deliverable 7.5 ecrf & edc system - · pdf filems9 electronic data capture (edc) system...

FP7-ICT-2013-10 – 7.5 – eCRF & EDC System

Project No.

610425 Deliverable Report

D7.5, 31/10/2015, Revision: Final Version

of 22

D7_5_ElectronicDataCapture_final 11/11/2015

Deliverable 7.5

eCRF & EDC System

Dissemination

Level Type Delivery Month

Confidential (CO)

Restricted (RE)

Public (PU)

Report (R)

Prototype (P)

Other (O)

24

Deliverable D7.5

Milestone MS9

Work Package

Leader UKA-CTCA

Task/Deliverable Leader UKA-CTCA

Deliverable Due

Date 31.10.2015

Date of Submission 31.10.2015

Version 1.1

Keywords Data management plan

Internal Report Review Done by management body


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Version Control

Version Date Author (Name, Institution) Comments

1.0 31.10.2015 Alexandra Greindl

1.1 04.11.2015 Thomas Deserno

1.X = 1st version circulating between the members / 2.X = 2nd version following comments of members

/ 3.X = 3rd final version


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Data Management Plan (DMP)

Research Project RASimAs

I. Study Title

Evaluation of Regional Anaesthesia Simulator (RASim) System for self-directed Training of Novices in Regional Anaesthesia

II. Study Title

Evaluation of the functionality of the Regional Anasthesia Assistant System (RAAS) as aid for US-image interpretation in the context of the Femoral Nerve Block (FNB)

Study Protocol Version

01


01

Study Protocol Date

---

Study Protocol Date

---

Study Code

14-160

Study Code

14-161

Coordinating Investigator

Dr Brian O`Donnell, MD


Dr Oliver Grottke, MD, PhD

Document Version 01, First Version

Document Date 2015-09-28

Author Alexandra Greindl

This document contains confidential information. Any information concerning the clinical

research activities of the RASimAs project which has not been specifically released to the

general public should be treated confidentially.


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Document History and Approval Page

The Data Management Plan (DMP) is a living document throughout the life cycle of a study.

Therefore any changes or modifications made to the study protocol or any processes having

an impact on data management will also be covered within the DMP. Changes will be tracked

in the following modification history table.

Version Date Affected Section(s) Summary of Revisions Made

01 30-10-2015 --- First Version

01.1 31-10-2015 Completion & Minor Corrections

The undersigned have reviewed the DMP and agree to scope, content and responsibilities.

Draft versions do not need approval.

Name Function Date Signature

Prof Dr Thomas Deserno Consortium`s Leader, Chief Data Manager

Dr Alexandra Greindl Study Project Manager

Dr András Keszei Statistician


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In-Scope

The present Data Management Plan (DMP) establishes an overall plan for the requirements

of the data management (DM) and all DM activities to ensure the accuracy, integrity,

consistency, reliability, and completeness of data. The DMP refers to the studies which will be

performed within the RASimAs project with the following study titles:

Evaluation of the Regional Anaesthesia Simulator (RASim) System for self-directed

Training of Novices in regional anaesthesia

Evaluation of the functionality of the Regional Anaesthesia Assistant System (RAAS)

as aid for US-image interpretation in the context of the femoral nerve block (FNB)

Both studies includes physicians at the beginning of their education in regional anaesthesia as

study subjects. The studies are in a clinical context but will not require study related inclusion

of patients and will be conducted under no regulation by the National Drug or Medical Device

Acts.

Study related specifications (custom functionalities) affecting the data management are

described and listed as dynamic reference which is annexed to the DMP.

The DMP applies to all data management personnel and relevant departments assigned to

this study. This section includes roles and responsibilities of all key personnel being involved

in the associated data management processes and related activities.


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Table of Content

1 INTRODUCTION ................................................................................................................... 8

1.1 Context ...........................................................................................................8

1.2 Objectives .......................................................................................................8

1.2.1 Deliverable Description ................................................................................8

1.2.2 Milestone 9 ..................................................................................................8

LIST OF ABBREVIATIONS AND DEFINITION OF TERMS .................................................................... 9

2 DYNAMIC REFERENCES .................................................................................................... 10

3 RESPONSIBILITIES ............................................................................................................ 11

4 ELECTRONIC DATA CAPTURE (EDC) ................................................................................. 12

4.1 Types of Data ........................................................................................... 12

4.2 Design and Set-up .................................................................................... 12

4.3 Access rights ............................................................................................ 12

4.4 Database Setup and Management ........................................................... 13

4.5 Data Storage ............................................................................................ 13

4.6 Data Security ............................................................................................ 13

5 VERIFICATION OF EDC SETUP AND IMPLEMENTATION ........................................................ 14

5.1 System Specifications ............................................................................... 14

5.1.1 Technical Access Requirements .............................................................. 14

5.2 User Acceptance Testing .......................................................................... 14

6 DATA ENTRY .................................................................................................................... 16

6.1 Case Report Forms (CRFs) ...................................................................... 16

6.2 Pre-requisites for Site Data Entry ............................................................. 16

6.3 Granting Access to the Production Version of the EDC ............................ 16

6.4 Entering Data ............................................................................................ 16

7 IMAGE DATA HANDLING ...................................................................................................... 17

8 DATA VALIDATION PROCESS ............................................................................................. 17

