Geographic Concentration of RCI-Listed Rehabilitation Training Institutions in India: A Reproducible National Register Analysis

Background: Reliable information on training institutions can support rehabilitation workforce planning, but regulatory listings do not directly measure active capacity or professional supply. This study describes the geographic distribution and concentration of institutional entries in a fixed Rehabilitation Council of India (RCI) register snapshot.

Methods: A descriptive census reconstructed every institution code and printed serial number from the 113-page RCI list dated 4 February 2026. Source-heading state assignments were checked against code prefixes. Every final institution label was reconciled with source text; extraction exceptions were reviewed with AI assistance. All 36 states and union territories were retained, including those absent from the source. Jurisdictional counts, cumulative shares, the Herfindahl-Hirschman index (HHI) and Gini coefficient were calculated. Course counts, seats, current approval status and population-adjusted rates were outside scope.

Results: The reconstruction recovered 1,068 unique codes and the complete serial sequence 1–1,068. Entries were present in 32 jurisdictions: 27 states and five union territories. Fourteen institutional display labels were corrected or restored without changing state totals. Uttar Pradesh and Rajasthan accounted for 482 entries (45.13%); the five largest counts totalled 663 (62.08%) and the ten largest 847 (79.31%). Four jurisdictions were not represented in the source. Gini across all 36 jurisdictions was 0.6914 and HHI was 0.1216. Excluding unrepresented jurisdictions reduced Gini to 0.6528.

Conclusions: RCI-listed institutional entries are geographically concentrated. The source-linked dataset offers a reproducible organisational frame for further workforce research. These counts do not establish active training capacity, workforce shortage or population-adjusted inequity; those questions require additional programme-period, student-flow, employment and need data.