# Balancing clinical relevance, legal boundaries, and technological solutions: a case-based analysis of secondary use of electronic health records in Sweden

## TL;DR

This paper examines how electronic health records can be used for cancer care improvements in Sweden, balancing legal and privacy concerns with technological solutions like federated learning.

## Contribution

The paper introduces a case-based analysis of federated learning as a privacy-preserving solution for secondary use of EHR data in Sweden's regional healthcare system.

## Key findings

- Federated learning can help overcome legal barriers to using regional EHR data for cancer care insights.
- Sharing personal data for quality assurance is a major bottleneck due to legal constraints.
- Data sharing for research is more feasible when participants provide consent.

## Abstract

The secondary use of electronic health records (EHRs) poses legal challenges, particularly when the responsibility for managing EHRs lies with local or regional authorities. This article presents a case-based analysis of the secondary use of EHR data in contexts where data privacy responsibilities are managed regionally in Sweden.

Using two distinct purposes for the secondary use of the digital tool Patient Overview Breast Cancer: (i) assessing the uptake of new treatment strategies in a real-world setting for quality assurance, and (ii) evaluating the effectiveness of these strategies in specific patient subgroups with limited evidence for research purposes, the study explored the distinctions between research and quality assurance, the legal implications of each framework, and the potential role of federated learning as a privacy-preserving technological solution.

Federated learning offers a promising approach to overcome legal and organizational barriers to secondary use of regional EHRs in Sweden, enabling scalable, clinically meaningful insights for cancer care. However, its effective implementation requires a unified national framework that balances personal integrity with patient safety, supported by regulatory sandboxes.

•Federated learning was assessed for scaling Swedish regional EHR data use.•The main bottleneck for quality assurance was sharing personal data.•In research, data sharing was less problematic when participants gave consent.

Federated learning was assessed for scaling Swedish regional EHR data use.

The main bottleneck for quality assurance was sharing personal data.

In research, data sharing was less problematic when participants gave consent.