The data exists. The route to it does not.
Someone holds the records. Getting them released for your specific purpose is a different problem, and it is the one that decides your timeline.
Real-world data, insight and evidence for life sciences
Gold-standard metrics for the decisions that matter most.
Life sciences teams do not lack data. They lack a defensible path from the data to a decision. Aurumetrics builds that path: we find the data, secure the permissions, run the analysis in-market and hand back evidence you can put in front of a regulator, a payer or a board. Across nine Asia-Pacific health systems, and further where a partner exists.
9markets, being eight national and territorial health systems plus a cross-border oncology hospital network reaching India
170m+lives under de-identified patient-level data we can analyse, in-market, under that market's own law
12data types, from government and insurance claims to genomics, biobank and linked data
The name
AURUMETRICS
Aurum, gold · Metrics, the measure
Aurum is the Latin for gold, and the root of the word for the standard everything else is judged against. Metrics is the discipline of measuring things properly. The company was named for what it is meant to produce: gold-standard measures of what is actually happening to patients, in markets where that is genuinely hard to establish.
It is a high bar to name yourself after, which is the point. A number is only worth having if it survives the person who has to defend it.
The problem we solve
In life sciences, data access is a governance problem before it is an analytics problem.
Health data becomes useful only after custodianship, ethics, privacy, residency and linkage are resolved. Most programmes stall long before anybody opens a dataset.
Nothing transfers between markets.
Every Asia-Pacific health system has its own regulator, HTA body, payment model, coding conventions and governance law. Knowing one tells you very little about the next.
Four suppliers, no single owner.
A broker, an analytics vendor, an ethics consultant and a translator, with you project-managing the seams and absorbing every delay that falls between them.
The failures happen at design, not analysis.
A study the data was never going to support costs far more than a feasibility read that says no. Most people find out in month four.
Before governance
- Custodian approval outstanding
- Ethics or IRB review not started
- Residency requirements unmapped
- De-identification undefined
- Linkage permissions unresolved
After governance
- Compliant extraction agreed
- Study-ready cohort defined
- Transparent, documented methodology
- Audit-ready evidence trail
- Decision-grade outputs
The five filters
- Custodianship
- Ethics and IRB
- Privacy and residency
- De-identification
- Linkage and delivery
Aurumetrics reduces friction by structuring governance-aware evidence pathways before analysis begins. That is the whole method, and it is why our answers arrive on a schedule rather than an apology.
How we bridge the gap
From real-world data, to insight, to evidence.
Three things that get talked about as if they were one. The gap between them is where most value is lost, and closing it is what we are for.
What we do
Two ways to work with us. Services, and a product.
Most firms in this field sell one or the other. Running both is what keeps the services honest: we use our own product, so we know what a good one costs to maintain.
Five offerings, one partner
We source the data, secure the permissions, run the analysis in-market and build the evidence. One accountable party on one contract, so nothing waits in a queue between two suppliers who do not report to each other.
- Data landscape assessment. What exists, what is permitted, how long it takes.
- Feasibility and cohort scoping. Can this specific question be answered at all.
- Analysis and insight. The answer, in a form you can use.
- Full RWE study. Built to survive scientific and payer review.
- Programme partnership. A standing evidence capability across a portfolio.
Health Grid Platform
An analytics platform for the Australian market: pharmaceutical claims, medical services claims, hospital activity and hospital diagnoses in one place, refreshed monthly. Every therapeutic area and every company, at once.
- The whole market, not a slice. Not one indication and one competitor.
- It keeps up on its own. New listings arrive in the monthly refresh.
- No training required. Pick, click, read.
- Make it yours. Your own market baskets, saved views, exports.
The five levels of data access
Most buyers ask for a level higher than they need, and pay for it.
"Access" means five quite different things in this field. Knowing which one your question actually requires is usually the single biggest saving available to you.
We will tell you the lowest level that answers your question, even when a higher one would be a larger piece of work for us. A cheaper answer that holds is worth more to both of us than an expensive one you cannot defend.
1
Published aggregates
Counts and totals already in the public domain. No permission needed, no patient records involved.
2
Custom aggregate extract
A tabulation prepared to your specification by the party that holds the data, then released.
3
De-identified patient-level analysis, in-market
Record-level analysis performed inside the alliance partner's controlled-access environment. The data does not move.
4
De-identified, analysis-ready dataset
A purpose-built extract released to you under a permission agreed for that use, with its specification and link-quality metadata.
5
Direct access to source data
The deepest level, and the most heavily conditioned. Discussed directly rather than advertised.
The operating model
The analysis travels to the data. The data does not travel to us.
A governance-first, privacy-preserving architecture. Four entities, defined roles, and a controlled flow between them. Your legal team's usual worry is what happens to patient records once they leave the hospital. In this model, they do not leave.
Raw identifiable patient data never leaves the custodian's controlled environment. What moves to the alliance partner is a de-identified patient-level subset, accessible only inside a controlled-access environment, by credentialed analysts, with no raw extraction permitted.
