System and method for generating a medical history

Abstract

A system and method for generating a medical history that is determined based on the patient's medication list. Medications are taken for specific indications, i.e., disease and / or symptom, and the system includes a knowledge base of all known medications and associated indications. Preferably, an expert system allows the patient, nurse or other user, to enter all or part of the name of the patient's medications, and creates a list of probable medications by determining which of the known medications the patient most likely takes. Based on a user selected probable medication, the system creates a list of probable indications associated with the selected medication. Based on a user selected probable indication, the system generates a medical history for the patient. The probable medications and probable indications are determined preferably based on the patient's demographic data, historical data for other patients, and responses to follow-up questions generated by the system.

Description

technical field [0001] The present invention relates to medical history and, in particular, to generating a medical history. Background technique [0002] A detailed medical history is the cornerstone of accurate patient assessment and medical diagnosis. Traditional medical histories taken by clinicians are often incomplete and time consuming because of the need not only to collect information but also to document it accurately. Clinicians are generally highly paid talents. There is therefore a need for a system that can take an accurate and complete medical history without the direct involvement of highly paid medical personnel. [0003] Computerized systems are available for patients to self-enter medical data in response to inquiries. Typically, these systems use a predetermined set of questions to be answered by the patient or another user on behalf of the patient. These computerized systems are considered superior to traditional history taking techniques because gen...

AI Technical Summary

Problems solved by technology

While known systems do use branching logic to hone in on specific patient complaints and clarify symptoms, these systems fail to identify which questions are the most important to ask patients up front

Therefore, these known systems require the patient to answer too many irrelevant questions

In addition, these known systems can introduce inadvertent patient errors during standard computerized interviews, as patients misinterpret questions, forget, and / or become tired and careless

Studies such as those described by Carr have found that these shortcomings contribute to a patient-induced error rate of 3%-7% for computerized interviews

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