Medical School, University of Minnesota, Minneapolis, Minnesota, United States.
Center for Learning Health System Sciences, University of Minnesota, Medical School, Minneapolis, Minnesota, United States.
Appl Clin Inform. 2022 May;13(3):752-766. doi: 10.1055/s-0042-1751305. Epub 2022 Aug 11.
Chronic disease is the leading cause of mortality in the United States. Health information technology (HIT) tools show promise for improving disease management.
This study aims to understand the following: (1) how self-perceptions of health compare between those with and without disease; (2) how HIT usage varies between chronic disease profiles (diabetes, hypertension, cardiovascular disease, pulmonary disease, depression, cancer, and comorbidities); (3) how HIT trends have changed in the past 6 years; and (4) the likelihood that a given chronic disease patient uses specific HIT tools.
The Health Information National Trends Survey (HINTS) inclusive of 2014 to 2020 served as the primary data source with statistical analysis completed using Stata. Bivariate analyses and two-tailed -tests were conducted to compare self-perceived health and HIT usage to chronic disease. Logistic regression models were created to examine the odds of a specific patient using various forms of HIT, controlling for demographics and comorbidities.
Logistic regression models controlling for sociodemographic factors and comorbidities showed that pulmonary disease, depression, and cancer patients had an increased likelihood of using HIT tools, for example, depression patients had an 81.1% increased likelihood of looking up health information ( < 0.0001). In contrast, diabetic, high blood pressure, and cardiovascular disease patients appeared to use HIT tools at similar rates to patients without chronic disease. Overall HIT usage has increased during the timeframe examined.
This study demonstrates that certain chronic disease cohorts appear to have greater HIT usage than others. Further analysis should be done to understand what factors influence patients to utilize HIT which may provide additional insights into improving design and user experience for other populations with the goal of improving management of disease. Such analyses could also establish a new baseline to account for differences in HIT usage as a direct consequence of the novel coronavirus disease 2019 (COVID-19) pandemic.
慢性病是美国死亡的主要原因。健康信息技术（HIT）工具在改善疾病管理方面显示出前景。
本研究旨在了解以下几点：（1）自我健康感知在患有和不患有疾病的人群之间的差异；（2）慢性疾病谱（糖尿病、高血压、心血管疾病、肺部疾病、抑郁症、癌症和合并症）之间 HIT 使用的差异；（3）过去 6 年 HIT 趋势的变化；以及（4）特定慢性疾病患者使用特定 HIT 工具的可能性。
健康信息国家趋势调查（HINTS）包括 2014 年至 2020 年的数据，作为主要数据源，使用 Stata 进行统计分析。采用双变量分析和双侧 t 检验比较自我感知健康和 HIT 使用与慢性疾病的关系。创建逻辑回归模型，以检查特定患者使用各种形式 HIT 的可能性，同时控制人口统计学和合并症因素。
控制社会人口统计学因素和合并症的逻辑回归模型显示，肺部疾病、抑郁症和癌症患者使用 HIT 工具的可能性增加，例如，抑郁症患者查询健康信息的可能性增加了 81.1%（<0.0001）。相比之下，糖尿病、高血压和心血管疾病患者使用 HIT 工具的比率似乎与无慢性疾病患者相似。总体而言，在研究期间，HIT 的使用有所增加。
本研究表明，某些慢性疾病患者群体似乎比其他群体更多地使用 HIT。应进一步分析以了解哪些因素影响患者使用 HIT，这可能为改善其他人群的设计和用户体验提供更多见解，目标是改善疾病管理。这些分析还可以建立一个新的基线，以解释 2019 年冠状病毒病（COVID-19）大流行直接导致的 HIT 使用差异。
