Invited commentary: the use of imperfect data--compromise or compromising?

Area of Science:

• Epidemiology
• Health Informatics
• Biostatistics

Background:

• Automated databases provide accessible, detailed information but often contain critical data gaps.
• Researchers frequently use proxy variables to fill these gaps, yet the validity of these surrogates is seldom assessed.
• Accurate gestational-age data is crucial for epidemiological studies, particularly those examining medication use during pregnancy.

Discussion:

• This study evaluates two algorithms for estimating medication timing in pregnancy without gestational-age data.
• The delivery-date algorithm shows potential but is effective only under specific, often un verifiable, conditions.
• The reliability of proxy variables in automated databases for pregnancy research is questionable.

Key Insights:

• Estimating medication timing during pregnancy using algorithms without gestational-age data presents significant challenges.
• The effectiveness of the delivery-date algorithm is highly conditional and difficult to predict a priori.
• Imperfect data from automated databases can be problematic, necessitating careful validation and supplementation.

Outlook:

• Future research should focus on developing robust methods to fill data gaps in automated health databases.
• Linking disparate databases may offer a solution to improve data completeness and accuracy.
• Caution is advised when utilizing automated databases for critical research, emphasizing the need for data validation.