8.1 Univariate Alerts ....................................................................................... 17

8.1.1 Valid Value Alerts for Multiple-choice Fields (select only 1) ..................... 18


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8.1.2 Valid Value Alerts for Multiple-choice Fields (select more than 1) ............ 18

8.1.3 Valid Value Alerts for Number Fields ........................................................ 18

8.1.4 Valid Value Alerts for Missing Data .......................................................... 18

8.2 Multivariate ............................................................................................... 18

8.2.1 Types of Multivariate Alerts ...................................................................... 18

8.3 Discrepancy Generation and Management .............................................. 19

9 PROTOCOL DEVIATIONS .................................................................................................... 19

10 REPORTS ......................................................................................................................... 19

11 RANDOMISATION ............................................................................................................... 20

12 ASSESSOR MANAGEMENT ................................................................................................. 20

13 CHANGES TO A PRODUCTION EDC .................................................................................... 21

14 DATABASE CLOSURE ........................................................................................................ 21

14.1 Closure Checks ........................................................................................ 21

14.2 Database Lock .......................................................................................... 21

15 DATA TRANSFER AND MAPPING ......................................................................................... 21

16 DATA ARCHIVING .............................................................................................................. 22


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1 Introduction

1.1 Context

The specifications given in the DMP, the processes, procedures, and responsibilities cover all

data management (DM) activities employed and performed, from creation of the case report

forms (CRF) to closure of a clean database, the data export to the statistician for analysis, and

archival.

Aim of the DMP is to create a database that provides high-quality data ready for analysis at

the end of the study. This requires that the numbers of errors and missing data are kept as low

as possible.

The DMP complies with regulatory requirements and guidelines, local laws of the countries

where the study is conducted, and the requirements of the protocol, as well as with the

standard operation procedures (SOPs) of RASimAs consortium.

1.2 Objectives

1.2.1 Deliverable Description

As stated in the Description of Work, the deliverable that constitutes this plan is described as

follows:

D7.5 eCRF & EDC System

Performing the clinical trials, all parameters will be captured in an electronic

Case Report Form (eCRF). It is planned to implement the eCRFs within the

open source system OpenClinica for Electronic Data Capture (EDC). The

deliverable is in form a web-address accessible with personalized login

data via the Internet. Then web page will allow feeding the patient-specific

clinical data into the corresponding report form, and automatically transfer

the data into the database.

1.2.2 Milestone 9

As stated in the Description of Work, the deliverable is described as follows:

MS9 Electronic Data Capture (EDC) system and Investigator´s

Brochure released


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List of Abbreviations and Definition of Terms

Abbreviation/Term Definition

CRA Clinical Research Associate (Monitor)

CRC Clinical Research Coordinator (Study Nurse)

CRF Case Report Form

CTC-A Clinical Trial Center Aachen

DCC Data Coordinating Center

Discrepancy Data point that fails to pass a validation check

DM Data Management

DMP Data Management Plan

DMP Data Management Plan

DMVP Data Management & Validation Plan

eCRF electronic Case Report Form

EDC Electronic Data Capture

EOT End of Trial

ICH International Declaration of Helsinki

ID Identity

KU Leuven Katholieke Universiteit Leuven

Multivariate Edit Check An edit check (above and beyond a range check, valid check, or required criterion) on a variable or set of variables on the same CRF page (module)

OC OpenClinica

RA Regional Anaesthesia

RAAS Regional Anaesthesia Assistant System

RWTH Rheinisch-Westfälische Technische Hochschule

SD Standard deviation

Sim Simulator

SOP Standard Operation Procedure

Study Project Manager Individual who manages the project at data coordinating center and takes over study team lead

UCC University College Cork

VPH Virtual Physiological Human

VR Virtual Reality

http://en.wikipedia.org/wiki/Standard_deviation


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2 Dynamic References

Dynamic references are part of the data management activities but not considered part of the

DMP. These documents are stored separately and annexed to this DMP.

Table 1: Dynamic References

Item Content Document Owner Comment

Annotated CRF and data entry screens

The full set of CRFs, including dataset and variable names, sorted in a modular schedule order

Study Project Manager

Data validation plan (DVP)

Univariate ranges, description of each electronic edit check

Study Project Manager Data validation plan will be reviewed by the data manager and the statistician; Data manager is responsible to integrate the edit checks in the database

Randomisation lists Creation of randomization list required to allocate study subjects and assessors randomly to groups and tasks, respectively

Statistician The statistician is the only person with access to the randomization list.

User accounts List of user accounts including names, email, and roles of each user

Study Project Manager Study Project Manager is responsible for creation of the list; Data manager is responsible for creation of user accounts

Invstigator`s brochure Instructions for implementation of the study protocol and the application of the electronic structures for data collection and recording



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3 Responsibilities

The Clinical Trial Center Aachen (UKA-CTCA) takes the lead in the data management

activities and delegate tasks to cooperation and project partners that are not executed by

employees of the CTC-A. Particularly all data management activities that require

computational expertise, soft- and hardware equipment, and technical environment are

assigned to the Department of Medical Informatics (UKA-IMI), RWTH Aachen University.

Table 2: Distribution of responsibilities of tasks for data management.

