0.4.6 - ci-build

StandardPatientHealthRecordIG, published by MITRE. This guide is not an authorized publication; it is the continuous build for version 0.4.6 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/personal-health-record-format-ig/ and changes regularly. See the Directory of published versions

Algorithms

Normalize Patient Identifiers

The algorithm for normalizing patient identifiers is developed to ensure consistency in patient data across different healthcare systems. This process simplifies the management of a health records, aiming to enhance the accuracy and accessibility of these records.

Longitudinal Chronology

An algorithm has been developed to organize patient records in chronological order. Its main function is to sort various entries, like doctor’s notes and test results, by their dates. This makes it easier to view a patient’s medical history over time. By putting the records in order, the algorithm helps doctors and healthcare providers track changes and patterns in a patient’s health, supporting more informed medical decisions and analysis. This straightforward approach aims to improve patient care by providing a clearer picture of each patient’s medical journey.

Reminders

A simple algorithm has been created to send out reminders based on a schedule. It uses a clock to keep track of time and automatically triggers alerts for tasks or events at predetermined times. This tool is designed to be straightforward and user-friendly, helping individuals stay organized and on top of their schedules without the need for manual reminders. By providing timely notifications, it assists in managing daily routines and appointments efficiently.

Summarize Document

An algorithm has been developed to summarize patient records by converting them into a clinical text normal form. After this standardization, it then uses large language models to create a narrative text. This process simplifies complex medical data into a more readable format, making it easier for healthcare professionals to quickly understand a patient’s history. The algorithm aims to enhance the efficiency of reviewing patient records by providing clear, concise summaries.

SCUBA Smart Agents

An algorithm has been designed, inspired by SCUBA diving technology, to act as a software agent that counts down a resource. This tool mimics the way a SCUBA diver’s equipment monitors air supply, but it applies this concept to other resources that need tracking. The algorithm provides a countdown, alerting users as the resource depletes over time. This functionality is particularly useful in scenarios where managing the usage of a limited resource is critical, ensuring users are aware of the remaining quantity and can plan accordingly.

Gaps in Care Reporting

An algorithm has been developed to generate reports on gaps in healthcare, specifically focusing on routine procedures like annual physicals or breast/prostate cancer screenings for middle-aged individuals. This tool scans patient records to identify when these important health checks are due or overdue. By highlighting these gaps, the algorithm assists healthcare providers in ensuring that patients receive timely and necessary medical attention. This approach aims to promote preventive healthcare and early detection, contributing to better health outcomes.