MII Implementation Guide Soziodemographie
2027.0.0-ballot - Germany

This page is part of the MII Implementation Guide Soziodemographie (v2027.0.0-ballot: 2027 Ballot 1) 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

Guidance for Implementers

Context in the overall project / relationships to other modules

Classification within the Core Dataset

The Sociodemographic Data module is designed as an extension module to the MII core dataset. The underlying information model was coordinated with the PCOR-MII project.

The module supplements medical, diagnostic, and administrative information with the social and economic context of the affected person. It should not be understood as an isolated dataset, but as a context-providing supplement to the other modules of the core dataset.

Relationship to the Person Module

The module is closely linked to the KDS Person module. The Sociodemography data collection is assigned to a person and can be documented multiple times over time for the same person.

Certain person-related information is extended within the scope of the Person module. These include:

  • Postal code;
  • First language;
  • Country of birth;
  • Nationality.

Relationship to the Intensive Care Module

The module also has a connection to the KDS Intensive Care module. The characteristics height and body weight are already available there.

Sociodemographic data can be evaluated together with diagnoses, procedures, medication, laboratory values, vital signs, and other clinical information. In doing so, they do not primarily serve medical classification, but rather the contextualization and stratified analysis of this data.

For example, sociodemographic characteristics can be used to:

  • examine differences in the utilization of care;
  • compare treatment outcomes between social groups;
  • identify possible biases in study populations;
  • assess the transferability of results to the care population;
  • analyze relationships between life circumstances and care outcomes.

Their use as an analytical characteristic should not automatically be understood as a causal interpretation. Depending on the research question, sociodemographic characteristics can be confounders, effect modifiers, exposure characteristics, or purely descriptive criteria.

References

  • GESIS – Leibniz-Institut für Sozialwissenschaften. Demographische Standards 2024. Mannheim: GESIS; 2024.

  • International Organization for Standardization. ISO 3166-1: Codes for the representation of names of countries and subdivisions – Part 1: Country codes.

  • International Organization for Standardization. ISO 639: Codes for the representation of names of languages.

  • Does Healthcare Deliver?: Results from the Patient-Reported Indicator Surveys (PaRIS) OECD Publishing, Paris, OECD 2025, https://doi.org/10.1787/c8af05a5-en.

  • Soziodemografische und erwerbsbezogene Merkmale in der NAKO Gesundheitsstudie. Dragano, N., Reuter, M., Greiser, K.H. et al., Bundesgesundheitsbl 63, 267–278, 2020, https://doi.org/10.1007/s00103-020-03098-8

  • Bundesministerium für Arbeit und Soziales. Schwerbehindertenausweisverordnung, insbesondere § 2–3.