Your protocol is ready, but the database is not
We translate protocol-defined endpoints, visit requirements and operational data needs into eCRFs and database structures designed for reliable downstream analysis.
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Clinical data management for medical devicesEclevar provides specialized clinical data management for medical device investigations, from protocol review, eCRF design and database build through data cleaning, reconciliation and database lock.
A traceable clinical database, designed to support inspection readiness and downstream statistical analysis, without a fragmented chain between clinical operations, data management and biometry.
European delivery, with clinical operations covering the DACH region.
Most conversations start from one of six situations, each with a different scope and a different entry point.
We translate protocol-defined endpoints, visit requirements and operational data needs into eCRFs and database structures designed for reliable downstream analysis.
We can add independent data management capacity without replacing your clinical operations team. Site relationships stay where they are; the queries, coding and reconciliation move.
We review open and aging queries, coding status, external data reconciliation, critical data completeness and lock documentation, then work the remaining list in priority order.
High query volume can reflect avoidable design issues, not only site performance. We review data capture design, edit check logic and form structure to remove unnecessary site burden.
Some sponsors prefer data management held separately from the party running the sites. Eclevar can act as a full service partner, an embedded resource or a specialized remediation team.
Traceability from the source record to the analysis dataset is built during the study rather than reconstructed afterward. We work backward from the evidence the submission has to carry.
Eclevar can own the full sequence or take a defined part of it. What does not work is a chain with a gap in the middle, where nobody owns the point at which one stage hands over to the next.
Scope is agreed stage by stage. A sponsor may hand over the full sequence, or only phases 3 and 4 on a study that is already running.
Eclevar can take responsibility for the complete clinical data management lifecycle, or integrate with your existing CRO, EDC vendor, statistics group or internal clinical organization. Data issues are easier and less disruptive to address during protocol and eCRF design than immediately before database lock.
Data management should begin before the database build. We read the protocol as a data specification and agree what is collected, at which visit, and what happens to it afterward.
The data management plan is the operational control document for the study, where decisions that would otherwise be made informally are written down and agreed with the sponsor.
Device studies collect information a pharmaceutical eCRF is not built to hold. Depending on the device and study design, the form may need to carry the procedure, the device and the technical performance of both.
eCRF design influences site burden, query volume, missing data, and whether an endpoint stays interpretable once the data are in.
We build the study in the environment that suits the program: a sponsor system, a third party platform, or the Milo environment used on Eclevar studies. What we sell is data management expertise, not a software license.
A database goes live once it has been shown to behave as specified, and once that demonstration is documented. Retrofitting the documentation later is the most common gap we find on rescue engagements.
Before the first participant is entered, we map the datasets that will exist outside the primary EDC and agree who owns each transfer, in which format, at which frequency.
The alternative is a backlog discovered at the end, when the sites have moved on and every question costs more to answer than it would have at the time.
Data review is continuous and prioritized by what the study has to demonstrate. Critical and endpoint data are reviewed on a defined cycle; lower-risk fields are handled through automated checks.
Queries are a cost borne by the sites, so the objective is the smallest number that resolves the real issues. We track aging as closely as volume.
Coding is performed against the dictionary versions agreed in the data management plan, with a documented review route for terms needing clinical input.
Medical device studies may generate substantial evidence outside the primary EDC, including imaging, core-lab, device-generated, safety and eCOA data. The clinical database should remain consistent with the external evidence used to evaluate device safety and performance.
Not every field deserves the same attention. Review effort is concentrated where an error would change the conclusion of the study, and the reasoning is documented so it can be explained later.
Our data managers work alongside the people who run the sites, so a pattern in the data can be assessed as a training issue, a form design issue or a clinical signal without waiting for the next steering meeting.
Lock is the point at which the study stops being an operation and becomes evidence. It should be a controlled milestone, not an emergency clean-up exercise.
Before we recommend a lock, we work through a readiness review against criteria agreed in the data management plan. As applicable to the study, that covers:
A lock that is a surprise to anyone in the study team was not a controlled lock.
