Comparing Matching Strategies to Address Selection into Palliative Care among Veterans
Brystana Kaufman, Sandra Woolson, Paul Dennis, Joshua Thorpe, Susan Hastings, David Bekelman, Courtney Van Houtven

TL;DR
This study compares different matching strategies to reduce selection bias in observational studies of palliative care among veterans.
Contribution
The study introduces a novel approach to quantify residual selection bias by comparing three matching strategies in palliative care research.
Findings
Matching on observed characteristics was not sufficient to control for selection into palliative care.
The smallest survival difference was observed among veterans with prior inpatient palliative care.
Residual unobserved confounding affected estimates of palliative care effects on veteran outcomes.
Abstract
Selection bias influences observational studies of palliative care because many of the reasons for palliative care referral are not documented in administrative data sources, making it difficult to control for unobserved confounders. In observational studies, matching and weighting methods aim to control for unobserved confounding that is correlated with observed characteristics. This study aimed to quantify residual selection bias due to unobserved factors by comparing 3 strategies (combinations of exact match, Mahalonobis distance, and propensity weighting) applied to multi-payer data (2014-2017) to support causal inference approaches. The national cohort included veterans with life limiting conditions who were new users of VA specialty outpatient PC (treat) and matched veterans with non-PC specialty outpatient encounter (active comparator). Residual unobserved confounding was…
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Taxonomy
TopicsPalliative Care and End-of-Life Issues · Chronic Disease Management Strategies · Advanced Causal Inference Techniques
