UnitedHealth employees use SQL to analyze healthcare data, helping them find valuable insights that guide preventive care strategies to improve patient outcomes. They also might be using as part of their AI UHG also uses SQL to manage large patient databases, which makes operations more efficient by streamlining processes and keeping accurate records, this is why UnitedHealth asks SQL questions during interviews for Data Science and Data Engineering positions.
To help prep you for the UnitedHealth SQL interview, here’s 11 UnitedHealth Group SQL interview questions in this blog.
UnitedHealth, a behemoth in the health insurance industry, wants to identify their "power patients". These are patients who frequently avail services and have a significant impact on their business. This can be measured by the number of claims submitted and the total amount claimed by a user in a year. Design a SQL query to find out the top 5 patients who have submitted the maximum number of claims and have claimed the highest amount in the year 2022.
claim_id | user_id | claim_date | amount_claimed |
---|---|---|---|
100001 | 123 | 01/06/2022 | 5000 |
100002 | 265 | 01/10/2022 | 7000 |
100003 | 123 | 02/18/2022 | 8500 |
100004 | 545 | 03/26/2022 | 5000 |
100005 | 265 | 04/05/2022 | 9500 |
100006 | 367 | 05/25/2022 | 10500 |
100007 | 367 | 06/15/2022 | 8000 |
100008 | 265 | 07/07/2022 | 7600 |
100009 | 965 | 08/09/2022 | 6700 |
user_id | total_amount_claimed | number_of_claims |
---|---|---|
265 | 24100 | 3 |
123 | 13500 | 2 |
367 | 18500 | 2 |
545 | 5000 | 1 |
965 | 6700 | 1 |
The SQL query uses the function to calculate the sum of and the count of for each . The function is used to filter the records for the year 2022. The result is ordered by the count of claims and total amount claimed in descending order. The function is used to list the top 5 power patients.
To solve a related super-user data analysis question on DataLemur's free interactive SQL code editor, try this recently asked Microsoft SQL interview question:
Delve into UnitedHealth Group's commitment to health technology and discover how they are developing and applying cutting-edge solutions for better healthcare outcomes! This knowledge can enhance your understanding of how technology is transforming the health sector.
Assume there was a table of UnitedHealth employee salary data. Write a SQL query to find the employees who earn more than their direct manager.
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 |
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.
Check your SQL query for this question directly within the browser on DataLemur:
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 code above is hard to understand, you can find a step-by-step solution with hints here: Employees Earning More Than Managers.
A full outer join returns all rows from both tables, including any unmatched rows, whereas an inner join only returns rows that match the join condition between the two tables.
For a tangible example, suppose you had a table of UnitedHealth orders and UnitedHealth customers.
Here's a SQL inner join using the orders and customers tables:
This query will return rows from the orders and customers tables that have matching values. Only rows with matching values will be included in the results.
Here is an example of a using the orders and customers tables:
This query will return all rows from both the orders and customers tables, including any rows that do not have matching values. Any rows with null values for either table will be included in the results.
UnitedHealth Group, being a healthcare company, typically deals with data related to patients, healthcare professionals, and hospital departments. For this question, consider two tables - "Patients" contains the details of patients including when they visited and "Departments" contains details of various hospital departments.
Given these two tables, your task is to identify the count of patients who visited each department each day, along with the count of patients who visited the same department the previous day.
patient_id | visit_date | department_id |
---|---|---|
1 | 2022-01-01 | 100 |
2 | 2022-01-01 | 200 |
3 | 2022-01-02 | 100 |
4 | 2022-01-02 | 200 |
5 | 2022-01-02 | 200 |
6 | 2022-01-03 | 100 |
department_id | department_name |
---|---|
100 | Cardiology |
200 | Neurology |
visit_date | department_name | daily_count | previous_day_count |
---|---|---|---|
2022-01-01 | Cardiology | 1 | 0 |
2022-01-01 | Neurology | 1 | 0 |
2022-01-02 | Cardiology | 1 | 1 |
2022-01-02 | Neurology | 2 | 1 |
2022-01-03 | Cardiology | 1 | 1 |
This query first finds the count of patients visiting each department daily using the CTE named . Then it uses the LAG window function in the main query to calculate the count of patients who visited the same department the previous day. The function is used to handle any NULL values (in case there are no records for the previous day) by replacing them with 0.
To practice a similar window function question on DataLemur's free online SQL coding environment, try this Google SQL Interview Question:
While knowing this answer is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at UnitedHealth should be at least aware of SQL vs. NoSQL databases.
Relational databases and non-relational (NoSQL) databases have some key differences, particularly in terms of how data is stored. Whereas relational databases have tables, made up of rows and columns, NoSQL databases use various data models like:
This added flexibility makes NoSQL databases well-suited for handling non-tabular data or data with a constantly changing format. However, this flexibility comes at the cost of ACID compliance, which is a set of properties (atomic, consistent, isolated, and durable) that ensure the reliability and integrity of data in a database. While most relational databases are ACID-compliant, NoSQL databases may not provide the same level of guarantees.
UnitedHealth Group offers health care products and insurance services. It would be beneficial to know the trends in patients' visits to healthcare providers and how it varies over time and across different specialties.
Please design a database to model this scenario, and also write a query to find out the number of patient visits recorded each month, along with the specialty of the healthcare provider for 2022.
