CLIP (CASRAI)

Clinical Data Management Certification

LevelProfessionalCLICLIP (CASRAI)

Lessons

12 modules

Domains

Exam blueprint

Exam items

Per attempt

70%

Pass mark

Fixed, uncurved

Retake wait

Days

What you earn

The credential itself

Pass the examination and CASRAI issues this certificate and the post-nominal CLIP (CASRAI), signed by the Programme Director and verifiable by anyone, permanently, from the code on its face.

CASRAI Certification

Certificate of Professional Competence

This is to certify that

Dr. Amelia R. Hartley

has completed the prescribed programme of study and passed the examination in

Clinical Data Management — Professional

and is admitted to the designationCLIP (CASRAI)

Verify atcasrai.org/verify/CASRAI-CLI-2026-6U7IBV

Specimen. Issued as a signed PDF and as a machine-readable Open Badge; the holder and code shown are illustrative.

How it appears on your CV

Certifications

CLIP (CASRAI) — Clinical Data Management, Professional

CASRAI·Issued Mar 2026·Credential ID CASRAI-CLI-2026-6U7IBV

casrai.org/verify/CASRAI-CLI-2026-6U7IBV

Every certificate is issued under the signature of Dr. Diana Nieves Castro, MD, Programme Director of CASRAI Certification, who sets the syllabus, blueprint and pass mark for this credential.

It certifies that its holder passed the CASRAI examination for this course on the date shown, scored against the blueprint and pass mark published on this page — and anyone can confirm it from the verification code, without an account and without contacting us.

About this credential

What it covers

Body of knowledge

Exam blueprint

The exam is assembled to these weights on every attempt. They are published before purchase because a blueprint you cannot see is not a blueprint.

Domains and weights7 domains · 39 scored items
Domain	Weight	Items
Data management planning and study start-upP1	14%≈ 5 items	≈ 5
Data collection design and collection standardsP2	15%≈ 6 items	≈ 6
Computerised systems, validation and data integrityP3	16%≈ 6 items	≈ 6
Data capture, cleaning and query managementP4	16%≈ 6 items	≈ 6
External data, medical coding and reconciliationP5	15%≈ 6 items	≈ 6
Data review, centralised monitoring and database lockP6	12%≈ 5 items	≈ 5
Submission data standards and data privacyP7	12%≈ 5 items	≈ 5
Total	100%	39

Item counts are approximate. Each attempt draws a fresh form to the weights above, so the exact number of items per domain varies between attempts.

Syllabus

12 modules, 12 lessons

Every lesson and every learning outcome is listed. The lesson bodies open on enrolment; nothing else about the course is withheld.

12 modules · 12 lessons

Lesson material opens once you are enrolled. The full syllabus and every learning outcome are shown here so you can judge the coverage before you pay.

