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arxiv:2605.04666

Feature importance analysis for patient management decisions

Published on May 6
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Abstract

Analysis of electronic health record data reveals that physician decisions for laboratory tests and medications can be accurately predicted using a limited subset of patient features.

AI-generated summary

The objective of this paper is to understand what characteristics and features of clinical data influence physician's decision about ordering laboratory tests or prescribing medications the most. We conduct our analysis on data and decisions extracted from electronic health records of 4486 post-surgical cardiac patients. The summary statistics for 335 different lab order decisions and 407 medication decisions are reported. We show that in many cases, physician's lab-order and medication decisions can be well predicted from a small subset of all features.

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