Task Description Person/ Department in

charge

eCRF design Definition of study protocol specific requirements,

completeness of relevant data, precise description

of parameters (format, unit, forms, alarm ranges,

rules), definition of study related validation checks


UKA-CTCA

Database setup Programming the specifications for data collection

and creation of eCRFs in OpenClinica

Data Manager

UKA-IMI

Database

maintenance

Hosting of the database is on the servers of the

RWTH Aachen University protected by external

firewalls.

Data Manager

UKA-IMI

User management Creation of site accounts and user profiles; support Data Manager

UKA-IMI

Database monitoring Query management, online monitoring Monitor

UKA-CTCA

Data entry Recording of study related parameters; processing

of queries

Investigator,

Clinical Research Coordinator

Study sites

Database closure Closure checks Monitor, Statistician

UKA-CTCA

Database lock Lock and archiving Data Manager

UKA-IMI


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4 Electronic Data Capture (EDC)

For the studies conducted within the RASimAs project OpenClinica is used as EDC system.

The electronic Case Report Forms (eCRF) are created with OpenClinica.

OpenClinica is a software solution that is used worldwide to collect (medical) data in studies

embedded in a clinical research setting. For this intended use, the OpenClinica software is

accepted by the US Food and Drug Administration (FDA)1. OpenClinica is developed

according to the requirements of the Operation Data Model (ODM) of the Clinical Data

Interchange Standard Consortium (CDISC)2. CDISC is an FDA-accepted standard for

submission of clinical data during the regulatory drug licensing procedures.

4.1 Types of Data

All study specific parameters is collected virtually anonymously in the EDC system. Personal

identifying information (i.e., names, date of birth, etc.) are not available in the system.

Information of each study subject is referred by a unique code used for de-identification

(pseudonym).

4.2 Design and Set-up

The Study Project Manager is responsible of drafting the study database specifications. The

Data Validation Plan defines three modules (see DVP):

1. Data collector I; baseline (un-blinded)

2. Data collector II; study event (un-blinded)

3. Data assessor (blinded)

There is one database specification template for each CRF module. These documents will be

used as the basis for the design of the study database and the set-up of the EDC system. Two

independent EDCs will be created, one for Modules 1 and 2 (data collectors) and one for

module 3 (data assessor) to allow blinded assessment.

4.3 Access rights

The access to each EDC system is controlled by user name and password. Roles are

connected to site-referential privileges or to access rights across all sites. The individual user

accounts with role-based data management and access privileges ensure that the site

personnel receive only sight of own data. Thus, data protection is retained.

The Data Manager is responsible of EDC user access management.

1 https://docs.openclinica.com/3.1/technical-documents/openclinica-and-cdisc-odm-specifications

2 http://www.cdisc.org/odm


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Table 3: Roles for user accounts and the corresponding privileges over the database.

Role Privilege over the database

Local Investigator Enter data, view subject data, resolve queries, validate

& sign data entry for own site

Clinical Research Coordinator (CRC) Enter data, view subject data, resolve queries for own

site

Clinical Research Associate (CRA)/ Monitor Review subject data, create queries across all sites

Data Manager Overall administrative rights

Statistician Data specialist,

Investigator across all sites

4.4 Database Setup and Management

The servers hosting the OpenClinica-based EDC for RASimAs are operated with respect to

the German Data Protections Acts at the department of Medical Informatics. Using the

infrastructure provided by the IT Center of RWTH Aachen University, daily backups are

performed from both, the servers (as virtual machine on VMware-systems) and the databases,

where study data is hosted. The backup files are encrypted such that they cannot be read by

personnel of the RWTH Aachen University IT Center.

4.5 Data Storage

All data and metadata are stored within relational databases according to the CDICS ODM

model. All data that is captured will be part of the data export for statistical evaluation and

assessment. The following data is stored:

Study structure including all relevant eCRFs, events and meta data allowing data

analysis via SAS

All data entries with type of entry (initial entry, changes of values), data entry person,

time stamp, old and new values tracked

All queries with complete courses for their clarification.

4.6 Data Security

The entire hard- and software of all computer systems which are operated by the Department

of Medical Informatics, RWTH Aachen University, is modelled according to the layer model as

defined by the Federal Office for Information Security (BSI). This includes structural analysis,

assessing the need of protection, threat and risk assessment as well as the establishment of

a protocol for data protection and safety.


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5 Verification of EDC Setup and Implementation

5.1 System Specifications

The system specifications are described by data entry screens and annotated CRFs.

5.1.1 Technical Access Requirements

Each user with a registered account requires an internet access for login to the system. The

EDC system is working in the standard browsers, recommended are Firefox and Google

Chrome, both guarantee best performance.

5.2 User Acceptance Testing

Each study-specific implementation of the EDC system will be tested by candidate users, with

the results being documented in a test summary report. The user acceptance test includes an

exercise involving data entry once for a complete mock subject from start to finish and second

a mock subject who discontinues early. The testing will include following items:

Item Details/Requirements of Testing

Univariate and valid value checks Confirm that checks have been properly imported from specifications document.

Multivariate and cross-checks Confirm a specified subset of data via test data designed to trigger a query.

Custom functions Confirm each custom function with test data designed to trigger an event

Generating of subject numbers Confirm that new subjects IDs are generated according to specifications

Customised form or variable deliverable Confirm against schedule of events and against other specifications

Derived variable computation Confirm against specifications using test data

Email alerts Confirm with test data designed to trigger email alerts

Role assignment Review system. Confirm using list of role functionality, have testers assigned to each role, and ensure that they are only able to do/see what they are to per their assigned role

Data upload Create test data to test upload function

System reports Review system reports and ensure that they are functioning according to expectations. Run reports on test data.


