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
an 8-month overall follow-up period after physical ther-
apy and two follow-up points were included to minimize
recall bias.
Statistical analysis
All data analyses were preformed using SPSS Version 22.0
(IBM Corp., Armonk, NY). We developed models to sep-
arately predict over the course of the entire follow-up
period: 1) the dichotomous outcome of no healthcare
utilization versus any healthcare utilization and 2) the
utilization of specific services. We decided to develop sep-
arate models since each outcome predicted by these
models might have unique future policy implications. For
instance, those who utilize no additional services might
represent a “low risk ” group for which physical therapy
alone might be particularly appropriate. Predicting use of
specific services would inform policy where reduction of
specific services is a high priority, such as utilization of
opioids or unnecessary use of emergency room services.
All prediction models used the following hierarchical
design, which is similar to prior analyses in this cohort
[20, 21]:
Block 1: age, sex, race, anatomical region of pain,
insurance, chronicity of pain, surgery for current
condition (yes/no), Charlson comorbidity index,
baseline disability, baseline pain intensity.
Lentz et al. BMC Health Services Research  (2018) 18:648 Page 4 of 14