August 7, 2019 – New findings from the DCRI suggest that how military service members interpret their pain may be able to predict pain-related costs and total medical costs.
New data from a DCRI study suggest that pain catastrophizing, a measure determined by the results of a 13-item questionnaire that indicates how patients interpret their pain, could be important in predicting future health care utilization and costs in patients with musculoskeletal pain.
A recently published study in the Journal of Pain, led by the DCRI’s Trevor Lentz, PT, PhD, MPH, (pictured), examined a cohort of 283 military service members returning from Afghanistan who reported musculoskeletal pain during a medical screening process in August or September 2011. These service members were asked to complete both the pain catastrophizing scale (PCS) and a body diagram that details the location of their pain. Scores on the PCS indicate how patients interpret their pain by measuring three components: rumination, or how often they think about their pain; magnification, or how much they emphasize their pain, and helplessness in managing their pain.
The study team examined the results of both to determine processes that influence the following outcomes at 12 months: incident use of opioids over a short term, chronic use of opioids, condition-specific medical visits, condition-specific medical costs, and total medical costs.
The team also looked at how pain intensity at intake, as well as disability, influenced these outcomes. However, prior to this study, not much was known about the role that pain catastrophizing or distribution of symptoms on a body diagram played in predicting outcomes.
“The influence of certain psychological factors, like pain catastrophizing, for predicting pain related clinical outcomes is well-established in the literature, but less is known about how these same factors influence healthcare utilization and costs,” said the DCRI’s Steven George, PT, PhD, FAPTA, one of the study co-authors.
“We wanted to understand the processes that result in these outcomes by asking, ‘What are the underlying characteristics we need to attend to while developing outcomes prediction models and treatment pathways?’” Lentz said.
The data showed that pain catastrophizing informs both condition-specific costs and total costs. This means that patients with higher pain catastrophizing scores were more likely to experience higher healthcare costs, even after considering the level of pain intensity at intake. The score also acted as a partial indicator for how many condition-specific visits a person would have.
“As we move toward value-based care, it will be important for us to determine where and with whom costs will be concentrated, enabling us to intervene earlier to improve the cost effectiveness of pain-related care,” Lentz said.
The results suggest that certain outcomes, such as healthcare costs and utilization, could be more accurately predicted by weighing factors like pain catastrophizing in addition to pain intensity or disability. In contrast, neither pain catastrophizing nor body diagram score improved prediction of future opioid use beyond baseline pain intensity and disability.
The findings also indicate that different approaches may be needed for building predictive models for costs versus healthcare utilization. But the primary takeaway, Lentz said, is the new information about how pain catastrophizing can be used.
“Although we’ve found that pain catastrophizing is important in predicting clinical outcomes, it is rarely screened for or evaluated in clinical practice,” he said. “We need to raise awareness of this measure’s utility in prediction—especially because pain catastrophizing is modifiable and can be addressed through treatment.”
The DCRI’s Steven George, PT, PhD, FAPTA and Duke adjunct faculty Daniel Rhon, DSc, also contributed to the study.