these risk models, and how they inform policy and prac-
tice should be the target of future study. However, phys-
ical therapy re-design might incorporate enhanced
treatment monitoring to assess ongoing risk for down-
stream utilization, as well as physical therapist-led inter-
ventions to more thoroughly address important
modifiable factors such as pain intensity, disability and
pain-related psychological distress [ 38]. Improved path-
way selection might entail the consideration of referral
to or co-treatment with other providers to more ad-
equately address non-modifiable characteristics. Collect-
ively, these approaches could improve the value of
physical therapy by minimizing risk for high downstream
healthcare utilization and potentially unwarranted escal-
ation of care.
The primary strength of the study is longitudinal
follow-up at multiple time points following an episode
of physical therapy for a variety of musculoskeletal pain
conditions. Anatomical location of pain was not a sig-
nificant predictor of healthcare use in all but one model,
suggesting results are widely applicable across a
spectrum of musculoskeletal pain conditions. Another
strength of this cohort study is the assessment of various
healthcare utilization outcomes of interest for establish-
ing health policy. When considered alongside more trad-
itional pain- or disability-related outcomes prediction
models, these findings will improve the ability of health-
care systems and providers to make decisions in
value-based purchasing environments. The consideration
of multiple screening tools (i.e. yellow flags and review
of systems) and treatment monitoring variables is also a
strength of this study as screening and systematic treat-
ment monitoring are not routine in clinical practice. A
final strength is inclusion of multiple sociodemographic,
health-related and psychosocial factors as potential pre-
dictors. Healthcare outcomes and utilization exhibit
emergent properties that require the consideration of
multiple, competing factors to fully explain [ 50].
Lentz et al. BMC Health Services Research  (2018) 18:648 Page 11 of 14