Diabetic Patients in the Hospital

A Look Into Male Diabetic Patients Below the Age of 25 With an Abnormal Test Result

Statistical Summary

Patients Identified: 10
Average Age: 21
Youngest Patient Age: 19
Oldest Patient Age: 24
Average Bill: $28,125
Total Bill Cost Across Patients: $281,247
Name Age Doctor Hospital Insurance Provider Billing Amount Admission Type Medication Test Results
Melissa Lawrence 20 John Hansen Humphrey and Browning Fitzgerald, Blue Cross $35,205 Emergency Lipitor Abnormal
Joyce Moody 22 Steven Clark Moore-Woods Cigna $7,733 Elective Paracetamol Abnormal
Matthew Bell 19 Doris Johnson Hicks-Perez Medicare $20,086 Urgent Aspirin Abnormal
Leah Frederick 19 John Cooper Giles-Miller Aetna $25,856 Emergency Lipitor Abnormal
David Payne 22 Linda Adams Ferguson-Liu Medicare $46,773 Emergency Ibuprofen Abnormal
Kathryn Smith 23 Daniel Johnson Hoover Rodriguez, and Vang UnitedHealthcare $11,419 Urgent Lipitor Abnormal
Oscar Nelson 24 Crystal Schwartz Wagner LLC Cigna $39,019 Emergency Ibuprofen Abnormal
Timothy Elliott 19 Tara Ruiz Ltd Curry Cigna $30,789 Urgent Ibuprofen Abnormal
Kathy Waller 23 Maria Jones Johnson PLC Medicare $42,346 Emergency Ibuprofen Abnormal
Benjamin Herrera 23 John Dickson Chavez-Webster Blue Cross $22,022 Urgent Aspirin Abnormal

Data Analysis

A clear trend emerges in the billing amounts across different admission types. Male diabetic patients under the age of 25 with abnormal test results incurred the highest charges when admitted for emergency care. In contrast, the lowest billing was recorded for a patient admitted electively. This suggests a direct and expected correlation between the urgency of admission and the overall cost of care. It is important to note that much of the data shown in this dataset appears to be filler data from an example dataset. This is most apparent in the names of the members of the dataset which appear distorted with random capitalization. For readability, the presented data has been adjusted to proper case formatting. With this in mind, making correlations between the data points should be done with caution as the data may not accurately represent real-world scenarios.