Implementation of New Systems

 

Why is it important to understand usability, configurability, and interoperability? Should these concepts outweigh the underlining cost of the new system? Which system do you recommend and why?
During phase one, you are selecting a team. What characteristics are important to consider when selecting a team?
During phase two the following principle was discussed, “lead with culture, determining where the resistance is,” and then, engage all levels of employees (Sipes, 2019, p. 161). What does this principle mean to you and how can you implement this principle?
How will you handle physician and other key professionals’ resistance to change and using the new system?
Discuss possible pitfalls during the implementation phase and how you can avoid them?
Describe your personal experience with automation and new information systems.

Sample Solution

Implementation of New Systems

The market for EMRs, electronic medical records, is healthy and expected to grow over the next several years. The adoption rate of this technology, incentivized through the adoption of the American Recovery and Reinvestment Act of 2009, was largely fueled by its acceptance by physicians, the major driver of ERM technology. Understanding the usability, configurability and interoperability ensures maximum utilization of the systems for the benefit of the end users and the clients. That also ensure proper sharing of data that supports evidence-based practice. These concepts should not outweigh the costs of a new system.

incompatible blocks in separate, consecutive blocks could distort scores through different sources of systematic error variance (Tiege-Mocigemba et al. 2010), causing the results to be invalid. The IAT can also be influenced by factors unrelated to the to-be-measured concepts, like the block structure, the order of compatible and incompatible blocks, and reordering processes (Tiege-Mocigemba et al. 2010). Reordering processes occur when participants try to recode the four categories into two using their own parameters; this lowers validity as the parameters that each participant uses will be subjective and different for each participant. Finally, this measure is comparative in nature: it assesses relative evaluations for one concept to another but does not give individual scores for each group, damaging the suitability for association measurement to an individual target.

There have been some adaptions to the IAT, trying to compensate for its limitations. For example, the Single Category IAT (SC-IAT; Karpinski and Steinman, 2006) attempted to cope with the comparative nature of the IAT by reducing it to a single category. This measure has demonstrated its value in a considerable number of studies. The Recoding-Free IAT (RF-IAT; Rothermund et al., 2009) and the Single Block IAT (SB-IAT) have replaced the original block structure, instead mapping response keys across trials. This adaption has the advantage of being uninfluenced by order effects of compatible and incompatible blocks (Nosek, Greenwald and Banaji, 2007). The Single Target IAT (ST-IAT; Bluemke and Friese, 2008) improves the IAT by allowing for the measurement of associations between evaluations and single categories (e.g. black/good and black/bad). These adaptions have all shown vast improvement on the standard IAT and support the usefulness of this measure.

Another implicit attitude measure is the Evaluative Priming (EP) Task, by Fazio, Sanbonmatsu, Powell and Kardes (1986). This measure employs the basic procedure of sequential priming to assess evaluative responses (Fazio et al., 1986), and is based on the assumption that the activation of one concept automatically activates re

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