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Nexus: A Deterministic Linkage Framework for Constructing Longitudinal Real-World Data in Brazil's Public Health
Julio Cesar Barbour Oliveira1, Tulio Tadeu Rocha Sarmento1, Daniela Mayumi Usuda Prado Rocha1
1Precision Data, São Paulo, Brazil.
Pharmacoepidemiology and Drug Safety
|May 17, 2026
Summary
A new framework, Nexus, enables longitudinal analysis of Brazilian health data by linking records without a unique person identifier. This method creates a valuable cohort for studying treatment pathways, though it results in a selected subpopulation.
Area of Science:
- Health Informatics
- Data Science
- Public Health
Background:
- Brazil's Unified Health System (SUS) lacks a person identifier in public inpatient microdata (SIH), hindering longitudinal studies.
- Existing data constraints limit the construction of comprehensive real-world datasets for health research.
Purpose of the Study:
- To propose and validate Nexus, a deterministic linkage framework for creating longitudinal real-world datasets from Brazilian administrative health data.
- To overcome structural limitations in public health microdata for enabling patient-level longitudinal analysis.
Main Methods:
- A cloud-based Lakehouse architecture was used to process and harmonize Ministry of Health administrative data (2008-2024).
- Encrypted National Health Cards (CNS) from SIA records were curated using internal consistency filters (sex, DOB, CEP).
- A quasi-identifier linkage (CEP, DOB, sex) with α-shrinkage was applied to SIH data, prioritizing unique matches for cohort construction.
Main Results:
- Data curation yielded 12.9 million patients from 224.7 million unique CNS records.
- The Nexus framework successfully constructed a longitudinal cohort of 9.2 million patients through exact-match linkage of SIH hospitalizations.
- Using α=40 and a 2012 start year optimized temporal consistency and disease event fraction stability.
Conclusions:
- Nexus provides a transparent, deterministic linkage method to build longitudinal cohorts despite data constraints.
- The framework generates a selected subpopulation enriched for specialized care due to data concentration in high-complexity claims.
- Nexus is suitable for analyzing treatment pathways and outcomes but not for population-level inference or incidence estimation.
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