shown to identify approximately 95% of positive red-flag re-
sponders. For statistical analyses, the “yes” responses were
added for each version and included in each model as a
continuous independent variable.
OSPRO Yellow Flag tool (OSPRO-YF)
The OSPRO-YF is a yellow flag assessment tool that in-
cludes items from pain vulnerability domains (negative
affect and fear-avoidance) and pain resilience domains
(positive affect and self-efficacy) to aid with identification
of pain-related psychological distress in outpatient ortho-
pedic physical therapy settings [ 37]. The OSPRO-YF has
good concurrent validity with pain intensity and
region-specific disability [ 37] and is capable of predicting
pain intensity, disability, quality of life and persistent pain
12 months following physical therapy in patients with
musculoskeletal pain [ 20, 21]. The full-length OSPRO-YF
has 17-items, however a shortened 10-item version is also
available with an acceptable trade-off in accuracy. Like the
OSPRO-ROS, the OSPRO-YF is designed for implementa-
tion into electronic medical record (EMR) systems to
quickly and accurately identify risk for a variety of clinical
outcomes [ 19]. For statistical analyses, a summary score
was derived for each version by adding the item responses
after reverse-scoring items 2, 13, 14, 15 and 17 so that
higher scores indicate higher pain-related psychological
distress. The summary score was then included in each
model as a continuous independent variable.
Intervention
All physical therapy treatment was provided at the discre-
tion of the treating clinician. The duration of the episode,
the number of physical therapy visits, and individual treat-
ment parameters (type, intensity, duration, frequency)
were not collected for pragmatic reasons. In particular,
clinical and utilization data are not commonly collected in
a standardized format and would need to be extracted
from disparate medical record databases across different
health care systems to assess treatment. This was not feas-
ible given the scope and design of this multisite
survey-based study. However, instead of coding treatment
type we included baseline-to-4 week change in pain inten-
sity, region-specific disability, and OSPRO-YF scores in
each model as measures of treatment response. In that
manner the individual effects of the treatment received
were included in the predictive models, without directly
accounting for the type of treatment.
Healthcare utilization outcomes
Self-reported health care utilization was assessed at 6- and
12-months following initial evaluation by online assessment.
Questions were derived from previous population-based
studies involving musculoskeletal pain that have used survey
methods for follow-up assessment [ 22, 23]. Study
participants were asked whether they used any of the fol-
lowing healthcare services for their primary musculoskeletal
pain complaint in the time following their physical therapy
treatment:
1. Opioid painkillers (eg. Vicodin, Lortab,
Hydrocodone, Fentanyl, Percocet, Oxycontin,
Oxycodone, tramadol, Ultram, Diludid, etc)
2. Injections
3. Surgery
4. Diagnostic tests or Imaging (eg. xray, MRI, CT
scan, nerve conduction test, etc.)
5. Emergency room visits
“Yes” responses were followed by questions regarding
the quantity of services utilized (i.e. number of opioid
painkillers, number of diagnostic tests or number of
emergency room visits). All utilization questions were
answered on a categorical scale (0, 1, 2 – 5, 5 – 10, or > 10)
indicating the quantity of a particular service received
during the applicable follow-up timeframe. At 6-month
follow-up, study participants reported their use of ser-
vices for the previous 2 months, allowing a timeframe of
4 months from initial evaluation for them to complete
physical therapy. At 12-month follow-up, study partici-
pants reported their use of services over the previous
6 months since their last survey. This method provided