IbrahimBishirBala/HealthConnect-Experience-Lab

HealthConnect data analytics project investigating patient appointment attendance and no-show patterns for the AnalystLab Africa Experience Lab. # HealthConnect Experience Lab ## Week 4: Problem Understanding and Initial Analysis **Track:** Data Analytics **Project:** Improving Patient Appointment Attendance and Healthcare Support Using Data and AI ### Week 4 objective Assess the appointment dataset, define business questions and proposed KPIs, and establish a transparent approach for investigating no-show patterns in Week 5. ### Dataset - 5,000 appointment records - 18 variables - 1,696 anonymised patients - Outcome categories: Attended, No-Show and Cancelled ### Initial quality observations - 0 duplicate rows - 0 duplicate appointment IDs - 1,366 structurally blank reminder channels where no reminder was sent - 90 missing distance values - 60 missing waiting-time values - Date, weekday, booking-lead and prior-history checks passed ### Proposed KPIs 1. No-Show Rate 2. Reminder Coverage Rate 3. No-Show Rate by Reminder Status/Channel 4. Repeat No-Show Rate 5. Slot Utilisation Rate These KPIs are proposed but not calculated in Week 4, in line with the assignment brief. ### Repository structure ```text HealthConnect-Experience-Lab/ ├── data/ │ └── HealthConnect_Appointment_Data.csv ├── docs/ │ ├── HealthConnect_Week4_Initial_Analysis_Document.docx │ └── HealthConnect_Week4_Project_Summary.docx ├── notebooks/ │ └── HealthConnect_Week4_Initial_Data_Assessment.ipynb └── README.md ``` ### Week 5 focus Create a documented analysis-ready dataset, calculate agreed KPIs, explore attendance patterns, and develop initial Power BI visuals.