Module 1
P-M1
1 lesson
1. Locked.Data management planning and the DMPLocked
  On completion you will be able to
  - N Author a complete data management plan for a supplied protocol.
  - N Construct a data flow diagram identifying every transfer and its control point.
  - A Set quality tolerance and review intensity proportionate to data criticality, and justify the proportionality against E6(R3) §4 and ICH E8(R1).
  - A Draft the CDM clauses of a service-provider agreement.
  - N Build a CDM timeline against go-live, FPI, interim analysis, DSMB deliveries and lock, and identify its critical path.
Module 2
P-M2
1 lesson
1. Locked.Collection design and CDASH implementationLocked
  On completion you will be able to
  - N Design a full eCRF set from a protocol.
  - A Apply the CDASH Model and CDASHIG to field naming and form structure.
  - N Evaluate the downstream mapping cost of a non-CDASH collection design.
  - A Design log forms, repeating events, unscheduled visits and partial-date handling.
  - N Govern a CRF library: reuse, versioning, change control, deviation from standard and its approval.
Module 3
P-M3
1 lesson
1. Locked.EDC build and user acceptance testingLocked
  On completion you will be able to
  - N Write a UAT plan with requirements traceability, scripts, expected results, evidence capture, defect logging and release criteria.
  - A Execute a scripted UAT pass and log defects with reproducible steps.
  - N Judge whether an unresolved defect may be accepted at release, and document the justification and mitigation required by E6(R3) §4.3.4(i).
  - A Apply E6(R3) §4.3.5 to the timing of trial-specific system release to an individual site.
  - N Design a mid-study change-control process covering revalidation against both previously-collected and new data.
Module 4
P-M4
1 lesson
1. Locked.Computerised system validation, security and user managementLocked
  On completion you will be able to
  - N Design a risk-based validation approach for a named system, scaled to intended use, data criticality and impact on participants and results.
  - A Map 21 CFR Part 11 §11.10(a)–(k) controls onto a system's design (US) and identify which are satisfied by the platform and which by the sponsor's procedures.
  - N Assess an investigator-deployed clinical-practice system (EHR, imaging, ISF) for fitness for purpose where it holds source records.
  - A Design a user-access model that survives an inspection: assignment by duty, blinding-aware, visible to the investigator, periodically reviewed, revoked on change.
  - N Design an audit-trail review procedure that is planned, risk-based and adjustable during the trial.
Module 5
P-M5
1 lesson
1. Locked.Edit checks, validation programming and cleaning strategyLocked
  On completion you will be able to
  - N Specify a complete edit-check set for a study, layered by check type and firing mode.
  - A Write testable check specifications with defined trigger conditions, query text and closure criteria.
  - N Evaluate a live study's check set against its query burden and recommend retirement of checks that generate noise.
  - A Apply E6(R3) §4.2.1(c) — automated validation checks considered "as required based on risk", with implementation "controlled and documented".
Module 6
P-M6
1 lesson
1. Locked.Query management and protocol-deviation dataLocked
  On completion you will be able to
  - A Run a query workflow end to end with routing, ageing, escalation and closure.
  - N Design deviation capture, categorisation and importance classification, and specify the handoff to the SAP's analysis-population definitions.
  - A Apply E6(R3) §4.2.4 to corrections: attribution, justification, support by source records "around the time of original entry", timeliness.
  - N Interpret a query-metrics pack and produce a corrective action plan that separates site issues, check-design issues and protocol issues.
Module 7
P-M7
1 lesson
1. Locked.External data acquisition and reconciliationLocked
  On completion you will be able to
  - N Write a data transfer specification covering format, variables, code lists, keys, frequency, mechanism, encryption, acknowledgement and failure handling.
  - A Run and reconcile a test and a production transfer.
  - N Design reconciliation for central and local laboratory data, ePRO/eCOA, imaging and centrally-read endpoints, device and sensor output, IRT randomisation and drug accountability.
  - A Ensure investigator access to external data that affects eligibility, treatment or safety (E6(R3) §2.12.3, §3.16.1(k)) without breaking the blind.
  - N Preserve blinding across the whole data architecture per E6(R3) §4.1.1.
Module 8
P-M8
1 lesson
1. Locked.Medical coding and SAE reconciliationLocked
  On completion you will be able to
  - A Apply coding conventions to verbatim terms and document the coding decision.
  - N Design a coding governance model: dictionary version selection, auto-encode rules, manual review, query-back thresholds, consistency review, upversioning strategy and its analysis impact.
  - N Design and execute SAE reconciliation between the clinical and safety databases, resolving discrepancies in term, dates, seriousness criteria, outcome and relatedness, and documenting closure.
  - R State the boundary: coding is terminology governance; causality, seriousness and severity are the investigator's medical judgement.
Module 9
P-M9
1 lesson
1. Locked.Data review, centralised monitoring and statistical surveillanceLocked
  On completion you will be able to
  - N Design a risk-based data review strategy: what, by whom, how often, against what, and how findings are actioned.
  - A Perform centralised monitoring as defined at E6(R3) §3.11.4.2(a) and contribute the data manager's share of it.
  - N Apply centralised statistical techniques — outlier detection, digit preference, variance and inlier analysis, enrolment and event-rate comparison, visit-window compliance — to identify systemic or site-specific issues.
  - N Convert a centralised-monitoring finding into a targeted on-site monitoring recommendation.
  - A Build patient profiles and listings that support medical review.
Module 10
P-M10
1 lesson
1. Locked.Database lock, unlock and the pre-analysis finalisationLocked
  On completion you will be able to
  - N Plan and execute the finalisation activities of E6(R3) §4.2.6(b) in full.
  - A Restrict edit access to data acquisition tools before final analysis and before unblinding (§3.16.1(r)); manage access around planned interim analyses (§3.16.1(q)).
  - A Obtain and evidence investigator endorsement of reported data at agreed milestones (§3.16.1(o), §2.12.5).
  - N Design and run a controlled unlock: trigger, impact assessment, authorisation, scope limit, re-lock, audit-trail documentation.
  - N Prepare the lock evidence pack an inspector would ask for.
Module 11
P-M11
1 lesson
1. Locked.Submission data standards: SDTM, ADaM and Define-XMLLocked
  On completion you will be able to
  - N Map a collected dataset to SDTM domains and justify domain and variable choices.
  - A Read an ADaM dataset and trace a derived analysis variable back through SDTM to the collected value.
  - N Review a Define-XML document for completeness: datasets, variables, code lists, computational method definitions, origins.
  - N Assemble and critique a submission data package from a reviewer's perspective.
Module 12
P-M12
1 lesson
1. Locked.Data privacy, eSource and direct data captureLocked
  On completion you will be able to
  - A Apply the HIPAA de-identification standard (US), choosing between expert determination and Safe Harbor and defending the choice.
  - A Apply GDPR concepts (EU/UK): lawful basis, pseudonymisation versus anonymisation, minimisation, retention, transfers, controller/processor roles.
  - N Assess re-identification risk in a dataset proposed for sharing.
  - N Design an eSource / direct-data-capture workflow and identify the source record at every point in it.
  - A Assess a clinical-practice computerised system for fitness for purpose in a trial, proportionately to data importance (E6(R3) §3.16.1).

