10 Allscripts Healthcare SQL Interview Questions (Updated 2024)
At Allscripts, SQL is typically used for extracting healthcare data from structured databases and performing analytics on patient records to inform decision making. For this reason Allscripts Healthcare almost always evaluates jobseekers on SQL coding questions in interviews for Data Science and Data Engineering positions.
Thus, to help you prep, we've curated 10 Allscripts SQL interview questions – can you answer each one?
10 Allscripts SQL Interview Questions
SQL Question 1: Identify VIP Users in Allscripts Healthcare
In the Allscripts Healthcare Company, the business considers users who have booked the most medical appointments and made the most prescription purchases in the last six months as 'VIP' or 'whale' users. Your task is to write a SQL query to identify these users from the customer database.
The company database consists of 2 main tables namely and given below:
Example Input:
| appointment_id | user_id | appointment_date | doctor_id |
|---|---|---|---|
| 2001 | 123 | 06/08/2022 | 101 |
| 2002 | 123 | 06/15/2022 | 105 |
| 2003 | 456 | 06/10/2022 | 105 |
| 2004 | 456 | 08/10/2022 | 101 |
| 2005 | 789 | 07/25/2022 | 102 |
Example Input:
| prescription_id | user_id | issue_date | medicine_id | quantity |
|---|---|---|---|---|
| 3001 | 123 | 06/08/2022 | 501 | 30 |
| 3002 | 456 | 06/18/2022 | 502 | 45 |
| 3003 | 789 | 07/22/2022 | 502 | 20 |
| 3004 | 123 | 07/15/2022 | 501 | 50 |
| 3005 | 789 | 08/05/2022 | 503 | 30 |
Answer:
In this query, we are creating a combined list of all appointments and prescriptions for every user from the past 6 months. Then we group the entries by user_id and calculate the total amount of appointments and prescriptions for each user. The users are then sorted in descending order, prioritizing users with the most appointments and prescriptions. Finally, the top 10 results are selected, representing the top 10 'VIP' or 'whale' users.
To solve a related super-user data analysis question on DataLemur's free online SQL coding environment, try this Microsoft Teams Power User SQL Interview Question:
SQL Question 2: Department vs. Company Salary
Assume there was a table of Allscripts Healthcare employee salaries, along with which department they were in. Write a query to compare the average salary of employees in each department to the company's average salary. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
Write a SQL query for this interview question directly within the browser on DataLemur:
The answer is LONG – 30+ lines of SQL. You can find a detailed solution here: Department Salaries.
SQL Question 3: How can you identify duplicates in a table? Do have any other approaches?
"One creative way is to use the window function ROW_NUMBER() and partition by whichver columns you are loooking for duplicates in. If any row has a row_number() more than 1, then it's a duplicate!
You could also use COUNT(DISTINCT col1) vs. COUNT(*) and see if they return different numbers, indicating the prescence of duplicates!
SQL Question 4: Doctor-Patient Interaction Analysis
You will find yourself working with the following two tables: Doctors, and Appointments. They represent the doctors in a hospital, the patients they see, and the time of the appointments respectively. Your task is to write a SQL query to find out the doctor who saw the most number of unique patients during the last month. If there are multiple doctors who have seen the same maximum number of patients, return all of them.
Example Input:
| doctor_id | first_name | last_name |
|---|---|---|
| 101 | John | Doe |
| 102 | Jane | Smith |
| 103 | Emily | Williams |
| 104 | Robert | Johnson |
Example Input:
| appt_id | doctor_id | patient_id | appt_datetime |
|---|---|---|---|
| 201 | 101 | 301 | 2022-08-01 08:00:00 |
| 202 | 101 | 302 | 2022-08-05 09:30:00 |
| 203 | 102 | 302 | 2022-08-10 11:15:00 |
| 204 | 104 | 303 | 2022-08-15 13:45:00 |
| 205 | 103 | 304 | 2022-07-27 08:00:00 |
| 206 | 101 | 305 | 2022-07-01 16:30:00 |
| 207 | 102 | 306 | 2022-08-19 10:00:00 |
| 208 | 102 | 302 | 2022-08-22 14:00:00 |
Answer:
In the query above, we are first counting the number of distinct patients seen by each doctor during the last month. Using a subquery, we then find the maximum count of patients seen by a doctor during the last month. Finally, we return the doctors who saw the most number of unique patients during the last month.
