services, suggesting injection may be the most difficult
service to predict with the included variable set.
Surgery
Baseline disability (OR = 3.13 – 3.25, p < 0.001), change in
disability (OR = 3.04 – 3.05, p = 0.01) and change in
10-item OSPRO-YF score (OR = 1.12 – 1.14, p < 0.05)
where consistent predictors of subsequent surgery. Not-
ably, magnitude of prediction was comparable between
change in disability and baseline disability. This was the
only parsimonious model to include an OSPRO tool. In
this case, an increase in pain-related psychological dis-
tress measured by the OSPRO-YF 10-item questionnaire
over the first 4 weeks was associated with higher odds of
surgery. The 3 predictors in this model explained just
over 30% of the variance in surgery utilization.
Diagnostic tests or imaging
Comorbidity index score (OR = 1.35 – 1.45, p < 0.05),
baseline disability (OR = 2.25 – 2.66, p < 0.001), and base-
line to 4-week change in pain intensity (OR = 3.04 – 3.05,
p = 0.01) were significant predictors of diagnostic test or
imaging utilization. Among these, baseline disability was
the strongest predictor. In these models, higher comor-
bidity index, higher baseline disability and worsening
pain were associated with higher odds of utilization.
Together, these variables explained approximately 30%
of the variance in utilization.
Emergency room
Models for emergency room use had the highest pseudo-R 2
values of any individual service (0.48 – 0.50), but also had
the largest number of predictors (8 – 9). Agreement between
complete case and weighte dm o d e l sw a sm o d e r a t e .T h e
models converged on the foll owing predictors: age (OR =
0.91– 0.94, p < 0.05), insurance (OR = 8.99 – 13.15, p <0 . 0 5 ) ,
baseline disability (OR = 3.33 – 4.88, p < 0.001), and change
in pain (OR = 1.59 – 1.77, p < 0.05). Higher utilization was
associated with younger age, other insurance (e.g., self-pay,
Worker’s Compensation, or other commercial insurance)
compared to private insurance , higher baseline disability
and worsening of pain. In the weighted analysis, subjects
with knee pain were less likely to utilize the emergency
room than those with low back pain. However, this rela-
tionship was not significant ( p = .06) in the complete case
analysis. Of the significant predictors in both models, insur-
ance status was the strongest individual predictor of subse-
quent emergency room use.
Discussion
This study identified novel predictors for pain-related
utilization outcomes following an episode of physical
therapy for a primary complaint of musculoskeletal
pain. The most robust finding from these analyses
was that baseline disability and change in pain inten-
sity over the first 4 weeks following physical therapy
evaluation were consistent predictors of subsequent
pain-related healthcare utilization in those participants
that completed all follow up. Aside from these robust
predictors, other individual predictors of utilization
were highly outcome-specific. High model specificity
for utilization outcomes observed in this study is con-
sistent with a recent systematic review that found
similar levels of model specificity for more traditional
outcomes like pain intensity, disability and work
absenteeism [ 14]. Across models, health-related vari-
ables were generally strong er predictors than sociode-
mographic factors, which is also supported by prior
research [ 15, 16]. Additionally, there were cases when
prediction models were improved for specific services
(e.g. surgery, use of opioids) when considering change
in pain, disability or pain-related psychological dis-
tress. A notable finding is that the OSPRO-YF had
the greatest utility when used to measure change in
pain-related psychological distress. Current risk pre-
diction paradigms in musculoskeletal pain consider
only baseline pain-related psychological distress. How-
ever, these results underscore the importance of