Ranked Levels of Influence Model: Selecting Influence Techniques to Minimize IT Resistance

From Clinfowiki
Revision as of 16:36, 26 March 2015 by Hgarcia2 (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

This is a review of Bartos, Butler, and Crowley's 2011 article, Ranked Levels of Influence Model: Selecting Influence Techniques to Minimize IT Resistance.[1]


The authors of this article believe that there will always be some resistance in the implementation of health information technology (HIT). They created the ranked levels of influence model to guide HIT leaders, such as the Chief Medical Information Officer (CMIO) in understanding how the use of power and influence can negatively impact the physicians’ attitude toward HIT adoption and implementation.


The ranked levels of influence model is built from five theories: French and Raven’s Six Power Bases, Kipni’s Model of Influence, Bruin’s Power Use Model, Coetsee’s Levels of Resistance, and Lapointe and Rivard’s Resistive Behavior.


The result is a model with 6 levels of influence, each of which uses a different power base. Use of any of the 6 levels of influence results in a type of resistive reaction, ranging from lack of interest, to boycotts against leadership. To test the viability of the model, the authors used it to analyze the influence techniques used by the leaders of Cedars-Sinai and Kaiser Permanente during CPOE implementation, both of which resulted in the failure of implementation. Cedars-Sinai mandated CPOE use and suspended privileges of noncompliant clinicians, which resulted in physician boycott. Kaiser-Permanente implemented CPOE to employed physicians in Hawaii without involving them in decision-making, which resulted in apathy degenerating into withdrawal from use.


The authors conclude that the ranked levels of influence model they created is a valuable tool for leaders and champions in assessing the type of resistive behavior HIT implementation has incited in physicians, and can guide them in employing the correct influence tactics to prevent further resistance.


I believe the ranked levels of influence model is a good tool. However, I think it has to be used in conjunction with other leadership and influence concepts since its focus is too narrow. The case studies performed for Cedars-Sinai and Kaiser Permanente Hawaii could be more conclusive if the authors linked the exact levels of influence used to the model, as opposed to merely alluding to concepts.


  1. Bartos, C. E., Butler, B. S., & Crowley, R. S. (2011). Ranked levels of influence model: selecting influence techniques to minimize IT resistance. Journal of Biomedical Informatics, 44(3), 497-504. doi: 10.1016/j.jbi.2010.02.007. http://www.j-biomed-inform.com/article/S1532-0464(10)00022-5/fulltext