Abstract
BACKGROUND: Chronic disease is the leading cause of mortality in the United States. Health information technology (HIT) tools show promise for improving disease management. OBJECTIVES: 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. METHODS: 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 t-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. RESULTS: 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 (p < 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. CONCLUSION: 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.