in DataLemur's online SQL environment:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the solution above is confusing, you can find a detailed solution with hints here: Well Paid Employees.
SQL Question 3: What sets the 'BETWEEN' and 'IN' operators apart?
The operator is used to select rows that fall within a certain range of values, while the operator is used to select rows that match values in a specified list.
For example, suppose you are a data analyst at Change Healthcare and have a table of advertising campaign data. To find campaigns with a spend between 5k, you could use :
To find advertising campaigns that were video and image based (as opposed to text or billboard ads), you could use the operator:
SQL Question 4: Filter Customers Based on Billing Region and Status
Given a table with the following structure, your task is to write a PostgreSQL query to find all customers from the "Western" billing region who are "Active".
The table has the following columns:
- : An unique identifier for each customer.
- : Customer's first name.
- : Customer's last name.
- : The region, either "Eastern", "Western", "Northern" or "Southern", where the customer receives their bill.
- : Customer's account status, either "Active" or "Inactive".
Example Input:
| customer_id | first_name | last_name | billing_region | status |
|---|---|---|---|---|
| 1 | John | Doe | Eastern | Active |
| 2 | Jane | Doe | Western | Active |
| 3 | Jim | Smith | Northern | Inactive |
| 4 | Janet | Brown | Southern | Active |
| 5 | Joseph | Black | Western | Active |
| 6 | Jill | White | Eastern | Inactive |
| 7 | Jerry | Gray | Western | Active |
| 8 | Jenny | Green | Northern | Active |
We want to filter the table to only include customers from the "Western" billing region who are "Active".
Answer:
The SQL query to solve this problem would look like this:
This query uses the clause to check each row in the table. Specifically, it checks if the column is 'Western' and the column is 'Active'. If both conditions are true, that row is included in the result set.
Based on the sample data provided above, this query will return the following:
| customer_id | first_name | last_name | billing_region | status |
|---|---|---|---|---|
| 2 | Jane | Doe | Western | Active |
| 5 | Joseph | Black | Western | Active |
| 7 | Jerry | Gray | Western | Active |
So, Jane Doe, Joseph Black, and Jerry Gray are our customers from the "Western" region with "Active" status.
SQL Question 5: What's an index, and what are the different types?
An index in a database is a data structure that helps to quickly find and access specific records in a table.
For example, if you had a database of Change Healthcare customers, you could create a primary index on the column.
Having a primary index on the column can speed up performance in several ways. For example, if you want to retrieve a specific customer record based on their , the database can use the primary index to quickly locate and retrieve the desired record. The primary index acts like a map, allowing the database to quickly find the location of the desired record without having to search through the entire table.
Additionally, a primary index can also be used to enforce the uniqueness of the column, ensuring that no duplicate values are inserted into the table. This can help to prevent errors and maintain the integrity of the data in the table.
SQL Question 6: Analyzing Click-Through and Conversion Rates
At Change Healthcare, one of the main goals in our digital marketing campaigns is to ensure that website visitors are not just clicking through to our product pages, but are also adding our products to their carts, indicating a strong interest in purchase. Therefore, we often look at our click-through rates and conversion rates in order to measure the effectiveness of our ads.
Given the two tables and , our task is to calculate the click-through rate. The click-through rate is defined as the number of unique users who clicked an ad (one row in the table) divided by the total number of ads displayed. Also, calculate the conversion rate, the number of unique users who added a product to the cart (one row in the table) divided by the total number of unique users who viewed a product.
Example Input:
| click_id | user_id | click_time | product_id |
|---|---|---|---|
| 2001 | 456 | 07/08/2022 12:00:00 | 60001 |
| 2002 | 469 | 07/09/2022 10:00:00 | 60002 |
| 2003 | 785 | 07/10/2022 11:00:00 | 60001 |
| 2004 | 456 | 07/11/2022 09:00:00 | 60003 |
| 2005 | 691 | 07/12/2022 08:00:00 | 60001 |
Example Input:
| add_id | user_id | add_time | product_id |
|---|---|---|---|
| 6001 | 456 | 07/08/2022 13:00:00 | 60001 |
| 6002 | 469 | 07/10/2022 11:00:00 | 60002 |
| 6003 | 785 | 07/11/2022 10:00:00 | 60003 |
Answer:
The SQL query first calculates total unique clicks in a CTE called and total unique cart adds in a CTE called . The final statement then divides these values by the total number of clicks and displaying ads to get the click-through rate and conversion rate respectively.
To practice another question about calculating rates, solve this TikTok SQL Interview Question within DataLemur's interactive coding environment:
SQL Question 7: What does the operator do?