To practice a related window function SQL problem on DataLemur's free online SQL coding environment, solve this Google SQL Interview Question:
SQL Question 5: What's a database view, and what's it used for?
Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're so similar to a regular table?
Views are advantageous for several reasons:
- views allow you to create a simpler versions of your data for specific users (such as hiding extraneous columns/rows from business analysts since they're relics of the Data Engineering pipelines setup)
- views help you comply with data security requirements by hiding sensitive data from certain users (important for regulated industries like govermnet and healthcare!)
- views can improve performance for complicated queries by pre-computing the results and caching them in a view (which is often faster than re-executing the original query)
SQL Question 6: Patient Prescription Data Analysis
Allscripts Healthcare provides various healthcare services, including managing patient prescriptions. Our system keeps track of patient information, physician details, and prescriptions issued. Here's a scenario you might encounter at Allscripts:
As a data analyst, you have been tasked to identify the physicians who prescribe the highest number of distinct drugs. For this task, you should consider only those physicians who have at least two distinct patients.
You are given two tables - and . The table has the structure and some sample data as follows:
Sample Input:
| prescription_id | physician_id | patient_id | drug_id |
|---|---|---|---|
| 1 | 200 | 300 | 400 |
| 2 | 200 | 301 | 401 |
| 3 | 200 | 300 | 402 |
| 4 | 201 | 302 | 400 |
| 5 | 201 | 302 | 400 |
The table has the structure and some sample data as follows:
Sample Input:
| physician_id | physician_name |
|---|---|
| 200 | Dr. Smith |
| 201 | Dr. Johnson |
Based on the provided tables, can you form an SQL query to answer the above question?
Answer:
Here we need to find the physicians who prescribe a large variety of drugs. We need also consider only those physicians who have at a minimum two different patients.
The above query returns the name of each physician along with the number of distinct drugs they have prescribed. It only includes those physicians who have over two distinct patients. The results are sorted in descending order by the number of drugs. If we want to limit the result to the top 10 physicians, we just need to add at the end.
SQL Question 7: Database transactions are supposed to be atomic, consistent, isolated, & durable. What does each term mean?
ACID refers to the four key properties that are essential to the reliable and correct execution of database transactions. These properties are:
Atomicity: ensures that a transaction is treated as a single operation, and either all of the changes are made or none of them are! Basically, the database version of a "-FULL SEND-"
Consistency: ensures that the data is in a consistent state before and after a transaction is completed. For example, if wiring money to a friendly Nigerian prince whose fallen on hard times, consistency ensures that the total value of funds lost in my account is the same amount that's gained in the prince's account!
Isolation: ensures that the intermediate state of a transaction is invisible to other transactions. Back to the wiring-the-prince-some-money example, isolation ensures that another transaction sees the transferred funds in my account OR the princes, but not in both accounts at the same time
Durability: ensures that once a transaction has been completed successfully, the changes made by the transaction are permanent and cannot be undone, even in the event of a system failure. Basically, no taksies backsies (even if your system has a meltdown!).
SQL Question 8: Retrieve Doctors with Specific Specialization
As a healthcare company, Allscripts maintains a detailed record of doctors that includes their name, postal code, and specialization. Allscripts would like you to filter their doctors' records, and retrieve all doctors who specialize in 'Pediatrics'.
Example Input:
| doctor_id | name | postal_code | specialization |
|---|---|---|---|
| 1201 | Dr. Smith | 60007 | Cardiology |
| 2302 | Dr. Johnson | 60008 | Neurology |
| 4503 | Dr. Williams | 60009 | Pediatrics |
| 8804 | Dr. Brown | 60010 | Obstetrics |
| 9505 | Dr. Garcia | 60011 | Pediatrics |
Answer:
In PostgreSQL, you would use the following SQL query to retrieve all doctors who specialize in 'Pediatrics':
This query uses the keyword as the condition in the clause to filter doctors based on their area of specialization. The result of this query would retrieve all details of the doctors (such as doctor_id, name, postal_code, and specialization) who are Pediatricians.
