OSMR cheat sheet

OSMR (open-source medical record / open-source medical reporting) denotes software whose source code is publicly available for clinical documentation, reporting, and record management, with licenses permitting inspection, modification, and redistribution.

Core distinction: open-source refers to the licensing and code-availability model, not to the openness of patient data; an OSMR system can and normally must enforce access control and privacy on the data it stores.

Permissive licenses (MIT, BSD, Apache-2.0) allow reuse in closed products with attribution; copyleft licenses (GPL, AGPL) require derivative works to be distributed under compatible terms, and AGPL extends this to network-served use.

Typical OSMR components: data model/schema, reporting or form engine, terminology and coding support, audit logging, interoperability interfaces (HL7 v2, FHIR, DICOM), and role-based access control.

A reporting template in OSMR is a structured definition of fields, sections, and value constraints; structured reporting improves downstream querying and analytics compared with free-text narrative.

Governance terms: maintainer, contributor, fork, upstream, pull request, release cadence, and roadmap; project health is judged by commit activity, issue resolution, release frequency, and contributor diversity.

Regulatory framing: clinical software may be a regulated medical device depending on jurisdiction and intended use; open-source status does not exempt a product from regulatory obligations.

Versioning and reproducibility: pinned releases, tagged versions, and documented dependencies are required for validated deployments, because untracked upstream changes break validation evidence.

Layered architecture: presentation layer (forms, viewers), application/service layer (business rules, validation), persistence layer (relational or document store), and integration layer (interfaces, message queues).

Normalized relational schemas separate patient, encounter, observation, and report entities; identifiers should be stable, non-reused surrogate keys, never natural keys such as name or MRN alone.

HL7 v2 messaging uses pipe-delimited segments and trigger events (for example ADT for admissions, ORU for observation results); FHIR uses RESTful resources (Patient, Encounter, Observation, DiagnosticReport) with JSON or XML payloads.

DICOM governs imaging objects and metadata; an OSMR reporting system typically receives study references via DICOM worklist or query/retrieve and stores links rather than pixel data.

Terminology binding: use coded values from controlled vocabularies (SNOMED CT, LOINC, ICD) with explicit code systems; free-text-only fields cannot support reliable aggregation or decision support.

Validation must occur server-side, not only in the client form; client-side checks are usability aids, while server-side rules enforce integrity and auditability.

Idempotent interface design: message handlers should tolerate duplicate deliveries by keying on message control IDs, since retries and replays are normal in integration engines.

Separation of content and presentation: report templates and their rendered output should be independently versioned so historical reports remain reproducible after template changes.

Access control models: role-based access control assigns permissions to roles; attribute-based access control adds context such as care relationship, time, and location for finer decisions.

Minimum necessary and least privilege: users receive only the access required for their function, and break-glass emergency access must be logged and reviewed after use.

Audit trails should be append-only and capture who, what, when, where, and why (purpose of use); tamper-evident logging via hash chaining or write-once storage strengthens integrity claims.

Encryption: TLS for data in transit, strong encryption at rest for databases and backups, with key management separated from the application; hashing alone is not encryption.

Data de-identification removes the 18 HIPAA-style identifier categories (names, dates finer than year, geographic subdivisions, device identifiers, biometrics, and similar) or applies expert determination.

Authentication controls include multi-factor authentication, session timeouts, account lockout, and prohibition of shared accounts; every action must map to a unique identity.

Vulnerability management: dependency scanning, static analysis, coordinated disclosure policy, and a documented patch timeline are expected of maintained open-source clinical systems.

Backup and recovery: define recovery point and recovery time objectives, test restores, and encrypt backups; an untested backup is not evidence of recoverability.

Environment separation: development, test/staging, and production must be distinct, with production data not copied to lower environments unless de-identified.

Configuration as code: keep settings, template definitions, and interface mappings under version control so environments can be rebuilt and differences audited.

Change control: every production change is traceable to a request, a tested build, an approver, and a rollback plan; emergency changes are retroactively reviewed.

Release management distinguishes upstream project releases from the local validated build; upgrades require regression testing of interfaces, reports, and access rules.

Monitoring covers availability, error rates, interface queue depth, and audit-log health; alert thresholds should be defined before go-live, not after an incident.

Capacity planning accounts for report storage growth, imaging link volume, and audit-log retention; retention schedules must satisfy legal minimums and maximums.

Disaster recovery exercises validate failover, data restoration, and interface replay; document actual measured recovery times against objectives.

Decommissioning requires data migration or archival, credential revocation, interface shutdown, and retention of records per legal schedule.

Test levels: unit tests for logic, integration tests for interfaces, system tests for end-to-end workflows, and user acceptance testing by clinical staff before release.

Traceability matrix links each requirement to design, test cases, and results; it is the primary evidence artifact for validation audits.

Clinical risk management follows a hazard-to-control chain: identify hazards, estimate severity and likelihood, define mitigations, and verify mitigation effectiveness.

Test data strategy: synthetic or de-identified data only; production copies require formal approval and documented safeguards.

Regression suites must cover report rendering, coded-value mapping, access-control decisions, and interface message parsing after any upgrade.

Performance testing specifies concurrent users, report generation latency, and interface throughput; clinical workflows have explicit acceptable response times.

Defect management records severity, reproducibility, affected versions, and resolution; known-issue lists must be reviewed before go-live decisions.

Documentation for users and administrators (installation, configuration, backup, troubleshooting) is part of the deliverable, not an optional extra.

License compatibility: combining GPL code with proprietary modules generally forces GPL terms on the combined distribution; Apache-2.0 includes an express patent grant that MIT lacks.

Contribution mechanics: fork, branch, commit with clear messages, open a pull request, pass continuous integration, obtain review approval, then merge; signed commits or contributor agreements may be required.

Open-source sustainability depends on funded maintenance, not only code availability; abandoned projects become security liabilities because patches stop.

Total cost of ownership includes integration, customization, training, hosting, support contracts, and upgrade labor, not just license fees.

Vendor neutrality: prefer standards-based interfaces and documented data export so records remain portable if the deployment changes hands.

Community health signals: number of active maintainers, time to first response, ratio of closed to open issues, presence of a security policy, and release recency.

Attribution and notice obligations require preserving copyright notices and license texts in distributions, including bundled third-party components.

Procurement due diligence: verify license inventory (software bill of materials), security disclosure history, and roadmap alignment with clinical needs.

Analytics pipelines extract from operational stores into a reporting warehouse; extraction must preserve coded values and timestamps with explicit time zone handling.

Aggregate reporting requires consistent denominators: define the population, inclusion criteria, and observation window before computing rates.

Structured fields enable cohort queries; narrative text requires natural language processing, which introduces recall and precision tradeoffs that must be validated.

Dashboards should distinguish data refresh time from event time so users do not mistake stale figures for current state.

Secondary use of records for research generally requires ethics review and either consent or a formal waiver, plus de-identification or a limited data set.

Data quality checks include completeness, range validity, duplicate detection, and cross-field consistency; report them alongside analytical results.

Small-cell suppression prevents re-identification in aggregate outputs; suppress counts below a defined threshold and complementary cells where needed.

Export formats and schemas should be documented and versioned so downstream consumers can reproduce published analyses.