Does the presence of a specialized rehabilitation unit in a Veterans Affairs facility impact referral for rehabilitative care after a lower-extremity amputation?

Objective: To determine if the presence of specialized rehabilitation units (SRUs) within Veterans Affairs medical centers (VAMC) influences access to rehabilitation services.

Design: Retrospective cohort analysis.

Setting: Two types of VAMCs: those with and without SRUs.

Clinical factors associated with prescription of a prosthetic limb in elderly veterans.

Objectives: To determine how advanced age influences prosthetic prescription.

Design: Retrospective cohort analysis with theory-driven logistic regression models. A Post Amputation Quality-of-Life (PAQ) framework of outcomes was proposed and empirically tested.

Why ethnic designation matters for stroke rehabilitation: comparing VA administrative data and clinical records.

Using existing administrative data to look at issues of ethnic disparities in rehabilitation-related outcomes may lead to misleading results. Problems can emerge from apparently small issues of reliability that are magnified by reclassification of ethnic designation and missing data in complete-subject analyses. We compared the reliability of ethnic assignment in Department of Veterans Affairs (VA) medical rehabilitation records for stroke patients with administrative records; reclassified the racial identifier from the administrative data in two ways; and examined the different sources of ethnic information in relation to severity, length-of-stay, disability assessment, and discharge disposition.

The hazards of stroke case selection using administrative data.

Background: Administrative data and ICD-9-CM diagnostic codes are frequently used in research efforts to evaluate risk adjusted patient outcomes, particularly mortality. Varying ICD-9-CM sampling algorithms have been used to identify stroke patients.

Objectives: This study evaluates the effects of different sampling strategies (one high sensitivity and one high specificity) on modeling stroke mortality as a performance indicator.