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Escola de Engenharia (Universidade do Minho)
Synthetic Dataset of Emergency Healthcare Services
Version 1.0
Ferreira, Marco; Antóno Vieira, 2025, "Synthetic Dataset of Emergency Healthcare Services", https://doi.org/10.34622/datarepositorium/AKSZQG, Repositório de Dados da Universidade do Minho, V1
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Description

Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

File Overview
  • CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.
  • CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).
  • Fill_Information.csv - (2 KB): Fill information records for new patients.
  • MedicalRecord1.csv - (10 KB): Medical record dataset for patient type 1.
  • MedicalRecord2.csv - (4 KB): Medical record dataset for patient type 2.
  • MedicalRecord3.csv - (2 KB): Medical record dataset for patient type 3.
  • MedicalRecord4.csv - (13 KB): Medical record dataset for patient type 4.
  • OutPatientDepartment.csv - (18 KB): Data related to the satisfaction and length of stay of an given patient.
  • Triage.csv - (13 KB): Data related to the triage process.
  • README.txt - (4 KB): Documentation of the dataset, including structure, metadata, and usage.
Common Fields Across Files
  • Patient ID (Integer): Unique identifier for each patient.
  • Patient Type (Integer): Classification of patient (e.g., 1, 4).
  • Medical Records Arrival Time (DateTime): Timestamp of the patient's first arrival in the medical record department.
  • Exiting Time (DateTime): Timestamp when the patient exits a Server.
  • Waiting Time (min) (Real): Total waiting time before being attended to.
  • Resource Used (String): Resource (e.g., Operator) allocated to the patient.
  • Utilization % (Real): Utilization rate of the resource as a percentage.
  • Queue Count Before Processing (Integer): Number of patients in the queue before processing begins.
  • Queue Count After Processing (Integer): Number of patients in the queue after processing ends.
  • Queue Difference (Integer): Difference between the before and after queue counts.
  • Length of Stay (min) (Real): Total time spent in the simulation by the patient.
  • LOS without Queues (min) (Real): Length of stay excluding any queuing time.
  • Satisfaction % (Real): Patient satisfaction rating based on their experience.
  • New Patient? (String): Indicates if this is a new patient or a returning one.
    •
Subject Computer and Information Science; Engineering; Medicine, Health and Life Sciences; Other
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00_readme.txt
Plain Text - 4.0 KB - Jan 17, 2025 - 2 Downloads
MD5: d06e08f62b344abb7d35d6f215087522
General Information about the dataset.
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CheckBloodPressure.csv
Comma Separated Values - 8.8 KB - Jan 17, 2025 - 3 Downloads
MD5: 4182ab61abcbb471d0348e4db00f707d
# README for CheckBloodPressure Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - CheckBloodPressure **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - CheckBloodPressure [Data set]. **File Size:** 9 KB --- ### Purpose of the Dataset The "CheckBloodPressure" dataset is part of a broader synthetic data project designed to simulate workflows within emergency healthcare services. This specific dataset models the flow of patients undergoing blood pressure checks, capturing timestamps, patient types, and queue dynamics before and after processing. It supports research and analysis focused on queue management, patient waiting times, and overall efficiency in healthcare services related to blood pressure checks. --- ### Data Summary This dataset includes detailed information about each patient’s journey through a simulated queue for blood pressure checks, covering 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 patient categories. - **Check Blood Pressure Arrival Time**: Timestamp indicating when a patient arrived for a blood pressure check. - **Exiting Time**: Timestamp indicating when a patient completed the blood pressure check. - **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, showing changes in queue length as each patient is processed. --- ### Usage Notes This dataset can be used for simulation, research, and development purposes, especially in areas related to: - Healthcare service efficiency studies - Queue management and optimization - Patient flow analysis in emergency settings - Simulation of healthcare service logistics ### Technical Requirements This dataset is provided in CSV format, which is 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 This dataset is freely accessible to the public without any 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 in alignment with the FAIR principles (Findable, Accessible, Interoperable, and Reusable), ensuring ease of access, usability, and integration into various analytical workflows. - **Findability**: The dataset is accompanied by this README file, providing clear metadata descriptions and variable explanations. - **Accessibility**: The dataset is openly available and accessible in standard CSV format. - **Interoperability**: Compatible with common data analysis tools, with universally understood variables and values. - **Reusability**: Licensed under CC BY 4.0, allowing for 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**: `CheckBloodPressure.csv` - **File Size**: 9 KB - **Row Count**: 113 - **Columns**: 8 columns (as described in the Key Variables section above) This dataset is part of a collection of synthetic datasets created to simulate various aspects of emergency healthcare workflows. Each dataset within the collection represents distinct components of the healthcare service process, aiding comprehensive analysis in healthcare service simulations. ---
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CheckPatientType.csv
