First, lets define enterprise traffic control and start to introduce some new terms. Don’t worry, they will all be explained, in detail, in future posts. Bear with me if some of this sounds a bit formal, but I want don’t want to over simplify this. I try to use as much alliteration as possible, as a memory tool, as much for myself as the reader. Let’s get going!!

Enterprise Traffic Control is a real time framework for coordinating and orchestrating the motion and data of People, Property and Places in a healthcare setting. We are going to talk mostly about healthcare but realize this concept can work in other industries. The ultimate goal of this framework is the unimpeded flow of the people and property that exists in a mobile workflow. Of course a mobile workflow is somewhat, we are calling, places. All this abstraction becomes important later on so we want to define it early. It is structured to recognize that people could be doing the work, but the work could also be done by other actuators, like robots and drones. That work uses property that could be assets, materials and supplies and they do that work in places, like hospital departments and procedural areas. The amount of work and delay associated with the workflow is reduced, resulting in a more efficient operation. Enterprise traffic control requires equal parts of technology and lean six sigma process improvements.

Enterprise Traffic Control exists within the current departmental structure in the organization. That structure is a network of interdependent, but functionally separate, systems. Enterprise traffic control acknowledges this and offers a new layer of connectedness that can address the queues and delays that occur.  With the emergence of real time systems and location-based services, these delays can be detected and, in many cases, remediated. This is accomplished by using location-based services for integration with new and existing systems to create new opportunities for automation and orchestration. The goal for any system that thrives on throughput is flow. The fundamentals of lean and six sigma state this clearly, but healthcare is fraught with variability which is the enemy of flow. When process has reached the limits of what it can do, the technology is used to close the gaps.

Motion and data for people, property, and places

The care traffic control structure exists within the current departmental structure and focuses on the motion of people and property.  To create this structure the care traffic control architect needs to have a framework to build with. Upon examination, this plays out much like the implementation of robotics in manufacturing where the mechanical motion of movement of parts and performance of work that involves motion was automated.  The assembly line changed very little, but the way it operated changed drastically and irreversibly.  Like manufacturing, the roles were changed to allow people to do more specialized tasks and the work that was highly repetitive or low value is done with automation.  It is important to understand that the definition of automation is not to remove the human, it is to augment the role of the human in a system.  Even robots, in many cases, require a human to complete a task. 

The structure of care traffic control resembles the structure of the current system because it operates in the gaps of time and space that exists in these systems. Let’s use supply chain as an example. The current state of the art for stocking supply closets is called “two bin Kanban”. It is intended to eliminate stock outs and optimize the restocking process. The way it works is to have two bins and when the first is empty you pull the second forward and pull a card from the empty bin and set in place where it can be scanned by the supply chain courier. None of this is care traffic control. Care traffic control is added by automating the restocking and eliminating the delay of waiting for the supply chain courier to trigger the restocking order for the scan. This is done with sensors, real time data and some minor process changes. 

Rational agents and PEAS

To find these gaps an architectural process is applied from the field of robotics and AI. It is based on examining and in many cases, creating rational agents. For this discussion, think of rational agents as people who are performing work and making decisions, inside a department that has customers.  In constructing a rational agent designers use a process called PEAS which is an acronym for Performance Measures, Environment, Actuators and Sensors.  These are the building blocks for a robotic system but it is also the building blocks for any system. 

• Performance Measures – Establish the criterion for success. 
• Environment – Provides the information necessary for decisions to be made, either by a person or machine. 
• Actuators – Do the work necessary for success as defined by the performance measures. 
• Sensors – Perceive conditions in the environment and provide real time information. 

When workflows are examined in the PEAS structure it is easy to find the opportunities for automation. It gets to the details without going so deep that it is hard to see the opportunities for improvement. A hospital that would go through this exercise for every workflow would easily find that have the most impact on improvement. In this way the priorities could be establish for moving forward with automation.

The first pass through the workflows is for automating the individual workflows and once that is complete another exercise is done where workflows are interdependent. This is for what we call “orchestration”. Orchestration is further automation done between workflows that have already had some automation applied. Consider Patient Transport and EVS. The patient is transported for a discharge and must be out of the room before the housekeeping can clean the room. We can automate the patient transport process with tracking, geofencing and other technologies and we can use the location of the housekeeper to track progress on jobs that are assigned. We would orchestrate by triggering the job to the clean the room with the exit of the patient from the room removing any delay between those two already automated workflows.

The intent of care traffic control is to catalog these opportunities for improvement enough to understand the architecture of the system required to do this at the enterprise level. This is the most efficient approach and the most effective at getting to ROI.

Technology

The PEAS model relies on sensors for perceiving conditions, but it also relies on integrations for the environmental information. This means that a platform needs to exist instead of individual point solutions. It is a location platform, but it is also an iOT platform. Some iOT vendors have seen this as the future but it is the implementation and architecture of the platform on top of the iOT that is the critical component for an enterprise care traffic control system. That air traffic control system has sensors for every phase of the journey. There is a ground radar for the gates and tarmac. There is terminal radar for the landings and takeoffs and there is air route radar for the routes between terminals. This is a partial list of sensors but the key thing to note is that they all work together in orchestration.

Maturity Curve

Borrowing from Gartner’s Real Time Healthcare model is the maturity curve that fits care traffic control the best. The list below has been adapted for care traffic control. Like any maturity curve, the organization may find element of each level in any point in time and the goal is not to bring the whole organization up at once. The best approach is to make progress in the most important areas first and that will set up a repeatable change mechanism to be used repeatedly.

• Reactive – Low situational awareness. Low use of mobility. No workflow automation. Inefficiencies cost the organization so much there is little room for innovation. Many point solutions with little integration between them.
• Monitored – Increased situational awareness. Increased use of mobility for workflow automation. Visibility into workflows has driven targeted improvement opportunities and expanded use of a location technologies. Workflows are cataloged and automation is underway.
• Managed – Situational awareness is used for incident management and operational efficiency. Significant workflow automation and some orchestration is in place. Mobility is built into every workflow that involves motion. A location platform is in place with integration to core systems.
• Intelligent – Situation awareness is focused on incident response because operational tasks are mostly automated. Command center structure is operating full time and covers many departments and workflows. Significant orchestration is in place. Robots and drones are actuators for many workflows. 

What Next?

Care traffic control offers a model for more efficient operations by focusing on motion and delay. It is also a bridge toward Real Time Healthcare. The important thing to realize is all the pieces to care traffic control currently exists and to get there it is more about architecture and execution. There will be more posts detailing how to create the architecture and tools for implementation.