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+!!! abstract inline end "Feedback"
+    You finished the tutorial - well done!. Either now, or after you've tried the quiz, we'd love it if you could fill in this very short [feedback form][1]{:target="_blank"}.
+
+To test your understanding of ehrQL, the tutorial repository contains a file (called `quiz.py`) with some gaps for you to fill in.
+
+Open the file now in your Codespace.
+You will see lots of lines like `questions[3].check(...)`.
+To work through the quiz, you'll have to replace the `...`s with an ehrQL object (a series, frame, or dataset).
+You'll see that the first question has been answered for you.
+
+You can check your answers by pressing CTRL-SHIFT-ENTER, or by clicking the play button in the top right:
+
+![play button](play-button.png)
+
+(You may need to use the drop-down next to the play button in order to select "OpenSAFELY: Debug ehrQL dataset")
+
+![OpenSAFELY debug ehrQL button](play-button-drop-down.png).
+
+
+You should see output matching the following:
+
+```
+Question 0
+Correct!
+
+Question 1
+Skipped.
+
+Question 2
+Skipped.
+
+...
+
+Summary of your results
+Correct: 1
+Incorrect: 0
+Unanswered: 11
+```
+
+To work through the quiz, we suggest trying to answer the questions one-by-one, and checking your answers after each question.
+
+If you get stuck, you can type `questions[7].hint()` into the `quiz.py` file, and run it to display a hint.
+
+Many questions build on the answers to previous questions, so you should consider giving names to some of your objects.
+
+The quiz takes you through categorising patients according to two other (simplified) QOF business rules:
+
+**DM014** Identify the patients who have been diagnosed with diabetes for the first time in the past year and who have a record of being referred to a structured education programme within nine months after their diagnosis.
+
+0: Create an event frame by filtering `clinical_events` to find just the records indicating a diabetes diagnosis. (Use the `diabetes_codes` codelist.)
+
+1: Create a patient series containing the date of each patient's earliest diabetes diagnosis.
+
+2: Create a patient series containing the date of each patient's earliest structured education programme referral. (Use the `referral_code` codelist.)
+
+3: Create a boolean patient series indicating whether the date of each patient's earliest diabetes diagnosis was between 1st April 2023 and 31st March 2024. If the patient does not have a diagnosis, the value in this series should be `False`.
+
+4: Create a patient series indicating the number of months between a patient's earliest diagnosis and their earliest referral.
+
+5: Create a boolean patient series identifying patients who have been diagnosed with diabetes for the first time in the year between 1st April 2023 and 31st March 2024, and who have a record of being referred to a structured education programme within nine months after their diagnosis.
+
+**DM020** Identify patients without moderate or severe frailty in whom the last IFCC-HbA1c is 58 mmol/mol or less in the preceding twelve months.
+
+6: Create a patient series with the date of the latest record of mild frailty for each patient.
+
+7: Create a patient series with the date of the latest record of moderate or severe frailty for each patient.
+
+8: Create a boolean patient series indicating whether a patient's last record of severity is moderate or severe. If the patient does not have a record of frailty, the value in this series should be `False`.
+
+9: Create a patient frame containing the latest HbA1c measurement for each patient.
+
+10: Create a boolean patient series identifying patients without moderate or severe frailty in whom the last IFCC-HbA1c is 58 mmol/mol or less.
+
+[1]: https://docs.google.com/forms/d/e/1FAIpQLSeouuTXPnwShAjBllyln4tl2Q52PMG_aUhpma4odpE2MmCngg/viewform