Mapping working example

Manually mapping hundreds of fields and values can be extremely laborious and prone to error.

Mapping suggestion algorithms offer machine assisted hints to manually selected mappings.

The algorithms work by starting with a context provided by the application, and via a series of iterations, narrow down the options to a small number. The algorithms are further tuned for specific patterns found in some source fields and values, and perhaps some authoring conventions when the target concepts were created.

In some cases, confidence levels are high enough to assume a single match (equivalent class axiom) and in this case it would be expected that a user validated a mapping once matched

Table and field hints

Take the following working example

{
  "InformationModel": {
    "Mapping": {
      "Source": {
        "Provider": "Barts",
        "System": "CernerMillenium",
        "Context": {
          "id": 1,
          "Table": "AdmittedPatientCare",
          "Field": "PatientClassificationCode",
          "Value": 1}}}}}