||In light of the accelerating rate of electronic health record [EHR] adoption in the U.S., there is a recognized need for guidance on the matter of successful implementation practices (Coiera, Aarts & Kulikowski, 2011; Cresswell & Sheikh, 2013; Waterson, Hoonakker & Carayon, 2013; Institute of Medicine [IOM], 2011; The Office of the National Coordinator for Health Information Technology [ONC-HIT], 2012; Chaudhry et al., 2006; Black et al., 2011; Kushniruk, Bates, Bainbridge, Househ &Borycki, 2013; Bloomrosen et al., 2009; Shekelle, Morton & Keeler, 2006; Goldzweig, Towfigh, Maglione & Shekelle, 2009). Success may be defined as improved patient outcomes, improved financial outcomes, user satisfaction, or any combination of these (Nahm, Vaydia, Ho, Scharf & Seagull, 2007). Whatever the identified outcome, clinical information system [CIS] evaluations to date have frequently treated the CIS itself as a single, binary variable (absent or present), monolithically representing the entire intervention (Keshavjee, Kuziemsky, Vassanji & Ghany, 2013; Goldzweig, Towfigh, Maglione & Shekelle, 2009; Chaudhry et al., 2006). It is well understood that this is a gross oversimplification (Karsch, 2004; Harrison, Koppel & Bar Lev, 2007; Nemeth, Feifer, Stuart & Ornstein, 2008; Stead, 2007; Kellerman & Jones, 2013). The conflation of the effects of clinical information systems with the techniques used to implement them limits the advancement of implementation science. Implementation strategies and techniques are an important factor in the success of such projects, and should be examined on their own merits. The object of this paper is to discover what is known about how to achieve successful CIS implementations, with a focus on specific strategies and assessment of their effectiveness. This paper examines the qualitative and quantitative evidence available regarding a particular implementation strategy referred to as EHR optimization to determine what evidence exists that this practice affects the acceptance, cost, and clinical outcomes of clinical information systems.