Schedule Utilization: Patient-Centered Access Metric? PT 1


By: Chris Profeta, MPH

Does a metric answer the question – is our access good?

Good patient access is not easy to define and even harder to measure. It takes a combination of metrics to paint the full picture. This blog series examines one of the most common metrics used by access leaders – schedule utilization.

Operational Metric vs Experience Metric

The providers’ time is the health system’s most valuable resource. Maximizing it is undoubtably a crucial operational goal, but does a provider’s schedule utilization contribute to understanding the patient’s access to care?

It is important to distinguish between an operational metric and a patient experience metric to maximize either’s value. An operational metric is a measurement of the health system’s process efficiency or resource utilization – a measure of the system’s internal performance. A patient experience metric captures the lens of the patient – an external stakeholder providing essential feedback about the system’s performance.

An operational metric is often easier to define and measure, however, both perspectives are crucial to understand access. The patient’s experience as they journey through the ambulatory enterprise a health system touches a multitude of providers, staff members, locations, technologies, and communications, and therefore can be difficult to define nevertheless quantify. Many health systems use a variation of the mantra to succinctly outline good patient access:

Right care, Right provider, Right time, Right location

The patient’s experience in this journey matters, undoubtedly. The patient deserves the right care, provider, time, and location – in the right way. If it takes four phone calls, three portal messages, a cancellation and rescheduling, and an hour wait in the lobby for the patient to the see the provider,
then that probably fails the test of good access as well.

The right way represents the ease of matching the patient with the right care, provider, time, and location. For the patient, the process should be frictionless. The right way minimizes the transaction costs of obtaining the care - the non-monetary costs of being put on hold, waiting in the lobby, changing one’s work schedule to make the only available appointment, and so on.

Does a provider’s schedule utilization score of 90% tell us about these pillars of good patient access? Not really. This percentage captures information about the “providers’ time” from a system resource perspective, an operational metric, but doesn’t provide any context to the “right time” from the lens of the patient.

Furthermore, even as an operational metric, does the score illuminate how well the system is using the provider’s time? One could argue that it does offer insight, but not without additional detail. That brings us to the challenge of measuring utilization as an operational metric. Before we discuss tactics to improve the patient-centricity of this metric (which we’ll cover in next week’s blog post), let’s examine how to improve the validity of the operational metric itself.

The Challenges of Schedule Utilization as an Operational Metric

Let’s assume that Dr. Smith had a schedule utilization of 95% in January and a score of 85% in February. It’s not clear which month was more productive, arrived more patients, utilized clinic space, etc. without evaluating the inputs of the metric.

Schedule utilization is often calculated with the following formula:

The numerator is straightforward – how many minutes were scheduled. However, the denominator is more complicated.

In order to evaluate if Dr. Smith had utilized their schedule more effectively between months, we need
to answer several questions regarding the denominator:

  1. How many minutes were open on the schedules in each month?
  2. Did the available minutes match the clinical expectation for Dr. Smith?
  3. Was there any private, frozen, or otherwise hidden (un-schedulable) time on the schedule?

Ideally, the denominator is fixed to a target of allocated minutes. A grounded denominator allows the metric percentage to be easily interpreted in the context of patient-facing availability.

If Dr. Smith’s allocated minutes are left undefined, the following may occur:

  • January Schedule Utilization = 950 minutes booked of 1000 allocated minutes = 95%
  • February Schedule utilization = 1275 minutes booked of 1500 allocated minutes = 85%

Which month did Dr. Smith’s schedule achieve the operational targets? A higher percentage of the schedule was filled in January, but more patient time was booked in February – which is preferable? Why was January’s allocation lower than February? Which allocation of minutes matches the
expectation for Dr. Smith? It is difficult to assess the 95% schedule utilization or the apparent decline in percentage the following month without intensive investigation.

There are many valid operational reasons January may have had a lower denominator, but unless the operational systems are established to maintain the integrity of the template, the metric becomes ambiguous.

How, therefore, can we ensure that the schedule utilization metric is valuable in our journey to attain good patient access? Consider these steps to improve the validity of the measure:

  • Analyze provider expectations for clinic time;
  • Build all provider schedules to the expected session duration;
  • Ensure the target number of sessions per month are open; and
  • Once the schedules are built to the expected durations, develop effective template security to maintain the fidelity of the build.

This type of schedule administration is often assigned to a Capacity Management team that focuses on the design and integrity of the schedules. The team is supported by security protocols that protect the build.

Despite the additional infrastructure and effort is undoubtedly worthwhile. Leaders who can rely on the provider templates to be built to the expected allocated minutes can trust the denominator of the utilization equation. With this consistency, leaders can learn valuable operational information from the schedule utilization metric without rigorously investigating the inputs.

In next week’s blog, we’ll discuss the evolution of schedule utilization from an operational metric – to a measure that captures the lens of the patient.

Read Part 2 Here