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Proposal: Add Cost Per Target Person (CTP) and Design Feasibility Ratio (DFR) as BCIO entities, and update BCW guidance to position cost-feasibility analysis before diagnostic expansion #1227

@oleksiikartashovde-glitch

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BCIO tool

Hi all,

I've just posted a preprint that may be relevant to two connected issues: BCW sequencing and BCIO ontology coverage.

The paper: Budget Before Diagnosis: Applying Established Cost-Analysis Methods to Behaviour Change Designhttps://papers.ssrn.com/abstract=6534918

The short version of the argument:

In commissioned programme design — where budget and target population are fixed before design begins — cost-feasibility analysis belongs at the opening of the BCW sequence, not at the APEASE stage. Deferring it to APEASE means diagnostic investment is made before financial feasibility is known. The Ingredients Method (Levin et al.) explicitly specifies prospective cost analysis; BCW practice doesn't currently reflect this.

Two constructs do the work at design stage:

  • Cost Per Target Person (CTP) — a prospective application of cost per participant (the standard Ingredients Method output), calculated from planned target population rather than actual completers. Formula: CTP = total full-loaded budget / planned target population. This is not a new metric; it is a design-stage reframing of an existing one.
  • Design Feasibility Ratio (DFR) — translates NICE QALY threshold logic into a design-stage ceiling: DFR = proposed CTP / (expected QALY gain per person × cost-effectiveness threshold). DFR < 1.0 = economically admissible; DFR > 1.0 = requires restructure.

The ontology proposal:

Both constructs have clear definitions, formulas, and relationships to existing BCIO-adjacent entities:

  • CTP relates to cost per participant, intervention population, budget, and cost-feasibility analysis
  • DFR relates to QALY, ICER, cost-effectiveness threshold, and affordability (already in APEASE)

If BCIO is to support operationalised intervention design — not just classification — these seem like candidates worth considering as formal entities. The paper includes a benchmark table (Table 1) and decision bands (Table 2) that could inform property ranges.

Oleksii

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