BACKGROUND
Despite an increasing adoption rate of the tracking technologies for hospitals in the United States (U.S.), scarce empirical studies examined hospital size, location, and types of hospital affiliations that are associated with the uptake, leaving the understanding towards the trend unclear. This research is critical since tracking technologies are essential for today’s smart hospital systems as part of smart healthcare ecosystems.
OBJECTIVE
This study aimed to identify the hospital characteristics, geographic location, and hospital affiliation type attributive to adopting tracking technologies. With a longitudinal dataset, we compared critical factors associated with tracking technologies adoption for clinical and supply chain uses. We assume that hospital characteristics and hospital location have more impact on tracking technologies for clinical use, and types of hospital affiliation would have more impact on tracking technologies for supply chain use.
METHODS
This study was conducted based on national census data obtained from American Hospital Association (AHA)’s Annual Survey, AHA’s Information Technology Supplement Survey, and the U.S. Bureau of Economic Analysis website. Using this dataset, we used population logistic regression models to analyze 3623 hospitals across 50 states in the U.S. from 2012 to 2015. We were able to capture and examine the effects of the hospital characteristics, location, and types of hospital affiliations with the adjustment of the innate development of tracking technology over time.
RESULTS
We observed that the proportion of hospitals where tracking technologies were implemented for clinical use increased from 36.3% to 54.6%, whilst that for supply chain increased from 28.6% to 41.3% from 2012 to 2015. We also found that time effect and hospital size positively impacted the hospital implementation of tracking technologies for both clinical and supply chain use. The implementation rate of tracking technologies for clinical use increased for the hospitals affiliated to urban health systems but decreased in the hospitals located in rural areas. This difference indicates the geolocation disparities exist between urban and rural hospital systems. For supply chain use, the implementation rate increased for the hospital affiliated to a more centralized health system but decreased for for-profit hospitals compared to not-for-profit hospitals.
CONCLUSIONS
We provided a census assessment of tracking technologies adoption, including RFID and barcode in U.S. hospitals for clinical and supply chain uses, and offered a comprehensive and longitudinal overview of the hospital characteristics, location, and types of hospital affiliations associated with the tracking technology adoption. This study informs researchers, healthcare providers, and policymakers that hospital characteristics, location, and types of hospital affiliations have different impacts on both the level and rate of implementation of certain tracking technologies for clinical and for supply chain use. This study also has important implications for developing smart hospitals using tracking technologies to build their hospital infrastructure and personalized medicine.
CLINICALTRIAL