Setting up natural language in Qnaires

You can use Qnaires to automatically populate parts of an encounter note with patient-reported information.

Natural language conversion supports this and refers to the ability to convert patient's Qnaire responses into custom paragraphs, lists, or clinically relevant summaries that can be directly attached to encounter notes. This contributes to increased efficiency when you create encounter notes.

You use basic HTML elements and specific variables when setting up natural language.

For example,

Qnaire question	Natural Language conversion field using HTML elements	Response to question in Qnaire	Response in encounter note
Please list all drug and non-drug allergies	<br><u>MEDICAL HISTORY</u><br><br><b>Drug or non-drug allergies: </b>"#answer"	Peanuts	MEDICAL HISTORY Drug or non-drug allergies: “Peanuts”

Qnaire question	Natural Language conversion field	Answer to question in Qnaire	Answer in encounter note
How long have you been using this set of medications?	Main question: #heshe has been taking this regimen for #answer.	Response option: 3-6 months	She has been taking this regimen for 3 to 6 months.

📌 Note: You can configure natural language in all question types, except form, picture, and draw question types.

Steps:

1. From the Questions page within an existing Qnaire, scroll to the specific question. See Creating Qnaires for information on how to navigate to the Questions page.

2. Scroll to the question you want to associate natural language with and click it. The field expands.

3. In the Natural Language Conversion field,

a. Type the response in a sentence format, using #answer to pull in the patient's selected response.

💡 Tip: Use the below HTML elements and tags for the sentence in the encounter note to appear formatted.

From the example in the above image, if the patient selects the response Nearly every day, the sentence in the encounter notes appears as: When asked how often the patient has had little interest or pleasure doing things, they reported: Nearly every day.

Or,

b. Type #answer to "pull in" the patient's selected response.

From the example in the above image, If the patient selects the response Nearly every day, the following appears in the encounter notes: Nearly every day which in this case has no relevance to the provider.

📌 Note: To create a unique answer per question response, for example, to create a coherent sentence with relevant information or to remove capitalisation, click a response option to the specific question, and in the Natural Language Conversion field, type a sentence as you want it to appear in your encounter notes.

From the example in the above images, If the patient selects the response Nearly every day, the following appears in the encounter notes: The patient mostly has little interest or pleasure doing things.

Use the following HTML elements when setting up natural language:

Code	Description
<p>	You can define the start of a paragraph using the <p> element. Paragraphs are blocks of text separated from adjacent blocks of text. ⚠ Important: Paragraphs must begin with a <p> tag and end with a </p> tag. For example, <p>Text</p>
</p>	You can close the paragraph with the </p> element.
<br>	You can create a line break using the <br> element. A line break denotes the end of one line and the start of a new one.
<br>-	You can create a bullet using a hyphen <br>-
<li>	You can create an item in a list (bullet point) using the <li> element. 📌 Note: When you insert a bullet point, a line break is automatically added, indicated by the code </li>
<em>TEXT</em>	The text you add between these codes appears in italics.
<strong>TEXT</strong>	The text you add between these codes appears in bold.
<u>TEXT</u>	The text you add between these codes appears underlined.

You can use the following variables when setting up natural language

Variables	Description
#heshe #himher #hisher #himherself	To add Male or Female pronouns add these variables when setting up natural language. 📌 Note: When the variables are converted they are automatically capitalized if placed at the beginning of a sentence.
#first_name	This pulls from the patient's demographics: First Name field.
#last_name	This pulls from the patient's demographics: Last Name field.
#age	This pulls from the patient's demographics: Date of Birth field.
#gender	This pulls from the patient's demographics: Sex field.
#patient_title	This pulls from the patient's demographics: Title field.
#answer	This pulls the patient's response to a specific question.

Updated March 14, 2023