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Item Details/Requirements of Testing

E-learning specifications Ensure that any e-learning items are delivered based on stated requirements and roles.


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6 Data Entry

The investigator(s) or designee(s) will be responsible of the data entry through the EDC

system. The access to the EDC system is personalized, controlled by user name and

password. Any change in the database is registered by means of an audit trail. User name;

date and time; subject, table and, item identifiers; old and new values; and – if applicable – the

reason for change are recorded.

6.1 Case Report Forms (CRFs)

Study details like objectives, intervals, visits, investigators, sites, and patients are defined in

the database and CRF layouts are designed for data entry. These entry screens are tested

with dummy data before moving them to the real data capture. The details of each CRF are

described in a standalone document, as cited in the above dynamic references.

The Study Project Manager and the Statistician are responsible of defining the content of the

CRF based on the study protocol.

6.2 Pre-requisites for Site Data Entry

Before data entry starts, site data entries (investigators or designees) will be trained on the

specific EDC test system prior to being granted permission to work in the production version

of the EDC system. This procedure is for data entry training and user acceptance testing

concurrently.

All investigators and clinical research coordinators receive training sessions by instructions of

the Study Project Manager. They must enter test data, even invalid data into the test system

in a self-directed manner to become trained with the data entry procedures and the resolution

of queries. The monitor will review and approve these data or identifies need of additional

training.

6.3 Granting Access to the Production Version of the EDC

Once the test has been reviewed and approved, the Monitor will send a written request to the

data manager to grant production system access.

6.4 Entering Data

The system is used as initial data record. The data is entered into the system directly, and

paper-based records can be released form the EDC system as on-site documentations.


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7 Image data handling

Ultrasound images and video sequences as well as videos of the nerve block performances

will be uploaded by the the investigator(s) or designee(s). The statistician will be responsible

for a randomised allocation of the videos to the relevant blinded assessor according to the

randomisation list which is to the exclusive access of the statistician. The statistician will load

the videos to the relevant assessor access in module 3 as separate CRF tool for assessment.

Table 4: Electronic Data to be Integrated in the EDC

Data type CRF section Data source/ format

Frequency of transfer/location

Special Instructions

US sequence Collection CRF DICOM 1/1 Link transferred to assessment CRF

User videos Collection CRF MP4 1/1 Link transferred to assessment CRF

User activity report Collection CRF Excel 1

8 Data Validation Process

Generating high-quality data requires data cleaning methods to keep deviations from the

defined data specifications as low as possible and to provide valid data for statistical analysis.

According to the study protocol specifications, validity of data will be tested by automated edit

checks of the EDC system.

The Data Validation Plan (DVP) contains all edit-checks to be performed and the calculations

for derived variables are also prepared. The edit check programs in the DVP help cleaning up

the data by identifying the discrepancies (i.e., a data point that fails passing a validation check).

The Study Project Manager is responsible of writing and distribution of the Data Validation

Plan (DVP).

The Data Manager is responsible for implementation of standard validation checks beside new

study specific requirements for validation. Modifications can be done as the knowledge of the

study increases. A history of modifications will be conducted and reviewed, and the final

version must be signed and dated by the Data Manager and the RASimAs Consortium’s

Leader before the database lock. All version of this document will be stored in the Data

Management Trial Master File.

8.1 Univariate Alerts

The EDC system provides several univariate alerts.


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8.1.1 Valid Value Alerts for Multiple-choice Fields (select only 1)

The user is required to choose only one out of a series that represents different data

choices. Such multiple-choice fields are defined as <radio button> or they are installed

in a <dropdown> layout.

The user must record a coded value taken from a list that is usually presented on a

page/ another electronic system (i.e. randomization number). Incorrect codes are

detected and rejected by the edit checks scripts.

8.1.2 Valid Value Alerts for Multiple-choice Fields (select more than 1)

The user is required to choose at least one and is allowed to choose even all from a

series that represents different data choices. This type of multiple-choice field type is

defined as <checkbox>.

8.1.3 Valid Value Alerts for Number Fields

The user is required to enter a number in a format as indicated in the completion

guideline and notes provided by the system or the system will not allow data entry.

The system does not allow entering any character that fails the specification (e.g.,

letters in a number field).

If applicable, the edit check scripts will validate range of entered data.

8.1.4 Valid Value Alerts for Missing Data

To ensure completeness even in the case that data are not available what could be

possible for some selected items the user requires always to choose an answer like

<not done>, <unknown> or <not applicable>.

8.2 Multivariate

Multivariate alerts are relational alerts among groups of variables and among the same

variable for protocol specific assessment times. Such alerts are referred to as multivariate

alerts (within on module, one assessment time).

8.2.1 Types of Multivariate Alerts

Confirming that <Other, specify> is completed when <Other> is marked.

Confirming data of part-fields which are references for system-based calculations when

calculated values are out of indicated range (i.e., BMI calculation based on weight and

height).

Generating automated plausibility checks to monitor that all inclusion and exclusion

criteria are applicable or if not to proceed with the End-of-Trial Form (EOT) and to

indicate dropout of the subject.

After filling the EOT form automated emails will be sent to the Monitor and Statistician

of the study.


