Spine Pain INtervention to Enhance Care Quality And Reduce Expenditure - Randomized Clinical Trial
Phase: NA
Conditions: Back Pain, Neck Pain
Sponsor: Brigham and Women's Hospital

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FINAL PROTOCOL AND STATISTICAL ANALYSIS PLAN 
 
Spine Pain INtervention to Enhance Care quality And Reduce Expenditure (SPINE CARE) – 
Randomized Clinical Trial  
 
NCT03083886 
 
10-01-2021 
 

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FINAL PROTOCOL 
1. Synopsis 
Low back and neck pain are among the leading causes of medical visits, lost productivity 
and disability. There is an urgent need to identify effective and efficient ways of helping 
subjects with acute spine pain while guiding practitioners towards high-value care.  This trial 
will be a block and cluster-randomized open-label multi-centered pragmatic randomized clinical 
trial comparing healthcare spending and clinical outcomes for subjects with spine pain of less 
than three months’ duration, in whom there are no red flag signs or symptoms.  Subjects will be 
randomized to one of three treatment strategies: (1) usual primary care provider-led care; (2) 
usual PCP-led care with spine pain treatment directed by the Identify, Coordinate, and Enhance 
decision making (ICE) care model, and (3) usual PCP-led care with spine pain treatment directed 
by the Individualized Postural Therapy (IPT) care model.  Our outcomes of interest will be spine-
related healthcare utilization at one year as well as pain and functionality of the study 
participants.  
 
2. Background 
Direct healthcare spending on neck and back pain (spine pain) exceeds $86 billion 
annually in the United States. While up to 80% of adults will experience clinically significant 
spine pain during their lifetimes, only a minority will progress to chronic pain with resultant 
high health care utilization (1–9).  For the vast majority of subjects, spine pain complaints are 
self-limited (10–12).  As a result, there is little evidence that the large amounts currently spent 
on spine pain has significantly improved population outcomes.  

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Many clinical guidelines exist for the treatment of spine pain, but much of the evidence 
supporting specific treatment modalities addresses subjects with chronic back pain rather than 
individuals presenting with more acute or subacute complaints (13).  Despite many clinical 
guidelines for the management of low back pain, research in this area has shown mixed results 
and has led to a non-uniform clinical approach to treating spine pain with predictably variable 
outcomes of pain progression (14–16).  Many patients with low back pain begin to incur 
substantial resource use and associated expenses soon after their first episode of pain (14). For 
example, there is mounting clinical evidence that imaging offers little help for the initial care of 
a subject with nonspecific spine pain (17,18), but despite the lack of utility therein, nearly 15% 
of clinicians admit it would be difficult to not order advanced imaging when subjects present for 
care (15). 
Currently there is also widespread use of non-traditional modalities of care, such as 
comprehensive and alternative medicine (CAM).  A recent study suggested that 30% of subjects 
are using CAM, and 42% of those subjects did not disclose this to their primary care physician 
(19).  A particularly promising strategy appears to be exercise or postural therapy, which is 
defined as “a series of specific movements with the aim of training or developing the body by a 
routine practice to promote good physical health (20–23).”  Despite this, there are substantial 
inconsistencies in the literature and many of the existing studies have been of low-quality (20).  
Given the discordance between number of subjects using these techniques and the amount of 
reliable data by which to judge their effectiveness, it is necessary to perform a rigorous 
evaluation. 

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One strategy for enhancing the efficiency of spine pain interventions is to target them at 
individuals with a high probability of progressing from acute to chronic pain.  For example, the 
STarT Back tool uses a biopsychosocial framework to identify features of a subject that helps to 
predict the likelihood of developing chronic pain, which can then direct treatments to improve 
pain and functioning (24).  Applying this risk stratification method to subjects with low back 
pain (24,25) and guiding treatment based upon it has been shown to improve clinical outcomes 
and reduce health spending (26).  However, the majority of subjects included in the studies 
evaluating the STarT Back tool had been experiencing back pain for more than three months 
and thus, further research is needed to risk stratify subjects earlier in the course of their illness 
to prevent the transition of acute pain into chronic pain.  These strategies must also be well-
received by providers, as acceptance of these new treatment pathways has been limited (27). 
The SPINE CARE trial seeks to fill the gaps in our knowledge about how to manage 
subjects presenting with acute and subacute spine pain by rigorously evaluating two methods 
of care: Individualized Postural Therapy (IPT) and the Identify, Coordinate, and Enhance 
decision making (ICE) Care Model developed by the Clinical Excellence Research Center (CERC) 
at Stanford University.  These two models of care represent novel approaches to the 
comprehensive treatment of subjects with spine pain with the potential to significantly reduce 
spine related cost of care and improve clinical outcomes. 
 
