The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.).

The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and within standardized analytics. Each Standard Concept belongs to one domain, which defines the location where the Concept would be expected to occur within data tables of the CDM.

Concepts can represent broad categories (like "Cardiovascular disease"), detailed clinical elements ("Myocardial infarction of the anterolateral wall") or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.).

Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom Concepts defined to cover various aspects of observational data analysis.

A Condition Era is defined as a span of time when the Person is assumed to have a given condition. Similar to Drug Eras, Condition Eras are chronological periods of Condition Occurrence. Combining individual Condition Occurrences into a single Condition Era serves two purposes:

• It allows aggregation of chronic conditions that require frequent ongoing care, instead of treating each Condition Occurrence as an independent event.
• It allows aggregation of multiple, closely timed doctor visits for the same Condition to avoid double-counting the Condition Occurrences. For example, consider a Person who visits her Primary Care Physician (PCP) and who is referred to a specialist. At a later time, the Person visits the specialist, who confirms the PCP's original diagnosis and provides the appropriate treatment to resolve the condition. These two independent doctor visits should be aggregated into one Condition Era.

This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient.

The COST table captures records containing the cost of any medical event recorded in one of the OMOP clinical event tables such as DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, VISIT_OCCURRENCE, VISIT_DETAIL, DEVICE_OCCURRENCE, OBSERVATION or MEASUREMENT.

Each record in the cost table account for the amount of money transacted for the clinical event. So, the COST table may be used to represent both receivables (charges) and payments (paid), each transaction type represented by its COST_CONCEPT_ID. The COST_TYPE_CONCEPT_ID field will use concepts in the Standardized Vocabularies to designate the source (provenance) of the cost data. A reference to the health plan information in the PAYER_PLAN_PERIOD table is stored in the record for information used for the adjudication system to determine the persons benefit for the clinical event.

The death domain contains the clinical event for how and when a Person dies. A person can have up to one record if the source system contains evidence about the Death, such as: Condition in an administrative claim, status of enrollment into a health plan, or explicit record in EHR data.

The Device domain captures information about a person's exposure to a foreign physical object or instrument which is used for diagnostic or therapeutic purposes through a mechanism beyond chemical action. Devices include implantable objects (e.g. pacemakers, stents, artificial joints), medical equipment and supplies (e.g. bandages, crutches, syringes), other instruments used in medical procedures (e.g. sutures, defibrillators) and material used in clinical care (e.g. adhesives, body material, dental material, surgical material).).

A Dose Era is defined as a span of time when the Person is assumed to be exposed to a constant dose of a specific active ingredient.

A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras.

This table captures records about the exposure to a Drug ingested or otherwise introduced into the body. A Drug is a biochemical substance formulated in such a way that when administered to a Person it will exert a certain biochemical effect on the metabolism. Drugs include prescription and over-the-counter medicines, vaccines, and large-molecule biologic therapies. Radiological devices ingested or applied locally do not count as Drugs.

Comprehensive logical model representing the Electronic Health Record (EHR) data structure for the EDSH (Entrepôt de Données de Santé Hospitalisé) core variables.

This model consolidates all healthcare dimensions into a unified structure supporting:

• Patient demographics and identity management
• Healthcare encounters and administrative data
• Clinical diagnostics and procedures
• Laboratory results and biological examinations
• Medication exposures and prescriptions
• Clinical care measurements and vital signs
• Lifestyle and behavioral factors

The model is optimized for healthcare data interoperability, research, and clinical analytics while maintaining alignment with FHIR standards and French healthcare requirements.

The EPISODE_EVENT table connects qualifying clinical events (such as CONDITION_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, MEASUREMENT) to the appropriate EPISODE entry. For example, linking the precise location of the metastasis (cancer modifier in MEASUREMENT) to the disease episode.

The EPISODE table aggregates lower-level clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) into a higher-level abstraction representing clinically and analytically relevant disease phases,outcomes and treatments. The EPISODE_EVENT table connects qualifying clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) to the appropriate EPISODE entry. For example cancers including their development over time, their treatment, and final resolution.

The FACT_RELATIONSHIP table contains records about the relationships between facts stored as records in any table of the CDM. Relationships can be defined between facts from the same domain, or different domains. Examples of Fact Relationships include: Person relationships (parent-child), care site relationships (hierarchical organizational structure of facilities within a health system), indication relationship (between drug exposures and associated conditions), usage relationships (of devices during the course of an associated procedure), or facts derived from one another (measurements derived from an associated specimen).

