Scholarlink

Purpose <p>Patient-reported outcome measures (PROMs) are increasingly integrated into routine clinical care and value-based accountability frameworks, yet systematic non-response may exclude structurally marginalized populations, including transgender and gender diverse (TGD) individuals. This study examined individual- and neighborhood-level predictors of non-response to the PROMIS Global Health (PROMIS-10) questionnaire among TGD individuals using an intersectional multilevel framework.</p> Methods <p>We conducted an observational cohort study used electronic health record data from 2015 to 2023 within a large U.S. healthcare system. TGD adults (≥18 years) assigned the PROMIS-10 during clinical encounters were included. PROM non-response was defined as a questionnaire assigned but not completed. Multivariable regression evaluated sociodemographic predictors, and multilevel analysis of individual heterogeneity and discriminatory accuracy quantified variance across intersectional strata. Structural predictors included segregation (Delta Index) and Social Vulnerability Index (SVI).</p> Results <p>Non-response at encounter level was high among 7528 TGD patients (85.8%; 95% CI 84.2–87.4). Older age (≥ 36 years; β = 3.3; 95% CI 1.12–5.50) and lower educational attainment (β = 3.23; 95% CI 1.05–5.41) were associated with increased non-response, while insurance type was not associated and ethno-racial identity showed a small, non-significant increase after adjustment. Intersectional strata explained only 1% of variance in non-response, decreasing to 0.3% after adjustment. Higher segregation (Delta Index; β = 10; 95% CI 4.0–17.0) and residence in the highest vulnerability areas (SVI &gt; 0.75; β = 7.9; 95% CI 0.6–15.0) predicted greater non-response.</p> Conclusions <p>PROM non-response among TGD individuals reflects individual and structural inequities. Equity-centered PROM implementation strategies are needed to prevent systematic exclusion from outcome-based evaluation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Understanding determinants of patient-reported outcome measure non-response among transgender and gender diverse individuals: an intersectional multilevel analysis of sociodemographic and structural vulnerabilities

  • 期刊论文

  • 发表日期：

    2026年6月22日

查看全文
  • Manraj N. Kaur,
  • Mahima Jain,
  • Tanujit Dey,
  • Dany T. Huerta,
  • Peter Meyers,
  • Chengbo Zeng,
  • Brittany M. Dragonetti,
  • Marc R. DeAngelo,
  • Calvin Schuster,
  • Mohammad Naser Lessani,
  • Zhenglong Li,
  • Andrea Pusic,
  • Maria Edelen

摘要

Purpose

Patient-reported outcome measures (PROMs) are increasingly integrated into routine clinical care and value-based accountability frameworks, yet systematic non-response may exclude structurally marginalized populations, including transgender and gender diverse (TGD) individuals. This study examined individual- and neighborhood-level predictors of non-response to the PROMIS Global Health (PROMIS-10) questionnaire among TGD individuals using an intersectional multilevel framework.

Methods

We conducted an observational cohort study used electronic health record data from 2015 to 2023 within a large U.S. healthcare system. TGD adults (≥18 years) assigned the PROMIS-10 during clinical encounters were included. PROM non-response was defined as a questionnaire assigned but not completed. Multivariable regression evaluated sociodemographic predictors, and multilevel analysis of individual heterogeneity and discriminatory accuracy quantified variance across intersectional strata. Structural predictors included segregation (Delta Index) and Social Vulnerability Index (SVI).

Results

Non-response at encounter level was high among 7528 TGD patients (85.8%; 95% CI 84.2–87.4). Older age (≥ 36 years; β = 3.3; 95% CI 1.12–5.50) and lower educational attainment (β = 3.23; 95% CI 1.05–5.41) were associated with increased non-response, while insurance type was not associated and ethno-racial identity showed a small, non-significant increase after adjustment. Intersectional strata explained only 1% of variance in non-response, decreasing to 0.3% after adjustment. Higher segregation (Delta Index; β = 10; 95% CI 4.0–17.0) and residence in the highest vulnerability areas (SVI > 0.75; β = 7.9; 95% CI 0.6–15.0) predicted greater non-response.

Conclusions

PROM non-response among TGD individuals reflects individual and structural inequities. Equity-centered PROM implementation strategies are needed to prevent systematic exclusion from outcome-based evaluation.