How Clean are ‘Clean Data’ before Medical Review Petra Weissenberger, MD
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Agenda • • • • • • • • •
Definition of Data Cleaning Regulatory Requirements Methodology of Data Cleaning Different Functions – Different Focus Medical Review Activities Neglected Medical Review Experiences, Hints and Helpful Tools Patient Drawing Conclusion: Added Value of Medical Review
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Definition of Data Cleaning I A process used to determine inaccurate, incomplete, or unreasonable data and then improving the quality through correction of detected errors and omissions.1
“An error not resisted is approved” 1Chapman,
A. D. 2005. Principles and Methods of Data Cleaning – Primary Species and Species-Occurrence Data, version 1.0. Report for the Global Biodiversity Information Facility, Copenhagen.
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Definition of Data Cleaning II • No matter how efficient the process of data entry is, errors will still occur. • Error prevention is by far superior to error detection and cleaning, as it is cheaper and more efficient to prevent errors than to try and find them and correct them later.
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Regulatory Requirements I • Quality control (ICH GCP 5.1.3) 2 • Quality control should be applied to each stage of data handling to ensure that all data are reliable and have been processed correctly. • The ultimate responsibility for the quality and integrity of the trial data always resides with the sponsor. 2ICH
Topic E 6 (R1) Guideline for Good Clinical Practice
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Regulatory Requirements II • Medical Expertise (ICH GCP 5.3)2 • The sponsor should designate appropriately qualified medical personnel who will be readily available to advise on trial related medical questions or problems. If necessary, outside consultant(s) may be appointed for this purpose. 2ICH
Topic E 6 (R1) Guideline for Good Clinical Practice
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Methodology of Data Cleaning I Electronic CRF* Simultaneous review by different functions (online access) Review activity as soon as entry occurs Direct review of data What you see is what you get Remote monitoring of data Online paperless query processing Time saving (although set-up needs additional time)
Paper CRF Sequential review by different functions Delay in review activity Indirect review (listings) Interpretation or additional preparation of data necessary Onsite or in-house monitoring Query processing via paper Time consuming (although quicker set-up)
* Case Report Form
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Methodology of Data Cleaning II • However, the general review systematics will not be influenced by the data capture tool • Programmed edit checks will be the same • Manual checks (performed by intellectual activity of the reviewer) will be the same
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Different Functions – Different Focus I CRA • Focus on inclusion/exclusion criteria (eligibility of patients), compliance with procedures and assessments as required by study protocol • Extent of data review determined by monitoring plan
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Different Functions – Different Focus II Data manager • General overview of whole study data • Focus on general inconsistencies and missing entries • Checks specified in data validation plan • Selection of subjects ready for medical review
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Different Functions – Different Focus III Safety officer • Focus on patients’ safety (SAEs, SUSARs, medically important adverse events and pregnancies) via manual review and DMsupported SAE reconciliation • Review procedure specified in safety plan
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Different Functions – Different Focus IV Medical expert • Focus on medical plausibility of data • Cross-linking of all available medical information per patient – Demography, med. history, inclusion/exclusion criteria, physical examination, assessment results (e.g. ECG, labs, X-ray), SAEs/AEs, concomitant medication
• Extent specified in medical review plan 11/10/2011
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Medical Review Activities Set-up
Execution
Medical review plan
Review of patient data
Patient data review listings Special reports for data review Listings for special parameters Tracking tables Protocol violation criteria Medical coding guidelines
Support for medical query generation Review of line listings (trend identification) Review of protocol deviations/violations [PDs/PVs] Support for SAE reconciliation Medical coding review
Liaison with Clinical Operations, Data Management, Drug Safety
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Neglected Medical Review • Reasons: – Financial constraints – Lack of resources (medic assumes also project manager role) – Tight timelines – Lack of knowledge or experience
• Consequences: – Lack of medical data quality questionable reliability of study results and conclusions
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Own Experiences • Relevance of medical review often underestimated => coverage by non-medical functions
• Understanding of review processes/ review interfaces often insufficient => redundant or missing review
• Other function reviewers appreciate – medical expertise and input/support – good organisation/sharing of review tasks 11/10/2011
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Hints and Helpful Tools I • Define review flow, processes and responsibilities in medical review plan • Decide on reasonable extent for medical review: – 100 % of inclusion/exclusion criteria, primary objectives, AEs and concomitant medication – All patients with SAEs/pregnancies/drop-outs due to AE – 100 % of data for n patients (n = sample size) 11/10/2011
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Hints and Helpful Tools II • Specify checks (especially manual ones) to be performed including examples in review plan • Specify content and form of patient data listings (paper CRF) or reports to be reviewed (EDC) • Specify how to track review findings and queries 11/10/2011
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Hints and Helpful Tools III • Specify wording for standard medical queries to minimise number of re-queries • Spot checks on query answers received • Specify collection and reconciliation of PDs/PVs (cave: PDs/PVs collected during monitoring visits need ongoing review and verification) • Provide coding specifications with examples 11/10/2011
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Patient Drawing I Review and cross-linking of the (medical) data of a patient creates an image: • Demography: female, 76 years, 72 kg, 165 cm
• Medical history: hypertension • Vital signs, physical examination: increased BP
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Patient Drawing II
• Lab/ECG/X-ray results: elevated blood glucose • AE/SAE (s): no entry related to increased glucose value present => query for explanation • Concomitant medication: antihypertensive medication, no anti-diabetic medication, diclofenac for knee pain (query: osteoarthritis/injury?) 11/10/2011
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Conclusion: Added Value of Medical Review I • Added value of medical review is very much depending on – complexity of study – expertise and ‘medical sense’ of other nonmedical functions – clinical study experience of the medical expert – a balanced consideration of what kind of data really require 100 % accuracy 11/10/2011
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Conclusion: Added Value of Medical Review II • About 3 medical queries per patient with any AEs for a moderately complex study (non-oncologic indication; no multi-morbid population) lead to data updates or corrections • About 10% coding changes or need for queries after medical coding review (autocoding plus manual coding according to coding specifications/guidelines) 11/10/2011
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Questions/Thank You Are there any questions?
A big ‘Thank You’ goes to my colleagues Dr. med. Johanna Schenk and Dr. med. Gerd Brunner from PPH plus for review and valuable input.
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Dr. med. Petra Weissenberger Head Medical Services PPH plus GmbH & Co. KG, Frankfurt am Main, Germany Phone: +49 69 58 700 35 – 38
[email protected]
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