Improving Population Health Outcomes: From Airplanes to Doctors’ Offices

To consider how to improve population health outcomes, let’s start in an unlikely place—an airplane. If you’ve ever flown on an airliner, chances are good that you’ve browsed through the inflight magazine. If so, you’ve likely seen one of these ads:

best doctors in new york coverThese ads—a staple of inflight magazines—speak volumes. They implicitly acknowledge that great variation exists in our healthcare system. When a loved one goes in for cancer treatment or surgery, we ask questions like, “Who’s your doctor? Where did she train and with whom?” We ask these questions because we want to know that our loved one is getting the best treatment possible in a healthcare market full of variation. We want to know that the individual physician caring for our loved one has the best credentials possible.

In that same vein, when we go to the doctor’s office, we don’t see ads that look like this:

best pilots coverWhy don’t we see advertisements touting individual pilots as the “best” of this or that? After all, you trusted the pilot when you climbed aboard that airplane and read the inflight magazine. However, I doubt you asked, “Who is my pilot? Where did she get her training? How many flight hours has she logged?”

The reason for the existence of ads for individual doctors and the lack of ads for individual pilots is simple—the airline industry operates a system of standardized production. This means that the airlines have built a system standardized by protocols, flight checklists, and routine maintenance schedules in order to create a consistently safe experience for the public. These protocols ensure that all pilots operate according to the same best practices. There is not a lot of room for individual variation among pilots.

This system of production represents one end of a spectrum of consistency and standardization. The other end of the spectrum is a craftsmanship mentality, in which a handful of masters train apprentices. The masters share their experiences with their apprentices, and the apprentices that train under the best masters eventually become the best masters.

Today’s healthcare industry is operating much closer to a system of craftsmanship than a system of production. Unfortunately, this system propagates variation and inconsistent processes in healthcare. The industry is making a lot of progress toward standardization of best practices, but we’re not there yet. We have to ask those questions about whom a doctor trained with or where she trained—because it matters!

Improving Population Health Outcomes Systematically

It is largely because of our system of craftsmanship that population health outcomes are not consistent across the nation. One of our favorite quotes here at Health Catalyst comes from Dr. Paul Batalden: “Every system is perfectly designed to get the results it gets.”

Currently, most healthcare systems are perfectly designed to deliver variable results. To have consistent, high-quality outcomes, we need to transform the industry into a system of production.

Sounds too good to be true? It’s not. Consistent, high-quality outcomes is a fully attainable goal if the following three critical areas—the best practice system, adoption system, and analytics system—are implemented and working together by healthcare systems.

The Best Practice System

Healthcare organizations that want to standardize care to best practices must implement a best practice system. Putting a best practice system in place means determining what the standard of care should be. It means defining your care processes (for example, cardiac rehab, or sepsis) and determining what best practices should be followed for that care process. It means applying knowledge assets, like best-practice order sets, to important decision points along the care process.

In the example of sepsis, a very important factor is early identification of the condition. So we might start by defining those things that we need to measure consistently to identify sepsis quickly—things like temperature, heart rate, respiratory rate, and so forth. As we move forward, we’ll want to tackle sepsis treatment itself and determine the best-practice protocol for the condition, such as the appropriate antibiotics to use. Another category we would consider for sepsis is stratifying groups of sepsis patients. How would we define or categorize patients who exhibit the beginning stages of sepsis? How would we define a patient with severe sepsis? What is the appropriate protocol for each of these groups?

The Adoption System

Healthcare organizations must also establish an adoption system to work hand-in-hand with the best practice system. The best practice system establishes what the standard of care should be; the adoption system complements that by setting up the organizational structures that will successfully push the standard of care across the organization to reduce variation. It ensures that the standard process is used consistently across the enterprise.

The adption system engages clinicians, operational leaders, workflow experts, and other key stakeholders to help define the process for implementing best practices. It uses organizational influencers and champions to create the charter for ensuring that septic patients are treated according to standardized best practices at every facility. This system establishes an organizational hierarchy that enables clinicians and other stakeholders to provide feedback and fingerprint the system to achieve buy-in for—and compliance with—the new standards.

The Analytics System

The analytics system puts the technologies and competencies in place to measure how well we are implementing best practices. It answers questions like: Are clinicians following the evidence-based guidelines we established in the best practice system? Are we achieving broad adoption using the adoption system? If not, where are we not seeing the guidelines adopted?

We typically look at three types of metrics using the analytics system:

  • Outcome metrics: In the case of sepsis, our outcome metric would be mortality rate. We would set a specific goal around that metric—for example, reducing the mortality rate from 24 percent to less than 10 percent by a certain date.
  • Process metrics: These metrics measure how well we are following best-practice processes. For example, we may have determined that clinicians treating sepsis need to do 11 things with each and every sepsis patient. An analytics system enables us to track if providers are following all 11 steps. Additionally, teams can create aim statements to target improvements in each of these 11 steps. Improvements to proven clinical processes lead to improvements in patient outcomes.
  • Balance metrics: We track balance metrics to ensure that a change in one protocol doesn’t generate adverse outcomes elsewhere. We also use them to measure whether, for example, investments made in staffing to meet new protocols are generating the results we want. Let’s say we decided to organize a “code sepsis” team that can respond quickly to sepsis cases. Balance measures help us determine whether that investment in personnel was worthwhile. So, the balance metrics around the code sepsis team would monitor the cost of providing the extra team while also looking at outcomes improvements.

Finally, the analytics system consists of methods for presenting and visualizing the data in a way that’s easy to use and understand. The system involves technology that enables clinicians and others to drill down into the data to determine the root cause of any issue.

Implementing these three systems is the roadmap for achieving this goal. Moving healthcare away from a craftsmanship mentality and toward an effective system of production is the key to improving population health outcomes.

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