We welcome your input on assembling our Track Report Out. Please contribute as necessary.

Short Description

The purpose of this track is to evaluate how well USCDI data elements (current and future versions required for certification) can be used for care coordination and how well standard value sets for multiple chronic conditions (MCC) can classify conditions and other data elements using the HL7 FHIR standard. 

This track builds on a series of Connectathons exploring the use of FHIR Resources to collect, share, and use data critical to person-centered care planning and goal-oriented decision-making for individuals with MCC.

Long Description

Care coordination is the activity that "involves deliberately organizing patient care activities and sharing information among all the participants concerned with a patient's care to achieve safer and more effective care. This means that the patient's needs and preferences are known ahead of time and communicated at the right time to the right people, and that this information is used to provide safe, appropriate, and effective care to the patient" (AHRQ). For the purpose of this track, we are focused on sharing information across provider organizations that are necessary to coordinate planning care for patients with complex care needs.

The objectives for the MCC eCare Plan track in Connectathon 33 are to:

  • Examine how consistently terminology used for classifying chronic conditions (condition.code) is being employed across systems using the MCC Chronic Conditions Value Sets (SNOMED CT, ICD10CM, ICD9CM) and leverage classifications to group related conditions.
  • [Reach] Examine how consistently terminology used for classifying labs, clinical tests, imaging, SDOH assessments, etc. (observation.code) is being employed across systems.
  • [Reach]  Explore the use of standard value sets that can be used to classify intervention orders (Procedure.code, ServiceRequest.code) such as education, counseling, lab tests, diagnostic tests, etc.
  • Examine the ability to reuse existing USCDIv1 data supported by US Core v3.1.1. implementation (i.e., Health Concerns, Problems, Care Team, Goals, Lab Tests and Values/Results, Vital Signs, Medications, Procedures, Provenance) for supporting relationships between and linking data for care coordination and care planning.
  • [Reach] Examine the ability to use later versions of USCDI/US Core v4 or later, including ServiceRequests, for supporting relationships between and linking data for care coordination and care planning.
  • Evaluate the extent to which systems that meet certification requirements also conform to the MCC FHIR IG specification.

This track is hosted by the Multiple Chronic Conditions (MCC) eCare Plan project. The track focuses on patient and person-level information collection and exchange across acute, ambulatory, post-acute care settings, community-based organizations, and patient digital mobile devices with the goal of generating, sharing and updating an interoperable electronic care plan to support care coordination and care planning for persons with MCC, including chronic kidney disease, type 2 diabetes, cardiovascular disease, chronic pain, and long COVID.

Type

Test an implementation guide

Related Tracks?

2023 - 05 US Core Testing Track

2023 - 05 TEFCA Facilitated FHIR

Call for participants

EHR vendors or other systems supporting US Core v3.1.1 or higher who want to see how those data elements can be reused for care coordination and care planning purposes.

Provider-facing SMART on FHIR applications that support providers in care coordination and/or care planning for patients with chronic conditions.

Patient/caregiver-facing SMART on FHIR applications that support patients and caregivers with access to their health data, care coordination, and/or care planning for chronic conditions.

Technical individuals with domain expertise interested in helping test out the specification.

If you don't have time to participate in person, but have a server that satisfies some of the requirements, let us know and we'll happily do some testing with it!

Track Prerequisites

Prerequisites by participant type:

  • EHR vendors/systems
    • Implemented US Core v3.1.1 or higher
    • Has FHIR endpoint with non-PHI data (bonus: if the data is realistically complex for chronic conditions)
  • Provider- and patient/caregiver-facing applications
    • FHIR-enabled and interoperable

Track Lead(s)

Dave Carlson

Bret Heale

Savanah Mueller

Himali Saitwal

Karen Bertodatti

Track Lead Email(s)

dcarlson@ClinicalCloud.solutions, savanah.mueller@emiadvisors.net, bheale@humanizedhealthconsulting.com, karen.bertodatti@emiadvisors.net

Specification Information

MCC eCare Plan FHIR IG: https://build.fhir.org/ig/HL7/fhir-us-mcc/branches/master/index.html

Zulip stream

https://chat.fhir.org/#narrow/stream/220328-Care-Plan.2FCare-Coordination/topic/Connectathon.2033

Track Kick off Call

The track orientation call occurred on at 2:00 PM ET. Please find the recording and materials below. The presentation deck includes hyperlinks to resources. Reach out to the track leads with any issues. 


Recording:

Slides: 

Testing Scenario:

Test Scenario #1: Care Planning Data Exchange Between Two or More SMART on FHIR Apps

Exchange care planning data elements, as scoped by MCC eCare Plan IG, between two or more independently developed SMART on FHIR applications intended for use by patients, caregivers, or clinicians. Applications will read and write to a shared FHIR server. A MELD sandbox FHIR server will be made available for use during the connectathon. In the actions described below, a "User" may be a patient, caregiver, or clinician as appropriate for the application being tested.

This scenario will evaluate coverage of data elements from MCC eCare Plan IG and/or US Core IG that are supported by participants' care planning applications, including the use and availability of FHIR extensions and inter-resource relationships described in the MCC eCare Plan IG.

Actions:

  • User of App 1 authors new care planning content, e.g., a Goal, Condition, or ServiceRequest.
  • App 1 writes new data elements into a FHIR data repository.
  • App 2 connects to the same  FHIR data repository and queries patient data.
  • User of App 2 reviews displayed data elements to confirm alignment or missing data from entries by App 1 User.

Success Criteria:

  • Care planning data elements entered in one application are read and displayed by a second application.
  • Data elements are present and complete.

Bonus: 

  • Reverse the roles of App 1 and App 2 to test bi-directional exchange of care planning data.

Test Scenario #2: MCC eCare Plan IG Conformance Testing using Inferno

The MCC Project will provide a conformance testing tool that uses Inferno (the same tool used to test USCDI and US Core conformance) extended with additional tests for profiles defined by the MCC eCare Plan IG. The track's objective is to test coverage and conformance of MCC data, ideally from systems that include real-world or de-identified patient data.

We intend to make the MCC conformance testing tool available on a cloud server, or for download and installation on-premise behind a participant's firewall for access to restricted or private de-identified data sources.

MCC test tool (Inferno): us-core-with-mcc-test-kit

Tests the following resources and MCC profile constraints:

  • Goals
    • Goal.startDate
    • Goal.addresses
    • Goal.target.measure
    • Goal.target.dueDate
  • Additional profile constraints to be determined as the tests are developed.

Actions:

  • Run the MCC test tool with connection to your FHIR endpoint.

Success Criteria:

  •  Generate an HTML report summarizing coverage of the MCC IG additional constraints for care planning/coordination.

Test Scenario #3: MCC eCare Plan IG Library of Value Set Classification

Evaluate the MCC IG library of value sets for their ability to classify Condition and Observation resources, e.g. to determine that a Condition is a kind of Type 2 Diabetes or a kind of Hypertension. Ideally, we would like to test these resources with real-world or de-identified data that represents how these data are actually coded in practice by EHR systems, laboratories and clinicians. The MCC IG includes more than 200 value sets for Conditions, and many more for lab results, Long COVID symptoms, and more.

Actions:

Success Criteria:

  • Patient conditions are correctly classified into diagnostic categories defined by value sets, using Condition SNOMED or ICD code.

Bonus Points:

  • Test MCC value sets using other terminology services that you may have


Educational Tooling Session:

Sunday, May 7, from 3:30-4:15 PM CT