How healthcare operational challenges impact different demographics
Coauthored by Dr. Tejal Gandhi, Chief Safety and Transformation Officer
The authors would like to thank Khephren Chambers, Data Scientist at Press Ganey, for his extensive work in compiling and analyzing the data related to operational friction and equity.
In healthcare, we put so much effort into the clinical aspects, like arriving at a correct diagnosis and coming up with the right treatment plan. While those are, undoubtably, critical milestones in the healthcare journey—and to the ultimate health of a patient—there’s even more to consider.
At least 50% of patients experience “operational friction”—like long hold times, difficulty getting an appointment, and accessing test results and follow-up information—at some point in their healthcare journey. This has a huge impact on patient safety, patient experience, and patient loyalty.
But operational friction isn’t a one-size-fits-all problem. People experience it differently. It’s vital to understand how different populations experience common operational challenges, so we, collectively, can improve healthcare access, safety, and experience.
Press Ganey’s team of data scientists decided to segment our data to understand how patients’ experiences around operational friction differ. In a recent analysis of 2021 integrated Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG CAHPS) surveys, we learned the following:
- People of color more frequently encounter friction within their care journeys—and that friction has a larger adverse impact on their loyalty than the loyalty of individuals who identify as white.
- Female and male patients are equally likely to encounter most types of friction.
- Younger adults (age 18–35) report friction more often than middle-aged patients or seniors.
Let’s take a closer look at the data to better understand how operational friction impacts different patient communities.
People of color report friction in healthcare more often than patients who identify as white
Inequities exist across the healthcare industry. And that extends to how groups experience friction and gaps in care. When we look at the data, we see that, in general, patients of color encounter friction more often than white patients. More specifically, Asian-identifying patients report friction most frequently. For example, though 69.8% of white patients describe their wait time at the clinic as optimal, only 55.8% of Asian patients report an optimal experience with wait times.
Patients of other races and ethnicities also report experiencing friction. For example:
- American Indian or Native Alaskan patients are less likely to describe the ability to talk to a provider on the phone during office hours as optimal (59.5%), compared with white patients (65.4%).
- Black or African American patients are less likely to say they were able to see the provider within 15 minutes (82.2%) than white patients (88.7%).
- Spanish, Hispanic, or Latino patients are less likely to describe the office follow-up as optimal (63.4%) as compared with white patients (76%).
Beyond the simple experience of friction, the data shows that the impact of friction is different based on patient demographics. As a group, when white-identifying patients experience friction, their likelihood to "definitely recommend” the practice is 12% lower than their white peers who experience no friction. But for patients who identify as Asian, Black/African American, or American Indian/Alaska Natives, experiencing friction lowers the likelihood to “definitely recommend” by 14 to 16 percentage points.
Female and male patients experience friction at nearly equal rates
Our analysis of more than 440,000 surveys completed by female patients and more than 370,000 surveys by male patients shows only minor differences in reporting friction across most measures. (Note: This analysis is based on the sex assigned at birth as recorded in the medical record, rather than the gender that an individual identifies with.)
The three areas where we see differences are:
Ease of contacting. Male patients are less likely to describe the process of contacting the office as an optimal experience (70.5%) than female patients (72.2%)—the equivalent of ranking in the 43rd percentile nationally vs. the 52nd.
Seeing the doctor promptly. Female patients are less likely to say they were able to see the provider within 15 minutes (86.4%) than male patients (88.9%)—the equivalent of ranking in the 35th percentile nationally vs. the 49th.
Office following up with test results. Female patients are less likely to describe the office follow-up as optimal (73.4%) than male patients (74.9%)—the equivalent of ranking in the 42nd percentile nationally vs. the 50th.
The data did not show a different impact on loyalty based on patients’ sex. Intention to recommend scores were 12% lower when patients encountered friction, regardless of their sex.
Younger patients report friction more frequently—and it has a greater impact on loyalty
Patients between 18–34 and 35–49 most frequently report encountering friction in their healthcare experiences. One of the more notable differences is in the ease of scheduling appointments. Adults age 18–34 are less likely (69.2%) to rate the experience of scheduling appointments as optimal, as compared with adults age 65–79 (77.4%).
For younger patients, the experience of friction has the most pronounced impact on loyalty across all the identity groups. Patients 18–34 years old who encounter friction are 20% less likely to “definitely recommend” the practice as compared to same-aged peers reporting no friction.
4 actions for hospital leaders
So, what can you do about operational friction? A cohesive approach to solving these problems is needed to eliminate patient frustrations for all.
- Segment your data to learn which of your patient groups are experiencing friction more often. You can’t understand how operational friction impacts populations without looking at individual groups like sex, race, ethnicity, and generation. Press Ganey Operational Friction reports now include breakouts for race, and analysis can be tailored to specific demographic identity groups.
- Dig deeper into quantitative and qualitative feedback. Do some patient populations have trouble accessing care? Do language barriers make communication difficult? Take your analysis further with focus groups or patient and family advisory councils—made up of people of different races, ethnicities, genders, and ages—to learn how various friction points impact their healthcare experience.
- Bring both DEI and safety leaders into the conversation. This data has organization-wide implications, and it can’t fall under the domain of one team or another. Safety and DEI leaders need to work together with patient experience and operational leaders to find ways to improve friction.
- Look at data from a high reliability lens. A high reliability organization is one that performs as intended consistently over time—and organizations need to ensure that their processes are designed reliably for everyone.
By reducing operational friction for patients, we not only improve their experience of and access to healthcare, but we also help drive the clinical outcomes we want. Reach out to a patient experience and DEI expert to discuss your organization’s challenges—and opportunities.