Agent-based simulation model for predicting adoption rates of Electronic Medical Records

There is an emerging trend among healthcare providers towards the replacement of paper-based health records with Electronic Medical Records (EMRs) in order to increase the quality of healthcare [1]–[4]. President Barack Obama's proposed health care plan encourages the adoption of state-of-the-art health information technology systems [5]. Interoperability is a critical issue in EMR systems, and uncertainty about which systems will become prevalent within the industry represents a barrier to adoption. This paper presents an agent-based model for characterizing the rate of adoption of EMRs based on the weighted importance of vendor functionality to institutional needs. Seeking to develop a decision-making tool within this arena, we have implemented an agent-based simulation that reveals the impact of various features on overall adoption rates. This paper discusses our model; the justification of its parameters; the uses among several social groups; and the interpretation of our findings.

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