A product thinking framework for continuous connected care. It gives healthcare stakeholders the tools to design, build and operate novel tech-enabled care delivery models and is intended for application at all levels of the healthcare sector. It enables multi-stakeholder collaboration with a common language and understanding of how Remote Patient Continuous Connected Care healthcare as a system works.
At Persimmon, we’ve combined our collective experience from the fields of design, care, and technology to create a holistic approach that considers interdependencies across connected care experiences for patients, caregivers, and healthcare staff.
We collaborate with the best minds in healthcare to design digital health products that solve meaningful patient problems remotely. We work with the people in tech and healthcare to find innovative solutions that improve patient outcomes. It is a way of thinking that leads to better implementation of complex ideas, using design thinking and user research as a foundation for impactful digital products.
Our design process involves a lot of thinking and many iterations.
For our process and product design, we follow a clear set of frameworks that help us achieve our goals. We understand our customers and we know the ‘Jobs to be Done’ behind building a robust solution for remote patient monitoring and telehealth. For our solution to succeed, the Habits Loop with the elements of a cue, a routine and a reward was something we had to study and decipher from the very early stage of product development to help us understand how to change bad habits or form better ones.
Also, from extensive research and study, we have come to a conclusion that for a Telehealth system to be successful, a human (i.e the clinician) needs to be in the loop. Thus we designed a framework that requires human interaction which readily allows for the identification of problems and requirements that may not be easily identified by other means of simulation. All of our frameworks are then integrated by Lean Design thinking which helps us empathize with the users and create solutions which can give them the best user experience.
Frameworks that we use:
(i) Jobs to be done
(ii) Habits Loop
(iii) Humans in the loop
(iv) Lean Design
(i) Jobs to be done
Jobs to Be Done is an approach inspired by the question: “Why do customers buy?” While conventional marketing focuses on market demographics or product attributes, this framework explores functional, social, and emotional dimensions that explain why customers make the choices they do. People don’t simply buy products or services; they pull them into their lives to make progress. We call this progress the “job” they are trying to get done, and understanding this opens a world of innovation possibilities.
When Persimmon CHF is looking at the ‘Jobs to Be Done’ framework, we are looking at how we can make sure that nurses can do their job faster and easier? Previously, nurses had to go through an abundance of data themselves to extract the values of the data, and monitor patients one by one. But when a nurse is assigned 80 or 100 patients, it becomes virtually impossible to be on top of everyone. So how can we use technology to make this process easier for the nurse?
For the patient, the providers always have to be reactive and act when something happens. Now, because of wearables, even if there are slightest changes in weight, heart rate, sleep patterns, the providers can take preventive action quickly. We also have to take alert fatigue into account. When nurses and providers get alerted too frequently for false positives or false negatives, the value of the alerts diminishes. So in that scenario, if there is a way for nurses and providers to configure the alerts according to the patient's need, then the probability of false positive and false negative reduces and then they know that whenever there is an alert from the system, it’s actionable.
(ii) Habit loop
Most digital tools miss the habit cycle. Have you tried waking up at a different time than your usual and failed miserably? Changing habits is hard and when a patient gets sick, their lifestyle needs to change immediately. They need to learn in detail about the disease they have, how and what they can do to stay healthy, and what can help them live a normal life with the disease.
In this scenario, the patients may feel overwhelmed with so many wearables and monitoring devices provided to them. Similarly, for the healthcare providers and nurses, when a new piece of technology has to be adopted they need to learn something new, they need to fit into the new technology and incorporate it into their habit cycle.
We understand how habits are formed and align digital technology to those habits. The habit cycle takes four components: trigger, action, reward, and investment. For example, ‘alert’ is a trigger for nurses to take action. Now, when the alert happens, the job of the nurse is to either connect with the patient or the care provider, take notes and navigate. With digital technology, the nurses’ jobs become easier and faster with feedback being their reward.
Most digital tools do not recognize ‘feedback mechanism’ and therefore they miss the habit cycle. Digital tools should not limit to one-time interactions and getting a task done. In the tool we develop, all actions are recorded and nurses get to act based on an external trigger. This makes their job faster, more efficient and when they see instant feedback, they will have the gratification of doing something impactful for the patients. This will encourage them more and adoption increases
(iii) Human in the loop
We hear a lot about technology replacing humans. But we have learned that patients crave human connection. For us, it is about balancing human touch and technology augmentation. When we design a solution, we do not eliminate the human. But we design to ensure humans can do their faster, easier, and better. In the debate between 100% automation vs technology augmentation for humans in the loop, we side with humans in the loop. That’s more practical and effective.
The future of care delivery is expected to include an increasing use of these evidence-based decision support systems. These tools can drive strategies for healthcare management, disease monitoring and prevention, patient engagement, clinical decision support, and outcome measurement. Professional clinical judgment remains essential however. So the value of human-in-the loop in clinical decision and support is increasingly apparent. The role of the human could become more critical as traditional expert-centric clinical decision support moves toward a hybrid model where learning algorithms are making more and more clinical recommendations based on the rapidly evolving body of evidence.
It’s important to have a data collection process that's very quick, lean, and agile. It's also extremely important to have a human in the loop that can correct the system on behalf of the user. For example, when the nurse has some data coming from the patient after which the patient and nurse can have a short call for extra information about the disease or another corrective action, the patient is accountable for the caregiver report, and the nurse is accountable for the patient. So in that scenario, there are loops of accountability. And that's why the human-in-the-loops system becomes more important. Finally, it's also about execution. In our product thinking framework, we have jobs to be done, we have a habit loop, and we necessarily need to have a human-in-the-loop system.
When we look at product design from jobs to be done, habit loops, and human in the loop framework it gives us opportunity to think about solutions that don't add extra work to different stakeholders. Either their work reduces or solutions fit into their workflow without creating lift to learn new workflow or upending the existing workflow. The reduction in friction or not adding friction improves adoption. And solutions we think of may not be 100% matched in the first iteration. We know that clearly because we have our biases. We learned that the best way to reject solution biases is to have the customer or user be part of the solution design process from day one. For that, we advocate for a lean design framework.
(iv) Lean design
Lean design is based on the fundamental principle of understanding customers and validating with them after building a product, as frequently and as early as possible. This is achieved by conducting multiple rounds of small experiments, each designed to refine the understanding of the problem and to test assumptions.
Patients and caregivers want us to find meaning in the data. Patients don’t have the time, or physical/psychological condition most of the time to extract information on their own. Or the data is too complex for them to process on their own. We aim to solve the problems of our patients by understanding real pain points by observing them, and working with them. While we want to make tech as frictionless as possible, but not having enough friction also makes it tough for users (patients) to adopt our solutions. And it’s all about the data: discovering patterns, using data insight to understand how people behave in real world conditions and working with them on repeat. Through all this we aim to simplify the complexity of modern day healthcare.
Assuming that we are the users, developers, or designers, is one critical mistake, and designing the product in the absence of patient providers is another mistake. Yes, we can have ideas and those ideas or opinions need to be tested. That's where the concept of lean design comes in. We have a problem, we have the idea of how to solve that problem. And before we go into that idea, it needs to be tested so that even before we start developing, we have a high degree of certainty that we are designing and building software that's going to work for the patient, and that can only happen in iterative design, which we call lean design, which some people call ‘design thinking.’
This is exactly why we realize that CHF patients can be the older generation who can not use smartphones, whereas the nurses can be trained or have already been initiated towards it. There are needs to be personalized and that can only happen when we work with the end-user. We iterate, experiment and to do that quickly, we follow the lean design principles and create a product that's easy to use and helps solve on-job problems. And those design decisions will make the product easy to adopt.