R1.
Research Task Identification
This step helps you identify the type of research question your EHR study is trying to answer. The task you choose will shape every later decision, including the estimand, data fitness checks, sources of bias, analysis plan, assumptions, interpretation, and reporting language.
Description
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Estimating the occurrence or distribution of a health state, event, exposure, or practice in a defined population.
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Estimating and comparing the occurrence or distribution of a health state, event, exposure, or practice or event in multiple populations or predefined subgroups.
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Estimating the occurrence or distribution of a health state, event, exposure, or practice over time.
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Estimating and comparing the occurrence or distribution of a health state, event, exposure, or practice over time and in multiple populations or predefined subgroups.
Signal Discovery
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Scanning high-dimensional omic spaces for associations with a defined outcome, including genetic variants (GWAS), gene expression (TWAS), epigenetic markers (EWAS), and metabolites, as well as interaction effects (e.g. gene-environment, gene-gene).
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Scanning the phenome for associations with a defined exposure, typically a genetic variant (PheWAS).
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Scanning the exposome for associations with a defined outcome, including environmental, lifestyle, and occupational exposures (ExWAS).
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Scanning drug-outcome spaces for previously unrecognised adverse effects (pharmacovigilance) or new therapeutic indications (drug repurposing).
Factual Prediction
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Estimating the probability that a health state is currently present, or the expected current value of a health state.
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Estimating the probability of an outcome occurring in the future - or the expected future value of an outcome - conditional on individual characteristics and under observed or expected treatment conditions.
Counterfactual Prediction
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Estimating the probability of an outcome occurring in the future - or the expected future value of an outcome - conditional on individual characteristics and under one or more specified hypothetical treatment conditions.
Causal Effect Estimation
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Estimating the causal effect of an exposure, treatment, intervention, or policy (including its level, dose, or intensity) on an outcome in a specified population.
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Estimating the causal effect of ongoing, dynamic, or sustained exposure, treatment, policy, or combination regimes (including their dose, duration, or intensity) on an outcome in a specified population.
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Estimating how the causal effect of an exposure on an outcome varies across levels of one or more predefined variables
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Decomposing the causal effect of an exposure on an outcome into different pathways and/or estimating the impact of intervening on intermediate variables
By the end of this step, you should have:
Identified the primary research task
Named any secondary task or subtask
Confirmed that your planned language matches the task
Flagged any areas where the study aim needs refinement