Radiology departments live and die by the order-to-report loop: a referral arrives, a study is scheduled against the right modality, the technologist runs the correct protocol, images and reports stay bound to the patient and exam, and a signed report reaches the referrer. Odoo out of the box has no concept of a radiology order, a modality worklist, an acquisition protocol, or a study file that must stay attached to one specific exam. Teams bolt this onto Calendar, Projects, or Documents and then discover that a generic scheduler cannot enforce protocol selection, a document folder cannot guarantee an image belongs to the right study, and a to-do board cannot represent the states a radiology exam actually passes through. A typical off-the-shelf apps.odoo.com module hands you a fixed data model you cannot bend to your referral sources, report layouts, or local compliance rules — and no one to change it when your workflow changes.

ECOSIRE builds a Radiology Information System as a proper Odoo module for your instance. At its core are new ORM models (models.Model) for the radiology order, the exam/study, the modality, the room, and the acquisition protocol, wired with real relational integrity — a study carries a Many2one to its order, patient, and referring physician, images are One2many study files, and a Selection state field drives each exam through requested → scheduled → in-progress → acquired → reported → verified. Compute fields with @api.depends derive turnaround time, report-due flags, and modality utilization so no one recalculates them by hand. Multi-format file storage is handled with binary/attachment fields (ir.attachment) so DICOM exports, JPEG/PNG key images, PDF reports, and structured measurements can all be stored, versioned, and retrieved against the exact study they belong to, with size and mimetype recorded.

The department sees the workflow through purpose-built views: a modality worklist (list + kanban) filtered by room and date, a study form with protocol picker and technologist assignment, and a calendar for scheduling. Radiologist reporting uses a structured findings/impression layout that renders to a branded QWeb PDF report, ready to sign and send. Automated actions (base.automation) handle the repetitive edges — flagging studies breaching turnaround SLA, notifying referrers when a report is verified, and prompting protocol assignment before a scan can start. Everything is permission-boundaried through ir.model.access.csv plus record rules so front-desk staff, technologists, radiologists, and referrers each see only what their role allows, and the whole model is reachable over the XML-RPC/JSON-RPC API for integration with PACS gateways, modality worklist brokers, or an external portal. We build against your edition — Community or Enterprise — and target Odoo 17.0, 18.0, or 19.0 to match your running version, noting where an Enterprise-only feature (such as advanced approvals or studio-style layouts) shapes the design.

Delivery is build-to-order: it starts with a scoping call where we map your referral sources, modalities, protocols, report templates, and roles, then confirm the exact data model and states before a line of code is written. You receive the installable module source, installation and configuration on your instance, UAT on a staging database with a rollback plan, technical documentation, a user guide and training session, and a post-go-live support window. Typical delivery is one working week from confirmed scope, depending on integration and report complexity. Pricing starts from $999 (indicative, single-company base scope); multi-company or multi-site operation, PACS/DICOM and modality-worklist integrations, localized report formats and regulatory fields, and migrating historical studies each increase the quoted scope.