The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites.

The BundleLogical has the same objective as the FHIR Bundle resource but allows for the grouping of logical models.

The MEASUREMENT table contains records of Measurements, i.e. structured values (numerical or categorical) obtained through systematic and standardized examination or testing of a Person or Person's sample. The MEASUREMENT table contains both orders and results of such Measurements as laboratory tests, vital signs, quantitative findings from pathology reports, etc. Measurements are stored as attribute value pairs, with the attribute as the Measurement Concept and the value representing the result. The value can be a Concept (stored in VALUE_AS_CONCEPT), or a numerical value (VALUE_AS_NUMBER) with a Unit (UNIT_CONCEPT_ID). The Procedure for obtaining the sample is housed in the PROCEDURE_OCCURRENCE table, though it is unnecessary to create a PROCEDURE_OCCURRENCE record for each measurement if one does not exist in the source data. Measurements differ from Observations in that they require a standardized test or some other activity to generate a quantitative or qualitative result. If there is no result, it is assumed that the lab test was conducted but the result was not captured.

The NOTE_NLP table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note.

The NOTE table captures unstructured information that was recorded by a provider about a patient in free text (in ASCII, or preferably in UTF8 format) notes on a given date. The type of note_text is CLOB or varchar(MAX) depending on RDBMS.

The OBSERVATION table captures clinical facts about a Person obtained in the context of examination, questioning or a procedure. Any data that cannot be represented by any other domains, such as social and lifestyle facts, medical history, family history, etc. are recorded here.

This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absense of records indicate such Events did not occur during this span of time.

The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table.

This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.

This table contains records of activities or processes ordered by, or carried out by, a healthcare provider on the patient with a diagnostic or therapeutic purpose.

The PROVIDER table contains a list of uniquely identified healthcare providers. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc.

The specimen domain contains the records identifying biological samples from a person.

The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain.

This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.

ValueSet des Sexe administratif du DPI

ValueSet des modes d'entrée du DPI

ValueSet des modes de sortie du DPI

ValueSet des types de séjour du DPI

valeurs standards de person.gender_concept_id dans le CDM OMOP 5.4

Système de codage des sexes administratifs du patient

CodeSystem des types de séjour

CodeSystem des modes d'entrée

CodeSystem des modes de sortie

Type de séjour

Alignement de l''expression de besoin vers le modèle physique du DPI dans le cadre de l''usage Core

Alignement de l''usage Core du modèle physique du DPI vers les ressources FHIR

Cette ressource présente les spécifications de l''alignement entre la ressource Patient vers les tables correspodantes du CDM OMOP.

Cette ressource présente les spécifications de l''alignement entre les ressources FHIR vers les tables correspodantes du CDM OMOP.

Mapping FHIR Patient resource to OMOP Death

Mapping FHIR Patient resource to OMOP Person

Mapping Observation laboratory resources to Measurement OMOP Domain

Mapping Patient resource to Location OMOP Domain

Mapping simple Observation laboratory resources to Measurement OMOP Domain

Transforms EHR logical model data to FHIR Semantic Layer resources using Bundle as container

Standardisation du sexe administratif des patients pour se conformer aux exigences de FHIR

TODO

L'objectif de cet alignement est rendre possible la conversion d'un code 'gender' d'HL7 vers son équivalent dans OHDSI

Vue se rapprochant de la table OMOP condition_occurrence

Vue se rapprochant de la table OMOP death, pour la cause de décès

Vue se rapprochant de la table OMOP drug_exposure, pour les administrations

Vue se rapprochant de la table OMOP drug_exposure, pour les prescriptions

Vue se rapprochant de la table OMOP location

Vue se rapprochant de la table OMOP measurement, pour les pressions artérielles

Vue se rapprochant de la table OMOP measurement, pour les analyses biologiques sanas component

Vue se rapprochant de la table OMOP observation

Vue se rapprochant de la table OMOP person

Vue se rapprochant de la table OMOP procedure_occurrence

Représente la dose et le processus d'administration d'Azithromycine au patient 10

Vue se rapprochant de la table OMOP visit_detail

Vue se rapprochant de la table OMOP visit_occurrence