title: The effect of payer mix on the adoption of information technologies by hospitals.
abstract: BACKGROUND
  Numerous studies have examined the relationship between organization characteristics and hospital adoption of information technology (IT). However, no known study has examined whether patient characteristics of those treated at a given hospital influences the decision to adopt IT.
  
  
  OBJECTIVE
  The present study combines primary and secondary data to examine the effect of payer mix (the combination of payers that make up a given hospital's patient discharges) on IT adoption in hospitals.
  
  
  METHODS
  Survey data from Florida hospitals were combined with the state's hospital discharge database. Multiple regression analyses were used to analyze the data.
  
  
  RESULTS
  When examining Medicare, Medicaid, traditional commercial insurance, and managed-care plans, only an increase of managed-care patients, as a percentage of hospital discharges, was associated with a significant increased likelihood to adopt clinical and administrative IT applications by hospitals.
  
  
  CONCLUSIONS
  Our results suggest that increasing cost pressures associated with managed-care environments are driving hospitals' adoption of clinical and administrative IT systems as such adoption is expected to improve hospital efficiency and lower costs. Given that such cost pressures are also emergent in Medicare, Medicaid, and traditional third-party payment environments, an opportunity exists for these parties to motivate hospital IT adoption as a means for cost reduction.
authors: College of Medicine, Florida State University, Tallahassee, FL, USA. nir.menachemi@med.fsu.edu
authors: Nir
authors: N
authors: Menachemi
authors: Neset
authors: N
authors: Hikmet
authors: Anol
authors: A
authors: Bhattacherjee
authors: Askar
authors: A
authors: Chukmaitov
authors: Robert G
authors: RG
authors: Brooks
mesh_terms: D003625:Data Collection; D004059:Diffusion of Innovation; D005431:Florida; D006751:Hospital Information Systems; D007348:Insurance, Health; D008484:Medicaid; D006278:Medicare; D012044:Regression Analysis