In Healthcare:
To Automate or Not to Automate, that is the Question

With modeling tools, you can define complex processes such as clinical guidelines. In theory these models can be automated. In practice it may be wise not to automate everything. The decision to automate depends on several factors, such as your goals and the problems that you need to solve. Automation is not without costs, and you need to consider the return on your investment (ROI).

The Decision to Automate

Certain processes or decisions are more attractive to automate than others. To identify these, you may ask some questions:

• Is it “high” value (high frequency, repetitive, something not to be overlooked)?
• Do users view automation of the process as something that would be helpful?
• Does the process or decision have a certain level of stability?
• Does it have reasonable data requirements?

How much data that the models require and how easy it is to obtain are key issues. If the automated process constantly interrupts the user or requires a large amount of data, then it may bring little value to the organization. One solution may be to have standing orders in place that will guarantee that the required data is always collected and available when it is needed.

The Emergency Department is an excellent example of practice setting which can be a challenge to automate. The environment can be chaotic, and some patients require dynamic care that is determined on the fly. Such tasks are a challenge to automate. However, even in the ED there are other processes where automation can relieve staff from drudgery and free them up for patient care.

One issue to consider relates to patient complexity. If most patients are straightforward while only a small subset are clinical challenges, then the complex patients can be triaged to a clinician while the remainder handled by an automated process. This improves overall efficiency and use of manpower.

Microservices

Even if a guideline is not fully automatable, it often contains elements that are. These can be encapsulated in microservices that are triggered when a certain set of conditions are met.

These are attractive since they often need a limited amount of data. They are easier to create and maintain. On the other hand, many of these services may be needed, which can introduce another set of challenges.