Send monitoring effort where the risk actually is.
Risk-based monitoring fails for a dull reason: the signals live in one system and the visit schedule in another, so the schedule wins. When enrolment, queries, deviations and document gaps sit beside visit planning, risk can change next week.
- Site risk scoring
- Configurable indicators
- Feeds visit planning
- ICH E6(R3) aligned working
- 01Enrolment pace vs plan
- 02Query volume and ageing
- 03Protocol deviations
- 04Overdue monitoring actions
- 05Site file gaps and expiries
- 06Training and delegation status
Scored without an export, a warehouse or an overnight refresh.
The signals and the schedule are in the same system.
Risk-based monitoring usually fails at the last step: the analysis is sound but lives in a tool with no route back to where visits are planned. Here scoring and planning are the same platform.
Nothing has to be exported
Enrolment, queries, deviations, overdue actions and document gaps are already operational records.
Automatic flags, not a monthly deck
A threshold crossing raises a flag as it happens, and notifies whoever owns that site.
Risk feeds visit planning
A site whose score moves is proposed for the next monitoring cycle, in the same tool.
Every score decomposes
The contributing signals stay visible. A score nobody can take apart is one nobody acts on.
Reports and portfolio view
Compare risk across sites and across studies, from the same report library.
The rationale is recorded
Why monitoring effort was allocated as it was is captured alongside the decision, which is what an inspector asks for.
Sites, ranked by what is actually happening.
Composite score from the configured indicators, with the contributing signals visible. Illustrative data.
| Site | Enrolment | Open queries | Deviations | Overdue actions | ISF gaps | Risk |
|---|---|---|---|---|---|---|
| Site 07 Lyon | 38% of plan | 24 · 9 aged | 6 | 3 | 5 | High |
| Site 04 Berlin | 91% of plan | 11 · 2 aged | 2 | 3 | 3 | Elevated |
| Site 02 Madrid | 104% of plan | 6 · 0 aged | 1 | 1 | 1 | Elevated |
| Site 09 Milan | 88% of plan | 4 · 0 aged | 0 | 0 | 0 | Low |
| Site 01 Paris | 112% of plan | 3 · 0 aged | 0 | 0 | 0 | Low |
From signal to changed behaviour.
Composite site score
Weighted across the indicators you choose, recomputed as records change.
Contributing signals
Every input stays visible. A score you cannot decompose is one nobody trusts.
Feeds visit planning
Risk changes which sites are proposed for the next monitoring cycle.
Escalation thresholds
Define what counts as escalation, and who is notified when a site crosses it.
Documented rationale
Why effort was allocated as it was, recorded alongside the decision.
Portfolio view
Compare risk across studies, not only across sites within one.
Common questions
How does this relate to ICH E6(R3)?
ICH E6(R3) expects sponsors to identify factors critical to quality and to apply monitoring proportionate to risk, rather than verifying everything everywhere at a fixed frequency. MonitoHQ supports that way of working by surfacing site-level risk signals and letting visit planning respond to them. The framework itself — your critical-to-quality factors, your risk assessment, your monitoring plan — remains yours to define; software does not supply it.
Where do the risk signals come from?
From operational records the platform already holds: enrolment pace, query volume and ageing, protocol deviations, overdue actions from previous visits, site file gaps, expiring documents, delegation and training status. Nothing needs to be exported or re-entered to be scored.
Can we define our own indicators and thresholds?
Yes. Which signals count, how they are weighted and what threshold constitutes an escalation are configured per study. A first-in-human study and a late-phase registry do not share a risk profile.
Does this replace on-site monitoring?
No. It changes how you decide where on-site effort goes. Some sites will warrant more visits than a fixed schedule would give them and some fewer, and the point is to make that judgement from evidence rather than from the calendar.
Is this the same as centralised statistical monitoring?
No. MonitoHQ scores operational risk from clinical operations signals. It is not a statistical data-surveillance product and does not perform statistical outlier detection on clinical data.
Connected in the same platform
Bring your risk indicators.
30 minutes with a founder. Tell us which signals you'd actually act on and we'll configure the scoring live against illustrative sites.