Healthcare
❯
Assisted Diagnosis & Prescription
❯Medical Assistants
❯AI solution for quality control of electronic medical records (EMR) in real time
Sudden infant death syndrome (SIDS)
For:
Healthcare industry, cloud-based AI providers, healthcare public policy makers,
parents of young children, insurance industry
Scope:
Use of facial recognition in healthcare.
Goal:
Other
Neural network formation of 3D-model orthopedic insoles
For:
Medicine, public sector
Scope:
Artificial intelligence methods are used to construct individual medical products
to reduce the risk of developing diseases of the musculoskeletal system.
Goal:
Improved Customer Experience
AI solution for quality control of electronic medical records (EMR) in real time
For:
Doctor, hospital, patient
Scope:
Detecting defects in EMRs by inspecting unstructured data based on natural language processing (NLP) ability.
Goal:
Improved Product Development / R&D
AI solution for quality control of electronic medical records (EMR) in real time
For:
Doctor, hospital, patientGoal:
Improved Product Development / R&DProblem addressed
To ensure the completeness, consistency, punctuality and medical compliance of
EMRs written by physicians.
Scope of use case
Detecting defects in EMRs by inspecting unstructured data based on natural language processing (NLP) ability.
Description
Medical records are the records of the occurrence,
development and prognosis of patients' diseases, as well as
the records of medical activities such as examinations,
diagnoses and treatments.
A high-quality medical record has great value at the medical
and legal levels.
When medical records are converted from handwritten
documents to electronic input, delayed or incomplete
written records and copying are endangering the quality of
medical records.
If the medical record data does not meet the requirements, it
greatly affects the health of patients, the development of
medicine and the judgment of responsibility in medical
accidents.
Nowadays, hospitals have a medical records department to
control the quality of medical records manually. However, as
the number of medical records increases, the inspection
requirements become more complex, and the medical
professional knowledge requirements are upgraded, so the
medical records quality inspection becomes harder.
The intelligent electronic medical record quality control
system is based on NLP. When a doctor writes medical
records, the system can analyse unstructured medical record
text, control the quality based on government requirements,
and ensure the integrity, consistency, timeliness and
compliance of medical records.
The ET (Evolutionary technology) Medical Brain medical
service support system has learning ability to build up
medical knowledge including clinical pathways, drug
compatibility taboos, etc. It can learn the habits and rules of
a doctors manual review to inspect records thoroughly.
The current system covers 189 medical record quality
inspection requirements. It has cut the review time required
by medical record departments by 60 %, which greatly
saved hospital costs, and has reduced the inspection time
and repetitive workload, and it will help doctors put more
energy into education and training.