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8.3 Discrepancy Generation and Management

Discrepancies may occur due to inconsistent data, missing data, range checks, and deviations

from the protocol. Management of discrepancies contains the following activities:

Reviewing discrepancies.

Detecting root causes and identify systematical errors that could require improved

workflows.

Resolving discrepancies with documentary tracking or declaring them as “acceptable”

due to non-resolvability.

Deviations from the data entry specifications trigger queries that will be resolved by the

database users with the access rights to enter data and resolve queries. Queries are issued

manually by the monitor, data manager, or data specialist, or they are generated automatically

by the EDC system. The discrepancies are flagged to the investigator or clinical research

coordinator for clarification. Additionally, the corresponding users receive system-generated

emails informing them that a query has been generated and require clarification. The data

entry person can resolve the discrepancy or writes the explanation of the reason that causes

the discrepancy into the separate query window of the EDC system. The monitor will be in a

close contact with the site personnel and clarification will take place by phone and email as

well.

OpenClincia provides a complete internal logging for documentation and archiving of queries.

The monitor is responsible to review the queries regularly and to follow-up all queries that

needs to be resolved. Once a query is resolved the monitor will close the query.

9 Protocol Deviations

Protocol deviations are identified from two different sources:

Automatically coded: most of the protocol deviations will be identified automatically

during the data cleaning process by the edit checks.

Manually coded: Protocol deviations that are not evident from CRF data or cannot be

programmed to be detected automatically must be identified by the data reviewer

(mainly the Clinical Research Associate (CRA) or the Monitor). The CRA is responsible

to register the protocol deviations and send them to the Data Manager.

The Data Manager is responsible of gathering all protocol deviations and incorporating them

into the clinical database.

10 Reports

Two types of reports are provided periodically (Tab. 5).

Table 5: EDC reports relevant for management of data collection and analysis.


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Report Name Description/Purpose Frequency Recipients/User Method for Provision

Query override report for EDC

List all queries where the data entry user overrode the query with no change, includes the explanation for the change/DM review for acceptability of overrides.

Monthly Monitor Automated report generated by EDC system

SAS raw data collection

Raw data report of data fields for final statistical analysis; entries of text fields are not part of this report. Filter functions allow directed requests of data

Once Statistician Automated report generated by EDC system

11 Randomisation

Randomisation of study subjects is done by a standalone tool. The Statistician provides a

randomization scheme to the randomizer tool. The data entry person on site is responsible to

create new subjects within the system and to apply the randomization tool. After receiving the

unique randomization number for the subject, the data entry person enters this number into

the EDC system manually, and uses this number continuously for identification of every source

data collected for this subject.

The Statistician creates a separate list for a random allocation of the videos of the trainees’

performances for evaluation by assessors. Assessors are investigators of any participating

study site. It will be excluded by the Statistician that a video will be allocated to an assessor of

the same study site.

12 Assessor Management

Study performances of the study subjects will be assessed by independent and blinded

assessors. Since the EDC system of OpenClinica does not provide flexibility that goes experts.

Beyond the roles and their corresponding privileges over the database, the module that is

created for assessment by the assessors is set up as a separate EDC system. The CRF

system for the study will be decomposed in a data collection system with an affiliated

assessment CRF tool. That ensures keeping the assessors blinded for the group allocation of

the subjects and for other data of the study sites.

The Statistician will provide the information required to be assessed by the assessors to the

independent CRF assessment module according to the randomization list.

Videos and ultrasound image material are stored within the CRF sections, which do not grant

access to the assessor. The Data Manager will provide links of the uploaded image material

to the assessment CRF section according to the instructions of the Statistician.


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13 Changes to a Production EDC

Changes of the study protocol or other substantial changes during the course of a study may

result in modifications to the EDC system. Changes can be directed only towards the future.

Thus, a new database test version is set up by the data manager according to the new

specifications and requirements defined by the Study Project Manager. This test version must

pass the user acceptance testing as performed with the initial database test version. Users

give feedback to the new version via email to the Study Project Manager, who reviews the

user’s comments and forward the essential information of the feedback to the data manager.

If changes of the database are accepted by the users and include all necessary changes for

the substantial amendment, the Study Project Manager sends a written request to the Data

Manager to grant production system access.

14 Database Closure

This section describes all processes associated with final database closure.

14.1 Closure Checks

Prior to database lock, a set of closure procedures are performed to verify the integrity and

completion of the database. In some cases, this may be the same data checks described in

the sections above, which are repeated until all queries are resolved and the data is

determined to be clean. Other appropriate checks at this stage may include:

Check that all expected CRFs have been entered.

Determine the status of each subject entered (i.e., excluded, ongoing, completed,

withdrawn, lost-to follow-up).

Check for data formatting problems in database exports.

Confirm that all expected site signatures have been applied.

14.2 Database Lock

Prior to final database lock a separate soft lock will take place to perform an audit in which a

completed CRF is compared to an exported SAS dataset to ensure integrity of the final study

data.

15 Data Transfer and Mapping

The Data Manager must prepare the database system to export the data when necessary.

After the database has been locked, the Data Manager is responsible of releasing final study

data to the Statistician in order to conduct the final statistical analysis.

All data and metadata is exported as CDISC ODM and transferred to R for statistical analysis

using a script-based import (ODM to R).


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16 Data Archiving

All study data recorded is considered as source document and archived on site until the end

of the RASimAs project.

