Medical Appointments No-Show

Published: 14 February 2023| Version 1 | DOI: 10.17632/wm6w2fvkfj.1
Contributor:
Luiz Henrique Salazar

Description

The data are used for the study of medical appointments no-show. The dataset consists of data obtained and extracted from the University of Vale do Itajaí Center of Specialization in Physical and Intellectual Rehabilitation (CER). The clinic serves the Unified Health System (SUS) in southern Brazil. The CER is an outpatient care service that performs diagnosis, assessment, guidance, early stimulation and specialized care. It has acted in functional rehabilitation and psychosocial qualification to encourage the autonomy and independence of people with disabilities. Firstly, we collected the relevant information on the no-show problem in loco at the rehabilitation centre by transcribing 49,593 medical records from an electronic spreadsheet of 2016 to2022. In order to add more information to the collected data, some other databases were combined with the initial database, namely: ICD, weather conditions data and other related attributes. Finally, this dataset is composed of the following attributes: 1. "Specialty": specialty that patient received the treatment; 2. "Appointment Time": appointment time scheduled; 3. "Gender": male or female gender of the patient; 4. "Appointment Date": appointment date scheduled; 5. "No-show": given whether the patient attended the scheduled appointment or not; 6. "No-show Reason": description of the reason why the patient did not attend the scheduled appointment; 7. "Disability”: the patient’s motor or intellectual disability; 8. "Date of Birth": the patient’s date of birth; 9. "Date of Entry into the Service": date of the patient’s first appointment at the CER; 10. "City": city where the patient resides; 11. "ICD": identifier of the patient’s disease; 12. "Appointment Month"; 13. "Appointment Year"; 14. "Appointment Shift"; 15. "Age": patient's age; 16. "Under 12 years old": patient's age under 12 years old; 17. "Over 60 years old": patient's age over 60 years old; 18. "Patient needs companion": patient's needs companion to go to the appointment; 19. "Patient needs companion": patient's needs companion to go to the appointment; 20. "Average Temperatura Day": Average temperatura in the day of the appointment; 21. "Average Rain Day": Average rain in the day of the appointment; 22. "Max Temperature Day": Maximum temperature in the day of the appointment; 23. "Max Rain Day": Maximum rainfall in the day of the appointment; 24. "Storm Day Before": Heavy rain in the day before the appointment; 25. "Rain Intensity": no rain, weak, moderate or heavy rain in the day of the appointment; 26. "Heat Intensity": cold, heavy cold, warm, heavy warm or mild in the day of the appointment;

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Institutions

Universidade do Vale do Itajai

Categories

Data Science, Machine Learning, Healthcare Research

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