RWE Analysis Readiness Editorial Worksheets

What these are

This is a small set of RWEdnesdays editorial worksheets, not an official FDA, EMA, ENCePP, ISPE, or ISPOR template and not a validated scoring instrument. They make three common implementation records explicit: whether each required study element is observable in the selected source, whether a phenotype or code-list algorithm has evidence that is applicable to the intended use, and whether the work departed from an approved protocol or statistical analysis plan (SAP). They are designed to supplement, never replace, official protocol templates and reporting checklists.

When to use

Start the data-fitness worksheet before cohort construction, especially when a study depends on claims/EHR linkage, continuity of enrollment, data lags, or nontrivial exposure/outcome capture. Complete one phenotype matrix for every study-defining exposure, outcome, eligibility definition, or key covariate whose algorithm could drive bias. Start the deviation log when the protocol or SAP is approved, then reconcile it before final analysis and reporting. For a hypothesis-evaluating treatment-effect study, use these worksheets inside a HARPER or STaRT-RWE protocol; for an EU PASS, use the official ENCePP Checklist and any applicable annexes when the study's regulatory pathway calls for them; for the completed paper, report against RECORD-PE.

When not to use them

Do not submit these files as if they were official regulatory forms. Do not use a completed data-fitness worksheet as proof that a study identifies a causal effect, a completed phenotype matrix as proof that an algorithm validates in a new database, or a deviation log to relabel an outcome-informed change as pre-specified. Use the official source documents when a sponsor, regulator, journal, or protocol requires their exact form.

Downloads

Copy and complete the Markdown files in any text editor, then retain the filled version with the protocol, SAP, code lists, and analysis code:

• Analysis-data fitness and observability assessment
• Phenotype and code-list validation evidence matrix
• Protocol and SAP deviation log

How this maps to the catalog concepts

The data-fitness record asks whether the candidate source can measure the study's population, treatment, outcome, confounders, and follow-up with sufficient relevance and reliability; implement that judgment with fit-for-purpose-data-assessment-rwe and fda-rwd-ehr-claims. The phenotype matrix keeps the operational definition, validation evidence, transportability judgment, and empirical checks together; implement it with diagnosis-phenotype-algorithm-1ip-2op-time-window-rwe. The deviation log preserves the relationship between the approved specification and the analysis that was actually run; use it with harper, start-rwe, and record-pe. Together, the cross-references give a reviewer a path from design decision to data evidence, code version, and final disclosure.

Checklist

• Use the data-fitness worksheet before cohort construction; record evidence for every required population, exposure, outcome, covariate, and follow-up element.
• Create a phenotype matrix for every study-defining algorithm and link its versioned code list, validation evidence, and transportability judgment.
• Start the deviation log at protocol/SAP approval; preserve the original rule, timing, whether results were viewed, rationale, approval, and reporting action.
• Use the applicable official template or checklist when a regulator, sponsor, or journal requires it; these editorial worksheets do not substitute for those instruments.

Citations

1. [1]U.S. Food and Drug Administration. Real-World Data: Assessing Electronic Health Records and Medical Claims Data To Support Regulatory Decision-Making for Drug and Biological Products. Guidance for Industry. CDER/CBER; July 2024.
2. [2]Wang SV, Pottegård A, Crown W, et al. HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: a good practices report of a joint ISPE/ISPOR task force. Pharmacoepidemiology and Drug Safety. 2023;32(1):44-55.
3. [3]Wang SV, Pinheiro S, Hua W, et al. STaRT-RWE: structured template for planning and reporting on the implementation of real world evidence studies. BMJ. 2021;372:m4856.

1. [4]Langan SM, Schmidt SAJ, Wing K, et al. The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE). BMJ. 2018;363:k3532.