Archival of electronic data is done in compliance with the data security concept of the

Department for Medical Informatics, RWTH University Aachen.

7th Framework

Programme

Project No. 610425

V01, 2015-09-28

DRAFT Data Validation Plan Page 1 of 23

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and

demonstration under grant agreement no 610425

Confidential

Data Validation Plan

Research Project RASimAs

I. Study Title

Evaluation of Regional Anaesthesia Simulator (RASim) System for self-directed Training of Novices in Regional Anaesthesia

Document will be updated for RAA study


01

Study Protocol Date

---

Study Code

14-160


Dr Brian O`Donnell, MD

Document Version 01, First Version

Document Date 2015-09-28

Author Alexandra Greindl

7th Framework

Programme

Project No. 610425

V01, 2015-09-28




Confidential

Document History and Approval Page

Any changes or modifications made to the study protocol or any processes having an impact

on data recording and validation will also be covered within the DVP. Changes will be

tracked in the following modification history table.

Version Date Affected Section(s) Summary of Revisions Made

01 28-09-2015 --- First Version

01.1 31-10-2015 Completion & Minor Corrections

The undersigned have reviewed the DMP and agree to scope, content and responsibilities.

Draft versions do not need approval.

Name Function Date Signature

Prof Dr Thomas Deserno Consortium`s Leader, Chief Data Manager

Dr Alexandra Greindl Study Project Manager

Dr András Keszei Statistician

7th Framework

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Project No. 610425

V01, 2015-09-28




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Table of Content

Document History and Approval Page ___________________________________________ 2

Table of Content ____________________________________________________________ 3

1 Introduction ____________________________________________________________ 4

2 Validated data entry _____________________________________________________ 5

3 Test Access for data entry training __________________________________________ 6

3.1 RASim Study: Data collector _________________________________________________ 6

3.2 RAA Study ________________________________________________________________ 6

4 Visit based CRF modelling _________________________________________________ 7

4.1 Visit based CRF modelling ___________________________________________________ 7

4.2 Study Site based CRF Modelling ______________________________________________ 8

5 Database specifications __________________________________________________ 9

5.1 Specifications: Module 1 (Data collector) _______________________________________ 9

5.2 Specifications: Module 2 (Data Collector) _____________________________________ 10

5.3 Specifications: Module 3 (Assessor) __________________________________________ 11

7th Framework

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Project No. 610425

V01, 2015-09-28




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1 Introduction

The Data Validation Plan (DVP) contains all edit-checks to be performed and the calculations

for derived variables are also prepared. The edit check programs in the DVP help cleaning

up the data by identifying discrepancies.

Study details like objectives, intervals, visits, investigators, sites, and patients are defined in

the database and CRF layouts are designed for data entry. These entry screens are tested

with dummy data before moving them to the real data capture.

The Clinical Trial Manager is responsible of DVP writing and distributing. The Data Manager

is responsible for implementation of standard validation checks and new study specific

requirements for validation.

The DVP is based on the information given in the CRF, the protocol, the Data Management

Plan (DMP), and the responsibilities defined within a study working plan.

Modifications of the DVP can be done as the knowledge of the study increases. A history of

modifications will be conducted and reviewed, and the final version must be signed and

dated by the Consortium’s Leader, the Study Project Manager and the Statistician before the

database lock. All version of this document will be stored in the Data Management Trial

Master File.

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2 Validated data entry

The EDC system provides several tools to improve reliable and validated data entries.

Validation checks can be provided only to data entry types as listed in the table below. Free-

text fields cannot be captured by automated validity checks. Contents of free-text will not find

the way into automated data queries.

Figure 1: Applied entry validation tools and tools to improve accuracy of data.

Tool Type Description Effect

Select only one Radio Button

Dropdown

Boolean selection

Only one option is possible to be selected

Unique answer

Select at least one Checkbox More than one option can be selected from a series of answers

Relevant answer options can be captured

Calendar function Date Data entry simplification Reduction of data entry errors due to wrong formats

Preset number format*) Number Sets of numbers before and behind the point are defined, or format is whole-numbered.

Only plausible number formats are accepted

Data file File Binary files for image and video data

Transfer and storage in on the host; creating a link in the eCRF

Mandatory field*) Force Data entry person is forced to fill the field.

Reduction of loss of data

Triggered questions Hide Sub-questions related to superior questions fade in only if the conditional relation is applicable

Improvement of interface usability due to greater clarity and reduction of loss of information

Automated calculation Calc Derivation of variables by automated calculation (e.g., BMI calculation)

Elimination of calculation errors

On- screen instructions Help Text Help texts continuously remaining on the screen or fade in as alert information will help to identify entry mistake and how to neutralize alerts

Instructions for self-directed resolution of alerts and queries.

