Data Analysis · Public Policy Research

Indian Healthcare - A Regional Disparity Analysis

Analysis of regional disparities in healthcare service delivery, infrastructure access, and health outcomes across Indian states using public datasets.

Python Public Datasets Data Visualization Health Policy
Year2024
RoleResearch Analyst
StackPython, Visualization tools
StatusCompleted

National healthcare averages hide state-level realities.

India's National Health Mission has spent over Rs. 2 lakh crore since 2005, but aggregate statistics mask dramatic variation. A child born in Kerala faces a different healthcare system than one born in UP or Bihar.

Outcome variation

IMR, MMR, under-5 mortality, and immunisation coverage vary sharply by state.

Infrastructure gaps

Beds, doctors, and PHCs per lakh population expose differences hidden by national averages.

Financial protection

High out-of-pocket expenditure can signal system failure even where infrastructure exists.

Compare healthcare systems across inputs, usage, outcomes, and financial burden.

The analysis uses NFHS-5, National Health Profile, and National Health Mission reports. It focuses on infrastructure availability, utilisation rates, outcome indicators, and household financial protection through out-of-pocket expenditure.

The framework avoids one-dimensional health rankings.

NFHS-5 as anchor dataset

NFHS-5 is comprehensive and methodologically consistent, making state comparison more credible.

Input and output indicators together

Infrastructure alone is incomplete. Usage and outcome data show whether systems actually serve people.

Financial protection as health indicator

Out-of-pocket burden reveals whether access is economically meaningful for households.

A multi-dimensional state-level healthcare analysis.

The completed analysis ranks and compares Indian states across key health indicators, showing regional disparities and policy-relevant patterns across public datasets.

What I learned

Aggregate national statistics almost always mislead in India. Analysis that does not account for state-level variation is incomplete, regardless of how good the visualization looks.

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