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Cost evaluation of integrating local HIV and housing data to facilitate service coordination in four demonstration sites.

Michele M AbbottRyan K McBainLisa WagnerHarry H Liunull null
Published in: AIDS care (2021)
As part of the evaluation of a federal initiative to integrate HIV medical and housing data at four local jurisdictions in the U.S., we estimated the financial costs of implementing data integration occurring from June 2016 to August 2018. We collected data on labor, non-labor, and overhead expenses based on invoices and surveys of staff time, staff compensation, and non-labor expenses. Non-labor expenses were directly charged or allocated to the project using the number of full-time equivalents as the allocation basis. Reported indirect cost rates were used to estimate overhead expenses. Demonstration sites spent an average of $273,656 over the full 27-month period, with an average monthly spending of $10,010 in 2018 U.S. dollars. There was sizable variation in the data integration costs across sites, implementation phases, and data integration models. Findings may help policymakers and potential adopters of similar data integration efforts customize parameters for local conditions and estimate resources required.
Keyphrases
  • electronic health record
  • big data
  • quality improvement
  • healthcare
  • hiv infected
  • hiv positive
  • hiv aids
  • climate change
  • machine learning
  • hiv testing
  • risk assessment
  • deep learning
  • mental illness
  • artificial intelligence