Clinical Data Management and Case Report Form

Clinical Data Management and Case Report Form
by Jen-Pei Liu, Ph.D. Professor Division of Biometry Department of Agronomy National Taiwan University and Division of Biostatistics and Bioinformatics National Health Research Institutes

Copyright by Jen-pei Liu, PhD
Introduction Case report form Objectives Needs of CRF users Standardization of CRF Guidelines for designing CRF Clinical data management Database development and validation Flow and tracking of CDR Data entry Data validation and correction Clinical database audits Summary 2018/12/6 Copyright by Jen-pei Liu, PhD

I. Introduction Clinical Data Management To provide consistency, accuracy and validity of clinical data in timeliness and cost-effective manner to support of conclusion on efficacy, safety, quality of life and pharmacoeconomic assessment of a pharmaceutical product. 2018/12/6 Copyright by Jen-pei Liu, PhD

Data Flow for a Clinical Trial
Clinical Investigators at Site  Source Documents (Medical charts, image, labs, etc.s) Case Report Forms Clinical Data Management of Sponsors Data Entry into Database Data Checking and Validation Database Locking Statistical Analyses Final Clinical Report 2018/12/6 Copyright by Jen-pei Liu, PhD

Case Report Form Objectives To collect the clinical data outlined in the protocol so that the clinical research questions can be answered To collect information related to efficacy, safety, quality of life, and pharmacoeconomics To minimize the clinical trial processing and to maximize its efficiency Easy to use for all members of clinical study team 2018/12/6 Copyright by Jen-pei Liu, PhD

Needs of CRF Users (1) The needs of each member in the clinical study team using CRFs may be different Each member should be considered Investigators Study coordinators/Study nurses Clinical research associate (CRA) Data entry personnel Data reviewers Database programmers Statisticians 2018/12/6 Copyright by Jen-pei Liu, PhD

Needs of CRF Users (2) Investigators/Study Nurses easy to complete and CRF's are organized based on how data are generated Clinical Research Associates easy for review blanks and inconsistency can be easily spotted Data Entry Personnel Easy for entry Data are lined up on one side Not too busy easily readable 2018/12/6 Copyright by Jen-pei Liu, PhD

Needs of CRF Users (3) Database Programmers Standardization of CRF's Easy copying between applications Statisticians Arranged in a logical and analytical order Easy for merging and grouping 2018/12/6 Copyright by Jen-pei Liu, PhD

Standardization of CRF's (1) Collect similar data across studies in a standard manner as much as possible Easy to computerize Easy to integrate Easy to review Easy to validate Improve efficiency Improve accuracy Improve quality 2018/12/6 Copyright by Jen-pei Liu, PhD

Standardization of CRF's (2) Consistency of data collection will facilitate and speed up review and summarization of data by Investigator/Study Nurse CRA CRF designer CRF reviewer Regulatory Agency 2018/12/6 Copyright by Jen-pei Liu, PhD

Standardization of CRF's (3) Standard CRF design style Bold, large and upper case for headings Bold for emphasis Italic for notes, etc. Margin for binding Standard heading information Protocol number Site number Patient identification number Patient initials Visit number Visit Date Organization logo, etc Use of bar codes 2018/12/6 Copyright by Jen-pei Liu, PhD

Standardization of CRF's (4) Standard coding system Standard Layout Standard module Standard page number system Document control CRF tracking Necessary when CRF are collected intermittently 2018/12/6 Copyright by Jen-pei Liu, PhD

Guidelines for Designing CRFs (1) Same data never collect twice Collection of the same data will create inconsistency and unnecessary work for data checking Example Collect age and date of birth Vital sign including blood pressure in an anti-hypertensive trial Toxicity and Adverse events 2018/12/6 Copyright by Jen-pei Liu, PhD

Guidelines for Designing CRFs (2) Do not collect leading or open-ended question if data is needed for summarization need detailed information and consistency Do not require unnecessary computation Only to collect raw data and only ask investigators/study nurses to do calculations on data they need to use during the study 2018/12/6 Copyright by Jen-pei Liu, PhD

Guidelines for Designing CRFs (3) Choices provided for each question should include all options investigators may encounter and/or have "other" category for the unexpected. Unambiguous instructions Example Bad Date: Intensity of event Mild: Moderate: Severe: Acceptable Date: / / mm dd yyyy Intensity of event: = Mild 2 = Moderate 3 = Severe 2018/12/6 Copyright by Jen-pei Liu, PhD

Guidelines for Designing CRFs (4) If findings were not present or test was not done, the CRF should indicate it Use "Not Done" or "Not Applicable" Do not assume that a blink on CRF implies no findings Easy to find data on CRF Minimizing the page turning No tedious transcription To collect data that allows for the most efficient computerization Use pre-codes for data that may need to be summarized or searched Use check boxes whenever possible 2018/12/6 Copyright by Jen-pei Liu, PhD