Here are the tables in the database:
visit_id | patient_id | provider_id | visit_date |
---|---|---|---|
1001 | 3001 | 2001 | 01/01/2022 |
1002 | 3002 | 2001 | 01/02/2022 |
1003 | 3003 | 2002 | 02/01/2022 |
1004 | 3001 | 2002 | 02/01/2022 |
1005 | 3002 | 2002 | 02/02/2022 |
provider_id | specialty |
---|---|
2001 | Cardiac |
2002 | Orthopedic |
The table contains records of all patient visits. A new row gets inserted whenever a patient visits a healthcare provider.
The table contains information about the healthcare provider's specialty.
We'll write a query using straightforward JOIN, GROUP BY clauses and date functions.
This query first joins the and tables using the (which is the common column across the two tables). It then groups by both and , which is exactly the breakdown we need. Lastly, it counts the number of visits for each for each , and orders the result by and total number of visits in each in each .
Note that we filter the data for the year 2022 in the WHERE clause. If this was not mentioned, we could simply remove the WHERE clause to get the data for all years.
First things first, figure out why the query is slow! You can use and commands in PostgreSQL to identify any performance bottlenecks. You might discover that your query is inefficient, or that there are many database writes at the same time you are doing a read, or maybe too many people are concurrently running queries on the same database server.
For Data Analyst and Data Science positions, knowing the ins-and-outs of SQL performance tuning is out-of-scope for the SQL interview round. However, knowing that joins are expensive, and indexes can speed up queries, is generally enough of an answer for UnitedHealth SQL interviews.
Given a table , we want to identify those patients who are under 30 years old, are located in 'Minnesota', and their (PCP) is 'Dr. Snow'. Write an SQL query to filter these records from the table.
patient_id | age | state | primary_care_physician |
---|---|---|---|
101 | 28 | Minnesota | Dr. Snow |
202 | 35 | Minnesota | Dr. Snow |
303 | 27 | Wisconsin | Dr. Snow |
404 | 30 | Minnesota | Dr. Doe |
505 | 25 | Minnesota | Dr. Snow |
patient_id | age | state | primary_care_physician |
---|---|---|---|
101 | 28 | Minnesota | Dr. Snow |
505 | 25 | Minnesota | Dr. Snow |
This SQL query will select all records from the table where the patient's age is less than 30, the state in which the patient resides is 'Minnesota', and the patient's Primary Care Physician is 'Dr. Snow'.
UnitedHealth, being a healthcare company, handles numerous insurance claims related to medical services for patients. They are interested in understanding their average expenses. For a particular month, can you find out the average claim amount per patient from the table?
claim_id | patient_id | submit_date | claim_amount |
---|---|---|---|
7561 | 268 | 05/12/2022 | 1200.00 |
9002 | 587 | 05/19/2022 | 850.00 |
4103 | 268 | 05/28/2022 | 200.00 |
6212 | 398 | 05/30/2022 | 1800.00 |
3235 | 587 | 05/31/2022 | 550.00 |
mth | patient_id | avg_claim_amount |
---|---|---|
5 | 268 | 700.00 |
5 | 587 | 700.00 |
5 | 398 | 1800.00 |
This query extracts the month from the column and groups by this month value and the . It then calculates the average for each group, providing us with the average claim amount per patient for each month. The clause then orders the result first by month, then by .
To practice a very similar question try this interactive CVS Health Pharmacy Analytics (Part 1) Question which is similar for calculating average related financial data or this Alibaba Compressed Mean Question which is similar for the need to calculate an average from given data.
Database normalization is the process of breaking down a table into smaller and more specific tables and defining relationships between them via foreign keys. This minimizes redundancy, and creates a database that's more flexible, scalable, and easier to maintain. It also helps to ensure the integrity of the data by minimizing the risk of data inconsistencies and anomalies.
Suppose we want to find the average cost of each insurance plan offered by UnitedHealth for 2021. We are also interested in knowing the maximum and minimum cost within each plan for the same period as it may give us insights about the range of prices customers are paying for each plan.
plan_id | plan_name | user_id | purchase_date | cost |
---|---|---|---|---|
1100 | Silver | 285 | 01/10/2021 | $4500 |
2050 | Gold | 625 | 02/15/2021 | $6000 |
3050 | Platinum | 315 | 03/27/2021 | $8500 |
1100 | Silver | 790 | 04/22/2021 | $5500 |
2050 | Gold | 520 | 05/12/2021 | $6500 |
plan_id | plan_name | avg_cost | min_cost | max_cost |
---|---|---|---|---|
1100 | Silver | $5000 | $4500 | $5500 |
2050 | Gold | $6250 | $6000 | $6500 |
3050 | Platinum | $8500 | $8500 | $8500 |
This query first filters the insurance_plans records for the year 2021 using the function. It then groups by and , and calculates the , , and for each group, which will give the average, minimum, and maximum cost of each insurance plan for the year 2021.
The key to acing a UnitedHealth SQL interview is to practice, practice, and then practice some more! In addition to solving the above UnitedHealth SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like FAANG (FB, Apple, Amazon, Netflix, Google).
Each DataLemur SQL question has multiple hints, full answers and best of all, there is an online SQL code editor so you can right online code up your SQL query and have it executed.
To prep for the UnitedHealth SQL interview it is also a great idea to practice SQL problems from other healthcare insurance companies like:
In case your SQL query skills are weak, forget about jumping right into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers SQL concepts such as LEAD/LAG and WHERE vs. HAVING – both of which come up often during UnitedHealth SQL assessments.
In addition to SQL interview questions, the other question categories to practice for the UnitedHealth Data Science Interview are:
To prepare for the UnitedHealth Data Science interview make sure you have a deep understanding of the company's values and company principles – this will be key to acing the behavioral interview. For technical interviews prepare by reading Ace the Data Science Interview. The book's got: