Farouk Dako, Pavel Karasek, James Seward, Kollin White, Anil Vachani, Katharine Rendle, Carmen Guerra
{"title":"测量肺癌筛查队列中与健康相关的社会风险","authors":"Farouk Dako, Pavel Karasek, James Seward, Kollin White, Anil Vachani, Katharine Rendle, Carmen Guerra","doi":"10.1016/j.jacr.2025.04.018","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the feasibility and limitations of measuring health-related social risks (HRSRs) affecting individuals in a lung cancer screening (LCS) cohort from multiple data sources.</p><p><strong>Methods: </strong>A single-institution study analyzed data from 227 participants in a pragmatic LCS trial in west and southwest Philadelphia. HRSRs were assessed using three approaches: (1) electronic health records (EHRs) capturing individual-level social risks (eg, financial strain, housing stability); (2) neighborhood-level analysis using a modified Yost index to determine socio-economic status; and (3) semistructured interviews with 15 participants to identify barriers and facilitators to LCS adherence.</p><p><strong>Results: </strong>EHR data revealed financial strain and housing instability as the most documented HRSRs, although missing data ranged from 64% to 69%. Neighborhood-level analysis showed participants had lower socio-economic status compared with their broader communities, with Yost index scores of 1.28 (west Philadelphia) and 1.20 (southwest Philadelphia). Interviews highlighted limited knowledge of LCS (87% unaware before clinician referral), reliance on public or supplemental transportation, and overall trust in health care providers. Transportation was not a significant reported barrier to LCS adherence.</p><p><strong>Discussion: </strong>This study demonstrates the promise and limitations of EHR data, neighborhood-level data, and patient interviews to assess HRSRs. Although EHRs provided limited and inconsistent data, interviews captured granular individual experiences, and neighborhood-level analysis contextualized socio-economic influences. Comprehensive and consistent data collection across multiple sources is critical in understanding HRSRs experienced by individuals.</p>","PeriodicalId":73968,"journal":{"name":"Journal of the American College of Radiology : JACR","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring Health-Related Social Risks in a Lung Cancer Screening Cohort.\",\"authors\":\"Farouk Dako, Pavel Karasek, James Seward, Kollin White, Anil Vachani, Katharine Rendle, Carmen Guerra\",\"doi\":\"10.1016/j.jacr.2025.04.018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To evaluate the feasibility and limitations of measuring health-related social risks (HRSRs) affecting individuals in a lung cancer screening (LCS) cohort from multiple data sources.</p><p><strong>Methods: </strong>A single-institution study analyzed data from 227 participants in a pragmatic LCS trial in west and southwest Philadelphia. HRSRs were assessed using three approaches: (1) electronic health records (EHRs) capturing individual-level social risks (eg, financial strain, housing stability); (2) neighborhood-level analysis using a modified Yost index to determine socio-economic status; and (3) semistructured interviews with 15 participants to identify barriers and facilitators to LCS adherence.</p><p><strong>Results: </strong>EHR data revealed financial strain and housing instability as the most documented HRSRs, although missing data ranged from 64% to 69%. Neighborhood-level analysis showed participants had lower socio-economic status compared with their broader communities, with Yost index scores of 1.28 (west Philadelphia) and 1.20 (southwest Philadelphia). Interviews highlighted limited knowledge of LCS (87% unaware before clinician referral), reliance on public or supplemental transportation, and overall trust in health care providers. Transportation was not a significant reported barrier to LCS adherence.</p><p><strong>Discussion: </strong>This study demonstrates the promise and limitations of EHR data, neighborhood-level data, and patient interviews to assess HRSRs. Although EHRs provided limited and inconsistent data, interviews captured granular individual experiences, and neighborhood-level analysis contextualized socio-economic influences. Comprehensive and consistent data collection across multiple sources is critical in understanding HRSRs experienced by individuals.</p>\",\"PeriodicalId\":73968,\"journal\":{\"name\":\"Journal of the American College of Radiology : JACR\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American College of Radiology : JACR\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jacr.2025.04.018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American College of Radiology : JACR","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.jacr.2025.04.018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measuring Health-Related Social Risks in a Lung Cancer Screening Cohort.
Objective: To evaluate the feasibility and limitations of measuring health-related social risks (HRSRs) affecting individuals in a lung cancer screening (LCS) cohort from multiple data sources.
Methods: A single-institution study analyzed data from 227 participants in a pragmatic LCS trial in west and southwest Philadelphia. HRSRs were assessed using three approaches: (1) electronic health records (EHRs) capturing individual-level social risks (eg, financial strain, housing stability); (2) neighborhood-level analysis using a modified Yost index to determine socio-economic status; and (3) semistructured interviews with 15 participants to identify barriers and facilitators to LCS adherence.
Results: EHR data revealed financial strain and housing instability as the most documented HRSRs, although missing data ranged from 64% to 69%. Neighborhood-level analysis showed participants had lower socio-economic status compared with their broader communities, with Yost index scores of 1.28 (west Philadelphia) and 1.20 (southwest Philadelphia). Interviews highlighted limited knowledge of LCS (87% unaware before clinician referral), reliance on public or supplemental transportation, and overall trust in health care providers. Transportation was not a significant reported barrier to LCS adherence.
Discussion: This study demonstrates the promise and limitations of EHR data, neighborhood-level data, and patient interviews to assess HRSRs. Although EHRs provided limited and inconsistent data, interviews captured granular individual experiences, and neighborhood-level analysis contextualized socio-economic influences. Comprehensive and consistent data collection across multiple sources is critical in understanding HRSRs experienced by individuals.