Dossier patient informatisé

An electronic health record (EHR) is the systematized collection of patient and population electronically stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information. For several decades, electronic health records (EHRs) have been touted as key to increasing of quality care. Electronic health records are used for other reasons than charting for patients; today, providers are using data from patient records to improve quality outcomes through their care management programs. EHR combines all patients demographics into a large pool, and uses this information to assist with the creation of "new treatments or innovation in healthcare delivery" which overall improves the goals in healthcare. Combining multiple types of clinical data from the system's health records has helped clinicians identify and stratify chronically ill patients. EHR can improve quality care by using the data and analytics to prevent hospitalizations among high-risk patients. EHR systems are designed to store data accurately and to capture the state of a patient across time. It eliminates the need to track down a patient's previous paper medical records and assists in ensuring data is up-to-date, accurate and legible. It also allows open communication between the patient and the provider, while providing "privacy and security." It can reduce risk of data replication as there is only one modifiable file, which means the file is more likely up to date and decreases risk of lost paperwork and is cost efficient. Due to the digital information being searchable and in a single file, EMRs (electronic medical records) are more effective when extracting medical data for the examination of possible trends and long term changes in a patient.

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

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