Clinical Decisions and Software
Helping Medical Teams Provide Better Care
Jun 26, 2017
Clinical decision support in hospitals is complex and ever-changing. Bryan Young, Senior Engineer and member of Asymmetrik’s Health Strategy Team, recently explored the role of software in helping doctors, nurses, and clinical staff make the right decisions for patient care. To understand it better, let’s dive a little deeper into Bryan’s post.
Clinical Decision Support is Hard
On a daily basis, doctors, nurses, and clinical staff must gather, make sense of, and evaluate tons of patient data. In the news recently, more and more software is coming out to support companies in the running of their businesses. It has recently been suggested that software for insurance agencies has kick started the trend in getting software to ensure effective client communication. Getting this process right is critical, so medical professionals can make correct and informed decisions. In theory, clinical decision support (CDS) software systems help this process by providing contextual patient data. However, the doctors, nurses and staff using these systems are often dealing with poorly designed software that doesn’t meet their needs.
Common Problems with Clinical Decision Support Systems
- Built on bad assumptions: CDS systems are commonly built based on the wrong workflows and hierarchies, making them hard to use
- Not enough information: CDS systems provide limited details and context, making the data they provide hard to act on
- Too much noise: These systems don’t prioritize information, making it hard to parse the flood of data
In the best cases, poorly designed systems frustrate busy doctors, nurses, and hospital staff. In the worst cases, they lead to mistakes, poor advice, and failed handoffs between providers.
The Problem may be Structural
Melvin Conway came up with an idea to explain why it’s so hard to build good software systems. To paraphrase Conway’s Law, software systems tend to reflect the communication structure of the organizations that build them. In other words, if an organization is bureaucratic and rigid, the software created by that organization will also be.
In hospitals, doctors, nurses, and staff tend to organize into silos of expertise, rather than cross-functional teams. This structure isn’t good for real-time teamwork because staff can’t communicate effectively. This prevents them from quickly sharing the data they need. Conway’s Law suggests that the structure that limits these clinical teams also limits the software built to support them.
Ultimately, we must design software that reflects a modern workflow focused on collaboration
Disruptive Thinking may be the Key
Some medical centers, like Children’s Hospital in Minneapolis, recognize that the common structure of clinical teams is broken. They took steps to switch to a team-based approach. This includes training staff to leverage the expertise of their employees while pushing for more collaboration. Through these changes, doctors, nurses, and staff work closely together to handle patient care cases more effectively.
What Makes a Good CDS System?
So, what if we want to build an CDS system that follows a similar team-based approach? Ultimately, we must design software that reflects a modern workflow which is focused on collaboration. A successful system should address the following:
- Provide relevant patient status in real-time: See everything at a glance, including real-time patient status, in-process procedures and tests, current medications, and a list of all current providers
- Suggest a specialist: Identify the right team resources based on patient status and provider availability, including tools for coordinating between care providers with heavy patient loads
- Communicate instantly: Provide simple, purpose-driven text or video communication to quickly exchange relevant data
- Optimal ordering of tasks: Prioritize tasks based on each patient’s status, and the team at hand. And, raise alerts before critical conflicts come up
- Learn from mistakes: Teams face many challenges while trying improve patient outcomes. Mistakes can happen. By identifying why they happened and making appropriate changes, we can prevent them from happening again. To learn from mistakes, teams must focus on fact-based causes and solutions, rather than blame
What’s the Big Picture?
Software systems are powerful tools for solving problems. But, they will never overcome the shortcomings of the processes and workflows on which they are based. We must strive to build software that improves patient care by rethinking how caregivers work together efficiently and effectively. Because at the end of the day, our goal is not just automation or cost savings, it’s to help people.
We know that the end-user is often the single most important factor in success. That’s why at Asymmetrik, we follow a user-centered design approach. By putting the end-user at the center of the design process, we’re able to gain a better understanding of their tasks and workflows, within the context of their environment. This way, we can ensure that we meet the needs of the people who actually use and rely on our software, day in and day out.