Da Vinci - Coverage Requirements Discovery
2.0.1 - STU 2 United States of America flag

This page is part of the Da Vinci Coverage Requirements Discovery (CRD) FHIR IG (v2.0.1: STU 2.0) based on FHIR (HL7® FHIR® Standard) R4. This is the current published version in its permanent home (it will always be available at this URL). For a full list of available versions, see the Directory of published versions

CRD Metrics

Page standards status: Informative

This Implementation Guide (IG) is one of 4 HL7 Da Vinci IGs that are designed to address the challenges of automating the exchange of information between a provider and the responsible payer to determine coverage of services, items, and referrals. In particular, these IGs standardize the exchange of information required to automate the Prior Authorization (PA) process. The specific IG are:

  1. Coverage Requirements Discovery (CRD) (this IG)
  2. Documentation Templates and Rules (DTR)
  3. Prior Authorization Support (PAS)
  4. Clinical Documentation Exchange (CDex)

Each guide supports a specific set of functions and exchanges required to determine payer coverage for specific services, items, and referrals.

To maximize the value of these IGs, it is imperative that each IG is integrated into clinical workflow at the appropriate point and all of the exchanges required by each IG are fully supported by all of the participants (providers, intermediaries, and payers).

Each of these IGs recommends a set of metrics that SHOULD or MAY be collected by their respective implementations to facilitate the evaluation of adoption, functionality, processes, and improved outcomes. While there is currently no requirement to report on these metrics, it is reasonable to believe that in the future interested entities (providers, payers, regulators, quality organizations, certification agencies, states, etc.) will ask for these metrics to evaluate the ongoing automation of the supported processes / exchanges. While this guide will not require these metrics to be captured in this release, the authors strongly suggest each implementation should do so with the expectation that collection and dissemination of these metrics may become a requirement (SHALL) in future version of these IGs.

The table below defines a set of measures with a short name, purpose, conformance, stakeholder, and collection/calculation instructions that represent what the project group designing this IG felt would be both reasonably collectable and useful in evaluating implementations of this IG. These measures are based on the metric data model logical model also published in this IG.

Suggested Metrics

Nbr Metric Metric Type Provider/Payer Calculation Example
1 Volume/% of Orders with results (coverage info) returned Adoption Process Both For volume:
CRDMetricData.exists(response.coverageInfo).count()
For percent:
Divide volume above by CRDMetricData.where(httpResponse=200).count() and express as percentage
2 % by coverage response type (covered, not covered, conditional) Segmentation Both For volume:
Iterate where $ResponseType is one of covered, not-covered, conditional CRDMetricData.exists(response.coverageInfo.where(covered=$ResponseType)).count()
For percent:
Divide volume above by CRDMetricData.where(httpResponse=200).count() and express as percentage
3 Volume/% of PA required with DTR launch context Process Compliance Both For volume:
CRDMetricData.exists(response.coverageInfo.where(paNeeded = "auth-needed" and questionnaire.exists())).count()
For percent:
divide volume above by CRDMetricData.exists(response.coverageInfo.where(paNeeded = 'auth-needed')).count() and express as percentage
4 Volume/% of Documentation required with DTR launch context Adoption Both For volume:
CRDMetricData.where(response.coverageInfo.where((docNeeded='clinical' or docNeeded='admin' or docNeeded='both') and questionnaire.exists())).count()
For percent:
divide volume above by CRDMetricData.exists(response.coverageInfo.where(docNeeded='clinical' or docNeeded='admin' or docNeeded='both')).count() and express as percentage
5 Volume/% with service determination Adoption Process Both For volume:
CRDMetricData.where(response.coverageInfo.exists(paNeeded = 'satisfied')).count()
For percent:
divide volume above by CRDMetricData.where(httpResponse=200).count() and express as percentage
6 % in under 5 seconds Process Compliance Both CRDMetricData.where(httpResponse=200 and (requestTime + 5 seconds > responseTime)).count() /
CRDMetricData.where(httpResponse=200).count() and express as percentage
7 Reduction in PA submission (relative to current practice) Outcome Both Needs information external to CRD metric data
8 All of the above by payer for provider metrics and for provider for payer metrics Segmentation Both Segmentation based on CRDMetricData.source and (CRDMetricData.payerID or CRDMetricData.groupID)
9 All of the above by hook type Segmentation Both Segmentation based on CRDMetricData.hookType