3. Objectives and Overall Design 
This block and cluster-randomized, open-label, multi-centered three-arm pragmatic 
randomized clinical trial seeks to compare healthcare spending, pain, physical functioning, and 

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quality of life for subjects with acute and subacute spine pain receiving care in one of three 
ways: (1) usual primary care provider (PCP)-led care; (2) usual PCP-led care with spine pain 
treatment directed by the ICE care model, and (3) usual PCP-led care with spine pain treatment 
directed by the IPT care model. ICE and IPT will both be integrated with typical clinical practice 
to test strategies that, if effective, could easily be incorporated into existing models of care.  
We hypothesize that the ICE and IPT models of care will decrease spine related healthcare 
spending while improving physical functional and quality of life.  
 
4. Study Setting 
This trial will be conducted in primary care clinics in geographically distinct areas in the U.S. 
with the following characteristics: 
1. Provide primary care to adult subjects with acute back and neck pain. 
2. Offer same day or next day appointments. 
3. Do not have an existing specialized program for back or neck pain subjects. 
4. Are located within 30 minutes driving distance of an Individualized Postural Therapy 
clinic. 
5. Agree to equipoise for all study arms and study protocol, and defer spine related pain 
treatment direction to ICE staff for subjects randomized to the ICE treatment arm. 
The sites will be selected so as to not have overlapping clinical staffs in order to 
minimize the risk of contamination (given that sites are cluster randomized) and to thereby 
minimize the possibility that subjects at control sites will be exposed to potentially beneficial 
aspects of either of the interventions. 

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5. Subjects 
5.1. Inclusion Criteria 
● Patients with back or neck pain of ≤ 3 months’ duration. All patients must have spine 
pain with or without radiation to the extremities or the head  
● Age ≥ 18 years 
● Willing and able to provide informed consent 
 
5.2. Exclusion Criteria 
● Patients with symptoms attributed to the spine but without actual pain in the spine (e.g. 
those with cervicogenic headache without neck pain) 
● Currently pregnant 
● Currently receiving disability benefits, worker’s compensation, or involved in litigation 
for a workplace injury 
● Currently enrolled in another intervention trial for the management of acute back or 
neck pain 
● Cancer that is metastatic or being actively treated. (i.e., chemotherapy, radiation, 
surgery) 
● History of receiving active therapy for back or neck pain in the past 3 months (7+ 
consecutive days of narcotic use, 6+ sessions of PT, chiropractic care, acupuncture, 
postural therapy, or other spine therapy delivered by a trained provider)  
● History of spine surgery or spine injections/ablation in the past 6 months  
● Severe, active psychosis or major depression inhibiting ability to physically participate in 
intervention 
● Red Flag Symptoms (fever, night sweats, unintentional weight loss, bowel or bladder 
dysfunction, neurologic weakness, current intravenous drug use) 
 

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6. Interventions 
Clinics will be randomized to one of the following three arms as described below. 
 
6.1 ARM 1: Usual care 
Subjects seeking care at a clinic assigned to this arm will receive usual care as directed 
by their primary care provider.  Treatment modalities may include medications, specialty 
referrals, imaging, procedures such as injections, physical and psychological therapy, as 
appropriate.  
 
6.2 ARM 2: PCP-led care + ICE 
Subjects seeking care at a clinic assigned to this arm will receive the ICE care model 
through referral by their primary care provider.  The ICE care model was developed by the 
Clinical Excellence Research Center at Stanford University based on a review of the peer-
reviewed literature for adult subjects with incident neck or back pain who are not using high-
dose opioid medications or receiving spine-related long-term disability payments.  The care 
pathway is designed to take place over the course of six weeks and is intended to avoid low-
value healthcare expenditures for subjects presenting with spine pain by: 
1. Stratifying subjects with back or neck pain into “low” and “high” risk groups, based on 
the STarT Back risk assessment tool (Appendix A) (25), and directing care accordingly 
(Figure 1).  The STarT Back tool is a validated instrument that was created to assist with 
the prediction of the transition of acute to chronic pain.  This tool measures a subject’s 
physical functionality as well as their experience with pain by determining how much 

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their pain causes psychological distress that may magnify the disability caused by the 
pain itself.  Baseline STarT Back tool responses have been shown to be predictive of pain 
intensity at six months (28). 
 
