# README for CheckPatientType Dataset
**Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - CheckPatientType
**Author:** Ferreira, Marco.
**Date Created:** 2024
**Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - CheckPatientType [Data set].
**File Size:** 19 KB
---
### Purpose of the Dataset
The "CheckPatientType" dataset is part of a broader synthetic data project designed to simulate emergency healthcare service workflows.
This dataset specifically models patient flow through a queue system, capturing important timestamps, patient types, and queue dynamics before and after processing.
It is intended to support research and analysis on queue management, patient waiting times, and overall system efficiency in emergency healthcare contexts.
---
### Data Summary
This dataset includes detailed information about each patient's journey through a simulated queue, capturing attributes related to patient types, arrival and exit times, waiting times, and queue positions.
#### Key Variables
- **Patient ID**: Unique identifier for each patient in the dataset, represented as an integer.
- **Patient Type**: Category indicating the urgency or type of patient. Possible values are integers that represent different types of patients.
- **Queue Ticket Machine Arrival Time**: Timestamp indicating when a patient received their queue ticket upon arrival.
- **Exiting Time**: Timestamp indicating when a patient was assigned a patient type.
- **Waiting Time (min)**: Calculated waiting time in minutes between arrival and exit times.
- **Queue Count Before Processing**: Number of patients in the queue just before this patient’s data was recorded.
- **Queue Count After Processing**: Number of patients remaining in the queue immediately after processing the current patient.
- **Queue Difference**: Difference between queue counts before and after processing, indicating queue length changes as each patient is processed.
---
### Usage Notes
This dataset can be used for simulation, research, and development purposes, particularly in areas related to:
- Healthcare service efficiency studies
- Queue management and optimization
- Patient flow analysis
- Simulation of emergency service logistics
### Technical Requirements
This dataset is provided as a CSV file, compatible with standard data analysis software and programming languages, such as Python (Pandas), R, and Microsoft Excel.
### Access Rights and Licensing
- **Access Rights**: Open Access
The dataset is freely available to the public, with no restrictions on access.
- **License**: Creative Commons Attribution 4.0 International (CC BY 4.0)
Under this license, users are permitted to share, adapt, and build upon the dataset, provided appropriate attribution is given to the original author (Ferreira, M., 2024). For more details on the license, visit: [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/).
---
### FAIR Compliance and Metadata
This dataset has been developed to align with the FAIR principles (Findable, Accessible, Interoperable, and Reusable), facilitating ease of access, usage, and integration into various analytical workflows.
- **Findability**: The dataset is accompanied by this README file, providing clear metadata descriptions and variable explanations.
- **Accessibility**: It is openly available and accessible in standard CSV format.
- **Interoperability**: Designed to be used in common data analysis tools, with universally understood variables and values.
- **Reusability**: Licensed under CC BY 4.0, supporting reuse, adaptation, and redistribution with appropriate credit.
### Additional Information
This dataset forms part of a larger synthetic dataset project on emergency healthcare services.
For questions, comments, or requests for related datasets, please contact the author.
---
### File Structure and Additional Metadata
- **File Name**: `CheckPatientType.csv`
- **File Size**: 19 KB
- **Row Count**: 298
- **Columns**: 8 columns (as described in the Key Variables section above)
This dataset is part of a larger set of synthetic datasets generated for emergency healthcare simulations.
Each individual dataset within the collection has been designed to represent different components of the healthcare service workflow.
---