Yan Alice S, Apathy Nate C, Chen Jie
Department of Health Policy and Management, School of Public Health, University of Maryland, College Park.
Hospital and Public Health Interdisciplinary Research (HAPPY) Lab, School of Public Health, University of Maryland, College Park.
JAMA Health Forum. 2025 Sep 5;6(9):e253035. doi: 10.1001/jamahealthforum.2025.3035.
Access to and quality of care vary substantially by area socioeconomic status. Expanding hospital health information technology (HIT) adoption may help reduce these disparities, given hospitals' central role in serving underserved populations.
To examine variations in US hospital adoption of telehealth and health information exchange (HIE) functionalities by hospital service area (HSA) socioeconomic deprivation.
DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study links data from the 2018-2023 American Hospital Association Annual Survey and Information Technology Survey with HSA-level area deprivation index. Nonfederal acute care hospitals with complete data on HIT outcomes, comprising 16 646 observations for the telehealth outcomes and 9218 observations for the HIE outcomes across 6 years, were included. Data were analyzed from February 2024 to February 2025.
HSA-level area deprivation index in quartiles.
Hospital adoption of treatment-stage telehealth and postdischarge telehealth services and HIE infrastructure supporting electronic data query and availability. Descriptive, regression, and Blinder-Oaxaca decomposition analyses and visualized time trends in hospital HIT adoption were used in analyses.
This study included 16 646 hospital-level observations and 9218 observations for health information exchange functionalities. Hospitals in the most socioeconomically deprived HSAs were significantly less likely to adopt HIT compared with those in the least deprived areas (treatment-stage telehealth: marginal effect [ME], -0.03; 95% CI, -0.06 to -0.01; postdischarge telehealth: ME, -0.03; 95% CI, -0.07 to 0.01; electronic data query capability: ME, -0.03; 95% CI, -0.06 to -0.01; electronic data availability: ME, -0.06; 95% CI, -0.11 to -0.01). Year fixed effects indicated significant increases in HIT adoption from 2018 to 2023, regardless of HSA deprivation level. Decomposition analyses showed that differences in hospital bed size, urban/rural location, and accountable care organization participation explained a substantial portion of the disparities by HSA deprivation.
In this study, hospitals in more socioeconomically disadvantaged HSAs remained likely to adopt telehealth and HIE functionalities. Nevertheless, HIT adoption has grown steadily over time. Accountable care organization participation may support HIT infrastructure and help reduce geographic disparities in adoption and access to care.
医疗服务的可及性和质量因地区社会经济地位的不同而有很大差异。鉴于医院在为服务不足人群提供服务方面的核心作用，扩大医院健康信息技术（HIT）的应用可能有助于减少这些差距。
研究美国医院按医院服务区（HSA）社会经济贫困程度在采用远程医疗和健康信息交换（HIE）功能方面的差异。
设计、设置和参与者：这项横断面研究将2018 - 2023年美国医院协会年度调查和信息技术调查的数据与HSA层面的地区贫困指数相联系。纳入了具有完整HIT结果数据的非联邦急症护理医院，6年中共有16646条远程医疗结果观测值和9218条HIE结果观测值。数据于2024年2月至2025年2月进行分析。
按四分位数划分的HSA层面地区贫困指数。
医院对治疗阶段远程医疗和出院后远程医疗服务的采用情况以及支持电子数据查询和可用性的数据交换基础设施。分析中使用了描述性、回归和布林德 - 奥克亚分解分析以及医院HIT采用情况的可视化时间趋势。
本研究包括16646条医院层面的观测值和9218条健康信息交换功能的观测值。与最不贫困地区的医院相比，社会经济最贫困的HSA地区的医院采用HIT的可能性显著更低（治疗阶段远程医疗：边际效应[ME]，-0.03；95%置信区间，-0.06至-0.01；出院后远程医疗：ME，-0.03；95%置信区间，-0.07至0.01；电子数据查询能力：ME，-0.03；95%置信区间，-0.06至-0.01；电子数据可用性：ME，-0.06；95%置信区间，-0.11至-0.01）。年份固定效应表明，无论HSA贫困水平如何，2018年至2023年HIT的采用率都有显著提高。分解分析表明，医院床位规模、城乡位置以及 accountable care organization（可问责医疗组织）参与度的差异解释了HSA贫困导致的大部分差距。
在本研究中，社会经济处境更不利的HSA地区的医院仍有可能采用远程医疗和HIE功能。尽管如此，随着时间的推移，HIT的采用率稳步增长。可问责医疗组织的参与可能会支持HIT基础设施，并有助于减少在采用和获得医疗服务方面的地理差距。
