The analysis includes a value chain' analysis of EMRs and how EMRs create value for physicians and for society. The EMR policy analysis will critique current EMR implementation policies and point out where failures are occurring in the value chain and how the same mistakes are being repeated across the country.
EMR implementation theory and research on EMR uptake will be used to provide insight into where economic drivers and EMR roll out policies have collided to create poorly aligned incentives, opportunities for cheating and an environment that is keen for uptake, but is paradoxically mired in apathy as well-intentioned programs founder on the treacherous shoals of complex ICTs in health care.
The analysis will attempt to illustrate that the policy failure in Canada is largely due to a misunderstanding of the dynamics of deploying complex technologies into complex organizational settings, the incentives for doing so and the returns necessary to justify continuing investment. EMR investment and deployment policies have been largely based on an erroneous understanding of the benefits of ICT in health care and how they can be realized. This has led to large of sums of money being expended, but poor or inadequate uptake.
 Keshavjee K. EMR Implementation in Ontario: A position paper to increase EMR implementation in Ontario. Intel of Canada White Paper. July 2007.
 Kucukyazici B, Keshavjee K, Bosomworth J, Copen J, Lai J. Best practices for Implementing Electronic Health Records and Information Systems. In Human, Social and Organizational Aspects of Health Information Systems [Eds: Kushniruk A and Borycki E]. IGI Global 2008.
 Wang SJ, Middleton B, Prosser LA, Bardon CG, Spurr CD, Carchidi PJ, Kittler AF, Goldszer RC, Fairchild DG, Sussman AJ, Kuperman GJ, Bates DW. A cost-benefit analysis of electronic medical records in primary care. Am J Med. 2003 Apr 1;114(5):397-403.
 Nancy M. Lorenzi, Laurie L. Novak, Jacob B. Weiss, Cynthia S. Gadd, and Kim M. Unertl. Crossing the Implementation Chasm: A Proposal for Bold Action. J Am Med Inform Assoc 2008; 15: 290-296.
This paper describes the design of an informatics architecture to extract data from community-based EMRs to a central data repository. Challenges encountered, including un-coded and unstructured data, poor meta-data binding and incomplete data will be described. Approaches to improving data quality when data comes from multiple EMRs, each with a proprietary database, and multiple physicians, each with different charting habits, will be proposed. Improvements to EMR functionality to facilitate data capture will also be proposed.