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2025-01-17

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# README for MedicalRecord3 Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - MedicalRecord3 **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - MedicalRecord3 [Data set]. **File Size:** 2 KB --- ### Purpose of the Dataset The "MedicalRecord1" dataset is part of a larger synthetic data project designed to model various steps in emergency healthcare service processes. This dataset simulates patient flow through the "Medical Records 3" stage, capturing timestamps, resources used, queue metrics, and utilization rates to analyze operational efficiency in managing patient records. --- ### Data Summary This dataset provides detailed information on patient interactions within the "Medical Records 3" process, including data on waiting times, resource usage, and queue conditions before and after processing. #### Key Variables - **Patient ID**: Unique identifier for each patient, represented as an integer. - **Patient Type**: Integer value representing different patient urgency levels or categories. - **Medical Records 3 Arrival Time**: Timestamp indicating the patient’s arrival at the "Medical Records 3" stage. - **Exiting Time**: Timestamp marking when the patient completed the "Medical Records 3" process. - **Waiting Time (min)**: Calculated waiting time, in minutes, between arrival and exit times. - **Resource Used**: Identifier for the resource (e.g., Operator_3) handling the patient at this stage. - **Utilization %**: Utilization percentage of the resource used, representing how busy each resource is. - **Queue Count Before Processing**: Number of patients in the queue before this patient’s record processing began. - **Queue Count After Processing**: Number of patients remaining in the queue after processing. - **Queue Difference**: Difference between queue counts before and after processing, indicating the net queue change due to this patient's record handling. --- ### Usage Notes This dataset is useful for analysis, simulation, and research in areas related to: - Resource utilization in healthcare settings - Queue management and optimization - Patient wait time analysis in medical records handling - Simulation of healthcare workflows ### Technical Requirements This dataset is provided in CSV format and can be readily used with common data analysis software such as Python (Pandas), R, and Microsoft Excel. ### Access Rights and Licensing - **Access Rights**: Open Access This dataset is freely accessible to the public with no restrictions. - **License**: Creative Commons Attribution 4.0 International (CC BY 4.0) Users are allowed to share, adapt, and build upon the dataset, provided appropriate credit is given to the original author (Ferreira, M., 2024). For license details, see: [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/). --- ### FAIR Compliance and Metadata This dataset adheres to the FAIR principles (Findable, Accessible, Interoperable, and Reusable) for ease of access, usability, and integration with other data sources. - **Findability**: This README file includes metadata descriptions and definitions of all key variables. - **Accessibility**: Distributed in CSV format, compatible with most data analysis tools. - **Interoperability**: Uses standardized variable names and values to support integration across different tools. - **Reusability**: Licensed under CC BY 4.0, encouraging reuse and adaptation with proper attribution. ### Additional Information This dataset is part of a broader project that simulates different stages of patient processing in healthcare settings. For inquiries, comments, or additional datasets from this project, please contact the author. --- ### File Structure and Additional Metadata - **File Name**: `MedicalRecord3.csv` - **File Size**: 2 KB - **Row Count**: 11 - **Columns**: 10 columns (as described in the Key Variables section above) The "MedicalRecord3" dataset provides insights into resource allocation, queue dynamics, and patient flow within the medical records processing stage, contributing to the broader understanding of healthcare service efficiency. ---

2024-12-14