Diagnoses

Your diagnosis list is what clinicians can record as a patient’s condition, such as type 2 diabetes or hypertension. Each row is one diagnosis, identified by your own id. Use type=diagnosis with the API, or pick Diagnoses in the console.

Mandatory columns: diagnosis_id and name. Every other column is optional; leave the cell empty if you don’t have the value.

Columns

Column	Required	What it means	Allowed values	Example
`diagnosis_id`	Yes	Your own id for the diagnosis. Any text works, including a code you already use. Writing a row with an id that already exists updates it.	Text, up to 200 characters	`DX1001`
`name`	Yes	The diagnosis name. Used for search.	Text, up to 200 characters	`Type 2 Diabetes Mellitus`
`ekaid`	No	Eka’s own id for the same diagnosis, from Eka’s reference list. Lets Eka products recognise it. See Mapping your records to Eka ids.	Text, up to 64 characters	From Eka’s list
`display_name`	No	The name shown to doctors and patients. Defaults to `name`.	Text, up to 200 characters	`Type 2 Diabetes Mellitus`
`aliases`	No	Synonyms and everyday words people search by.	Several values separated by `\|`	`T2DM\|Type 2 Diabetes`
`snomed_id`	No	SNOMED CT concept id. The most reliable link to standard terminology, when you have it. Not checked against SNOMED.	Text, up to 32 characters	`44054006`
`icd10`	No	ICD-10 code. Not checked against the ICD list.	Text, up to 32 characters	`E11.9`
`icd10_term`	No	The ICD-10 description for that code.	Text, up to 255 characters	`Type 2 diabetes mellitus without complications`
`gender`	No	Use when the diagnosis applies to one gender only. Leave empty when it applies to everyone.	`M` or `F` (capital letter)	`M`
`is_active`	No	Set to `false` to keep the diagnosis but hide it. Defaults to `true`.	`true` or `false`	`true`

Example file

diagnoses.csv

diagnosis_id,name,ekaid,display_name,aliases,snomed_id,icd10,icd10_term,gender,is_active
DX1001,Type 2 Diabetes Mellitus,,Type 2 Diabetes Mellitus,T2DM|Type 2 Diabetes,44054006,E11.9,Type 2 diabetes mellitus without complications,,true
DX1002,Essential Hypertension,,Essential Hypertension,HTN|High Blood Pressure,59621000,I10,Essential (primary) hypertension,,true
DX1005,Benign Prostatic Hyperplasia,,Benign Prostatic Hyperplasia,BPH|Enlarged Prostate,266569009,N40,Benign prostatic hyperplasia,M,true

Put quotes around any value that contains a comma, like "Chest pain, unspecified". Spreadsheet programs do this for you when they save as CSV.

The smallest valid file has just the two mandatory columns:

minimal.csv

diagnosis_id,name
DX1001,Type 2 Diabetes Mellitus

Example JSON

Records sent to Create or update records. In JSON, multi-value fields are lists.

[
  {
    "diagnosis_id": "DX1002",
    "name": "Essential Hypertension",
    "aliases": ["HTN", "High Blood Pressure"],
    "snomed_id": "59621000",
    "icd10": "I10",
    "icd10_term": "Essential (primary) hypertension"
  },
  {
    "diagnosis_id": "DX1005",
    "name": "Benign Prostatic Hyperplasia",
    "aliases": ["BPH", "Enlarged Prostate"],
    "gender": "M"
  }
]

Common mistakes

Lowercase gender. Use M or F; m, male or Female are rejected.
Several codes in snomed_id or icd10. Each holds one code. Put alternative names in aliases instead.
Reusing an id for a different diagnosis. An existing diagnosis_id updates that record; it never creates a second one.

Authorization

Webhooks

Encryption

HealthAI

ABDM Connect

Datasets

Doctor Tool

Medical Knowledge-bases

Medical Records

User App

Medical Database

Columns

Example file

Example JSON

Common mistakes

​Columns

​Example file

​Example JSON

​Common mistakes

Columns

Example file

Example JSON

Common mistakes