Figure 1. Care Stratification Based on STarT Back Scoring Tool (©Keele University 01/08/07 
Funded by Arthritis Research UK) 
 
 
2. Directing low-risk subjects with uncomplicated back or neck pain and few psychosocial 
risk factors to a limited physical therapy course without additional diagnostic evaluation 
or specialty referral (Table 1). If subjects do not improve, they will be referred back to 
their primary care providers for further evaluation and treatment.  
3. 
Referring high- and medium-risk subjects with significant biopsychosocial risk factors 
(i.e., a high degree of pain catastrophizing) predictive of chronicity to a novel spine 
team which focuses treatment on physical rehabilitation, normalization of experience, 
and self-management skills.  The team will consist of a physical therapist serving as the 

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rehabilitation lead, a “Spine Coach” focusing on enabling subject self-motivation and 
an “ICE MD” who fulfills an advanced medical consultation role for those who do not 
improve after initial course of therapy.  The Spine Coach is a psychology counselor 
trained in motivational interviewing and supportive care delivered by telephone.  
The specific components of the ICE model are summarized below: 
Table 1.  Levels of care: Proposed frequency of contact 
Subject Risk 
Physical 
Therapy 
Spine Coach ICE MD 
Low risk 
1 session* 1 session 
None.  Patients who do not improve in six 
weeks will return to usual care. 
High and 
medium risk  
Up to 3 
sessions 
Up to 3 
sessions† 
Consult to provide an individual treatment 
plan for all subjects. 
*If subject has improved prior to visit they will be able to cancel PT session in the conservative care pathway. 
†Frequency will be determined by subject and spine coach 
 
Responsibilities of the ICE care providers will be as follows: 
1. Physical Therapy (PT) – The ICE PT will perform their typical practice of taking a detailed 
history pertinent about the subject’s spine pain, perform a thorough physical exam, and 
then tailor the frequency and goals of therapy based on the subject’s STarT Back risk 
level.  Each practitioner will be trained to communicate with subjects using enabling 
language that reinforces self-efficacy skills and provides tools for self-management.  
These encounters will take place in a local physical therapy practice commonly used by 
participating referring clinics that are willing to undergo training about the ICE pathway. 
2. Spine Coach – The Spine Coach will use motivational interviewing to teach coping skills, 
improve subject self-efficacy, and provide ongoing reinforcement. These encounters will 

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occur by telephone with frequency directed by the STarT Back tool.  Subjects who are at 
low risk for chronicity will receive one call whereas individuals who are medium or high 
risk will receive up to three calls over the first six weeks of the intervention.  The coach 
will provide recommendations on self-management, guided by principles in the Back 
Book (29) and normalize the subject’s experience.  The Back Book was developed to 
explain the most common causes of musculoskeletal spine pain, and ways to stay active 
while recovering.  The first outreach will take place within 3 business days of the initial 
visit to the PCP for spine pain to the primary care provider and be provided at regular 
intervals based on the needs of the subject, as agreed upon by the spine coach and 
subject. The Spine Coach and the Physical Therapist will coordinate care using a 
Communication Checklist (Appendix K) after each visit. 
3. ICE MD – All subjects who are stratified to high or medium risk by the STarT Back Tool as 
well as low-risk subjects who have no improvement in their pain despite treatment with 
the ICE pathway for 6 weeks will receive an ICE MD consultation.  The ICE MD will be an 
MD or DO with pain medicine or physical medicine and rehabilitation specialty 
experience.  They will be experienced in conservative musculoskeletal care and have an 
active medical license in the state in which they are providing consultations.  All 
assessments by the ICE MD will occur remotely via chart review of the subject’s 
electronic health record available through their primary care provider’s office in 
conjunction with any study communication between the physical therapy team and 
spine coach.  Based on review of this information, individualized treatment 

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recommendations will be provided to the primary care provider in a written summary 
that can then be carried out at the discretion of the primary care provider (Appendix B). 
 
