The role of routine and structured social needs data collection in improving care in US hospitals.

IF 4.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of the American Medical Informatics Association Pub Date : 2024-11-06 DOI:10.1093/jamia/ocae279
Chelsea Richwine, Vaishali Patel, Jordan Everson, Bradley Iott
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Abstract

Objectives: To understand how health-related social needs (HRSN) data are collected at US hospitals and implications for use.

Materials and methods: Using 2023 nationally representative survey data on US hospitals (N = 2775), we described hospitals' routine and structured collection and use of HRSN data and examined the relationship between methods of data collection and specific uses. Multivariate logistic regression was used to identify characteristics associated with data collection and use and understand how methods of data collection relate to use.

Results: In 2023, 88% of hospitals collected HRSN data (64% routinely, 72% structured). While hospitals commonly used data for internal purposes (eg, discharge planning, 79%), those that collected data routinely and in a structured format (58%) used data for purposes involving coordination or exchange with other organizations (eg, making referrals, 74%) at higher rates than hospitals that collected data but not routinely or in a non-structured format (eg, 93% vs 67% for referrals, P< .05). In multivariate regression, routine and structured data collection was positively associated with all uses of data examined. Hospital location, ownership, system-affiliation, value-based care participation, and critical access designation were associated with HRSN data collection, but only system-affiliation was consistently (positively) associated with use.

Discussion: While most hospitals screen for social needs, fewer collect data routinely and in a structured format that would facilitate downstream use. Routine and structured data collection was associated with greater use, particularly for secondary purposes.

Conclusion: Routine and structured screening may result in more actionable data that facilitates use for various purposes that support patient care and improve community and population health, indicating the importance of continuing efforts to increase routine screening and standardize HRSN data collection.

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常规和结构化社会需求数据收集在改善美国医院护理方面的作用。
目的:了解美国医院如何收集与健康相关的社会需求(HRSN)数据及其使用意义:了解美国医院如何收集与健康相关的社会需求(HRSN)数据及其对使用的影响:利用 2023 年美国医院的全国代表性调查数据(N = 2775),我们描述了医院对 HRSN 数据的常规和结构化收集与使用情况,并研究了数据收集方法与具体使用之间的关系。我们使用多变量逻辑回归来确定与数据收集和使用相关的特征,并了解数据收集方法与使用之间的关系:2023 年,88% 的医院收集了 HRSN 数据(64% 为常规数据,72% 为结构化数据)。虽然医院通常将数据用于内部目的(如出院计划,79%),但那些常规收集数据并采用结构化格式的医院(58%)将数据用于与其他组织协调或交流的目的(如转诊,74%),其使用率高于那些未常规收集数据或采用非结构化格式的医院(如转诊,93% vs 67%,P< .05)。在多变量回归中,常规和结构化的数据收集与数据的所有用途均呈正相关。医院位置、所有权、系统隶属关系、基于价值的护理参与度和关键准入指定与 HRSN 数据收集有关,但只有系统隶属关系与数据使用持续(正)相关:讨论:虽然大多数医院都会对社会需求进行筛查,但以常规和结构化格式收集数据以方便下游使用的医院较少。常规和结构化的数据收集与更大程度的使用有关,尤其是用于次要目的:常规和结构化筛查可能会产生更多可操作的数据,便于用于支持患者护理、改善社区和人口健康的各种目的,这表明继续努力增加常规筛查和规范 HRSN 数据收集的重要性。
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来源期刊
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association 医学-计算机:跨学科应用
CiteScore
14.50
自引率
7.80%
发文量
230
审稿时长
3-8 weeks
期刊介绍: JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
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