We know different team members in the hospital have different needs when it comes to business intelligence. For instance, a nursing staff director will have different requirements than a perioperative command center lead. So it’s only natural that when it comes to hospital reporting and analytics, a persona-based reporting model delivers the greatest insights. But in practice, this approach has been hard to implement because of two factors:

  1. Most reporting systems lack a deep understanding of the various hospital roles, instead holding to blind faith that all reporting is good reporting.
  2. Even if the nuances of individual roles were well understood, reporting systems lack the flexibility and configurability to actually implement the right report for the right person at the right time.

Properly implemented, persona-based reporting is much more than a fancy dispatch method to ensure your staff doesn’t get bombarded with irrelevant reporting and business intelligence. Establishing persona-based reporting requires the following understanding of the role:

  1. Authority: What decisions is the role approved to make? Can they pull in flex staff? Open or close beds? Cancel elective surgeries? Approve overtime?
  2. Understanding workflows: Getting the right information and recommendations to the right person at the right time to effectively draft into their particular workflow.
  3. Appetite for details: How much history and granularity does the role require to make a decision? What relevant trends should be considered when making that decision?
  4. What ifs: The reporting should include the results of simulations showing the forecast outcome of different scenarios. If a bad situation requiring intervention is forecasted, reporting should shine a light on various paths out.

For example, a hospital forecast might show an inpatient nursing shortage. This would be based on the care pathway of currently admitted patients, booked and in-progress surgeries, ED crowding, and so on. A perioperative director might be interested to know about this, but there’s not much that can be done about the situation short of making drastic decisions, like cancelling surgeries. Surgeons will continue doing surgeries while patients will pile up in the PACU, all while perioperative staff argue with the ED over who gets any inpatient beds that open up.

But this same report in the hands of an inpatient nurse manager is a different story. This person actually has the authority to do something about this situation. He or she can bring in staff floaters or travelers, or can implement a surge plan such as transferring patients to a suburban hospital. This person is going to want much more detail, and will want to be informed at a much lower trigger threshold than the aforementioned perioperative director.

Sometimes persona-based reporting is as simple as customizing what data goes at the top of the report and what gets bolded. But if that requires an IT trouble ticket and a six-week lead time to configure, the value of this customization will be overrun by the anticipated pain and suffering of getting the changes made. Conversely, too much configurability can be overwhelming – business intelligence cannot expect roles to build every report from scratch. The ideal system is purpose-built for hospitals and comes with predefined role templates such as “surgical service line manager,” “case manager,” or “hospitalist.” Customization is still possible, but it’s only the last 20%, instead of everything.

This opportunity for persona-based reporting is a natural byproduct of the transition to electronic medical records and the corresponding ease of generating reports. When records were on paper, reporting was labor intensive, which put natural limits to how much reporting hospital leadership could be expected to consume. Now that hospital operations are finally digital, hospital leadership has come to experience the same “alarm fatigue” as clinicians, but instead of IV drips demanding attention, it’s bed shortages. Persona-based reporting aims to filter out some of the noise so each hospital role gets the report that’s situationally correct. It’s the logical next step in the evolution of hospital operations.

In 1865, the economist William Stanley Jevons observed that as a process becomes more efficient, we actually invest more resources in producing it. He was writing about how the increased efficiency of coal engines makes coal more valuable and, paradoxically, leads to more coal consumption, not less. But if Jevons were alive today, he would probably note how the digitization of hospital data has made report generation more efficient — leading to hospitals investing more resources in producing ever higher quality reporting.

In the end, the hundreds of billions of dollars that have been invested in the digitization of hospital and patient data has enabled a persistent view of the patient across the healthcare continuum. Actually mining that data into a purpose-built set of recommendations, tailored to the various hospital personas, will dramatically increase the efficiency of healthcare management, improve patient care, and begin to address and capture a real return on that investment to the benefit of all involved.



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