6.3. ARM 3: PCP-led care + IPT 
The Individualized Postural Therapy (IPT) is an alternative method of care for subjects 
with neck and back pain. This intervention was chosen to be representative of an alternative 
care model that is commonly used by individuals with back pain, either in conjunction with, or 
as an alternative to, usual care.  
IPT involves the evaluation of a subject’s posture to identify postural and alignment 
deviations and, based on this, a personalized corrective exercise program is prescribed.  This 
method does involve the use of prescription medications, surgery, or manipulation. The initial 
consultation typically takes between 60-90 minutes, at which time a regimen of exercises is 
provided.  The exercise menu consists of exercises, specific to the individual, which take 
between 15-75 minutes daily and can be performed at home once the subject has been 
evaluated by an IPT clinician.  The amount of exercise required depends on the individual’s 
postural and mechanical dysfunctions, and time allowance.  A treatment course typically lasts 
eight sessions over eight weeks.  In order to allow for the consistent delivery of this arm of the 
study at multiple study-sites across the country, IPT will be delivered by The Egoscue Method 
(30).  Egoscue was founded in 1971 and has 25 clinics worldwide.   
 
7. Study Procedures 
7.1 Randomization 

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Randomization will occur at the clinic level (i.e. subjects will be cluster randomized) in a 
1:1:1 ratio to usual care, usual primary care + ICE, and usual primary care + IPT.  To ensure 
adequate balance between the treatment arms with respect to sample size practices will be 
categorized into blocks of 3 based on the average number of patients with spine pain that they 
see in a typical week, their location, and/or their provision of other services such as 
urgent/walk-in care.  Because of differences between the delivery networks participating in the 
trial, the stratification factors may differ by location. Randomization will occur within these 
blocks. 
 
7.2 Subject Identification 
The study will include individuals presenting for care with a chief complaint of back pain 
or neck pain.  Potentially eligible subjects will be identified by reviewing clinic schedules for 
upcoming visits and/or through screening when they present to the clinic for “same-day” or 
“walk-in” care. 
 
 
 
7.3 Eligibility Screening  
Patients presenting for care with spine pain will be informed of the study when they 
arrive for care and will be given a screening form to assess them for eligibility.  Subjects who 
meet the initial eligibility criteria will be given either a written informed consent form 
(Vanderbilt and UBC, Appendix D) or a verbal informed consent form (HonorHealth, Appendix 

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D) detailing the potential benefits and risks of participating in the study, and what would be 
required of them.  Consenting subjects will then be asked to complete the baseline surveys 
while waiting to be seen by their primary care provider.  Their primary care provider will 
confirm that their symptom criteria are completed correctly and evaluate them for additional 
exclusion criteria that require clinical expertise (Appendix E).  Subjects who meet all the 
inclusion and exclusion criteria will be enrolled in the study.  
 
7.4 Baseline Surveys 
After providing consent, subjects will be asked to complete the baseline demographic 
data (Appendix F) and other baseline surveys (Table-3) using the study’s electronic data capture 
system (see Section 9.3).  
 
7.5 Subject cost-sharing 
Subjects randomized to the usual care arm will pay standard copayments as determined 
by their insurance carrier for all services recommended by their PCPs.  Subjects randomized to 
the ICE or IPT will face no out-of-pocket costs for study recommended visits but will, as in the 
usual care arm, pay standard copayments as determined by their insurance carrier for other 
services recommended by their PCPs.  
 
8. Informed Consent 
Vanderbilt and UBC sites will be required to obtain subject authorization to participate 
in the study using written informed consent at the time of their enrollment clinic visit. 

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HonorHealth sites will be required to obtain verbal consent for the subject to participate in the 
study. Information about the trial and the requirements of trial participation will be 
summarized in an informed consent document, whether verbal or written consent is obtained 
(Appendix D).  
 
