A project analysing disease burden and patient flow in Kenya County Hospitals using Python determining the conditions that drive the most cases, how long patients stay in hospital, and which diseases place the highest demand on inpatient resources.
# Hospital-Analysis
A project analysing disease burden and patient flow in Kenya County Hospitals using Python determining the conditions that drive the most cases, how long patients stay in hospital, and which diseases place the highest demand on inpatient resources.
Overview
This project analyses patient records from a Kenya County Hospital to understand disease burden, patient flow, and resource utilisation patterns between 2021 and 2023. The goal was to identify which conditions place the greatest pressure on the hospital system, how patients move through the facility, and which diseases consume the most inpatient resources.
This project is personal to me. During my attachment at Kiambu County Referral Hospital and Ruiru Sub-County Hospital, one of my daily tasks was coding diseases using ICD-10 classification. I noticed that some conditions appeared in the records far more frequently than others and I always wondered why. This project is my attempt to answer that question using data.
Dataset
Source: Simulated dataset inspired by Kenya Ministry of Health disease surveillance reports and real clinical workflows observed during health records attachments
Period: January 2021 — December 2023
Rows: 84,958 patient records
Columns: 12
Columns included:
ColumnDescriptionPatient_IDUnique identifier per patient visitYear / MonthTime period of the visitDiseaseDiagnosed conditionICD10_CodeInternational Classification of Diseases codeDepartmentHospital ward or clinicAge_GroupPatient age bracketGenderMale or FemaleVisit_TypeOutpatient or InpatientLength_of_Stay_DaysNumber of days spent at the facilityOutcomeTreated & Discharged, Referred, Admitted, DAMA, Deceased
Diseases included:
Malaria, Diarrhoeal Disease, Respiratory Tract Infection, Hypertension,
Pneumonia, Urinary Tract Infection, Diabetes Mellitus, Anaemia,
Injuries & Trauma, Typhoid Fever, Skin Infections, HIV/AIDS Related,
Eye Infections, Tuberculosis, Malnutrition
Tools & Libraries
Python 3
Pandas
Nu …