Comma Separated Values - 18.8 KB - Jan 17, 2025 - 3 Downloads
MD5: a29effbfdd439b10584479c78fb8b29b
# 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. ---
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Fill_Information.csv
Comma Separated Values - 1.2 KB - Jan 17, 2025 - 1 Download
MD5: 6012e6328e39710285e26878d9194a1b
# README for Fill_Information Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - Fill_Information **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - Fill_Information [Data set]. **File Size:** 2 KB --- ### Purpose of the Dataset The "Fill_Information" dataset is part of a comprehensive synthetic data project developed to simulate various processes within emergency healthcare services. This particular dataset models patient flow through the "Fill Information" stage, capturing key timestamps and queue metrics to analyze waiting times and queue dynamics. --- ### Data Summary This dataset records patient movement through the "Fill Information" process, with data on arrival and exit times, waiting duration, and queue metrics before and after processing. Only new patients to the hospital are required to Fill Informations. #### Key Variables - **Patient ID**: Unique identifier for each patient, represented as an integer. - **Patient Type**: Classification of patient urgency or type, with integers representing various patient types. - **Fill Information Arrival Time**: Timestamp marking the patient’s arrival time for filling out information. - **Fill Information Exiting Time**: Timestamp marking the time the patient completed the "Fill Information" stage. - **Waiting Time (min)**: The calculated waiting time, in minutes, between arrival and exit times. - **Queue Count Before Processing**: Number of patients in the queue before this patient’s information was processed. - **Queue Count After Processing**: Number of patients in the queue immediately following the processing of this patient. - **Queue Difference**: Difference in queue counts before and after processing, indicating the net change in queue length. --- ### Usage Notes This dataset is useful for simulation, research, and performance analysis purposes, particularly in studies related to: - Patient wait time management in healthcare settings - Queue length analysis and optimization - Workflow efficiency in information processing stages ### Technical Requirements This dataset is provided in CSV format, compatible with common data analysis tools such as Python (Pandas), R, and spreadsheet software like Microsoft Excel. ### Access Rights and Licensing - **Access Rights**: Open Access This dataset is openly available to the public with no access restrictions. - **License**: Creative Commons Attribution 4.0 International (CC BY 4.0) Under this license, users can share, adapt, and build upon the dataset, provided appropriate credit is given to the original author (Ferreira, M., 2024). For more details, visit: [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/). --- ### FAIR Compliance and Metadata This dataset has been created in accordance with the FAIR principles (Findable, Accessible, Interoperable, and Reusable) to ensure ease of access, usability, and integration with other data. - **Findability**: This README file includes clear metadata descriptions and definitions of all variables. - **Accessibility**: Available in a standard CSV format for easy access and compatibility with data analysis tools. - **Interoperability**: Contains universally understood variable names and values, suitable for use with common analytical software. - **Reusability**: Licensed under CC BY 4.0, allowing for reuse, adaptation, and redistribution with appropriate attribution. ### Additional Information This dataset is part of a larger synthetic data project that models emergency healthcare workflows. For questions, comments, or additional datasets in this project, please contact the author. --- ### File Structure and Additional Metadata - **File Name**: `Fill_Information.csv` - **File Size**: 2 KB - **Row Count**: 15 - **Columns**: 8 columns (as described in the Key Variables section above) This dataset is a component of a broader collection designed to simulate various stages of patient processing in healthcare environments. The "Fill Information" dataset specifically offers insights into waiting times and queue behaviors during the information-filling stage. ---
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MedicalRecord1.csv
Comma Separated Values - 9.1 KB - Jan 17, 2025 - 1 Download
MD5: 07a9552da1d97f0309840889c173e735