Mail alert feature E-mail Monitor, Data Manager, Statistician receive alert-triggered emails for information, review and introduction of measures if needed

Allows immediate intervention by authorized data entry experts to monitor and in case of need to take corrective actions

*) Queries are created (red flags) and warnings fade in if the CRF page is saved with fields

incompleted. or incorrectly filled

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3 Test Access for Data Entry Training

3.1 RASim Study: Data collector

The training system for data entry by study staff with sight views for own data entries (CRF

module 1 &2), can be accessed through the link and login data below:

URL: http://oc-dev.imib.rwth-aachen.de/ (TST 187) Study: RASimAs – SIM (CTC-A 14-160) Site: Data Collector Site (14-160 Assessment) Visits:

Screening/Baseline

1st FNB

3rd FNB

5th FNB Login data (Role: Data Entry Person): User Account: data_collector_sim

Password: data_collector_sim

The training system for data entry by assessors with sight views for own data entries (CRF

module 3), can be accessed through the link and login data below:

URL: https://oc-dev.imib.rwth-aachen.de/ (TST 187) Study: RASimAs – SIM (CTC-A 14-160) Site: Assessor 01 (S_ASSESS01) Visit: Assessment 1st FNB Login data (Role: Data Entry Person): User Account: assessor_01_sim Password: assessor_01_sim

3.2 RAA Study

The training system for data entry by study staff with sight views for own data entries (CRF

module 1 &2), can be accessed through the link and login data below:

URL: http://oc-dev.imib.rwth-aachen.de/ (TST 187) Study: RASimAs – RAA (CTC-A 14-161) Site: TestSite (RAA) (14-161 TST) Visits:

Screening/Baseline

Training Visit Login data (Role: Data Entry Person): User Account: data_entry_raa Password: data_entry_raa

http://oc-dev.imib.rwth-aachen.de/

https://oc-dev.imib.rwth-aachen.de/

http://oc-dev.imib.rwth-aachen.de/

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This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 610425

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4 Visit-based CRF Modelling

CRF modules are identified by grouping the questions per visit. Repeated question groups are combined to make one CRF module.

4.1 Visit based CRF modelling

Figure 1: Visit-based Modelling

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4.2 Study Site based CRF Modelling

According to the study protocol all parameters for data collection and recording were defined and structured due to certain schedule. The following

figure shows how the data collection for the evaluation of the regional anaesthesia (RA) nerve block is structured in three modules.

Figure 2: Module structure of EDC database for the evaluation of the RA simulator

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5 Database specifications

The Clinical Project Manager and the Statistician are the responsible of defining the content of the CRF based on the study protocol. The content of

the CRF is defined in the document CRF Sections. After this document is approved, the Data Manager proceeds with the design of the Electronic

Data Capture (EDC).

5.1 Specifications: Module 1 (Data Collector, Part 1)

Group Item Reference Field type Validation format Help text Forms Validation rules

Inclusion Physician with no previous experience in performing loco-regional anaesthesia

1 Radio Button

if no, proceed with EOT yes, no [force]

Inclusion Written informed consent prior to study participation

2 Radio Button


Inclusion Written approval for storage and use of image material

3 Radio Button


Exclusion Previous ultrasound-guided training

4 Radio Button

if yes, proceed with EOT yes, no [force]

informed Consent Trainee date of consent 5 Date if no, proceed with EOT [force]

informed Consent Subject ID 6 Number S[0]-[00] Example S1 as center ID, 01 first patient in at center S1: S1-01

[force]

Randomisation Random ID 7 Number [000]-RAND-[0000] Number obtained by randomiser tool [force]

Randomisation Group allocation 8 Radio Button

simulator group, control group

[force]

Demographic Data

Date of birth 9 Date [force]

Demographic Data

Age 10 Number [00] years Please calculate age [force]

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Demographic Data

Sex 11 Radio Button

male, female

[force]

Demographic Data

Professional experience 12 Number [00].[00] years.months

Please calculate number of years and months since entry of a department of anaesthesia

[force]

5.2 Specifications: Module 2 (Data Collector, Part 2)

Group Item Reference Field type Validation Format Help text Alarm-Min Alarm-Max Forms Validation rules

Theoretical training

Subject followed standardised theoretical training completely

1 Radio Button

if no, proceed with EOT

0 0 yes, no [force]

Theoretical training

Date of training 2 Date 0 0 [force]

Simulator session Subject followed self-directed simulator training

3 Radio Button

if no, proceed with EOT

0 0 yes, no [force]

Simulator session Duration of training 3.1 Number [00.00] hours.minutes

Please enter sum score as indicated in the user activity report

4 hours 10 hours [force]

Simulator session User activity report 3.2 Upload User activity report is generated by the simulator software

0 0

[force]

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5.3 Specifications: Module 3 (Assessor)


General information

Date of assessment Date

General information

Assessor ID Number S[0]-A[00] CenterID of assessor S[0]- running number of assessor A[00]

General information

Video ID Number S[0]-[00]-[0]-Video pesudonymise with patient ID-Video

General information

US sequence ID Number S[0]-[00]-[0]-US pesudonymise with patient ID-Uss

Video Video Upload

US sequences US sequences Upload

Patient interaction, patient comfort, anxiolysis

Operator removes non-patient-related and non-procedure related tasks and personnel conversation from the anaesthesia block room

1 Radio Button yes, no Overriding rule for questions 1 to 34, every <no> that is ticked should be counted as 1 to create a sum score of errors detected in total at the end of entire FNB procedure; every <yes> that is ticked in the sub-question "intervention by supervisor" should be counted as 1 to create a sum score of interventions by the supervisor in total


Error timing on video Number [00]:[00] minutes:seconds

sub-question Reference 1, [add] sub-question is created for several times if Assessor detects error at several distinct time points; [hide] if 1 is `yes


