Data Quality: Missing Data (PPT slides)


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This module describes how missing data can be managed while maintaining data quality. It explains how to plan for missing data; defines different types of “missingness;” outlines the benefits of documenting missing data and illustrates how to document missing data; and describes procedures to minimize missing data. Upon completion of this module, students will be able to explain why data managers should strive to minimize missing data and develop a plan to record or code why data are missing.

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Data Quality: Missing Data (PPT slides)

  1. 1. Ethics and Integrity in Data Use and Management John E. Sidle, M.D., M.S. May 10, 2010This module was recorded at the health informatics-training course – data management series offered by the Regional East AfricanCentre for Health Informatics (REACH-Informatics) in Eldoret, Kenya. Funding was made possible by NIH’s Fogarty Center and a (REACH-Informatics)grant from the Rockefeller Center. The training was held at the Academic Model Providing Access to Healthcare (AMPATH), a (AMPATH),USAID-funded program, supported by the Regenstrief Institute at Indiana University. The modules were created in collaboration with University.the School of Informatics at IUPUI. IUPUI. Content licensed under Creative Commons Attribution-Share Alike 3.0 Unported
  2. 2. ObjectivesExamine a brief history of ethics in researchand data managementDiscuss pertinent principles of ethics in datamanagementDiscuss the concept of “data integrity” andethics in data managementDiscuss applications for data managementpersonnel in ethical use of data
  3. 3. OutlineDefinitionsEthical Principles in BioethicsGuidelines and RegulationsData IntegrityApplications for ethics and maintenance ofdata integrity
  4. 4. Definitions In·teg·ri·ty n. 1. Strict adherence to a standard of value or conduct. 2. Personal honesty and independence. 3. Completeness: unity 4.Soundness Eth·ic n. 1. A principle of right or good conduct. 2. A system of moral values. 3. ethics (sing. In number). The branch of philosophy dealing with the rules of right conduct.Source: Webster’s II New Riverside Dictionary, Based on the Webster’s II New College Dictionary (1996)
  5. 5. Ethical PrinciplesBeneficence Minimize harm Maximize BenefitsRespect of Persons (Autonomy) Informed voluntary consent Vulnerable subjects must be protectedJustice Equity in distributing risks and benefits between populations “fairness” in dealing with research participants Equity between institutions and research partners
  6. 6. Clinical Data vs. Research Data: Are the Ethics Different?Privacy and ConfidentialityInformed Consent vs. Implied ConsentData Integrity / Data QualityData Security and Storage
  7. 7. Ethical Guidelines (for Research)Declaration of Helsinki ethical standard used by the International Committee of Medical Journal Editors guidelines govern all medical researchCIOMS Guidelines Council for International Organizations of Medical Sciences developed guidelines in collaboration with WHOBelmont ReportNational Guidelines (Kenya)
  8. 8. RegulationsUS: Code of Federal Regulations Title 45,Part 46 (45CFR46)FDA– 21CFR50 and 56NIH--“he who has the gold makes the rules”HIPAA—related both to clinical records anduse of subject data in research
  9. 9. 45CFR46US Code of Federal Regulations Title 45, Part46 (45CFR46) Human Subjects Protections IRB requirements Protection of Vulnerable SubjectsHuman subject Human subject means a living individual about whom an investigator (whether professional or student) conducting research obtains: (1) data through intervention or interaction with the individual, or (2) identifiable private information.
  10. 10. Privacy/ConfidentialityApplies to both clinical and research dataMajor concern for patients when it comesto electronic records and dataMust be safeguarded by all members onthe team
  11. 11. HIPAAHealth Insurance Portability andAccountability Act of 1996 (HIPAA), HHSissued regulations entitled Standards forPrivacy of Individually Identifiable HealthInformation.For most covered entities, compliance withthese regulations, known as the PrivacyRule, was required by April14, 2003.
  12. 12. HIPAA and Privacy RuleThe Privacy Rule, at 45 CFR parts 160 and 164,establishes a category of health information,defined as protected health information (PHI),which a covered entity may only use or discloseto others in certain circumstances and undercertain conditions.Usually requires an individual to provide signedpermission, known as an Authorization before acovered entity can use or disclose theindividuals PHI for research purposes.Need for authorization may be waived in someinstances by an IRB (and a Privacy Board)
  13. 13. Individually Identifiable Information and Protected Health Information Includes any subset of health information, including demographic information, that identifies the individual (or there is a reasonable basis to believe that the information can be used to identify the individual). 1. Name 2. All elements of dates except Year. 3. SSN 4. Drivers License Number 5. Geographic subdivisions smaller than a State. 6. URLs and IPs 7. Vehicle Identifiers including VIN and License # 8. Phone numbers
  14. 14. PHIIndividually identifiable information becomes PHI when itis created or received by a covered entity: US health plans US health care clearinghouses US health providers that transmit electronic health informationA researcher is not a covered entity unless he/she isalso a provider within a covered entity.Research is also governed by HIPAA if data is obtainedfrom a covered entity.IRB may on occasion waive the HIPAA restrictions onuse of PHI
