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The medicines business | A question to investigate

Can the available data answer the question?

A large dataset can still be the wrong dataset. It may record prescriptions but not treatment use, hospital activity but not the relevant outcome, or a population that differs from the decision being considered. Before a medicines business commits to a real-world evidence study, the useful question is whether the proposed evidence can bear the intended claim. NEUVIOR is interested in making that feasibility decision more explicit and easier to challenge.

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Feasibility has scientific and commercial value

A poorly framed study can consume budget without resolving the uncertainty that justified it. A careful feasibility review can prevent that outcome or reveal a smaller, more credible question. It should connect the research objective to an actual decision: a development choice, an evidence-generation priority or a defined stakeholder uncertainty. The review needs an accountable scientific owner and a clear understanding of how the result would influence the next investment decision.

Use recognised methodological context

NICE’s data-suitability chapter addresses provenance, quality and relevance (NICE, 2022). Its comparative-effects chapter discusses non-randomised study design and sources of bias (NICE, 2022). These references inform feasibility; they do not automatically validate a dataset or analysis. A proposed review would identify the population, exposure, comparator, outcome and observation period before examining what information is available. The intended claim should determine the data requirements, rather than the available fields determining an attractive claim after the fact.

Ask what is absent as well as present

A field called treatment may represent prescribing, dispensing or administration. An outcome may be recorded only when a person returns to care. Missing follow-up can differ between groups. A feasibility brief should describe these limitations in relation to the question, including changes in coding and care pathways over time. It should also identify whether important confounders are measured with sufficient detail, rather than treating the presence of many variables as a substitute for relevance.

A go, redesign or no-go brief

The proposed deliverable would show which elements of the research question are supported, which need further data-provider clarification and which cannot be answered with the proposed source. It would include a reasoned recommendation for the next commissioning decision. That makes the feasibility investment useful even when the conclusion is not to proceed.

A public decision brief | An illustrative example

Open the question.
Inspect the reasoning.

Choose a business question, then look beneath its claim. See what a public source supports, what depends on the local setting and what a useful next step could be.

A medicines or implementation team considering an AI-supported evidence review.

Would a quicker review make the decision better?

The interesting question is the complete piece of work: finding relevant material, checking it, correcting the draft and reaching an accountable decision.

A proposition to investigate

Less preparation. The same ability to challenge.

An evidence-review approach could be useful if it reduces avoidable preparation while preserving source access, relevant qualifications and professional checking. That is the proposed value to test. No time reduction, accuracy improvement or customer result is asserted in this example.

The proposition is constructed for this public brief. It is not a published finding about PHARMORIS.

What the next brief would contain

A decision someone
can commission.

The decision
Whether one defined review task merits an agreed evaluation.
The comparator
The team's existing complete review process, including checking and corrections.
The evidence
Representative cases, source records, reviewer decisions, complete-task effort and exceptions.
Stop or redesign
Stop or redesign if source checking weakens, errors are unacceptable or the complete task offers insufficient value.

Constructed public example | Not PHARMORIS-generated software output or a measured customer result.

Keep this example brief

A bounded PHARMORIS scoping evaluation

The initial work could use a study concept, public dataset documentation and permitted aggregate feasibility information. No patient records are needed merely to decide which access questions require answering. The comparator would be the current feasibility paper. Independent methodological reviewers could assess whether a proposed evidence-linked brief identifies material limitations, distinguishes fixable problems from design failures and preserves uncertainty. Any later data access or research would require its own permissions and governance.

Define a meaningful result

Candidate measures include agreement between reviewers about the feasibility decision, material limitations identified before commissioning and the completeness of the proposed next-step requirements. A useful output may recommend redesign, another data source or no study. These are legitimate outcomes. It should not claim treatment effectiveness or commercial value from the feasibility exercise itself. If the question is viable, the next stage would specify an appropriate design and analysis plan rather than treating a scoping result as evidence.

Conditions that prevent further work

The evaluation should pause if the target decision is undefined, if the data provider cannot clarify essential meanings, or if a desired conclusion has already been selected. It should stop when access costs or timelines make the proposed study commercially impractical, even if the science is interesting. A transparent no-go decision can protect resources for a stronger research opportunity. The rationale should remain inspectable so that a later change in data availability can be assessed fairly.

A first discussion before commissioning

An evidence-generation, medical or development leader can bring one study question and the data source currently being considered. We can discuss what the study would need to establish, which uncertainties are resolvable and how an independent feasibility comparison could be scoped. The aim is a decision the organisation can act on: proceed with a credible design, change the question, seek another source or avoid commissioning work that cannot deliver the evidence it promises.

Sources and scope

NICE | Assessing data suitability | NICE | Methods for comparative real-world studies

Discuss an evidence-study feasibility question

NICE (2022) Assessing data suitability. Available at: https://www.nice.org.uk/corporate/ecd9/chapter/assessing-data-suitability (Accessed: 14 October 2026).

NICE (2022) Methods for comparative real-world studies. Available at: https://www.nice.org.uk/corporate/ecd9/chapter/methods-for-real-world-studies-of-comparative-effects (Accessed: 14 October 2026).

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