IVPatient experience

Against-medical-advice (DAMA) rate

The share of patients who leave against medical advice after being assessed (DAMA/LAMA). In Indian EDs it is often less about defiance and more about money, fear, and family logistics — which makes it a window into access and trust, not just risk.

Capture & escalation pipeline

From a patient wanting to leave to capacity, counselling, reason capture, and high-acuity escalation.

How it’s measured

Numerator: Patients who leave against medical advice (DAMA/LAMA) after assessment by a treating clinician.
Denominator: All ED patients seen (or all admissions, stated explicitly).
Formula: (Numerator ÷ Denominator) × 100.
Unit: % of patients

Target

India

India: NABH tracks LAMA/DAMA as a quality and patient-rights indicator; the aim is a low, falling rate with documented capacity, counselling, and consent — not zero at the cost of coercion.

Global

International: Internationally treated as a balancing/experience measure; high rates flag access, communication, or trust problems.

Keep DAMA (left after assessment, against advice) distinct from LWBS (left before being seen) — different problems.

Who does what

The clinical chain of responsibility at the bedside.

Treating doctor	Assesses capacity, explains risks/benefits and alternatives, documents the discussion, and offers a safe alternative where possible.
Nursing	Supports counselling, completes the DAMA documentation, and gives safety-netting advice.
Counsellor / social worker	Addresses financial, transport, and family barriers that often drive the decision.
ED in-charge	Reviews high-acuity DAMA cases and offers escalation/options.

What to capture & how it’s automated

Who captures it

Treating team (the DAMA event and documentation).

What is captured

The DAMA event, triage acuity, documented reason, capacity assessment, and counselling.

Manual reality

A signed DAMA form filed in the record; the reason is often blank, so themes are lost.

Automated in real life

A structured DAMA form in the HMIS that captures reason codes (financial, fear, family, wait) and acuity, feeding a dashboard that shows why patients leave.

Who in the hospital is involved

Beyond the bedside — the functions that make capture and improvement happen.

Quality cell / QI nurse	Trends DAMA by reason and acuity and reviews high-acuity cases.
Counsellor / medical social worker	Tackles the financial and logistic drivers behind departures.
Billing / PMJAY desk	Resolves cost fears via Ayushman Bharat/insurance counselling — a major Indian driver of DAMA.
Medical records / HIM	Captures the structured DAMA data and links to outcomes.
ED manager	Acts on themes — wait times, cost, communication.

Why it affects performance

DAMA is a NABH patient-rights/quality indicator and a sensitive balancing measure for access and trust. Reason-coded data points directly at fixable causes (cost, waits, communication).

Why it affects patient care

A high-acuity patient leaving against advice is a real risk of harm. Understanding why — and removing the barrier, especially cost — keeps patients in care rather than sending them home to deteriorate.

Capture pitfalls & gaming to watch for

Confusing DAMA (left after assessment) with LWBS (left before being seen).
A signed form with no recorded reason, so no learning is possible.
Skipping capacity assessment and documentation, creating medico-legal risk.
Treating DAMA as the patient's fault rather than a signal about access and trust.

What actually moves the number

Early financial counselling and Ayushman Bharat/PMJAY navigation.
Structured reason codes on the DAMA form to surface themes.
Capacity assessment and clear, documented risk communication.
Shorter waits and better communication to reduce frustration-driven departures.
Senior review and a genuine safe alternative for high-acuity cases.

References

Freely citable

Compiled from contemporary emergency-medicine quality practice and freely citable accreditation and guideline standards. Educational use only.