The operator is used to return all rows from the first statement that are not returned by the second statement. Note that is available in PostgreSQL and SQL Server, and its equivalent operator is called and is available in MySQL and Oracle.
For a tangible example, suppose you were doing an HR Analytics project for Change Healthcare, and had access to Change Healthcare's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all employees who never were a contractor using this query:
SQL Question 8: Average Monthly Diagnosis Rate
Change Healthcare is a healthcare technology company. Suppose that they have an application that lets healthcare providers document diagnoses for their patients. We are interested in finding out the average number of unique patients diagnosed per month for each disease in the past year. To this end, the application stores diagnostic information in a table , containing the following columns:
- diagnosis_id
- patient_id
- provider_id
- disease_id
- diagnosis_date
Example Input:
| diagnosis_id | patient_id | provider_id | disease_id | diagnosis_date |
|---|---|---|---|---|
| 3812 | 789 | 901 | 123 | 01/03/2021 |
| 4569 | 567 | 901 | 456 | 02/15/2021 |
| 9128 | 345 | 901 | 123 | 01/21/2021 |
| 8665 | 234 | 901 | 123 | 02/12/2021 |
| 2937 | 678 | 901 | 456 | 02/27/2021 |
Example Output:
| year_month | disease_id | avg_patient_count |
|---|---|---|
| 2021-01 | 123 | 2 |
| 2021-02 | 123 | 1 |
| 2021-02 | 456 | 2 |
Answer:
PostgreSQL query:
This query first truncates the date to 'month' which results in losing day and time part. Then, it groups the diagnoses by the truncated date and disease_id. Finally, it counts the unique patients per each group (month, disease_id).
SQL Question 9: Filter Customer Records
You work at Change Healthcare and you handle a large database of customer inquiries. You've been informed that there has been a surge of inquiries about a new healthcare plan called "BetterHealth".
Your task is to find all customer inquiries that mention the "BetterHealth" plan in the inquiry details. The records table is defined as below:
Example Input:
| inquiry_id | customer_id | inquiry_date | inquiry_detail |
|---|---|---|---|
| 1 | 301 | 2022-07-07 | "I have questions about BetterHealth plan" |
| 2 | 295 | 2022-08-16 | "Tell me more about the regular plans" |
| 3 | 279 | 2022-08-19 | "Why is BetterHealth plan more expensive?" |
| 4 | 342 | 2022-09-15 | "Appreciate information on all plans" |
| 5 | 325 | 2022-09-22 | "What benefits does BetterHealth plan offer?" |
Your filtered output should result in a table providing , , and for all records that mention "BetterHealth".
Answer:
This query uses the SQL operator to filter rows where contains the phrase "BetterHealth". The percent sign is a wildcard character that matches any sequence of characters. The '%%' on both sides of 'BetterHealth' ensure that the word can be anywhere in the string of .
This will give us the list of all inquiries by customers related to the new "BetterHealth" plan.
SQL Question 10: Do and a typically produce equivalent results?
No, in 99% of normal cases a and do NOT produce the same result.
You can think of more as set addition when it combines the results of two tables.
You can think of a more as set multiplication, producing all combos of table 1 with combos of table 2.
How To Prepare for the Change Healthcare SQL Interview
The key to acing a Change Healthcare SQL interview is to practice, practice, and then practice some more! Beyond just solving the earlier Change Healthcare SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Amazon, JP Morgan, and healthcare and pharmaceutical companies like Change Healthcare.
Each problem on DataLemur has hints to guide you, detailed solutions and most importantly, there is an interactive SQL code editor so you can right in the browser run your SQL query and have it executed.
To prep for the Change Healthcare SQL interview you can also be a great idea to solve interview questions from other healthcare and pharmaceutical companies like:
- ResMed SQL questions
- IDEXX Laboratories SQL questions
- Option Care Health SQL questions
- Charles River SQL questions
But if your SQL foundations are weak, forget about jumping right into solving questions – go learn SQL with this DataLemur SQL tutorial.
This tutorial covers things like handling strings and handling NULLs in SQL – both of which show up frequently during SQL job interviews at Change Healthcare.
Change Healthcare Data Science Interview Tips
What Do Change Healthcare Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the Change Healthcare Data Science Interview include:
- Statistics & AB Testing Questions
- Python or R Programming Questions
- Product Analytics Questions
- Machine Learning Questions
- Behavioral Interview Questions
How To Prepare for Change Healthcare Data Science Interviews?
To prepare for the Change Healthcare Data Science interview make sure you have a firm understanding of the company's cultural values – this will be important for acing the behavioral interview. For the technical Data Science interviews, prepare by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Google, Microsoft & tech startups
- A Crash Course on Python, SQL & ML
- Amazing Reviews (1000+ reviews, 4.5-star rating)