Example Output:
| doctor_id | name | postal_code | specialization |
|---|---|---|---|
| 4503 | Dr. Williams | 60009 | Pediatrics |
| 9505 | Dr. Garcia | 60011 | Pediatrics |
SQL Question 9: Joining and Analyzing Customer and Orders Tables
As a data analyst for Allscripts Healthcare, you'll regularly need to cross-reference information from multiple tables in our database. Write a SQL query that joins the table and the table to find out the total number of orders per customer who lives in 'New York'. Given below are the structures of the two tables.
Example Input:
| customer_id | first_name | last_name | location | |
|---|---|---|---|---|
| 123 | John | Doe | New York | johndoe@email.com |
| 456 | Jane | Smith | California | janesmith@email.com |
| 789 | Bob | Johnson | Texas | bobjohnson@email.com |
Example Input:
| order_id | customer_id | product | order_date | price |
|---|---|---|---|---|
| 101 | 123 | Product A | 06/08/2022 00:00:00 | 200.00 |
| 102 | 123 | Product B | 06/10/2022 00:00:00 | 250.00 |
| 103 | 456 | Product C | 06/18/2022 00:00:00 | 100.00 |
| 104 | 789 | Product A | 07/26/2022 00:00:00 | 210.00 |
| 105 | 123 | Product B | 07/05/2022 00:00:00 | 250.00 |
Answer:
The above PostgreSQL query joins the table (aliased as 'c') with the table (aliased as 'o') on the column. It then filters for customers in 'New York' before grouping the results by the customers' first and last names. The function is used to compute the total number of orders per each customer.
Since joins come up frequently during SQL interviews, try an interactive SQL join question from Spotify:
SQL Question 10: What are the similarities and differences between correleated and non-correlated sub-queries?
A correlated sub-query is a sub-query that depends on the outer query and cannot be executed separately. It uses the outer query to filter or transform data by referencing a column from it, and the outer query uses the results of the inner query. In contrast, a non-correlated sub-query is independent of the outer query and can be executed on its own. It does not reference any columns from the outer query and is used to retrieve additional data needed by the outer query.
Here is an example of a correlated sub-query:
This query selects the and total sales of all Allscripts Healthcare customers in the sales table whose are greater than the average of their own customer group. The sub-query in this case is correlated with the outer query, as it references the column from the outer query ().
Here is an example of a non-correlated sub-query:
The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.
Performance-wise, correlated sub-queries are generally slower to execute, as they have to be re-evaluated for each row of the outer query, while non-correlated sub-queries are faster, as they only have to be executed once.
Preparing For The Allscripts Healthcare SQL Interview
The best way to prepare for a Allscripts Healthcare SQL interview is to practice, practice, practice.
Besides solving the earlier Allscripts Healthcare SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups.
Each SQL question has hints to guide you, full answers and crucially, there is an interactive SQL code editor so you can right online code up your SQL query answer and have it executed.
To prep for the Allscripts Healthcare SQL interview you can also be a great idea to practice SQL problems from other tech companies like:
But if your SQL foundations are weak, forget about going right into solving questions – go learn SQL with this free SQL for Data Analytics course.
This tutorial covers SQL concepts such as aggregate functions and using wildcards with LIKE – both of these show up frequently in SQL interviews at Allscripts Healthcare.
Allscripts Data Science Interview Tips
What Do Allscripts Healthcare Data Science Interviews Cover?
In addition to SQL query questions, the other types of problems covered in the Allscripts Healthcare Data Science Interview include:
- Probability & Stats Questions
- Python Pandas or R Coding Questions
- Analytics and Product-Metrics Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Allscripts Healthcare Data Science Interviews?
I'm a bit biased, but I think the optimal way to prepare for Allscripts Healthcare Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book has 201 data interview questions sourced from FAANG (FB, Apple, Amazon, Netflix, Google). It also has a crash course on Product Analytics, SQL & ML. And finally it's helped a TON of people, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.