  15. 15. How does all this translate to practice?Electronic health information (clinical or research) Can improve quality and safety of medical care (beneficence) Is key to showing outcomes in research on health and health practices (beneficence) Confidentiality and Privacy can be lost (breach of autonomy and beneficence) Can be used without a patient’s knowledge or consent (breach of autonomy) Might exclude some populations (breach of justice)
  16. 16. Data IntegrityThe assurance that data is accurate, correct andvalid.Accuracy and consistency of stored data,indicated by an absence of any alteration in databetween two updates of a data record. Dataintegrity is imposed within a database at itsdesign stage through the use of standard rulesand procedures, and is maintained through theuse of error checking and validation routines.Exact duplication of the sent data at thereceiving end, achieved through the use of errorchecking and correcting protocols.Assurance that the data are unchanged fromcreation to reception.
  17. 17. Data Integrity (2)Process to maintain data integrity dependson: Collection (accurate representation) Data transfer (accurate recording and transfer of data) Storage and Security (preventing loss of data) Sharing of Data Use of data (analysis)
  18. 18. Data Integrity (3)Fabrication and Falsification of data are one ofthe most serious challenges to data integrityHuman error also contributes to loss of dataintegrityConcern about research misconduct was aprimary motivation for a 1990 conference ondata management sponsored by the USDepartment of Health and Human Services.Conference summarized the many ways inwhich the conduct of research depends onresponsible data management.
  19. 19. Data Integrity (4)Responsible research begins withexperimental design and protocol approvalIt involves recordkeeping in a way thatensures accuracy and avoids biasIt guides criteria for including andexcluding data from statistical analysesIt entails responsibility for collection, use,and sharing of data.
  20. 20. Data Integrity (5)Everyone with a role in research has aresponsibility to ensure the integrity of the data.The ultimate responsibility belongs to theprincipal investigator, but the central importanceof data to all research means that thisresponsibility extends to anyone who: helps in planning the study collecting the data analyzing or interpreting the research findings publishing the results of the study maintaining the research records.
  21. 21. Data Collection and IntegrityBecause data collection can be repetitious, time-consuming, and tedious there is a temptation tounderestimate its importance.Those responsible for collecting data must beadequately trained and motivatedThey should employ methods that limit oreliminate the effect of biasThey should keep records of what was done bywhom and when
  22. 22. Analysis and Selection of DataThe use of statistical methods varies widelyamong research disciplines and also clinicalprograms (reporting)It is a laudable ideal to analyze and report alldataBecause it is not possible to report everythingthat has been done, researchers must makedecisions about which studies, data points, andmethods of analysis to present.
  23. 23. Analysis and Selection of Data (2)Must critically evaluate the reasons forinclusion or exclusion of data, themeasures taken to avoid bias, andpossible ways in which bias maynonetheless influence data selectionMust clearly document how the data wereobtained, selected, and analyzed--especially if the methods are unusual orpotentially controversial
  24. 24. Retention of DataWhat should be retained?It may be impractical to storeextraordinarily large volumes of primarydata.At minimum, enough data should beretained to reconstruct what was done.How long should clinical records beretained?
  25. 25. Sharing of DataThis is considered an important part ofresponsible research.De-identified data should be shared sothat others can verify your conclusions oranalysisSharing of personal patient information isNOT a good practice as noted in Privacysections earlier.
  26. 26. Data SecurityLimiting Access Locked Paper Records Offices Limiting access to Paper or Electronic records to appropriate personnel Password Protection of electronic records Defined privileges for electronic data users Firewalls to prevent outside accessRegular Backups and proper archiving
  27. 27. Ownership of DataWho owns the data that is generated? Patient? Institution? Funder? Investigator? Publisher?
  28. 28. Ethics in Publication—General guidelines pertinent to dataResearch should strive to answer specificquestions—not just collect or mine dataStatistical issues (sample size) are animportant part of design to ensure that theresearch data is likely to answer thequestionIRB approval is required when usinghuman subjects, human tissues, ormedical records
  29. 29. Publication Ethics and Data Management/Data AnalysisData should be appropriately analyzedInappropriate analysis is not necessarilyethical misconductFabrication or falsification of data isalways ethical misconduct
  30. 30. Publication Ethics and Data Management/AnalysisSources and methods of obtaining andprocessing data should be disclosedData exclusions should be explained in fullMethods used to analyze data should beexplained in detailPost hoc analysis of subgroups isacceptable as long as this is disclosedData Bias should be discussed in allpublications of data or analysis
  31. 31. Questions??