Checklist: Guidance and key considerations for outcome selection and measurement for an observational CER protocol

GuidanceKey ConsiderationsCheck
Propose primary and secondary outcomes that directly correspond to research questions.

Followup period should be sufficient to observe hypothesized effects of treatment on primary and secondary outcomes.

Provide clear and objective definitions of clinical outcomes.

Outcomes should reflect the hypothesized mechanism of effect of treatment, if known.

Provide justification that the outcome is reliably ascertained without additional validation, when applicable and feasible, or propose validation and/or adjudication of endpoints.

If an intermediate (surrogate) endpoint is proposed, provide justification why the main disease outcome of interest is not being used, and that the intermediate endpoint reflects the expected pathway of the effect of treatment on the main outcome of interest.

Provide clear and relevant definitions of cost or health resource utilization outcomes.

Outcomes chosen should reflect the hypothesized effect of treatment on specific components of medical cost and/or resource utilization, if known.

Outcomes should be able to be measured directly or via proxy from data sources proposed for study.

For costs, consider proposing standard benchmark costs to be applied to units of resource utilization; especially when multiple health systems, payment systems, and/or geographic regions are included in study population or data source.

Describe a plan for use of a validated, standard instrument for measurement of patient-reported outcomes.

The instrument chosen should reflect the hypothesized effect of treatment on specific aspects of disease symptoms or treatment, or quality of life, if known.

Propose use of a standard instrument that has been validated for use in population representative of the study population, when possible.

Have the instrument validated for use in translation to other specific languages if it is intended to be used in those languages for study, when possible.

Have the instrument validated for the intended mode of administration, when possible.

Address issues of bias expected to arise, and propose means of bias minimization.

Describe potential issues of bias, misclassification, and missing data that may be expected to occur with the proposed outcomes, including those specific to PRO data.

Provide a plan for minimization of potential bias, misclassification, and missing data issues identified.

Analysis

Proposed analytic methods should correspond to the nature of the outcome measure (e.g., continuous, categorical [dichotomous, polychotomous, or ordinal], repeated measures, time-to-event).

Plan sensitivity analyses relating to expected questions that arise around the study outcomes.

Propose sensitivity analyses that address different relevant definitions of the study outcome(s) or multiple related outcomes (e.g., different measures of subclinical and clinical cardiovascular disease).

From: Chapter 6, Outcome Definition and Measurement

Cover of Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide
Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide.
Velentgas P, Dreyer NA, Nourjah P, et al., editors.
Copyright © 2013, Agency for Healthcare Research and Quality.

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