ORIGINAL COMPANY-CONTEXT PRACTICE
Evaluate a model with missing device inputs
Original practice scenario inspired by Abbott Laboratories's public business context; this is not a reported interview question or a description of its internal systems. A fictional healthcare-product analytics model uses measurements from several device channels. One channel is often missing in a particular site. Design an evaluation of missing-input handling without making clinical efficacy claims.
Written for independent practice using company context; this is not a verified question from a company interview.
A REASONED APPROACH
Model answer.
Missingness can encode site, workflow, or equipment differences. Evaluate the complete pipeline under realistic missing patterns, rather than judging an imputation formula only on randomly hidden values.
Work through it
- Describe which inputs are optional and record why values are absent when known. Keep sites or devices separated if deployment targets new settings.
- Fit imputation and scaling within training data only. Compare an explicit missingness indicator, a simpler reduced-feature baseline, and an abstention path for unsupported patterns.
- Report performance and coverage by missingness pattern and site. Stress-test channel outages and ensure the interface identifies unavailable or unsupported predictions.
Tradeoffs to discuss
- Abstention reduces coverage but may avoid unjustified outputs. A model that exploits site-specific missingness may fail when collection workflows change.
Common pitfalls
- Replacing missing with zero can create a plausible but false measurement.
- Offline predictive accuracy does not establish clinical safety or authorize automated care decisions.