Parting Thoughts: Engaging Your Data

The world of analytics has grown expansively in healthcare over the last decade. Measuring our business is no longer just optional, it is a critical component of operating carefully, efficiently and strategically. Analytics platforms abound in our space with many provided as embedded functionality within our imaging solutions. We can now effectively measure accuracy in reporting, overall performance across the entire patient encounter, operational efficiencies, and even infrastructural management and trending. Never before have we had as much information available to us based on the models we create including key performance indicators (KPIs). Most have become accustomed to accessing dashboards that provide a snapshot of current, recent past, and in some cases, predictive metrics. The next phase of meaningful adoption will move toward our engagement with this information.

John Boyd was a United States Air Force pilot during the Korean War who rose through the ranks due to his superior performance. He was nicknamed “Forty Second Boyd” for his standing bet that he could beat anyone in an air fight from a disadvantaged position. He developed a systematic model of engagement that became known as an OODA Loop. The OODA Loop stands for Observe, Orient, Decide, Act. This was adopted by the military and later as a model for executive decision making across industries and has been addressed by many books on management and leadership. It seems appropriate as we move to greater agility and innovation within healthcare that this simple model can serve in framing systematically how we turn our actionable data into actioned data. The dashboard only serves us well if that information is processed and acted upon.

Observing

We can observe data in many different forms. In analytics we typically use visualization tools that allow us to quickly see metrics that we have deemed important. Observation, though, is more than taking information from the dashboard or screenshots embedded in automated emails. Good observation includes ingesting all of the associated and peripheral information that we have access to. Merely looking at the output limits the full value of all input and ultimately affects the rest of the loop. Just as this has been a major influencer on how radiologists choose to read and interpret with reference to non-imaging patient information, those who engage in data analysis must see the entire picture.

I heard a story recently of a hospital that decided to build a clinic in a fast-growing suburban neighborhood. After a serious investment in capital and resources the clinic closed in short order due to lack of patients. Only after a post-mortem analysis did they realize that the population moving into that neighborhood were all commuters into the city where the larger hospitals and clinics existed. They had observed a construction boom but had failed to observe the lifestyle patterns of the residents.

Orienting

Orientation of data requires analysis. It is at this step of engagement that organizational behavior begins to have a major influence. Healthcare continues to find its way toward greater agility, though many argue the progress is slow. The exercise in developing KPIs should also include identifying the key stakeholders who both impact and are impacted by what is being measured. Orienting is the process of contextualizing information. Having the metrics must always move toward understanding its meaning. One organization I’ve worked with has regular meetings centered around analytics for the purpose of root cause analysis of problem statements or framing opportunities. They understand that every voice brings perspective and broadens context. As a result, they have an effective program in place related to data, analytics and business intelligence.

Deciding

Deciding is often the most difficult part of any analytics program. Often this is due to a clear definition of roles and responsibilities within an organization. The pendulum tends to swing between people with authority not wanting to make decisions to people without authority being expected to make decisions. Both circumstances are counter to real organizational progress. Governance in analytics is crucial to successfully benefiting from the initiative. In many cases organizations create charters for their governance to document its level of activity, authority and outcomes.

The criticality of the problem statement or opportunity will certainly define the process of decision making. But all decisions large or small should be well documented to serve as artifacts. This serves well as people leave or new positions are filled by providing a historical narrative that both guards against making the same mistakes again and ensures alignment on the path forward.

Acting

The final step is acting; executing on a plan that was informed by data and contextualized within a proper framework. This can be as small as provisioning an additional virtual machine (VM) for your software platform and as big as building new facilities to accommodate growth. Organizations can be defined by their ability to execute. In building an analytics program it is important to honestly assess your organization’s ability to act successfully.

Recently I sat in a room with leadership of an organization that had clearly defined a problem and had developed a remediation plan but lacked the necessary organizational and personnel capabilities to move forward. The frustration in the room was palpable. This is a common reason why people leave. The best analytics programs know their organization well and avoid overreaching.

Continuing the Cycle

The OODA Loop is only one of many systematic methods to engage with our data. And this loop is constant. Acting leads right back to Observing. Any loop should reflect the size and scope of the KPIs being addressed (some may take seconds; others may take years). We are all striving to improve our organizations through data analytics and business intelligence, and a carefully built program of engagement will increase the possibilities and the realities.

Jef Williams is managing partner for Paragon Consulting Partners, LLC, a Sacramento, Calif., based healthcare IT consulting group. Williams brings more than 25 years in strategic positions in both for-profit and not-for-profit organizations. His expertise lies in leading complex initiatives including large-scale healthcare IT strategy, business case analysis, and solution implementations for both public and private sector clients. Williams speaks regularly and is published on industry issues including operations, management, digital transformation and health IT.