The handover is a structured, documented dataset in the format agreed with the statistician, with the definitions and derivations that go with it. Controlled and traceable documentation is built during the study and designed to support inspection readiness, rather than reconstructed at the end. If an unlock becomes necessary, it is handled under change control, with the reason, the change and the re-lock documented.
Scope varies by study. This is the standard deliverable set named in an Eclevar data management scope and budget.
| Study stage | Typical Eclevar deliverable |
|---|---|
| Planning | Protocol and data strategy review |
| Setup | Data management plan |
| Data capture | eCRF specifications and site completion guidelines |
| Database | Configured EDC database |
| Validation | UAT and validation documentation |
| Conduct | Data review and query management |
| Coding | Medical coding |
| Integration | External data reconciliation |
| Quality | Data quality reviews |
| Close-out | Database lock documentation |
| Handover | Clean analysis-ready clinical data |
A device study is not a drug study with a different intervention. The unit of analysis often includes an implant, an operator and a procedure, and a substantial share of the evidence may arrive from outside the EDC.
Each source that applies is mapped, transferred against a specification and reconciled on a defined cycle, so the clinical database stays consistent with the external evidence used to evaluate safety and performance.
Structured for the statistical analysis the protocol requires, with definitions, derivations and a traceable route back to the source record.
Which sources apply depends on the device and the study design. A single-center early feasibility study and a multicenter pivotal investigation carry very different reconciliation loads.
Implant and procedure characteristics, operator and technique variables, and the device identifiers that let a later question about a specific unit be answered.
Structured collection, classification and reconciliation of deficiencies, malfunctions and the events they lead to, aligned with the reporting obligations that apply to the study.
Integration and reconciliation of independent assessments, including adjudicated endpoints, where the clinical conclusion depends on a reading performed away from the site.
PMCF and long-term observational designs can put years between the procedure and the last data point, which changes how identifiers, visit windows and missing data are handled.
Higher-frequency, machine-generated data needs a defined transfer, storage and reduction rule before it reaches the clinical database, or it becomes unusable volume.
Early feasibility databases have to absorb evolving procedural experience. Pivotal databases are built tightly around prespecified endpoints. The design decisions are not interchangeable.
Already working with another CRO or EDC provider? You may not need to replace the entire study team.
Many data management problems are contained. They sit in the database, in the query backlog or in the documentation, and a separate team can work on them without disturbing site relationships that took a year to build. Eclevar can be engaged for a defined remediation scope with a defined end point.
The right model depends on what you already have in-house, not on what is easiest to sell.
We want one partner to own CDM
Eclevar manages the function from protocol review through database lock and dataset handover, with a named data manager, a data management plan and one accountable route for every data question.
We need additional capacity inside our existing structure
Eclevar data managers work inside your organization, your systems and your procedures. You keep the platform, the standards and the oversight; we supply the people and the device experience.
We need a specific data problem fixed without replacing the entire CRO
A scoped engagement against a defined problem: database remediation, a cleaning or coding backlog, reconciliation, validation documentation or lock preparation, with a clear definition of done.
A randomized post-market clinical follow-up program in diabetic foot ulcers and venous leg ulcers, across France, the United Kingdom, Germany, Italy and Spain. Two wound populations with different assessment schedules had to produce data reviewable on a common structure.
Eclevar designed and is managing the program, including the clinical data management function across all participating countries.
eCRF design across both cohorts, database build in the Milo environment, data review, query management and reconciliation across five countries, on one data structure and one set of review rules.
Evidence intended to support EU MDR clinical evaluation and post-market surveillance documentation for the sponsor's chronic wound care portfolio.
Program described with the sponsor's permission. The program is ongoing. Figures describe the program design as planned, not completed follow-up. No clinical result, performance conclusion, regulatory outcome or authority acceptance is claimed or implied.
Data management is a named-person service. These are the people a sponsor deals with, not a resourcing pool.
Chief Data Officer · Biometry Lead
30+ years in clinical biometry. Sets data strategy and clinical data architecture across Eclevar programs, and owns the interface between data management and biostatistics, so databases are designed for the analysis they will have to support and not only for the data they will collect. Oversight of complex multicountry medical device data environments, across EDC and eCOA.