9. Outcomes 
9.1 Primary Outcomes  
The two primary outcomes for the trial will be: (a) spine-related cost of care at one year 
and (b) change in pain at three months as assessed by the Oswestry Disability Index (ODI, 
Appendix G).  Secondary outcomes will include pain at 12 months, quality of life at 12 months 
assessed using the EQ-5D, and self-efficacy at 12 months assessed using a scale developed by 
Lorig et al. (31).  
Table 2: Outcomes 
Primary 
Spine related cost of care at one year 
Change in pain (measured by ODI) at three months 
Secondary 
Change in pain (measured by ODI) at one year 
Quality of life (measured by EQ-5D) at one year 
Self-efficacy (measured by scale developed by Lorig et. al) at one year 
 
9.1.1 Spine-Related Cost of Care 
Spine-related cost of care will be estimated by applying unit costs incurred by subjects 
or third-party payers to estimates of resource utilization obtained from subject-reported 
utilization data (Appendix H).  Subject-reported utilization will be collected using monthly 
checklists for the first three months, then bimonthly for the following nine months, that are 

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based upon the approach recently employed by Fritz et al. (15) and originally developed by 
Goosens et al. (33).  Subjects will be asked about all healthcare services used, including primary 
care visits, emergency room encounters, hospital admissions, imaging studies (including MR 
and CT), prescriptions, and physical therapy services that pertain to spine-related healthcare 
(14,34).  
Data from the utilization checklists will be categorized using Current Procedural 
Terminology (CPT) and International Classification of Disease (ICD) codes. Medications will be 
characterized using the Unified Medical Language System® Master Drug Database, Medi-Span®. 
Unit cost of these different services will be estimated using publicly available data 
sources. In specific, for outpatient visits to PCPs, specialists, physical therapists and other 
providers and for tests and procedures, we will use the Centers for Medicare & Medicaid 
Services Physician Fee Schedule Look-Up Tool.1 For hospitalizations, we will use the hospital 
adjusted expenses per inpatient day value calculated by the Kaiser Family Foundation.2 For 
emergency department visits, we will use estimates from the Medical Expenditure Panel 
Survey.3 To calculate the average retail price of medications, we will use average retail prices 
from GoodRx.com.4,  
 
9.1.2 Pain 
The ODI is the most commonly used scale for low back pain (35). It is a self-administered 
questionnaire that has ten topics: intensity of pain, lifting, sexual function, social life, sleep, and 
ability to walk, sit, stand, care for oneself, and travel.  It has been recommended as one of the 
standardized metrics for research of low back pain based on its ability to quantify functional 

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status in this population (36). The ODI typically takes three to five minutes to complete, and 
one minute to score (37).  Previous studies have evaluated the ODI in pain-free subjects and 
found that mean score to be 10.19 (35, 38, 39) and those with disability from low back pain is 
22.07 (40).  Previous studies have indicated that a change in ODI by 6 points is clinically 
meaningful (41).   
 
9.2 Other outcomes 
9.2.1 Quality of Life 
Quality of life will be assessed by the EQ-5D (Appendix I), which has been shown to be 
beneficial in describing and valuing health related quality of life (42, 43). It was developed for 
self-completion, and has been validated against other measures of quality of life, including SF-
12 (44).  The EQ-5D has been shown to correlate well with low back pain specific 
measurements, and also be responsive to change (45,46).  The instrument consists of a 
descriptive section and a visual analogue scale. The descriptive section measures 5 dimensions 
of health (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) with each 
dimension having 5 levels ranging from “no problem” to “extreme problem”. The visual 
analogue scale is a self-rated horizontal health scale with end points labelled as “the best health 
you can imagine” and “the worst health you can imagine”. The raw scores are converted into 
index scores based on US norms5. Previous studies identify a change in EQ-5D index of 0.08 as a 
minimal important clinical distance (47), and in a study evaluating the sensitivity to change of 
EQ-5D index with back pain it was seen that after two weeks there was a decrease of 0.21 after 
treatment; albeit this was in an interventional study that included steroid injections (46).  The 

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EQ-5D is also helpful in converting to quality adjusted life years (QALY) to perform a cost utility 
analysis, and is the most common measure for conversion (37).   
 
9.2.2 Self-Efficacy  
 
We will evaluate self-efficacy at baseline, six months, and one year.  As the focus of this 
trial is to support those with acute spine pain to prevent the development of chronic pain, 
measuring self-efficacy both as a predictor and outcome of the treatment arms will be 
necessary as a metric of self-management for future episodes.  We will use Lorig et al.’s self-
efficacy scale for individuals with musculoskeletal complaints, which has three subscales that 
focus on pain, functioning, and other symptoms (31).  Because spine-specific pain is already 
captured with ODI, we will use the “functioning” and “other symptoms” subscales in this trial to 
measure self-efficacy (Appendix J).  The “function” subscale produces an average of 73.27 (s.d. 
20.22), and the “other symptoms” subscale produces an average of 55.62 (s.d. 21.64). 
 
