Short Description

Longitudinal Maternal & Infant Health Information for Research

Long Description

According to the 2021 Aspen Health Strategy Group report on “Reversing the U.S. Maternal Mortality Crisis”, 700 women die each year as the result of pregnancy or delivery complications, and 50,000 more face short-term or long-term health consequences because of pregnancy or labor. The U.S. has the highest maternal mortality rate of any high-income nation in the world (17.4 maternal deaths per 100,000 live births) according to The Commonwealth Fund. While rates of maternal mortality have been decreasing in other countries, they have been rising in the United States since 1987. Data are not standardized and data exchange in not interoperable across many settings, which impedes research on maternal morbidity, longitudinal maternal care, and associated impacts to infant and infant health.

Type

Test an Implementation Guide
Track Prerequisites
  • Servers will be able to support storing, receiving, and processing all resources specified in the measures of this IG (e.g. Encounter, Condition, Observation, Patient, RelatedPerson)
  • Servers implementing this IG shall support measure evaluation using CQL
  • Clients shall supply all resources necessary for measure evaluation
  • Clients shall support RESTful operations that allow interaction with the server (such as GET, POST, PUT)
  • Clients may use a REST client such as Postman for the purposes of this Connectathon

Track Lead(s)

Arvind Jagannathan

Track Lead Email(s)

arvind.jagannathan@lantanagroup.com

Specification Information

https://build.fhir.org/ig/HL7/fhir-mmm-ig/

Call for participants

Kids First Data Resource Center

Lantana

Zulip stream

https://chat.fhir.org/#narrow/stream/179290-research/topic/Connectathon.3A.20Maternal.20Health.20Research.20Track

Track Kick off Call

Thursday, 9/8 from 10-11am ET

Watch the Kick Off Call Recording Here

Clinical Input Required?
Related Tracks?

Testing Scenario:

System roles:

  • Data Source: Health Information Exchanges, clinical EHRs (ambulatory, inpatient) possibly for Ob/Gyn, birthing/delivery settings, pediatricians.
  • Data Receiver: Maternal Health Researchers (academic, federal, etc.) using data provided by the Data Source to evaluate measures. 


Scenario 1: Evaluate FHIR Data Against Hypertensive Disorders of Pregnancy and Pregnancy Related Deaths measures

Actions:

  • Data Source to provide FHIR data sufficient to test the measures, including the linkage between mother and child. Data may be as raw XML/JSON files or posted to a FHIR server. 
  • Data Receiver to execute $evaluate-measure for 2 measure instances defines in IG

Precondition: Data Source has FHIR data necessary to evaluate the Hypertensive Disorders of Pregnancy and Pregnancy Related Deaths measures. 


Success Criteria: For a given patient, provide researcher actor with accurate calculation of Patient inclusion/exclusion in (1) Hypertensive Disorders of Pregnancy measure instance and (2) death-related measure instance


Scenario 2: Convert C-CDA Data and Evaluate FHIR Data Against Hypertensive Disorders of Pregnancy and Pregnancy Related Deaths measures

Actions:

  • Data Source to provide FHIR data sufficient to test the measures, including the linkage between mother and child. Data will be provided in C-CDA format with the linkage between mother and child. 
  • Data Receiver transforms CCDA into FHIR and confirm resulting FHIR data adheres to standard FHIR guidance for appropriate linkage between mother and child
  • Data Receiver to execute $evaluate-measure for 2 measure instances defines in IG

Precondition: Data Source has C-CDA data necessary to evaluate the Hypertensive Disorders of Pregnancy and Pregnancy Related Deaths measures. 


Success Criteria: For a given patient, provide researcher actor with accurate calculation of Patient inclusion/exclusion in (1) Hypertensive Disorders of Pregnancy measure instance and (2) death-related measure instance

Bonus points:

  • IHE-XD*: For Scenario 2, use IHE-XD* to retrieve the C-CDA documents 
  • De-identification: While de-identification is expected to be needed for production implementations for researchers to view clinical data, no Hypertensive Disorders of Pregnancy I will be used during this connection. However, participants may wish to test de-identification techniques. 

TestScript(s): N/A

Server:  

HAPI (v5.4.1) https://connectathon-fhir.lantanagroup.com/fhir



Security and Privacy Considerations:

Identify any expectations around security (e.g. will TLS, mutual-TLS, OAuth, etc. be required to participate.