Senior Clinical Data Manager
10+ years in clinical data management. The hands-on lead on sponsor studies: eCRF design, EDC database build and configuration, validation, data cleaning, query management, consistency checks and database lock readiness through to the final analysis-ready dataset. If you engage Eclevar for data management, this is the level at which your study is run day to day.
Head of Quality & Compliance
The quality and governance interface supporting data management: QA oversight, controlled processes, documentation and data governance, procedural compliance and the quality system interface, with inspection readiness designed into the workflow. He is not the data manager on your study; his role is why data management sits inside a documented quality framework rather than individual habit.
One accountable chain from clinical data collection through quality oversight to analysis-ready datasets.
Every link in this chain is a decision, and a decision taken at one end constrains the other.
Eclevar's clinical data management and biostatistics teams work within the same broader data and biometry capability, helping reduce handoff gaps between database design, database lock and final analysis.
We are precise about this, because imprecision here is expensive later. Data management processes are designed against the requirements below. Meeting the requirements of one framework does not establish anything about another.
Eclevar does not represent that any study, dataset or system is certified or accepted by a Notified Body or a competent authority, and does not claim a guaranteed inspection outcome.
Data management designed around device, procedural and operator data, not adapted from a pharmaceutical template each time a device study arrives.
Data strategy set by the head of the biometry function, not delegated to whoever has capacity in the resourcing model that quarter.
Our data managers understand how the data were generated because they work alongside the monitors and project managers who generated them.
Data management operates under documented procedures with independent quality review, rather than the personal method of the data manager assigned.
Full service, embedded resource or a scoped rescue. Sponsors move between models as a program matures, and the contract should allow it.
The question we ask at eCRF design is what the statistician will need at the end. It is the cheapest question in the study, and the one most often skipped.
It is responsible for the clinical data of a study from the moment the protocol defines what will be collected to the moment a locked dataset reaches the statistician: data management strategy, eCRF design, the EDC database and its validation, data review and cleaning, query management, medical coding, reconciliation with external datasets, and database lock. In a device study it also covers the device, procedural and technical performance data a general clinical database is not designed to hold.
Before the protocol is final, where possible. A data manager reading a protocol draft will ask which variable each endpoint resolves to, which data arrive from outside the EDC, and how missing data will be handled. Those questions change the protocol, and they are easier to answer then than immediately before lock.
Yes. Data management is regularly contracted as a standalone function while another party runs the sites, or while the sponsor runs them internally. What we agree at the start is the interface: who owns the site relationship, who raises and chases queries, who owns the protocol deviation record, and who signs the lock.
Yes, and it is a common engagement. A transition starts with an independent review of the database, the validation documentation, the open query and coding position, and the state of external data reconciliation, so both sides know what is being inherited. We then agree a scope with a defined end point rather than an open-ended remediation.
Typically the data management plan, eCRF specifications and completion guidelines, the configured EDC database, validation and user acceptance testing documentation, data transfer specifications, ongoing data review and query management, medical coding, reconciliation of external datasets, quality review records, the lock readiness review and the final analysis-ready dataset. The exact list is written into the scope.
The data model has to carry the device and the procedure, not only the participant: identifiers, characteristics, implantation detail, deficiencies, malfunctions, revisions and explants, and often technical performance measured by the device itself. A larger share of the evidence may sit outside the EDC, in imaging, core laboratory and adjudication datasets, so reconciliation carries more weight. Post-market follow-up periods are also longer, which changes how identifiers, visit windows and missing data are handled.
Yes. We manage data for clinical investigations conducted under EU MDR and for medical device studies conducted under applicable FDA requirements, including IDE studies, as well as for programs running in both regions. The data management plan records which requirements apply to which part of the program, because the answer is often not the same across a single study.
Whether you need full-service clinical data management, additional CDM capacity or targeted support to bring a delayed database to lock, Eclevar can provide a specialized medical device data team aligned with your clinical and regulatory program.