The Clinical Dashboard: Brian Buys, Vice President, Product Management – Senior Care, PointClickCare
As VP, Product Management — Senior Care for international health care technology provider PointClickCare, Brian Buys is intimately familiar with the need for — and potential of — information dashboards serving clinicians in the long-term care and post-acute care industries.
In this Clinical Dashboard series interview, Buys details the most critical elements of his ideal clinical dashboard, as well as the questions care teams and managers need to be asking, how they can improve upon data collection, and where predictive analytics will be a key player in health care going forward.
To start, what are the three most important data points for an ideal skilled nursing clinical dashboard, and why?
Brian Buys: I think more about the questions we’re answering with data, rather than the data themselves, as we think about clinical dashboards. The three questions I think a lot about, and that we think a lot about as a product team helping to build clinical dashboards are: One, who do we need to pay attention to as a priority? Obviously, we have to provide care and monitor and provide a level of surveillance for everyone, but how do we know who needs our attention today most imminently? The second is, what is happening that is causing that need for us to pay attention? What is the trend? What is the context of this particular person? What’s their trajectory? What is their general set of conditions or things that require care and services, but also what’s going on in the current timeframe that has caused us to pay attention? Then the third question is, how is our team responding to that situation?
Do we have a plan to collect the right information, maybe to go deeper, to learn a little bit more about what’s going on? Are we communicating with other stakeholders or others who are part of the care team, but might not be directly in a facility or building, so that we can coordinate our response effectively and make sure that we’re delivering the best care for the best outcomes for a particular person?
Those are the three things that the data help, but they’re really answering those three broader questions: Who should we pay attention to most critically? What is happening that causes us to need to pay attention? And how are we responding as a care team?
How does an ideal clinical dashboard drive patient care decisions for operators?
Back to answering those three questions, if you can pretty quickly identify who needs our attention and what is happening without having to do a lot of additional investigation and reading and synthesizing of information, then you can pretty quickly and efficiently get to what actions need to be taken. If you’re also answering that third question, “What are we already planning or what have we already done?” then we can really focus on what we haven’t planned yet or what gaps are there and what we need to do to close those gaps to make sure that we’re responding appropriately to any given situation.
How does the ideal clinical dashboard help optimize reimbursement for operators?
As I think about reimbursement, and I put my clinician hat on, it always feels a little interesting for a clinician to talk about reimbursement, right? Really, clinical care is about delivering the best outcomes for particular patients and not necessarily about what we need to do to optimize reimbursement. There’s always a natural tension between reimbursement and clinical care, that’s just universal in health care.
What’s exciting for me as I look at the changes across health care, and particularly the focus on value-based care for seniors, is that value-based care really helps reduce that natural tension by allowing providers to benefit economically from delivering great outcomes. In a fee-for-service world where a payment is really, really connected just to the services, there’s less focus on the outcome of those services and more on making sure that reimbursement occurs for the service as it’s been delivered.
In a value-based model, which we are moving to broadly, there is significant incentive around the culmination of those services being a great outcome for everyone. If you think about the Triple Aim or Quadruple Aim in health care, I think value-based care is really helping align incentives toward those broader goals around great outcomes for patients, reducing costs, reducing the burden ultimately on clinicians and better managing populations.
How can this clinical dashboard improve staffing efficiency?
EHRs, just by definition, are electronic health records. A record, if you think back to the paper world even, is something that was designed to capture information and store it. In that scenario, when you make something that was paper electronic, you haven’t really saved much time because you still have to go back and read the record to understand the story of what is happening and to answer those questions: Who should I pay attention to? What is happening that we should pay attention to? How are we responding?
You need to read deeper into the record as you get to the answer. You might read across the records of many patients at a high level to understand who you need to pay attention to, then drill into each one to understand what is happening that causes us to need to pay more attention. Then read even deeper into the record to understand how our team is responding, and then infer [from there].
Some of that information may not be included in the record, the phone calls, the faxes, the other things that are happening surrounding that medical record. Our vision broadly is to help realize the promise of electronic medical records by breaking the paradigm and thinking more about the record as something that sits underneath and the dashboards that sit on top that help drive a tremendous amount of efficiency. That was the hope and the promise originally of EHRs, even 20 years ago or so when I started working in this area, we’ve been wrestling with that ever since.
