Jane does not provide a public API, so appointment and client data must be imported manually by uploading files exported directly from the Jane app.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/hack4impact-umd/breastfeeding-center-gw/llms.txt
Use this file to discover all available pages before exploring further.
File types
Two file types can be uploaded during a single import: Appointments file (required) An Excel or CSV export of appointment records from Jane. The file must include the following columns:id— appointment IDpatient_number— Jane patient numberpatient_first_name/patient_last_name— patient namestart_at/end_at— appointment start and end times (ISO)treatment_name— service or visit typestaff_member_name— assigned clinicianfirst_visit— flag indicating whether this is the patient’s first visit
Upload flow
Select your files
Choose the appointments file (required). Optionally attach the clients file if you need to add new patient records.
Processing logic
After files are submitted, the server performs the following steps:- Parse — the appointments file is converted from
.xlsxor.csvinto a list of appointment records. - Group — appointments are grouped by
start_attimestamp and clinician name. Each group represents a single session that may involve a parent and one or more babies. - Client matching — each appointment is looked up against client records by Jane patient number (
patient_number). If a clients file was provided, new records from that file are merged into the lookup. Otherwise, existing Firestore records are used. - Primary client selection — within each appointment group, the primary client is determined by which existing Firestore record has the most appointment history. Associated clients (co-attendees) are linked to the primary client.
- Baby matching — baby appointments in a group are matched to
Babyrecords and merged into the primary client’sbabyarray, avoiding duplicates. - Write — matched clients and appointments are upserted into the
ClientandJaneApptFirestore collections. Existing records are merged, not overwritten.
Supported formats
Both.xlsx and .csv are accepted for each file. Files must not be empty and must include all required column headers.
