Frequently Asked Questions
What is BigMouth?
BigMouth is a centralized oral health data repository derived from electronic health records (EHRs) at multiple dental schools. With demographic, medical history, and dental data on over 4 million patients, this oral health database is available for research and the advancement of evidence-based dentistry.
Who are the participating institutions?
Please visit this page to see a list of our Participating Institutions.
What does axiUm folder contain?
The axiUm node contains the (user's) site specific terminologies. Users can query for data available in axiUm at their own site. The number displayed adjacent to each folder/leaf node represents the number of patients.
- Demographics: contains age, gender, and race/ethnicity. User can query age by value with the following operators: <, >, ≥, ≤, =, between.
- Diagnosis: contains Dental Diagnostic System (DDS) terminologies, formerly known as the EZCodes diagnostic terminology. User can query a diagnosis with or without date range.
- Forms: contains medical, dental history of patients, and caries risk assessment. In addition, each site may have other specific forms. User can query a form question with or without date range.
- Insurance: contains the names of insurance companies that insure patients.
- Odontogram: contains existing materials, existing conditions on a specified tooth or surface and the total number of missing teeth.
- Perio: contains clinical periodontal parameters which could be queried by examination types (e.g. initial examination, re-evaluation examination). ' Medication: contains prescription and patient's current medication information and can be queried with or without date range.
- Practice: contains details about the different practices in a site.
- Procedures: contains Dental Procedure Codes (CDT) and Current Procedural Terminology (CPT) procedures which could be queried with or without date range.
- Providers: contains different dental health providers such as dental student, dentist, resident etc.
How is the age calculated?
Age is calculated from the date of patient's last recorded observation (procedure, diagnosis etc.).
What does the Combined Terms folder contain?
This folder provides an integrated terminology system that allows users to query for data from all schools that contribute data to BigMouth.
- Demographics: contains age, gender, and race/ethnicity from all schools.
- Diagnosis: contains Dental Diagnostic System (DDS) terminologies from HARVARD, UCSF, UTH, LLU, UB, UCD, UIOWA, UMN, and UMICH.
- Forms: contains medical and dental history from all schools. The combined BigMouth terminology contains caries risk assessment from all schools.
- Odontogram: contains existing materials, existing conditions on a specified tooth or surface, and the total number of missing teeth from all schools.
- Perio: contains clinical periodontal parameters from all schools.
- Procedures: contains CDT and CPT procedures from all schools.
- Providers: contains different dental health providers from all schools.
Where is the Race/ethnicity standard derived from?
Race/ethnicity standard derived based on NIH guidelines.
How can I get data for my research from BigMouth?
The BigMouth interface provides query tools to users to get the number of patients having conditions or diseases of interest such as the number of patients with caries or periodontal diseases, etc...
There are two levels of access:
- Level 1: Users who have access to BigMouth can run queries themselves and use the count for their research.
- Level 2: If the user wants to get detailed data for each individual patient, a3\ copy of the IRB approval document will need to be provided along with the data request template. The template will facilitate us to extract the requested data which will be presented in an Excel sheet with requested variables in columns and individual patients in rows.
In addition to it, the users are also required to sign a data access request form. If the user is interested in accessing patient data from outside the school to which the user is affiliated, in addition to the IRB approval document from the user's school, the project will need to be approved by the BigMouth project review committee. The following documents contain all the required information:
- Clinical Research Committee Checklist
- BigMouth Clinical Research Committee Proposal Guidelines
Please contact the BigMouth team for details of the form.
How can I make a 2x2 table using BigMouth?
- For example, I am interested in a diagnosis A and a treatment B. I would like to see how many patients with that diagnosis A had that treatment, and how many did not. - I'd also like to see how many without that diagnosis A had that treatment B how many did not.
This can be achieved using the exclude/include option in each column. Here are few screen shots:
How can I make a temporal query?
There are five basic steps in defining a temporal query in the Query Tool view:
- Change Temporal Constraint to Define sequence of Events.
- Define Population in which events occur (optional step).
- Define Events
- Define order of events (temporal relationships)
- Run the query
How do I query for a specific date range?
Users can specify the date range of the observation as shown below
Why do the patient counts not add up in the navigation tree?
The reason is because one patient may have more than one specific condition. For example, total number of patients of the category 'Abnormalities of teeth' in the picture below is 984. The number of patients of the subcategories of the category 'Abnormalities of teeth' adds up to 1041. This is because one or more patient may be in both subcategories such as 'Cementum Defect' and 'Dentin Defect'.
What data do I have access to?
Upon login, a user is presented with two folders. The folders are:
- axiUm - Contains data from the user's local axiUm instances.
- Combined Terms - Contains data from all the participating sites. This folder is normally used when a user is interested in querying data from all BigMouth members. The folder is designed in such a way that the user can get a summary of the data from all sites at the same time, keeping the source of data anonymous.