Guidelines for Designing CRFs (5) Self documented Example Intensity of event (1-3): Intensity codes 1 = Mild 2 = Moderate 3 = Severe Ensure enough space is provided to capture expected data. Ensure that forms are not too busy and are readable for all users. Complete and accurate instructions for CRF completion should be provided. 2018/12/6 Copyright by Jen-pei Liu, PhD

2018/12/6 Copyright by Jen-pei Liu, PhD

Clinical Data Management
Concept of Data Management For a single study, it starts from the protocol development and ends with completion of the study For a clinical development program, it starts from the very first protocol until the approval of the pharmaceutical product if it gets approved A high quality database of a clinical trial reflects a well designed and a well-conducted study which generated accurate and reliable inference to the targeted patient population 2018/12/6 Copyright by Jen-pei Liu, PhD

Standard statement for data management in a protocol Complete Case Report Forms will be reviewed by both clinical and data management personnel. Data will be entered directly into the database and verifying using a database management system that provides formatted screens, range checking, and relational consistency checking. Subject-oriented edit listings will be generated for comparison to the database, a complete audit trail of the corrections, as well as any coding procedures, will be retained as an integrated part of the study record. 2018/12/6 Copyright by Jen-pei Liu, PhD

2018/12/6 Copyright by Jen-pei Liu, PhD

Responsibilities Protocol design/review CRF design/review Clinical database development Computer system validation CRF tracking Data acquisition and verification Medical dictionary encoding Data review/edit check (data validation) Database quality assurance Clinical database security Clinical database archiving 2018/12/6 Copyright by Jen-pei Liu, PhD

Data Validation Garbage in and garbage out No quality data, no product CRF data checks Missing data Incomplete data Illegible data Inconsistent data Incorrect data Questionable data 2018/12/6 Copyright by Jen-pei Liu, PhD

Data Acquisition Single data entry followed by visual verification Double data entry online key-to-key verification offline batch-file verification Electronic data load Remote data entry Optical character recognition Optical mark recognition Bar code systems Web-site entry 2018/12/6 Copyright by Jen-pei Liu, PhD

Review of Protocol and CRF Development
Objective Review of new protocol Development of statistical section Development and review of CRF Scope Processes to implement the objectives 2018/12/6 Copyright by Jen-pei Liu, PhD

Responsibility Protocol initiation － Clinical Research Statistical Section － Biostatistics CRF initiation － Clinical Research CRF review － Biostatistics 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (1) Retrieval of a protocol Draft Statistical Section Sample size requirement Methods and procedures for final and interim Analysis w. r. to primary and secondary endpoints To meet the protocol objectives 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (2) Review of Statistical Section by Clinical Research Approval via a sign off process Project statistician clinician Director of Biostatistics Director of Clinical Research Chair of Protocol Review Committee Review of CRF from Clinical Research Data collection Protocol Analysis Objectives Standard modules Demographic Lab AE ……… 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (3) NCR papers (white, canary, pink) Margin Requirement 1 inch on the left 1/2 inch margin a Header, logo, name, protocol number a footer, distribution of CRF Form name last revision date 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (4) Approval process of CRF Project CRM Database Coordinator Data Analyst Statistician Directors of Biostatistics Clinical Research Distribution of CRF Project members Study workbook 2018/12/6 Copyright by Jen-pei Liu, PhD

Revision Protocol Affect the statistical analysis Sample size, power, Design, objectives, etc. Projective statistician － Review and assessment of the changes CRF Review the changes New form － date of creation on the bottom of the form Database or data entry screens Documentation in study workbook 2018/12/6 Copyright by Jen-pei Liu, PhD

Database Development and Validation
Objective Design, generate, and validate a database Scope Database development for all clinical protocol 2018/12/6 Copyright by Jen-pei Liu, PhD

Responsibility Clinical Data Management Design and generate of a database Rapid CRF Computer Accurate Validation Database Statistical Analysis Report Retrieval 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (1) Study workbook (files) Final approved protocol and CRF Final database file layout Validation procedures All data management activities Data entry conventions and guidelines Clinical Data Dictionary database file structure File size large enough all possible data Only defined variables on CRF, Primary keys security to control access 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (2) Data entry screen as close as CRF Edit specifications Protocol CRF Statistical analysis plan Discrepancy reports 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (3) Test ≧6 Complete patients Artificial data Data entry screen Collect all data from CRF Fields with enough space for all data Accurate of database files Database audit report listings CRF database printout 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (4) At the conclusion of database development and validations annotated CRF field names file names Approval process Documentation in Study workbook All development Validation Testing Data dictionary Annotated CRF 2018/12/6 Copyright by Jen-pei Liu, PhD

