Some policymakers argue that consumers need legal protection of their privacy before they adopt interactive technologies. Others contend that privacy regulations impose costs that deter adoption. We contribute to this growing debate by quantifying the effect of state privacy regulation on the diffusion of Electronic Medical Record technology (EMR). EMR allows medical providers to store and exchange patient information using computers rather than paper records. Hospitals may not adopt EMR if patients feel their privacy is not safeguarded by regulation. Alternatively, privacy protection may inhibit adoption if hospitals cannot benefit from exchanging patient information with one another. In the US, medical privacy laws that restrict the ability of hospitals to disclose patient information vary across time and across states. We exploit this variation to explore how privacy laws affect whether hospitals adopt EMR. Our results suggest that inhibition of EMR's network benefits reduces hospital adoption by up to 25 percent. We find similar evidence when we control for the endogeneity of state laws using variation in signups to the Do Not Call list.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by NET Institute in its series Working Papers with number
07-16.
Find related papers by JEL classification: I1 - Health, Education, and Welfare - - Health K2 - Law and Economics - - Regulation and Business Law L5 - Industrial Organization - - Regulation and Industrial Policy O3 - Economic Development, Technological Change, and Growth - - Technological Change
This paper has been announced in the following NEP Reports:
Did you know? Citation analysis on IDEAS includes online papers that are freely accessible and whose text could be automatically analyzed, currently about 210000 papers.