Services / NHS data analysis
NHS data analysis, by a named statistician
Trusts, ICBs, primary care networks and public health teams bring us in when an audit, an evaluation or a service review needs statistical judgement the department does not employ full time — and when the result has to stand up to a board, a commissioner or a regulator.
- Named statistician assigned before you commit
- DPA, IG schedule or NDA signed before data moves
- Reporting a board or commissioner can act on
- Follow-up questions included
Turning routinely collected healthcare data into findings a service can act on: clinical audit against a standard, service evaluation of what a service is achieving, outcomes and PROMs analysis, and statistical process control to separate real change from ordinary variation. The work is normally done on a pseudonymised extract, with the information governance paperwork signed before any data moves.
What is included
What we do for NHS and public sector teams
Clinical audit
Sample size that holds up, criteria two auditors score the same way, and analysis that makes a re-audit comparison meaningful.
Service evaluation
What a service is achieving, who it reaches and who it misses — reported without claiming causation the design cannot support.
Outcomes and PROMs
Patient-reported and clinical outcome measures analysed with the case mix and the missing data handled honestly.
Statistical process control
Run and control charts that distinguish a genuine shift from ordinary month-to-month variation.
Research support
Sample size, analysis plan and a named statistician on the application for NIHR and other funders.
Independent review
A second pair of eyes on analysis done in house, before it reaches a board, a regulator or a journal.
Who it is for
Who we work with
- Clinical audit departments without statistical support
- Quality improvement teams needing SPC done properly
- Service redesign and decommissioning decisions
- Research teams needing a named statistician
- Needs assessments and population estimates
- Health inequalities analysis by population group
- Programme and intervention evaluation
- Evidence for a commissioning or business case
The work itself
What makes healthcare data different
Three things recur in NHS data and each one changes the analysis. Case mix: the patients a service sees are not the patients another service sees, so a raw outcome comparison between units is usually meaningless without adjustment. Missing data: rarely missing at random — the records with gaps are often the patients with the most complex care, and dropping them quietly biases the result. Small numbers: a ward, a clinic or a cohort is often small enough that ordinary variation looks like a trend.
The practical consequence is that the headline figure is seldom the finding. A readmission rate that rose is not evidence that care worsened until case mix and chance have been accounted for — and a board paper that implies otherwise tends to be unpicked by the first person in the room who knows that.
We report what the data supports, with the uncertainty stated, and say plainly where it will not support the conclusion the service hoped for. That is the point of bringing in someone independent.
Typical work
What we are most often asked for
If your project resembles one of these, we have done it before and can quote quickly.
Audit sample size and design
How many records, selected how, and whether the planned re-audit could detect the improvement you want.
Service evaluation
Activity, reach, outcome and experience — with the breakdown by population group commissioners ask for.
SPC and run charts
Control limits set properly, so a quality improvement programme can tell a real shift from noise.
Risk adjustment
Comparing units or periods fairly once case mix is accounted for.
Survey and PROMs analysis
Validated instruments scored correctly, with the missing data handled rather than ignored.
Second opinion
Independent review of an analysis before it is published or acted on.
How to compare us
Questions worth asking before you commission
These apply to any provider you are considering, including us.
| What to ask | Why it matters | Our answer |
|---|---|---|
| Will you sign our IG paperwork before we send data? | Sending data first and papering it afterwards is the common failure. | Yes — DPA, IG schedule or NDA, signed before anything moves. |
| Do you need identifiable data? | Every identifiable field increases the governance burden on you. | Almost never. We work from pseudonymised extracts by preference. |
| Who specifically will do the work? | Agencies sell on a senior name and deliver with a junior analyst. | A named statistician, told to you before you commit. |
| Will we get the code? | Analysis that cannot be re-run cannot be checked next year. | Always delivered, as standard. |
| What if the data does not show what we hoped? | An analyst whose answer always matches the hoped-for result is not independent. | You are told before it reaches a board or a commissioner. |
| Can you complete our supplier forms? | Procurement stalls more projects than analysis does. | Yes — see our published supplier information. |
Security and governance
How your data is handled
Usually the first question from NHS, university and local authority buyers — reasonably so.