For your legal team, this removes the longest item on the critical path. The cross-border data transfer agreement is normally the single slowest thing in a regional evidence programme. In this model there is not one to negotiate.
Where we work
Asia-Pacific depth. Global reach through partners.
Our proven depth is in nine Asia-Pacific markets, which is where the alliance partners, the governance knowledge and the track record are. Where a question sits outside the region and a data partner exists, we will say so plainly and tell you what we can and cannot do there.
What existsWhich data types are actually present, at what scale, at what grain, covering which slice of the population.
What is permittedDifferent from what exists, and the difference is where programmes die.
How long it takesApproval timelines, not analysis timelines, decide most schedules in this region.
What it will costScoped against a defined deliverable, with pass-through items disclosed up front.
The data we work with
Twelve data types, in plain English.
Most people who need this work are not data specialists, and should not have to be. Here is what each type actually is and what it is good for.
Claims, government
Records of what a public scheme paid for. Excellent for treatment pathways, volumes and cost. Blind to anything the scheme does not fund.
Claims, insurance
The same shape of record from private insurers. Strong where private coverage is dominant; the covered population is not the whole population.
EMR and EHR
What clinicians wrote down: diagnoses, notes, orders, results. The richest clinical detail available, and the messiest.
Hospital activity
Admissions, procedures, length of stay, day cases. Answers where this is happening, and how much of it.
Dispensing
What was actually handed to a patient at a pharmacy, which is closer to real use than what was prescribed.
Laboratory results
Test values over time. The difference between "was treated" and "responded", and essential for biomarker-defined cohorts.
Registry
Purpose-built collections for one disease or procedure. Deep, curated, consistent, and limited to what the registry was built to capture.
Biobank
Biological samples with linked clinical records. The bridge between what is in a person's biology and what happened to them.
Genomics and precision medicine
Sequencing and molecular profiling linked to outcomes. Where targeted-therapy questions are actually answerable.
Linked data
Two or more sources joined at the patient level so a journey can be followed across settings. The most valuable and the most governed.
Population data
Census and vital statistics. Not clinical, but the denominator. Without it a count is a number, not a rate.
Epidemiological studies
Existing cohort and surveillance studies. Often the fastest route to a defensible incidence or prevalence figure.
Availability differs by market. A data type that answers your question in one country may not exist, or may not be releasable, in the next. Read the full deep dive on all twelve or see what is available where.
From first conversation to first deliverable
You see the direction before you see the deck.
Five steps, and the second one is the one that saves you money. A written feasibility view arrives before any money moves, and it sometimes says no.
1
Your question
A conversation, under NDA if you prefer. What decision are you trying to make, and by when.
2
A written feasibility view
Is it answerable, in which market, from which data type, how fast. In writing, before money.
3
Scope signed
Method note and cohort specification agreed and dated. This is where most projects are saved or lost.
4
Approvals and extraction
Run in parallel with analysis design wherever governance permits.
5
Interim read, then final
You see the direction before you see the deck.
Alongside every engagement, from step three: weekly updates, monthly stakeholder reviews, methodology agreed before work starts, quality control at every phase, interim reports rather than a single reveal, and milestones you accept rather than discover.
Four to six weeks to a first feasibility read on hospital records where access is already established. Four things decide whether you get that: whether access exists, what approvals are needed, how precisely the question is specified, and how many markets are involved. The detail is here.
Who does the work
Meet the firm
Senior researchers who already know your market's data.
Real-world data punishes generalists. The difference between a defensible result and a misleading one is usually something nobody wrote down: a coding change three years ago, a scheme rule that makes an obvious denominator wrong, a field that means one thing in one province and something else in the next.
Aurumetrics runs as a network of the people who know those things. Senior researchers, many holding doctorates and post-doctoral research backgrounds, with two decades or more working directly with their own country's health system and its datasets, plus the analytics teams of our alliance partners in each market.
Large vendors put a senior name on the proposal and a junior team on the work, because a pyramid has to be fed. There is no pyramid here to feed, so the person who knows the market is the person on your project.
Local system expertise
How the health system actually pays, codes and records, and what that does to a denominator.
Local data expertise
Which datasets exist, who holds them, what they will and will not release, and how long each step takes.
Disease and therapy-area depth
What a clinically meaningful cohort looks like in this indication, and which endpoints a payer will accept.
Technical depth
Study design, causal inference, linkage quality, and the discipline to say when a result will not hold.
The limits, stated plainly
Any supplier who will not tell you what they cannot do is telling you something else.
- We do not licence anyone's database. No feeds, no data subscriptions, no identifiable records, and we will not resell an alliance partner's data.
- Records cannot be joined across national health systems in this region. Multi-market work is harmonisation, not linkage, and we publish where the comparison stops being defensible.
- We will not quote a timeline before we know what the question needs. Approval timelines, not analysis, decide most schedules here.
- We do not run clinical trials, and we do not produce evidence to a predetermined conclusion.
- We do not name our alliance partners publicly. Named under NDA on request, disclosed by role in every contract.
Send us the question you actually need answered.
We will tell you whether the data can answer it, in which market, and how long it will take, before you commit anything.