# README for MedicalRecord1 Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - MedicalRecord1 **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - MedicalRecord1 [Data set]. **File Size:** 10 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 1" 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 1" 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 1 Arrival Time**: Timestamp indicating the patient’s arrival at the "Medical Records 1" stage. - **Exiting Time**: Timestamp marking when the patient completed the "Medical Records 1" process. - **Waiting Time (min)**: Calculated waiting time, in minutes, between arrival and exit times. - **Resource Used**: Identifier for the resource (e.g., Operator_1) 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**: `MedicalRecord1.csv` - **File Size**: 10 KB - **Row Count**: 85 - **Columns**: 10 columns (as described in the Key Variables section above) The "MedicalRecord1" 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. ---
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MedicalRecord2.csv
Comma Separated Values - 3.2 KB - Jan 17, 2025 - 1 Download
MD5: 4bd16a345b2038224d9127fb1cd78063
# README for MedicalRecord2 Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - MedicalRecord2 **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - MedicalRecord2 [Data set]. **File Size:** 4 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 2" 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 2" 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 2 Arrival Time**: Timestamp indicating the patient’s arrival at the "Medical Records 2" stage. - **Exiting Time**: Timestamp marking when the patient completed the "Medical Records 2" process. - **Waiting Time (min)**: Calculated waiting time, in minutes, between arrival and exit times. - **Resource Used**: Identifier for the resource (e.g., Operator_2) 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**: `MedicalRecord2.csv` - **File Size**: 4 KB - **Row Count**: 29 - **Columns**: 10 columns (as described in the Key Variables section above) The "MedicalRecord2" 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. ---
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MedicalRecord3.csv
Comma Separated Values - 1.2 KB - Jan 17, 2025 - 1 Download
MD5: fa3f731128441f65d6c9f187d3239538
# 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. ---
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MedicalRecord4.csv
Comma Separated Values - 12.2 KB - Jan 17, 2025 - 1 Download
MD5: e0c33e9984a3ded68e0b9223c831b809
# README for MedicalRecord4 Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - MedicalRecord4 **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - MedicalRecord4 [Data set]. **File Size:** 13 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 4" 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 4" 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 4 Arrival Time**: Timestamp indicating the patient’s arrival at the "Medical Records 4" stage. - **Exiting Time**: Timestamp marking when the patient completed the "Medical Records 4" process. - **Waiting Time (min)**: Calculated waiting time, in minutes, between arrival and exit times. - **Resource Used**: Identifier for the resource (e.g., Operator_4) 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**: `MedicalRecord4.csv` - **File Size**: 13 KB - **Row Count**: 118 - **Columns**: 10 columns (as described in the Key Variables section above) The "MedicalRecord4" 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. ---
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OutPatientDepartment.csv
Comma Separated Values - 17.6 KB - Jan 17, 2025 - 1 Download
MD5: 46d0ca9e018abd7c41fca365cd4805b8
# README for OutPatientDepartment Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - OutPatientDepartment **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - OutPatientDepartment [Data set]. **File Size:** 18 KB --- ### Purpose of the Dataset The "OutPatientDepartment" dataset is part of a synthetic data project aimed at simulating workflows within emergency healthcare services. This specific dataset models patient flow and experience in the outpatient department, capturing details on length of stay, satisfaction levels, and whether patients are new or returning. It is intended to facilitate research and analysis on patient experience, resource allocation, and service efficiency in outpatient settings. --- ### Data Summary This dataset includes detailed information on each patient's visit to a simulated outpatient department, focusing on variables that impact patient satisfaction, length of stay, and departmental efficiency. #### 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 representing different patient types. - **Exiting Time**: Timestamp indicating when a patient exited the simulation. - **Length of Stay (min)**: Total time, in minutes, the patient spent in the simulation. - **LOS without Queues (min)**: Calculated time spent in simulation without waiting in queues, in minutes. - **Satisfaction %**: Satisfaction level of the patient, represented as a percentage. - **New Patient?