S8
Satisfy reporting and transparency standards
Transparent reporting allows readers to understand what was done, why it was done, and how results should be interpreted. EHR studies should clearly document the research task, estimand, data source, sample construction, variable definitions, analytical decisions, assumptions, limitations, and reporting standards used.
This step helps researchers align their study with relevant reporting guidance and open science practices.
Description
Consider pre-registering a study protocol and statistical analysis plan (e.g. on OSF) before data access, clearly stating the descriptive estimands of interest.
Make analytical code available (e.g., as a supplement to the publication or in a public repository), having reviewed for disclosive content
Provide a data availability statement describing the process for obtaining access to the source data. Report relevant summary-level information including sample flow diagrams and sample characteristics
Follow the Lesko et al (2022, AJE) methodological and reporting framework for descriptive epidemiology.
Signal Discovery
Consider pre-registering a study protocol and statistical analysis plan (e.g. on OSF) before data access, clearly stating the signal discovery estimands of interest.
Make analytical code available (e.g., as a supplement to the publication, alongside the protocol, or in a public repository), having reviewed for disclosive content
Provide a data availability statement describing the process for obtaining access to the source data. Report summary-level information including sample flow diagrams and baseline sample characteristics
Follow RECORD reporting guidelines, along with appropriate task-specific reporting and methodological guidance (STREGA for GWAS, CIOMS Working Group VIII for pharmacovigilance signal detection).
Factual Prediction
Pre-register a study protocol and statistical analysis plan (e.g. on OSF) before data access, clearly stating the factual prediction estimands of interest.
Make analytical code available (e.g., as a supplement to the publication, alongside the protocol, or in a public repository), having reviewed it for disclosive content
Provide a data availability statement describing the process for obtaining access to the source data. Report summary-level information including sample flow diagrams and baseline sample characteristics
Follow RECORD and TRIPOD+AI reporting guidelines. Use PROBAST to assess and report risk of bias
Counterfactual Prediction
Pre-register a study protocol and statistical analysis plan (e.g. on OSF) before data access, clearly stating the counterfactual prediction estimands of interest.
Make analytical code available (e.g., as a supplement to the publication, alongside the protocol, or in a public repository), having reviewed it for disclosive content
Provide a data availability statement describing the process for obtaining access to the source data. Report summary-level information including sample flow diagrams and baseline sample characteristics
Follow RECORD reporting guidelines, plus relevant items from TRIPOD+AI as appropriate.
Causal Effect Estimation
Pre-register a study protocol and statistical analysis plan (e.g. on OSF) before data access, clearly stating the causal effect estimations of interest. Consider prospective registration on a formal registry (e.g. EU PAS Register).
Make analytical code available (e.g., as a supplement to the publication, alongside the protocol, or in a public repository), having reviewed it for disclosive content
Provide a data availability statement describing the process for obtaining access to the source data. Report summary-level information including sample flow diagrams and baseline sample characteristics
Follow RECORD reporting guidelines (or RECORD-PE for pharmacoepidemiology studies), along with appropriate design-specific or context-specific reporting and methodological guidance (TARGET guidelines for target trial emulations, AGREMA for mediation analyses, STROBE-MR for Mendelian randomisation studies, Tennant et al 2021 (IJE) for studies using DAGs to estimate causal effects through backdoor adjustment, Jandoc et al 2015 (J Clin Epi) for studies conducting interrupted time series analysis).
By the end of this step, you should have:
Identified relevant reporting guidelines for the research task
Prepared or referenced a study protocol and statistical analysis plan where appropriate
Written a data availability statement
Documented code availability or restrictions
Reported sample flow, variable definitions, and sample characteristics
Completed a transparency checklist for the study