Assessment

How the exam works

The exam is closed-book and multiple choice. Each attempt draws a fresh form to the domain weights above, so no two attempts are the same paper and no answer key circulates. The pass mark is 70% and is fixed — there is no curve, no quota and no adjustment by cohort.

Scoring is immediate. You are shown your overall result and, for every item, the option you chose, the correct option and the reasoning behind it — whether you passed or not. A failed attempt may be retaken after 90 days. The wait exists so a retake is a second attempt at the material rather than a second attempt at remembering the paper.

Forms are assembled to the blueprint above or not at all: where a domain cannot yet be sampled to that standard, the exam declines to start rather than issue an unbalanced paper. Your material and progress are never affected, and there is no time limit on when you sit.

Passing candidates are issued a certificate with a verification code. Anyone can check that code on our public verification page without an account and without contacting us.

Certifying authority

Signed by Dr. Diana Nieves Castro, MD

CASRAI’s certification programme is academically and medically directed by Dr. Diana Nieves Castro, MD, Programme Director, who sets the syllabus and blueprint for this credential and signs every certificate issued under it.

CASRAI has maintained the terminology and reporting standards of research administration for over a decade. It assumed leadership of the CRediT contributor-roles taxonomy in 2014 and carried it through to adoption as ANSI/NISO Z39.104-2022, now in use by publishers, funders and institutions worldwide. This examination is drawn from that body of work.

What the credential certifies: that its holder passed the CASRAI examination for this course on the date shown, scored against the blueprint and pass mark published above — verifiable by anyone, permanently, from the code on its face.

The ladder

Other levels of Clinical Data Management

Levels are independent purchases. There is no prerequisite chain — sit whichever level matches the work you already do.

CLIF (CASRAI)Foundation

Clinical Data Management — Foundation

Domains: 7
Exam items: 39
Cut score: 70%

$149USD

View credential

All CASRAI credentials

Common questions

About CLIP (CASRAI)

What is clinical data management certification?

It attests examined competence in collecting, cleaning, coding and locking clinical trial data to a standard a regulator would accept. The CASRAI credential covers CDASH, EDC build and validation, query management, medical coding, reconciliation and submission standards.

Do I need CDISC knowledge for clinical data management?

Yes. CDISC standards govern how trial data is structured for submission, and the CASRAI syllabus covers CDASH for collection and SDTM/ADaM with Define-XML for submission.

Is clinical data management a good career?

It is a specialist role with a defined body of knowledge and a clear standards base, which is precisely why an examined credential is worth holding rather than a course-completion certificate.