In the healthcare sector, medical records are an integral part of patient health and medical condition diagnosing and tracking. Primarily, the medical health records are generated on the basis of consultations given by health practitioners during patient visits. The medical records can be found in the form of hand-written notes, laboratory reports and evidence, referral letters, audio recordings of patient narration, clinical forms, insurance forms or disability data, and all other forms of reports. The last five years are to be noted in terms of Artificial Intelligence enabling digital transformation in patient care and treatment.
Medical documentation, an umbrella term used for maintaining patient healthcare data in the process of patient treatment, has served as the basis of AI application in the medical sector. AI applied in building better predictive models for patient diagnosis has also resulted in increased treatment efficiency and reduced burden on physicians. AI-based Clinical Decision Support or CDS can process vast chunks of medical documents and produce hypotheses for patient diagnosis. Usage of AI has also eased out internal processes for keeping stockpiles of patient records, making medicare hassle-free and seamless. Also, reducing dependency on medical document processing services, healthcare document processing for patient care.
Artificial Intelligence programs like CDS are based on machine learning models, trained with medical records labeling data that have successfully diagnosed conditions beforehand basis patient history. Due to this, along with improvement in clinical decision making, patient's overall experience plus expenditure have undergone a complete transformation. Today, patients are ready with their expenditures and are in a better position to manage their expenses. The time for examining a multitude of diagnosis to patient and treating their condition have reduced leading to an overall augmentation in the revenue of health institutions and other stakeholders involved. Originally Published at Click
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