Revision Approval process Documentation is study workbook Before and after 2018/12/6 Copyright by Jen-pei Liu, PhD

Flow and Tracking of CRF
Objectives Flow ＆ Procedure to log and track CRF’s before entry Scope CRF from Center Distribution Computer Tracking 2018/12/6 Copyright by Jen-pei Liu, PhD

Responsibility Retrieval from Center：Clinical Research Logging into tracking system：Biostatistics Patient Status Receipt and processing of CRF Procedure (1) Retrieval of CRF from Center by Clinical Research Patient identification number － Clinical Research Corrections on all 3 copies (NCR) 2 photocopies from the original (non-NCR) 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedure (2) NCR CRF Canary － Investigator White － Clinical Research archives （Clinical Documentation） Pink － Biostatistics Non-NCR CRF original － Clinical Research archives one copy － Investigator one copy － Biostatistics Transmittal Clinical Research Biostatistics Form (signed ＆Dated) 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedure (3) After Receipt by Biostatistics check completeness of Patient identification Information Study number Investigator number Patient number，initials If information is incomplete, return CRF to Clinical Research. 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedure (4) Logged into tracking system within 2 days Tracking System Each page Patient Identification Information Dated logged in Status of CRF New Discrepancy outstanding Corrected Corrected After logging in Data entry Revision Discrepancies of Patient information data require formal corrections. 2018/12/6 Copyright by Jen-pei Liu, PhD

Data Entry Objective Process：timeless and accurate CRF Database Audits Retrieval and manipulation for analysis and reporting Scope CRF Clinical database Study and project specifications 2018/12/6 Copyright by Jen-pei Liu, PhD

Responsibility：Biostatistics Accurate is paramount No interpretation of investigators intent 100% Database CRF Procedures (1) CRF logged into the tracking system Order：First in, First out No CRF should be left on a desk overnight All CRF’s returned to the files Files locked at the end of each day 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (2) Double entered and verified Entry：Consistent throughout each study via clinical trial data dictionary All data in the designated areas must be entered All data in non-designated areas must not be entered Data Assistant CRF form the 1st entry file Password into data entry system(Study specific) After entry stamp“1st ENTRY ” on back of CRF on each page with the current Date and put the CRF in the verification (2nd ENTRY) file 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (3) Different Data Assistant：Data verification CRF form the 2nd entry file Program checks the 1st and 2nd entry Display any mismatched fields Make appropriate corrections to the database based on the CRF Stamp “2nd ENTRY ” and current date Put the CRF in the completed file. 2018/12/6 Copyright by Jen-pei Liu, PhD

Procedures (4) Run the edit program Pre-specified conditions for quality and accuracy Output form the edit program should be reviewed and sent to Clinical Research. Data quality assurance audit Do NOT write or make anything on the face of CRF. 2018/12/6 Copyright by Jen-pei Liu, PhD

Revision No corrections will be made until the changes have been documented according to the appropriate correction procedure. For blinded studies, data entry and revision should be performed in a blinded fashion. 2018/12/6 Copyright by Jen-pei Liu, PhD

Data Validation and Correction Processing
Double-key data entry and verification of all CRF’s Range and completeness checking On-line field value checking Edit programs Logical inconsistency 2018/12/6 Copyright by Jen-pei Liu, PhD

Errors Data entry error? Yes  systematic problem No  data discrepancy form  logged into the tracking system  CRAs  investigators CRAs  data operators  corrections to database  tracking system Corrected CRFs be on top of the original version Audit trails The value before and after, date of the change and persons 2018/12/6 Copyright by Jen-pei Liu, PhD

Clinical Database Audits
Schedules 1/3 of CRFs entered – interim audit All CRF entered – final audit Interim audit – 10% of the total patients Final audit – a different 10% 2018/12/6 Copyright by Jen-pei Liu, PhD

Final audit Patient identification – 100% Adverse events – 100% Termination reason – 100% Gender and date of birth – 100% Random codes – 100% Dosing information – 25% Efficacy data and key fields requested In the statistical analysis plan – 25% 2018/12/6 Copyright by Jen-pei Liu, PhD

Comparison of printout with CRFs and corrections Discrepancy – Data Audit Goal – overall error rate <0.1% Data Audit Summary Report Number of fields checked Number of errors found A total count of investigators, patients, visits, and CRF pages in the study A total count of investigators, patients, visits, and CRF pages in the study workbook 2018/12/6 Copyright by Jen-pei Liu, PhD

Summary Clinical Data Concept and Procedures Collection Standardization Management Entry Verification Validation Efficiency Quality 2018/12/6 Copyright by Jen-pei Liu, PhD

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