How Can A “Worst-Case Scenario" Exercise Support The Digitization Projects?

30 January 2019
e-health
News
Transformation, not technology The first step in the digitization of the processes carried out in healthcare institutions is to learn the basic mistakes made when implementing other IT systems and to find ways to avoid them. When something goes wrong or not according to plan, software is most often blamed because it is too slow, because some errors appear, or because it is unintuitive. However, many case studies show something completely different. The most common reasons for the failure of an IT project include incorrect management of risks and of the digitization process, budget miscalculations and failures of the training plan. The computers on which doctors and nurses enter data and the structure of the IT system is usually of secondary importance. Besides, technology alone is not enough. If we want to see real change, we should look at the big picture and introduce a culture of innovation. Transforming old work rules, habits and patterns is not easy and naturally encounters resistance. It will also not happen overnight. It requires us to work hard and work together. Good communication with all employees and transparent actions are also a must. Visualization of failures Digitization is a very complicated process, especially in healthcare institutions, where medical data interlocks with administrative data. The variety of professions (medical and administrative) and, thus, the variety of expectations, can lead some groups to engaging in conflict, sabotaging new solutions or even demonstrating considerable resistance. Everything cannot be expected to go swimmingly. Furthermore, digitalization is a change process, and each change causes a natural disruption in previously established organizational procedures. Even if these procedures were not perfect before, it will take time for the IT system to streamline them, so it is very possible that, at the very beginning, the procedures will function even worse than before.
Digitalization is a change process, and each change causes a natural disruption
The transitional period between the launch of an IT system and the complete implementation of the planned way of its functioning is the most difficult. Frustration and dissatisfaction grow, employees feel stressed and lost. If such a situation lasts for a few weeks or even months, there is a high risk that the negative attitude will remain for longer, even forever. There are several ways to deal with this. The staff must feel constantly supported and understood by the management. System issues must be removed on an ongoing basis (hence why supervision is such an important stage of post-implementation). Regular meetings are used to gather opinions and respond quickly, if necessary. Moreover, staff should be informed of even the smallest successes. What can go wrong? The most important thing, however, is to be prepared for every circumstance. Most of them can be foreseen. It doesn’t matter if the organization makes first steps in digitalization or plan to expand already existing solution with new features. What will help is a conversation with those who carried out a similar project, and a short survey to learn what the staff is afraid of when it comes to digitization and what they think may go wrong. The exercise consists of visualizing worst-case scenarios. Imagine an expensive digitization project at a healthcare institution that turns out to be unsuccessful a year after its implementation. What could have been the reasons for this, what went wrong? Could this have been prevented, and, if so, how? Answers will help not only identify concerns but, above all, will help to prepare for many worst-case scenarios. It’s one of the easiest ways to recognize the fears of the workers and to monitor the general approach to the digitalization. Medical and administrative staff should be also regularly surveyed. What makes work difficult? What kind of problems the doctors and nurses have to face and how – in their opinions – IT could help? What slows the work? Where are the bottlenecks in patient flow? The results might be both surprising and inspiring.