Intervention by supervisor Radio Button yes, no sub-question ref 1


Operator communicates with the patient during the procedural steps

2 Radio Button yes, no

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sub-question Reference 2, [add] sub-question is created for several times if Assessor detects error at several distinct time points; [hide] if 2 is `yes`




The operator does attach standard monitoring (SaO2,ECG,NIBP)








The operator does establish iv access or check and flush an existing cannula








Following administration of sedation and in the presence of hypoxia, the operator administer O2




sub-question Reference 5, [add] sub-question is created for several times if Assessor detects error at several distinct time points;[hide] if 5 is `yes`

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Procedural ergonomics, equipment & patient positioning

The operator adopts an awkward posture during the block procedure

6 Radio Button Example: the operator rotates their body and reaches behind their back back to pick an item off block tray.

yes, no







Operator maintains patient`s dignity when exposing the groin of the limb to be blocked








Operator persists to position the limb despite causing patient`s pain and discomfort

8 Radio Button yes, no, not applicable




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Aseptic preparation

Operator removes personal apparel before hands decontamination


Aseptic preparation

Time putting on gloves Number [00]:[00] minutes:seconds

Aseptic preparation



Aseptic preparation


Aseptic preparation

Operator dries antiseptic preparation if antiseptic preparation still wet prior to needle insertion


Aseptic preparation



Aseptic preparation


Aseptic preparation

Operator maintains integrity of sterile field and takes corrective actions if needed to ensure sterility


Aseptic preparation



Aseptic Intervention by supervisor Radio Button yes, no sub-question ref 11

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preparation

Ultrasonography The operator orients probe sidedness with the screen and the patient’s surface anatomy


Ultrasonography Error timing on video Number [00]:[00] minutes:seconds


Ultrasonography Intervention by supervisor Radio Button yes, no sub-question 1 ref 12

Ultrasonography Start time placing probe on skin Number [00]:[00] minutes:seconds

enter time displayed on the video

sub-question 2 ref 12

Ultrasonography The operator progresses with optimising the image using PART manoeuvre.




Ultrasonography Intervention by supervisor Radio Button yes, no sub-question ref 13

Ultrasonography The operator obtains a final image consisting of the femoral artery on the medial side of the screen with the femoral nerve visible in the medial 1/4 of the screen


Time to evaluate and describe all necessary anatomical landmarks

Number [00]:[00] minutes:seconds

enter time displayed on the video

sub-question ref 14; [calc] duration by subtracting time of sub-question 2/12



Ultrasonography Intervention by supervisor Radio Button yes, no sub-question ref 14

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Needle guidance and injectate placement

Operator raises a skin wheal on the intendant needle insertion point if local anaesthetic skin infiltration is used (it is not an error not to use skin infiltration)

15 Radio Button yes, not applicable







On advancing the block needle through skin the operator advances through a site other than through the infiltrated skin area








Operator advances block needle other than at the middle of the upper border of the ultrasound probe and other than in-plane to ultrasound beam





Needle guidance and injectate


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placement


Operator does not maintain visibly patent veins during aspiration and injectate placement








Operator keeps needle tip and distal part of needle shaft in view when the needle in foreward motion








Operator continues to advance needle towards target without tip and a portion of the shaft being visible







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Should the needle visibility be lost, the operator advances the needle in an attempt to restore needle visibility








Operator makes multiple needle redirections without tip being visible








Operator makes multiple skin punctures using the block needle







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Operator asks the patient about pain and parasthesia when they advance the needle or before placing injectate








Operator aspirates prior to injection of test dose and/or block dose








Operator injects less than 1mls as a test dose








Operator places sufficient injectate to contact a minimum 50% of nerve circumference as block dose


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Operator stops injecting or repositions the needle because of ultrasonographic evidence of injectate moving away from the vicinity of the nerve








Operator takes corrective actions and stops advancing the needle in forward motion because the patient reports pain and/or parasthesia







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Operator injects not more than test dose or withdraws needle because of visual ultrasonographic evidence of nerve surface area increasing








Operator injects more than the test dose of 0.5-1mls of local anaesthetic after visual ultrasonographic evidence of spread of injectate








Operator stops injecting and repositions the needle because of visible blood on needle hup and/or tubing when aspirating







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Operator does not places the block needle into a nerve, and does not correct by withdrawing the needle






Intervention by supervisor Radio Button yes, no sub-question ref 2/33


Time of retraction of needle from the patient

Number [00]:[00]

minutes:seconds

sub-question ref 3/33


Time to perform nerve block Number [00]:[00]

minutes:seconds

sub-question ref 33, [calc] 3/33 -

Block assessment Operator undertakes complete block assessment


Block assessment Error timing on video Number [00]:[00] minutes:seconds


Block assessment Intervention by supervisor Radio Button yes, no sub-question ref 34

Successful surgical block

Patient has no sensation to cold/pin prick in the area of surgery for ar least 30 minutes after FNB

35 Radio Button yes, no `yes` only possible if no sensation is reported by the patient within 30 minutes, [calc] sub-question 2/35 - 1/35


Starting time Dropdown [00]:[00]

minutes:seconds

time of day recorded by study nurse

am, pm sub-question 1/35


End time Dropdown [00]:[00]

minutes:seconds



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Time of onset of the nerve block 36 Number [00] minutes [calc] 2/36 - 1/36


Starting time 1/36 Dropdown [00]:[00]

minutes:seconds




End time 2/36 Dropdown [00]:[00]

minutes:seconds



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