Discuss the significance of data harmonisation in India's health statistics ecosystem with reference to NFHS-6.

Data harmonisation means aligning indicator definitions, methods and reporting across surveys so that numbers from different agencies are comparable and non-duplicative. NFHS-6 (2023-24), whose fact sheets were released in May 2026, is the first round shaped by the Government's Data Harmonisation Initiative, making it a live test of this reform [1][2].

How harmonisation shaped NFHS-6

• Indicators were finalised by a Technical Advisory Committee (TAC) with members from MoSPI, NITI Aayog, the Registrar General of India, Ministry of Women & Child Development, Department of Drinking Water & Sanitation and DEPwD — a cross-ministerial design that avoids single-agency bias [1].
• The fact sheets were trimmed to 101 key indicators from 131 in NFHS-5, ending duplication with other official data streams [1].
• Anaemia estimates were shifted to an ICMR survey using venous ("gold standard") haemoglobin testing, replacing the capillary finger-prick method whose accuracy had long been questioned [1].

Significance for the health statistics ecosystem

• Credibility: methodological correction on anaemia signals willingness to fix known measurement error rather than protect a trend line [1].
• Comparability: common definitions let NFHS talk to SRS, CRS and the NITI Aayog SDG India Index, strengthening SDG-3 monitoring.
• Policy targeting: harmonised numbers underpin schemes like POSHAN Abhiyaan and the National Health Mission; NFHS-6 records institutional deliveries at 90.6%, first-trimester ANC at 76.2% and stunting down to 29.3% [2][3].

Concerns

• Dropping indicators such as anaemia, infant mortality and clean-fuel use creates temporary evidence gaps and breaks time-series continuity with NFHS-5 [1].
• Harmonisation succeeds only if the alternative sources deliver on time and at comparable disaggregation.

Harmonisation thus trades short-term data loss for long-term accuracy and coherence — a defensible bargain if institutionalised. The way forward is a published inter-survey calendar, clear mapping of each dropped indicator to its new source, and district-level disaggregation, so that India's health statistics remain both trusted and usable for equitable, evidence-based policy.