आरोग्य

Emergency care within 30 minutes

Too many people cannot reach a working emergency facility fast enough. We will map travel times, upgrade the nearest facilities that close the biggest gaps, and measure how many people can reach care within 30 minutes. If the pilot does not improve access, we stop.

EN · अद्याप भाषांतर नाही — इंग्रजीत दाखवलेउदाहरण: पायलटv1.0सामायिकजबाबदार: Mission Lead — Health◌ उदाहरण — not real data

तीन स्तरांवर वाचा

६० सेकंद

५ मिनिटे

The problem is not the number of hospitals; it is whether a person with a heart attack, road injury or obstetric emergency can reach a facility that can actually treat them within the window where treatment works.

There is no national baseline. Step one is a GIS travel-time study, independently audited, in 100 districts. We refuse to publish a made-up number in the meantime.

We do trust one related number: out-of-pocket spending was 43.4% of total health expenditure in 2022-23 (National Health Accounts), up from 39.4% the year before — emergency episodes are a major driver of that burden.

The intervention is targeted: identify the facilities whose upgrade closes the largest access gaps per rupee, staff and equip them for a defined emergency-care standard, and link them with ambulance dispatch that actually reaches rural blocks.

The pilot runs in 12 districts across 4 states with matched comparison districts. Success is measured by travel-time coverage and, secondarily, by time-to-treatment for three tracer conditions.

Kill criteria are explicit: if coverage does not improve by at least 8 percentage points in pilot districts within 24 months relative to comparison districts, the design is stopped and redesigned.

Health is a State subject. The Union role is funding, standards and measurement; States run facilities; local bodies handle roads and last-mile logistics. Nothing here works without State ownership.

संपूर्ण धोरण

संपूर्ण तांत्रिक दस्तऐवज खाली.

Problem

A significant share of the population cannot reach a facility capable of delivering basic emergency care within 30 minutes. Time-to-treatment drives mortality for trauma, cardiac events, stroke and obstetric emergencies. Existing facility counts do not reveal functional access.

Baseline

Not measured nationally. No Indian government series reports travel time to emergency-capable care. Labs project LAB-01 (GIS travel-time model, 100 districts, independently audited) is establishing the baseline; expected by end of Year 1. Until then this policy has no baseline number, by design.

Out-of-pocket expenditure as share of total health expenditure

Target

80% by end of Year 3 (3-year mission); 95% by Year 10 (10-year outcome).

Evidence

Time-to-treatment is a primary determinant of survival for trauma, stroke and cardiac emergencies.
आंतरराष्ट्रीय मानकWHO Emergency Care System Framework — World Health Organization · source
Out-of-pocket spending was 43.4% of total health expenditure in 2022-23, up from 39.4% in 2021-22.
प्राथमिक सरकारी डेटाNational Health Accounts Estimates 2022-23 — MoHFW / NHSRC (via PIB) · source
No national measurement of travel time to emergency-capable care exists; the baseline must be built.
गृहीतकPragati Shakti Labs — placeholder pending baseline study — Pragati Shakti Labs

Alternatives considered

Option	Why not
Build new district hospitals	Highest cost per unit of access gained; long build time; does not address staffing.
Ambulance fleet expansion alone	Reduces reach time but not treatment capability at destination.
Telemedicine-only triage	Useful adjunct; cannot substitute for physical emergency care.
Unconditional grants to states	No mechanism ensures spending targets access gaps; no measurement.

Proposed intervention

GIS travel-time mapping of all facilities against a defined emergency-care capability standard.
Gap-closure ranking: facility upgrades ordered by population coverage gained per ₹ crore.
Upgrade top-ranked facilities (staffing, equipment, protocols) to the standard.
Integrated ambulance dispatch with measured response time by block.
Public monthly dashboard of coverage and tracer-condition time-to-treatment.

Legal authority

Public health and hospitals: State List (Seventh Schedule, List II, Entry 6). Union participation via Article 282 grants and centrally sponsored scheme framework. Emergency care obligations reinforced by Article 21 jurisprudence on right to emergency medical treatment.

Government responsibility

केंद्रFunding share, capability standard, national measurement, medical-education seats.
राज्यFacility operation, staffing, ambulance services, referral networks.
स्थानिकRoad access, last-mile transport coordination, community reporting.

Overall classification: SHARED. See Who can act?

Budget

Year 1: ₹350 cr
Five-year cost: ₹1.8k cr
Ten-year implication: ₹4.2k cr
Capital expenditure: ₹900 cr
Recurring expenditure: ₹180 cr / year
Funded?: Yes — funding source identified

Fiscal assumptions

Facility upgrade average cost ₹6 crore (assumption; to be validated in pilot). गृहीतक
Recurring staffing cost per upgraded facility ₹1.2 crore/year (assumption). गृहीतक
State matching share secured via MoU before disbursement. गृहीतक

Funding source

Reprioritisation within existing centrally sponsored health-scheme envelope (60%) + State matching (40%). ILLUSTRATIVE.

Opportunity cost

Equivalent funds could expand primary-care screening; modelling suggests emergency access has higher mortality impact per rupee in the near term, but this is to be tested in Labs.

KPIs

KPI	Baseline	Target	Method
Population within 30 min of emergency-capable care	Not measured (LAB-01)	80% by Year 3	GIS travel-time model, independently audited annually.
Median time-to-treatment, tracer conditions	To be measured	−25% vs. comparison districts	Facility registry sampling with case audit.
Ambulance response time, rural blocks	To be measured	≤ 20 min median	Dispatch-system logs, quarterly published.

Risks

R1L: HIGHI: HIGH
Upgraded facilities cannot retain specialists.
Mitigation: Rotation contracts, telemedicine backup, incentive evaluation in pilot.
R2L: MEDIUMI: MEDIUM
GIS model overstates access due to road quality.
Mitigation: Ground-truth sample of 500 routes per state.
R3L: MEDIUMI: HIGH
State matching funds delayed.
Mitigation: Disbursement gated on MoU; public dependency status.

Dependencies

METState health department MoUs (12 pilot districts) — State Teams
PENDINGGIS facility and road dataset — Pragati Shakti Labs
METEmergency-care capability standard, expert reviewed — Mission Lead — Health

Pilot design

12 intervention districts, 12 matched comparison districts across 4 states.
Pre-registered outcomes and analysis plan published before intervention.
24-month duration with 6-monthly public interim reports.
Independent evaluator contracted before launch.

Kill criteria

Coverage gain < 8 percentage points vs. comparison districts at 24 months.
Cost per additional covered person exceeds 2× the modelled estimate.
Specialist retention below 50% at 18 months with no viable mitigation.

Scale criteria

Coverage gain ≥ 8 points with statistical confidence.
Tracer-condition time-to-treatment improved.
Unit costs within 1.3× of model.
At least 2 pilot states commit matching funds for scale-up.

Independent evaluation

External academic evaluator selected by open call; evaluation protocol pre-registered; report published unedited alongside organisational response.

Revision history

v0.1Invalid DateResearch — Problem statement and evidence scan.
v0.2Invalid DateExpert review — Capability standard revised after emergency-medicine panel.
v0.3Invalid DatePublic consultation — Added rural ambulance response KPI following consultation.
v0.4Invalid DateFiscal revision — Recurring cost raised 20% after staffing assumption challenged.
v1.0Invalid DateApproved pilot — Pilot approved in 12 districts.

Historical versions are never silently rewritten. Each version remains retrievable via the API.

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