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DATA. East African IeDEA PI Meeting Zanzibar, Tanzania May 4, 2010. Beverly Musick Regional Data Manager. Introduction. Revised Data SOP 2 nd Data Submission Data Quality Data Audits Data Requests. Revised Data SOP.

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DATA

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  1. DATA East African IeDEA PI Meeting Zanzibar, Tanzania May 4, 2010 Beverly Musick Regional Data Manager

  2. Introduction • Revised Data SOP • 2nd Data Submission • Data Quality • Data Audits • Data Requests

  3. Revised Data SOP • Standard Operating Procedures for Data Quality and Transfer was updated in January 2010 • Changes include • Adding the “Description of Data Submitted” form • Request that all data files submitted to the Regional Data Center (RDC) be archived at the site • Request that data be submitted within 45 days of the call for data

  4. Revised Data SOP Request for additional variables Mandatory • ARVs for PEP and type of pMTCT received prior to enrolment • Drop out status and reason • Pregnancy outcome, gestation weeks, delivery date • HIV status at each visit (pediatric patients) • CDC classification (if WHO stage not available) Optional • Disclosure of HIV status • Marital status, number of children, religion, education • Entry point into care • Family ID • Who administers medicine to children

  5. Description of Data Submitted Form • This form provides crucial information about the data being submitted AND the data not being submitted • The information is vital for the accurate understanding, harmonization, interpretation, and distribution of each site’s data • To be completed by site data managers in conjunction with site PI’s. • Electronic entry now available on-line (REDCap)

  6. Description of Data Submitted Form • Important items include • Date of database closure • Cohort definition (age range, ART status) • Encounter/Visit data included • Encounter/Visit data excluded • Details regarding missing data (variables, values, encounters, reasons, plans) • Data quality procedures • Description of physical data files submitted

  7. 2nd Data Submission • So far the RDC has requested data from 5 sites and has received data from 1 site • We hope to be requesting data from the remaining sites in the next couple of months

  8. Data Quality Issues • Ambiguous Date for Lab Results • Prompts from some of the data collection forms: • “Date sample taken / test performed” • “CD4 Specimen Date” • “Date” • “Visit Date” • “Test Date” • Leave us wondering which date is entered: sample collection date, date samplewas analyzed, date the result was recorded or the data entry date

  9. Data Quality IssuesAmbiguous Date for Lab Results (cont.) • The most important date is the specimen collection date. • The specimen analysis date may serve as a proxy for the collection date in cases where the samples are analyzed within a day or two of collection (i.e. CD4) or for sites that do not record specimen collection date.

  10. Data Quality IssuesAmbiguous Date for Lab Results (cont.) • Proposed Solution: • Capture the specimen collection date • Ensure that this date follows the specimen to the laboratory and is clearly associated with the result • In the data entry system and on the data collection forms, clearly specify that this date is to be recorded • If specimen analysis dates are used, be sure to properly label

  11. Data Quality Issues • CD4 counts entered multiple times • It should be extremely rare for a patient to have the same CD4 count from independent blood samples • Some of the EA sites have quite a few patients with duplicate CD4 values • Presumably, these CD4 counts are not unique but from the same blood draw and entered under different dates

  12. Data Quality IssuesCD4 counts entered multiple times (cont.) • The dates associated with these duplicate results are sometimes only a day apart while others are over 3 years apart • Suspect that some of these are data recording errors but that most are associated with the ambiguity regarding what date should accompany a lab result • Proposed Solution: • Record and enter specimen collection date • Confirm any duplicate results before entering

  13. Data Quality Issues • Accuracy of ART start dates • Ensure that the correct ART start date is recorded for patients transferring from other clinics • If ART was started at a visit that is not part of the submitted data, provide the ART start date separately

  14. Data Quality Issues • Lack of Pregnancy Details • Need to be able to • Estimate date of conception • Identify women on ART for pMTCT • Estimate date of delivery if not directly available • Determine pregnancy outcome • Proposed Solution • Collect date of delivery, gestation age, pMTCT as reason for starting/stopping ART

  15. Data Audits • Regional Data Center is now conducting data monitoring visits at EA member sites • Purpose • To assess quality and reliability of data submitted to RDC • To provide guidance on quality improvement procedures • Process • Prior to visit, RDC will randomly sample about 20 patients from each site and generate data audit forms • During visit, audit team will record values found in source documents • After visit, RDC will compare recorded values with submitted data and produce consistency rates and provide recommendations

  16. Data Audits • Data audits have been completed at 3 Tanzanian sites • Preliminary findings include • Need to refresh training of data entry clerks regarding entry of next scheduled visit date, TB status, transcription of only the data found in chart for specific visit, and verification of data entered • Need for collection of additional variables: indicator for estimation of birth date • Need for additional training of clinicians in transferring data to the CTC 2 blue card specifically CD4 results, WHO stage

  17. Data Requests • Since the last PI meeting, we have generated analysis datasets for the following concept proposals (EA Region): • Hunt: Changing Characteristics of HIV-infected Patients Initiating Antiretroviral Therapy in East Africa • Braithwaite: Comparing the effectiveness of alternative laboratory monitoring strategies for HIV patients in East Africa under various resource constraint scenarios • Elul: Incidence and determinants of pregnancy among women enrolled in care and treatment programs in East Africa • Braitstein: Models of Patient Outreach and their Associated Rates of Loss to Follow-up in the East African IeDEA Consortium • Braitstein: Pediatric losses to follow-up from a comprehensive HIV clinical care program in Western Kenya

  18. Data Requests • IeDEA-Wide: • Zhou: The use of zidovudine (AZT) containing antiretroviral regimens and its impact on the risk of anemia and survival in HIV-infected patients in developing countries • Dabis: Baseline characteristics, 24-month mortality and retention in antiretroviral programs in children in the IeDEA pediatric collaboration • Ciaranello: Pediatric Simulation Model • Egger: Information for article describing the African regions of IeDEA (Cohort Profile in Int J Epidemiol).

  19. Thanks • Site-level Data Managers • Site PIs • Edwin Sang • Gilbert Simiyu • Stephen Wafula • Mariano Erpe • Kendra Jones

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