If your organisation has a standard supplier assurance process, send it with the enquiry and we will complete it during scoping rather than after you have committed.
Pricing
What it costs, and why it is quoted rather than listed
The honest answer is that price depends on the state of the data and the scope of the question. A clean dataset with a well-specified question costs a fraction of a project that begins by reconciling three incompatible systems. So we look first and quote after.
Typical agency model
- Hourly billing against a scope that expands
- A senior name sells it, a junior delivers it
- Output without the code behind it
- Revisions billed as new work
How we work
- Fixed price agreed before anything starts
- The statistician named on the quote does the work
- Syntax and method note delivered as standard
- Follow-up questions included in the price
For most organisations this is materially cheaper than the alternatives — a permanent analyst hire for intermittent work, or a large consultancy billing hourly.
How it works
Three steps, entirely in writing
Send what you have
Attach the data, or just describe the project. No account, no mandatory call, and a five-field form rather than a fifteen-field one.
Approve a fixed quote
Usually within one working day, naming the statistician assigned, the deliverables and the deadline.
Receive the work
Output, syntax and a plain-English explanation — with follow-up questions answered at no extra cost.
Client feedback
What clients say about this work
“Professional statistical consultancy with practical recommendations that helped us make informed business decisions.”
“Their organisational data analysis was thorough and easy to understand. The final report provided valuable insights.”
Proof
This work, on real projects
Clients are not named and no identifying detail is published, so what is described is the statistical problem — which is the part that shows whether a consultancy knows what it is doing.
Cox Proportional Hazards Modelling to Identify Patients Most at Risk of Readmission
Modelling time-to-event rather than event-or-not, so a large public sector organisation could target risk assessment where it mattered.
Public services · Time series forecastingSeasonal ARIMA Forecasting with Intervention Analysis for Resource Planning
Twelve years of monthly demand with seasonality, trend and structural breaks — where simple smoothing methods failed consistently.
Manufacturing · Generalised linear mixed modelsGeneralised Linear Mixed Models to Identify the Drivers of Production Defects
A quarter of a million production records across six lines and two years, where univariate analysis could not separate interacting process variables.
Your statistician
Who does this work
Member of the Royal Statistical Society
Econometrics, forecasting and causal inference for policy evaluation, business analytics and operations.
This page was reviewed for statistical accuracy by Saad Tariq on 14 August 2026.
Common questions
Answers before you ask
Do you work with NHS trusts and ICBs?
Yes. Most of this work is clinical audit, service evaluation, outcomes analysis and statistical process control for trusts, integrated care boards, primary care networks and public health teams. We work on invoice with PO references and can complete supplier onboarding.
Can you sign our information governance paperwork?
Yes — data processing agreement, information governance schedule, NDA, or your own supplier forms. We sign before any data is sent, not after. Our full supplier information, including insurance and data handling, is published.
Do we need to send identifiable patient data?
Almost never. Audit and evaluation work can nearly always be done on a pseudonymised extract, and we would rather you sent one. Where identifiable data is genuinely required we will say so and work within your DPIA.
Can you help decide whether our project is audit, evaluation or research?
Yes, and it is worth settling before data collection. The distinction decides whether REC approval is needed, and the HRA decision should be recorded at the outset rather than justified afterwards.
Can you be named on a research application?
Yes. NIHR and most funders expect a named statistician with a stated role on the application. We can be named, write the statistical methodology and confirm the sample size before submission.
How quickly can you turn work around?
Scoping usually takes a day or two. The analysis depends on the state of the data — a clean extract with a clear question is quick; one that starts by reconciling three systems is not. Both are written into the fixed quote before you approve it.
Related
Often needed alongside this
Send the data. Get a fixed quote.
Send a pseudonymised extract or just describe the audit or evaluation. A named statistician replies with a price and a deadline, usually within one working day.