Barriers to and enablers of use of infectious disease decision support systems: a scoping review

Decision support systems are computerized programs that support decision making and subsequent action by organizations. In public health, decision support systems can support more rapid detection and response to infectious disease outbreaks, which can limit health, economic, and other societal impacts. Given their potential utility, there is opportunity to increase their implementation. To support uptake and sustainable use, this scoping review aimed to identify barriers to and enablers of use of infectious disease decision support systems according to the human, organization, technology-fit (HOT-fit) framework. Of the 19,268 unique studies identified in the search, 26 studies were included. Most studies (n = 20, 77%) described a decision support system for singular infectious diseases, including human immunodeficiency virus (HIV) (n = 4, 15%), COVID-19 (n = 3, 12%), and pneumonia (n = 3, 12%). Over half of the decision support systems were developed for use in the Americas (n = 14, 54%). In total, 118 study-specific barriers and 115 study-specific enablers were identified. Using the HOT-fit framework, study-specific barriers mapped onto 51 HOT-fit sub-factors (13 human, 16 organizational, 22 technology), and study-specific enablers mapped onto 41 HOT-fit sub-factors (9 human, 10 organizational, 21 technology, and 1 net benefit). Human, organizational, and technological factors must be considered when designing infectious disease decision support systems for sustained use. Identified barriers and enablers are often inter-related allowing multiple factors to be targeted by relevant implementation strategies. By encouraging communication between decision support system designers and end users, better designed decision support systems can be developed for improved prediction, response to, and control of infectious diseases.