It’s really exciting where we are, and particularly with some advancing technology that makes some of the synthesis of information much easier. As we talk about some of the recent advances with machine learning and large language models, I’m really optimistic about where the future is going and how technology is going to help us get there. It’s really exciting to unlock some of those long promises of technology helping health care be more effective and efficient.
How would you like to see the clinical dashboard integrated with a predictive analytics tool?
When you can answer those three questions [I mentioned] at any given point in time, it’s an incredibly powerful tool. Who do I need to pay attention to? Why? How is our team responding? All of those questions can be answered looking backwards. If you look at a time frame and a history and have context, what becomes really powerful is if we can start to see trends and predict before things are going to happen.
If I am able to say: “Who should I pay attention to not because of where they are today, but because of where we think they might be in three days if a very subtle trend continues?” That becomes infinitely more powerful than just answering those questions looking backwards. As we look at technology and synthesis of data to drive these types of insights into dashboards for clinicians and clinical teams, one of the most exciting things is we can look at historical data to predict the future and intervene before that future starts to unfold.
I still think we can intervene in a timely manner to effect outcomes without predictive technology, but with it, we can intervene more frequently with more subtle changes. Even when we intervene and avoid a negative outcome like a hospitalization, there still might be an infection or something that is happening that is unpleasant for the individual patient and for that staff to deal with even if it doesn’t result in a bad outcome.
When we introduce predictive [capability], hopefully we can avoid those things that cost staff time and cause a patient discomfort as they go through a clinical scenario. Even if the outcome is still good in the end, sometimes it’s not pleasant to get through the intermediate period. Predictive increases the scope of how many things we can intervene in. Then, how quickly we intervene can also determine the experience for the patient and the time of the care team to make sure that we’re intervening appropriately.
Who do you think are the most important roles within SNFs to have access to the clinical dashboard?
One of the ways that we’re thinking about dashboards and insights is for different personas. I would say the specific care team is one group. Think of nurses who are working at the bedside and CNAs, physicians, nurse practitioners, therapists — the whole care team. We think about how to take information that might be summarized on a dashboard for a management team and push some of those insights closer to the workflows for the care team.
For care managers, whether it’s a director of nursing or an administrator who is primarily working in a building, it’s really important to look at answering those three questions: Who should we pay attention to? What’s going on? How is our team responding?
That allows any number of roles who are responsible for overseeing care in a particular facility the opportunity to, one, make sure that the facility is operating according to policy and procedure, that the facility is working and delivering great outcomes for the patients and residents that they serve, and that it’s running smoothly and at capacity.
Then if I go one step higher than that, to managing corporately across facilities, it’s important to know which facilities are performing really well and what types of patients those facilities are performing well with. Maybe we can match the flow of demand and services to the supply. If we’re getting referrals, how do we match the referral to the facility that can meet their needs best? If facilities are not performing well in certain areas, how do we make sure that we’re intervening to either supplement with education or provide tools so that those facilities can perform better and we can bring each facility’s performance up to a level of standard or quality for an organization?
We want to take a lot of those insights, unpack them from dashboards, and move them into workflows.
What are some things you think SNFs could do to improve the collection of patient health data?
It’s a great question. I think developing consistency in data collection is important. The MDS is a wonderful tool and instrument and it’s a requirement for skilled facilities. If we think of the MDS as the beginning, instead of thinking of it as an output, sometimes we lose the opportunity to stay true to our nursing roots which are to assess patients head to toe. The MDS allows you to do that and look through the lens holistically. I do think that there’s a high degree of variability in the front-end documentation tools that eventually feed into the MDS.
Where we need to be dynamic and put some intelligence into systems is the context around a patient changes, not just to feed the MDS, but to drive the best clinical outcomes and to drive insights that will allow us to make good decisions.
There’s an opportunity to really align around standard approaches to collecting consistent data to the ways that we go about doing that. There are a lot of people that will say, “Well, don’t worry about some of that front-end data collection. You can just process it on the backend using large language models or other things to filter through the data.” There’s no guarantee at that point that you’ve had anyone document anything that says “depression” or another keyword that might be really critical. Thinking about structure on the front end helps us be efficient in data gathering and helps us have the data that we need to answer those questions.
It can feel like a lot to collect data and it can be very visible the time we spend. What’s often hidden is the time we spend actually searching through the data to answer questions. The more structured and consistent we can be on the front end, the more we save time on the back end in terms of answering all those really critical questions.
We’ve made investments as a vendor and as a partner to help support movement in that direction and we’ll continue to partner with our customers toward that end.