Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

Version 1 Next »

This page presents the analysis of AI algorithm’s input data model. First, we analyse the openIMIS data structure and extract the minimal required openIMIS entities and fields representing the information used by the Medical Officer to adjudicate a claim. Second, we look at the openIMIS-FHIR mapping and extract the minimal required FHIR resources and fields to feed the AI algorithm during the learning, development and test processes.

Minimal required openIMIS entities and fields

As are looking on the openIMIS claim adjudication process, we are interested to identify the entities/tables and their fields that are used by the Medical Officers to review and categorise the items and services present in a claim.

openIMIS Claim Review Web Page

openIMIS Database Tables

Diagram

The following database diagram displays openIMIS tables and their relations. The analysis is centred on Claim and identifies other entities in relation to a Claim and used in the adjudication process.

Fields definition

tblClaim

Field

Type

Description

ClaimUUID

uniqueidentifier

Unique identifier of the Claim

DateFrom

smalldatetime

DateTo

smalldatetime

ClaimStatus

tinyint

Claimed

decimal(18, 2)

VisitType

char(1)

Emergency, Referral, Other

ClaimCategory

char(1)

Automatically defined in checking process: Surgery, Delivery, Antenatal, Hospitalisation, Consultation, Visit

tblHF

Field

Type

Description

HfUUID

uniqueidentifier

tblClaimAdmin

Field

Type

Description

ClaimAdminUUID

uniqueidentifier

tblInsuree

Field

Type

Description

InsureeUUID

uniqueidentifier

DOB

date

Date of birth

Gender

char(1)

Gender in codded format: e.g. M/F, 0/1

tblFamilies

Field

Type

Description

tblInsureePolicy

Field

Type

Description

tblICDCodes

Field

Type

Description

tblClaimServices

Field

Type

Description

tblClaimItems

Field

Type

Description

  • No labels