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Table 1 Data quality indicators of Registry design that affect the quality of Research derived from the Registry according to the Agency for Healthcare Research and Quality

From: An assessment of the quality of the I-DSD and the I-CAH registries - international registries for rare conditions affecting sex development

Parameter Criteria of good Quality practice for Research
Purpose of the Registry -Research questions clearly defined
-Meet the needs of key stakeholders
-The Registry should be an appropriate/the best means to achieve the purpose
Study Design Choice of study design which is more efficient for addressing the research questions: Cohort, Case-control or case-cohort.
Data elements Relevance to the objectives of the registry
Acceptability to subjects and researchersa
Validityb
Reliabilityc
Use of standardized data collection form CDISC, CDASH, BRIDG when possible
Use of disease coding system ICD coding system, MIM, ORPHA codes
Data sources (good quality means the use of the appropriate data sources to collect relevant data) Clinician:accurate and specific clinical data
Patient:data on health-related quality of life, utilities (patient preferences), behavioral data, family history.
Electronic Health Record: information on routine medical care and practice, comprehensive view of patient medical and clinical history.
Linkage with other sources:data difficult to obtain, subject to recall bias, not collected because of loss to followup, or likely inaccurate by self-report.
Population definition - Patient selection: inclusion and exclusion criteriarelevant to the purpose
- Patient sampling: consider representativeness in terms of patients and sites
Registry size and duration Calculation of target sample size and definition of the duration of enrollment and follow-up should consider the aims of the registry, the desired precision of information sought, and the hypotheses to be tested.
  1. CDISC Clinical Data Interchange Standards Consortium
  2. CDASH Clinical Data Acquisition Standards Harmonization
  3. BRIDG Biomedical Research Integrated Domain Group
  4. areasonably feasible to collect, minimal response burden
  5. bdoes each data element truthfully measure what it is supposed to?
  6. ccan the instrument yield replicate metrics or estimates?