How to Truly Achieve a Data Driven Culture in Healthcare: Lessons learned from Population Health
Despite substantial investment in data and analytics, many healthcare leaders don’t feel their organizations have achieved the “data driven culture” that they have been promised.
Why does this cultural gap still exist despite substantial investment? In our experience, having worked with over 50 healthcare organizations in the past five years, this is because the model most organizations are following for data and analytics is incomplete. To better explain, I will use an analogy to the clinical continuum of care.
The Continuum of Care Analogy
The clinical continuum of care is about expanding from a model that is focused solely on treating the sick to one that is expanded to perpetuating health/wellness. We understand the importance of preventive care and ensuring that we support the full care continuum, as opposed to solely treating the sick. This shift was transformative in supporting population health and the cultural change needed to support the many as opposed to the few.
This is the type of cultural shift that is needed in regards to Data and Analytics programs.
To elaborate on the analogy, in current approaches, individuals come to Data and Analytics teams with a problem much like a patient presents with pain. Data and Analytics teams then build solutions to address the problem or meet the need, much like a doctor would prescribe medicine or perform a procedure. In these ways analytics and data teams are focused on “treatment”.
So how exactly can organizations improve their culture of data and analytics by leveraging the lessons learned in the continuum of care approach? The table below explains the relationship between the clinical and analytics continuum of care.
Very few organizations execute on all areas within the Analytics Continuum of Care outlined above. Most organizations that have made investments are addressing the green (Treatment) phase, creating solutions. Many organizations are focused on improving their capabilities in the blue phases (Diagnostic and Rehabilitation). But very few organizations have progressed into the yellow areas (Education, Preventive, and Maintenance).
Which parts of this Analytics Continuum are you covering in your organization? Evaluating your organization’s performance against this continuum will help you identify the root of your data driven culture problem and resolve it. Success with this Analytics Continuum is contingent on two characteristics, completeness and quality. It is essential to cover each phase (completeness) and do them well (quality).
While there are many culprits that contribute to gaps in this continuum, either completeness or quality, one factor is the most far reaching, the inbound vs. outbound approach. Successfully executing on this Analytics Continuum involves incorporating an outbound approach in addition to the traditional inbound model.
Inbound vs. Outbound Approach
We should not just be waiting for data and analytics requests to come in, we should be seeking them out. This is precisely what the yellow portions of the table highlight, and in smaller part, the blue areas. But there are a number of barriers to seeking them out strategically.
The most common barrier is the volume of requests flowing in. Few Data and Analytics departments are looking for work to do. These groups are typically so overloaded that they focus on creating processes, buying tools, or hiring people to help with the volume. But many of these approaches, while they may help, still do not get us to answers on the following questions:
This inbound approach, as opposed to an outbound approach, results in a very reactive structure. It becomes hard to break this structure because of the volume of requests that come in. Additionally, without a larger strategic vision, it is hard to determine which requests are valuable and which are not, which is where many organizations turn to departments to prioritize. However, having departments prioritize existing requests is not the goal, though it may help as a bandaid.
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The goal is creating a strategy for data and analytics with stakeholders, one that creates comprehensive solutions. This approach will diminish the flood of requests coming in and will provide solutions that add more value to the stakeholders and their respective departments. This is just as important to implement across the organization, not just within each department.
But who will be responsible for conducting these outbound approach discussions? Resources capable of this task are hard to come by. This is not a resource that will simply be taking down the details of a request or asking detailed follow-up questions to flesh out requirements. These are individuals who are capable of having strategic discussions with stakeholders where their goal is to understand the stakeholders’ business, goals, initiatives, people, process, and tools, such that they can collaboratively propose beneficial solutions where data and analytics can be leveraged. This resource must possess a rare set of soft skills to compliment the required hard skills. These resources have exceptional relationship building skills to establish trust, communication skills to act as an intermediary between business and technical teams, as well as the patience and skill to work with many stakeholders that may be hesitant, resistant, or downright opposed to these activities.
Often, if organizations have these resources, they do not have the bandwidth in their current role to have these conversations, even if they want to. The “want to” is an important consideration. These resources are either performing development efforts to satisfy requests, or managing the team, but this is often not allowing these resources to take advantage of their unique skill set. Creating this opportunity for identified resources to take advantage of their talents is beneficial for the resources, as well as the organization. This is, however, a very unique skill set and many organizations are faced with a lack of these resources. In some scenarios the skills associated can be taught to capable individuals. But quite often there is a misalignment between existing resources and what is needed, meaning not everyone is capable of taking on this type of role, even with substantial training.
While finding the right resources to support this outbound model is challenging, there is a fundamental barrier preventing most organizations from even getting to that task. This is, who owns this transformation and the associated investment to make it?
Owning the Transformation
The easy answer seems to be Information leadership, the Data and Analytics team, right?
Well, with the inbound approach as the current operating model for most Data and Analytics teams, identifying needs and submitting requests is owned by the stakeholders, meaning not the responsibility of Data and Analytics leadership. Many Data and Analytics leaders are already overwhelmed with the amount of work on their plate, so they are not actively seeking out more work outside the scope of their responsibilities. In addition, many are not aware of this model and the benefits it could have to them even inside the existing inbound model. Lastly, there are the rare few Data and Analytics leaders that are aware of this model and are trying to pivot to it, but without ownership of the identification/submission process, they struggle to obtain the investment to pivot to this model.
If the stakeholders own these steps in the current model, do they own the transformation? The term stakeholder is incredibly broad and includes leaders from all areas within the organization, so ownership here is incredibly ambiguous. Moreover, this again puts the onus on stakeholders to request a change regarding data and analytics which is quite difficult to request if you are not a Data and Analytics expert. So what they currently have is dissatisfaction with the current model and a curiosity, enough to have read this far.
This is the impetus for this article. The first step is to educate. There is a better way.
Value Proposition
Cultural change at this scale has a number of moving parts and requires investment, commitment, and follow through. If you find yourself questioning the value and wondering if this is a “nice to have” as opposed to a necessity, let’s understand the impacts. Simply stated, by continuing to operate with these identified gaps you are operating at less than an optimal level which results in waste as well as diminished value.
The costs associated by operating with identified gaps along the analytics continuum of care, either in completeness or quality, are substantial. You will continue to pay these costs until corrective action is taken. While there is an investment in implementing and adhering to a new model, the funds should be recovered not just in removing the waste, inefficiency, and pain but also in the additional value generated.
To make this transition and get this value, organizations will need to use the right people, demonstrate quick wins, collaborate, seek feedback, and ensure stakeholders feel supported. At Waypoint we help with the difficult cultural transformation necessary for data and analytics to permeate through healthcare organizations, allowing them to reach their potential. We help you fill these gaps, overcome your barriers, and maintain this level of cultural change.
If you are ready to embrace data and analytics wellness in your culture, please schedule your “initial check-up” today!