9.2.3 Productivity 
We will also evaluate the impact of spine pain on work-related activities by evaluating 
absenteeism and presenteeism.  Absenteeism will be assessed by subject self-report.  Time lost 
from work, or other usual activities, associated with spine pain and all other health problems 
will be collected and measured.  The total number of unplanned work absences will be 
multiplied by an average employee's daily wage to obtain the cost per participant of work 
absenteeism. Presenteeism will be assessed using the methods of van den Heuvel, et al (49). 
Three assertions will be ranked on a scale of 1-5: 1) I achieve all objectives of the job, 2) Job-

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related tasks come easily to me, and 3) I perform well in my job.  The scores will be 
dichotomized using the median value from all respondents.  A study participant will be 
described as suffering from presenteeism if they are above the median value. 
 
9.2.4 Other outcomes 
We will measure implementation-related outcomes to assess intervention fidelity. 
These will include the number of protocol-specified appointments (i.e., Spine Coach, physical 
therapist, or the Egoscue practitioner) scheduled and attended, the timing of visits and the 
length of the treatment course, which we originally expected to last 6 to 8 weeks. 
 
9.3 Data Collection 
 
Study data will be collected and managed using REDCap electronic data capture tools 
(50)  hosted at Brigham and Women’s Hospital.  Data will be collected based on the schedule in 
Table 3.  Study subjects will be contacted by email five business days prior to a survey being due 
for completion to be notified that the survey is available.  If the survey is not completed they 
will be notified again three and five business days after the due date.  Should the study subject 
still not complete the survey, they will have three phone attempts to be reached and guided 
through completion. 
Table 3: Subject Reported Outcome Administration Schedule 
 
Months After Enrollment 
Metric 
0 
1 
1.5 
2 
3 
4 
5 
6 
7 
8 
9 
10 
11 
12 
STarT Back Tool 
x 
 
 
 
 
 
 
 
 
 
 
 
 
 
Healthcare Utilization 
Checklist 
 
x 
 
x 
x 
 
x 
 
x 
 
x 
 
x 
x 
Oswestry Disability Index 
x 
 
x 
 
x 
 
 
x 
 
 
 
 
 
x 

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EQ-5D 
x 
 
x 
 
 
 
 
x 
 
 
 
 
 
x 
Self-Efficacy 
Questionnaire 
x 
 
 
 
 
 
 
x 
 
 
 
 
 
x 
 
10. Statistical considerations 
10.1 Analysis plan 
All analyses will be performed using intention to treat principles based on study arm 
with which a subject is assigned at study enrollment and regardless of whether or not all 
protocol steps have been completed. We will report means and frequencies of pre-
randomization variables separately by study arm. Comparison of these values will be made with 
generalized estimating equations to adjust for the block and cluster randomized design.  
Because cost data in healthcare is not normally distributed (32) due to significant zero 
data representing subjects for whom there is little to no cost, we will have to model the data 
accordingly.  We will evaluate the two primary outcomes, total cost of care, using generalized 
estimating equations with gamma distributed errors and an identity link function which can 
account for a positively skewed distribution. Changes in ODI from baseline to three months will 
be compared for the treatment arms using generalized estimating with normally distributed 
errors and an identity link function.  All models will adjust for age and sex, account for the 
cluster and block randomized study design and include fixed effects for the 3 different delivery 
networks that were used for recruitment. In secondary analyses, we will repeat our models 
adjusting for unmatched confounders that remained despite randomization.  Our primary 
analyses will compare each of the two treatment arms separately with usual care (i.e., ICE 
compared with usual care and IPT with usual care). Because we are evaluating two primary 

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outcomes, we will use a Bonferroni-corrected two-tailed type 1 error of 0.025. Analysis of 
secondary outcomes will also be performed using generalized estimating equations with error 
distributions and link functions appropriate to the outcomes being evaluated.  
 
Missing data will be accounted for using multiple imputation (51), which has been 
determined an adequate strategy to minimize both false positive and false negatives in clinical 
trials.  We will perform 20 imputations using Proc MI in SAS with a fully conditional 
specification. The following variables will be used to perform the imputation: age, study arm, 
study site, clinic, sex, race/ethnicity, BMI, exercise frequency at baseline, education level, 
employment status, smoking status, other medical conditions at baseline, number of 
medications used for spine pain at baseline, length of pain at baseline, number of previous pain 
episodes, STarT back score, baseline ODI, baseline self-efficacy, baseline EQ-5D, and scores for 
patient-reported outcomes at every follow-up timepoints (ODI, cost, Lorig self-efficacy scale, 
and EQ-5D).  
 
