Common Key Service (CKS) Use Case

The Common Key Service use case provides a consistent and reliable way to match patients with their electronic health information across multiple organizations, applications, and services.

Use Case Summary, Implementation Guide and Supporting Documents


Common Key Service (CKS) Use Case Summary

Common Key Service (CKS) Use Case Implementation Guide

 

To improve the match rate and accuracy of identity resolution processes, we are working to create a more standards based Common Key implementation based on:

  • Leveraging assigning authority ID (the OID representing the organizational source of the patient identifiers) and local ID (the actual patient identifier assigned by that source
  • Updating the Common Key API interface to support standards-based IHE interaction paradigms including Patient Identity Management, Patient Identity Feed, Patient Data Query as well as others aligning with MPI metrics of XCA (cross community access) or XCPD (cross community patient discovery)

An object identifier (OID) has a central utility in providing a traceable source for the meaning of an identifier appearing in a cross-system communication.  The need to know who owns the identifier is critical in case questions arise concerning the meaning of the identifier.

OID values and mappings are instrumental in strengthening patient matching and contributing to the creation of a robust and accurate longitudinal patient record that our network participants can leverage within their workflows.

About this Use Case

One of the most important goals of sharing patient information electronically is helping doctors build complete, current pictures of their patients using health information from multiple sources. These sources can include other doctors or specialists, hospitals, clinics, pharmacies, skilled nursing facilities and any other healthcare setting where care is provided.

Enabling doctors to gather the details to build these complete patient pictures requires accurate “patient-matching” to make sure electronic health information from outside sources is attached to the correct patient.

These patient-matching challenges can cause higher healthcare costs and lower care quality in many ways. When a patient’s health information is shared among doctors who use different systems, a lot of effort is needed to find and evaluate variations and identify the correct patient in each health information system. Errors can and do occur, meaning the wrong information can be matched to a patient.