Health and Community Systems, University of Pittsburgh School of Nursing, 3500 Victoria Street, Pittsburgh, PA 15261, USA.
J Biomed Inform. 2011 Jun;44(3):497-504. doi: 10.1016/j.jbi.2010.02.007. Epub 2010 Feb 20.
Implementation of electronic health records (EHR), particularly computerized physician/provider order entry systems (CPOE), is often met with resistance. Influence presented at the right time, in the right manner, may minimize resistance or at least limit the risk of complete system failure. Combining established theories on power, influence tactics, and resistance, we developed the Ranked Levels of Influence model. Applying it to documented examples of EHR/CPOE failures at Cedars-Sinai and Kaiser Permanente in Hawaii, we evaluated the influence applied, the resistance encountered, and the resulting risk to the system implementation. Using the Ranked Levels of Influence model as a guideline, we demonstrate that these system failures were associated with the use of hard influence tactics that resulted in higher levels of resistance. We suggest that when influence tactics remain at the soft tactics level, the level of resistance stabilizes or de-escalates and the system can be saved.
电子健康记录 (EHR) 的实施，特别是计算机化的医师/提供者医嘱输入系统 (CPOE)，常常会遇到阻力。在正确的时间、以正确的方式提出的影响因素可能会最小化阻力，或者至少限制系统完全失败的风险。我们结合了关于权力、影响策略和阻力的既定理论，开发了等级影响模型。将其应用于 Cedars-Sinai 和 Kaiser Permanente 在夏威夷的 EHR/CPOE 失败的记录案例，我们评估了所应用的影响因素、遇到的阻力以及对系统实施的风险。使用等级影响模型作为指导，我们表明这些系统故障与使用导致更高阻力的强硬影响策略有关。我们建议，当影响策略保持在软策略层面时，阻力的水平会稳定或降低，系统可以被挽救。