**: Indicates whether the patient is a new or returning patient ("Yes" or "No"). --- ### Usage Notes This dataset can be utilized for simulation, research, and analysis purposes, particularly in studies related to: - Patient satisfaction analysis in outpatient settings - Service time optimization - Resource management and patient flow studies - Evaluation of waiting times and their impact on patient experience ### Technical Requirements This dataset is provided in CSV format, compatible with widely used data analysis software and programming languages, including Python (Pandas), R, and Microsoft Excel. ### Access Rights and Licensing - **Access Rights**: Open Access The dataset is freely available for public access without restrictions. - **License**: Creative Commons Attribution 4.0 International (CC BY 4.0) Users are allowed to share, adapt, and build upon this dataset, provided proper attribution is given to the original author (Ferreira, M., 2024). For more information on the license, please visit: [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/). --- ### FAIR Compliance and Metadata This dataset aligns with the FAIR principles (Findable, Accessible, Interoperable, and Reusable), ensuring ease of access, use, and integration in different analytical contexts. - **Findability**: This README file provides detailed metadata descriptions and explanations of the dataset variables. - **Accessibility**: Available openly in standard CSV format for easy access and analysis. - **Interoperability**: Designed to work with common data analysis tools, with straightforward variable names and values. - **Reusability**: Licensed under CC BY 4.0, supporting reuse, adaptation, and redistribution with appropriate credit. ### Additional Information This dataset is part of a larger synthetic dataset project focused on emergency healthcare services. For further inquiries, comments, or requests for related datasets, please reach out to the author. --- ### File Structure and Additional Metadata - **File Name**: `OutPatientDepartment.csv` - **File Size**: 18 KB - **Row Count**: 237 - **Columns**: 7 columns (as described in the Key Variables section above) This dataset is a component of a broader synthetic dataset project, with each individual dataset in the collection representing different aspects of healthcare service workflows. The OutPatientDepartment dataset specifically provides insights into patient satisfaction, wait times, and length of stay in outpatient settings. ---
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Triage.csv
Comma Separated Values - 12.2 KB - Jan 17, 2025 - 2 Downloads
MD5: 345cbcf21676e6e74b6c212a7c3b7cdc
# README for Triage Dataset **Dataset Title:** Synthetic Dataset of Emergency Healthcare Services - Triage **Author:** Ferreira, Marco **Date Created:** 2024 **Citation:** Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services - Triage [Data set]. **File Size:** 13 KB --- ### Purpose of the Dataset The "Triage" dataset is part of a comprehensive synthetic data project created to simulate emergency healthcare service workflows. This dataset specifically models patient triage processes, capturing information on arrival and exit times, waiting times, resources used, and utilization percentages. It is designed to support research and analysis on resource utilization, patient waiting times, and queue management within emergency triage settings. --- ### Data Summary This dataset includes detailed information about each patient’s experience in a simulated triage process, covering attributes related to patient types, timestamps for arrival and exit, waiting times, and resource allocation. #### 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 representing different patient categories. - **Triage Arrival Time**: Timestamp indicating when a patient arrived at the triage station. - **Triage Exiting Time**: Timestamp indicating when a patient completed the triage process. - **Waiting Time Triage (min)**: Calculated waiting time in minutes from arrival to exit. - **Resource Used**: Type of resource used for triage (e.g., "Nurses_Type1"). - **Utilization %**: Percentage of resource utilization during triage. - **Queue Count Before Processing**: Number of patients in the triage 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**: Change in queue length as each patient is processed. --- ### Usage Notes This dataset can be used for simulation, research, and analysis purposes, especially in areas related to: - Emergency healthcare service efficiency studies - Resource utilization and optimization in triage - Patient flow and queue management - Analysis of healthcare service logistics ### Technical Requirements This dataset is provided in CSV format, compatible with common data analysis software and programming languages, such as Python (Pandas), R, and Microsoft Excel. ### Access Rights and Licensing - **Access Rights**: Open Access This dataset is freely accessible to the public without any 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), ensuring ease of access, usability, and integration into various analytical workflows. - **Findability**: The dataset is accompanied by this README file, providing clear metadata descriptions and variable explanations. - **Accessibility**: The dataset is openly available and accessible in standard CSV format. - **Interoperability**: Compatible with common data analysis tools, with universally understood variables and values. - **Reusability**: Licensed under CC BY 4.0, allowing for 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**: `Triage.csv` - **File Size**: 13 KB - **Row Count**: 294 - **Columns**: 10 columns (as described in the Key Variables section above) This dataset is part of a collection of synthetic datasets generated to simulate various components of emergency healthcare workflows. Each dataset within the collection represents distinct parts of the healthcare service process, supporting in-depth analysis of healthcare service efficiency and resource management. ---
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