A Design History File (DHF) is a compilation of records that describes the complete design history of a finished medical device, demonstrating that development followed the approved design plan and 21 CFR Part 820.30 design controls. It serves as the definitive evidentiary record that design outputs meet design inputs, encompassing everything from initial user needs to final design transfer.
Glossary
Design History File (DHF)

What is a Design History File (DHF)?
A Design History File (DHF) is the formal compilation of records that proves a medical device was developed in accordance with an approved design plan and regulatory requirements.
The DHF contains or references all design review minutes, verification and validation protocols, risk management files per ISO 14971, and approved design changes. For Software as a Medical Device (SaMD), the DHF integrates software development lifecycle documentation aligned with IEC 62304, providing auditors with a traceable narrative of how safety and performance requirements were methodically translated into the released product.
Core Components of a DHF
A Design History File (DHF) is not a single document but a compilation of records proving a medical device was developed according to its approved design plan and regulatory standards. These are the essential artifacts auditors expect to find.
Design and Development Plan
The master schedule and organizational blueprint that defines who does what and when. This document outlines all design activities, assigns responsibilities, identifies interfaces between groups, and is continuously updated throughout development. It must align with ISO 13485 and 21 CFR Part 820.30(b).
Design Inputs
The physical and performance requirements that form the basis of the device. These must be unambiguous, verifiable, and complete. For SaMD, inputs include:
- Intended Use Statement and clinical claims
- Functional, performance, and safety requirements
- Cybersecurity and interoperability specifications
- Applicable regulatory standards (e.g., IEC 62304)
Design Outputs
The tangible results of the design effort that deliver against the design inputs. Outputs include software architecture diagrams, source code, compiled binaries, user manuals, and the Software Bill of Materials (SBOM). Each output must reference the specific design input it satisfies, creating a traceable, auditable link.
Design Review Records
Formal, documented assessments conducted at major milestones to evaluate the design's maturity. Records must identify the reviewers, date, issues found, and resolution actions. Reviews confirm that the design can proceed to the next phase and that Verification and Validation (V&V) plans are adequate.
Design Verification Records
Objective evidence confirming that design outputs meet design inputs (i.e., 'did we build the thing right?'). For software, this includes unit test results, integration test logs, static code analysis reports, and traceability matrices. Verification is a continuous, iterative process, not a final gate.
Design Validation Records
Objective evidence confirming that the final device meets user needs in the intended clinical environment (i.e., 'did we build the right thing?'). For diagnostic SaMD, this includes clinical validation study data, Human Factors Engineering (HFE) usability test reports, and evidence of diagnostic accuracy (sensitivity/specificity).
Design Transfer Records
Documentation proving the design was correctly translated into a production specification for manufacturing or, for SaMD, a reproducible release process. This includes build scripts, deployment configurations, and installation qualification records ensuring the software can be consistently distributed to end-users without corruption.
Design Change Records
A chronological log of all post-approval modifications, maintained under Corrective and Preventive Action (CAPA) procedures. Each record must describe the change rationale, risk assessment, verification/validation activities performed, and regulatory impact analysis—especially critical for determining if an Adaptive Algorithm update requires a new 510(k).
Frequently Asked Questions
Essential questions about the Design History File (DHF), its contents, and its role in FDA clearance pathways for Software as a Medical Device (SaMD).
A Design History File (DHF) is a compilation of records that describes the complete design history of a finished medical device, demonstrating that it was developed in accordance with the approved design plan and 21 CFR Part 820.30. The DHF works as a chronological narrative of the design and development process, containing or referencing all records necessary to prove that the design was conducted according to established procedures. For Software as a Medical Device (SaMD), the DHF captures the evolution of software architecture, algorithm selection, and iterative testing cycles. It serves as the primary evidence during an FDA inspection or audit that the manufacturer followed a controlled, documented design process. The file is not a single document but a structured index linking to design inputs, design outputs, verification and validation protocols, design reviews, and risk management files. Critically, the DHF must be maintained for the lifetime of the device and be readily accessible for regulatory review.
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Related Terms
The Design History File (DHF) is the central narrative of medical device development. These related terms define the critical inputs, processes, and standards that populate the DHF and demonstrate compliance to regulatory bodies.
Verification and Validation (V&V)
The core evidentiary activities documented within the DHF. Verification confirms that design outputs meet specified design inputs (did we build the software right?), while Validation confirms that the final device meets user needs and intended uses (did we build the right software?). For SaMD, validation often includes rigorous clinical performance studies.
IEC 62304 Compliance
The international standard governing the software development lifecycle for medical device software. The DHF must contain evidence that software planning, requirements analysis, architectural design, detailed design, unit implementation, integration testing, and maintenance processes strictly followed this standard's risk-based classification system (Class A, B, or C).
Quality Management System (QMS)
The overarching organizational structure, such as ISO 13485, that mandates the creation of a DHF. The QMS defines the procedures for document control, design reviews, and change management. The DHF is a living collection of records generated by executing the QMS's design controls, proving a systematic, traceable development process.
Design Inputs and Outputs
The fundamental traceability pair within the DHF. Design Inputs are the physical and performance requirements of the device, including the Intended Use Statement and risk controls from ISO 14971. Design Outputs are the results of the design effort, such as the software architecture, source code, and test protocols. The DHF must prove each output maps back to a specific input.
Risk Management File (ISO 14971)
A distinct but cross-referenced file that feeds directly into the DHF. It contains the Hazard Analysis, Failure Mode and Effects Analysis (FMEA) , and risk control measures. The DHF must demonstrate that identified risks were mitigated through specific design choices and that residual risk is acceptable, creating a direct link between safety and software architecture.
Design Review Records
Formal, documented assessments conducted at key milestones. The DHF must include meeting minutes, attendee lists, and sign-off records proving that independent, qualified reviewers systematically evaluated the design for correctness, completeness, and compliance before advancing to the next development phase. These records are critical evidence of management oversight.

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Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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