As resource utilization and ODI were collected at multiple time points, we will also 
evaluate non-missing cost and ODI data from each time point using a repeated measures 
design. In specific, we will use generalized estimating equations, with link functions and error 
distributions appropriate to the study outcomes, to assess changes in outcomes over the 12 
months of follow-up, while accounting for correlations in the repeated measurements. For 
spine-related health spending, these analyses will be conducted using the time intervals at 
which raw data were collected as well as after converting estimates to evenly-spaced months. 
Because cost data in healthcare is not normally distributed with zero values for participants 
with no resource utilization during follow-up, we will winsorize estimated costs at the 95th 

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percentile in secondary analyses. We will report relative spending differences with confidence 
intervals and a two-tailed p value. As a sensitivity analysis, we will conduct a complete-case 
analysis on all non-missing values. 
Exploratory analyses will be performed evaluating the effect of the interventions on cost 
in various strata of clinical interest, including age, sex, STarT Back risk group, location of pain, 
and whether or not this was the subject’s first pain episode. We will also evaluate the 
percentage of subjects in each arm with a decrease in ODI of six points at three, six, and twelve 
months of follow-up.   
 
10.2 Sample size 
The ICE model was anticipated to reduce total cost of care by 25% compared to usual 
care (52–54). Because of the lack of peer-reviewed literature evaluating the economic impact of 
IPT, an effect similar to ICE was assumed for the purpose of performing power calculations.  We 
will need to enroll a total of 3,096 patients (1,032 per arm) to conservatively detect a change in 
spending of 20% between either treatment arm and usual care with 80% power and an alpha of 
0.05, with 33 clusters, and 10% loss to follow-up over the 12-month study period. Our results 
are robust to a standard deviation of 1.25 times the mean and an ICC value of 0.01. Given the 
substantially larger sample size required for our economic analyses, we powered our trial on 
the basis of this outcome, which would also give us more than 98% power to detect a 6-point 
change in ODI between each intervention arm and the usual care arm. 
 

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11. Risk Protection  
11.1 Risks Associated with the Inventions Under Investigation  
Since the interventions under investigation are accepted forms of treatment for neck 
and lower back and leg symptoms, it is anticipated that the potential risks to the subjects are 
the same as for any standard treatment in these areas.  If adverse effects occur, we anticipate 
that appropriate medical care will be provided by the subject’s primary care physicians, who 
will continue to be involved in the care of subjects in all three of the study arms. Systemic red 
flag symptoms, including leg weakness and urinary incontinence are not expected to occur 
because enrolled subjects will be screened by their primary care doctors and are required to be 
low risk at study entrance.  However, in the event a red flag symptom occurs, subjects in all 3 
arms will be instructed to urgently report this to their primary care physician, who will arrange 
for triage per standard of care.  Adverse events will not be actively solicited but they will be 
tracked should an event come to the awareness of the investigators. 
 
11.2 Subject Confidentiality  
Identifiable research material shall consist of medical records, questionnaires, and data 
that will be obtained specifically for the study.  Identifiable data will be retained and secured in 
a locked cabinet at each site. In specific, electronic study data will be stored in a 21 CRF part 11 
compliant system and all paper documentation with personal health information would be 
stored in a secured location at each site. Each study site will be individually responsible for 
complying with all local and state laws, regulations and Human Subjects Committee policies 

23 
FINAL PROTOCOL (10-01-2021) 
regarding collection and distribution of subject information.  The questionnaire information is 
not unusually sensitive and will be subject to strict confidentiality safeguards.   
Subjects will be informed of the confidentiality of the data and assured that it will be 
used only in aggregate for statistical purposes, with no identification of individuals.  No data 
beyond what is included in the informed consent will be sought without authorization from 
hospitals and doctors and without signed medical release from the subjects.  All study 
personnel will be instructed not to discuss any cases with persons other than other study 
personnel.  All hard copies of study records will be kept in locked files to which only study 
personnel have access.  
 
11.3 Reporting requirements 
The Site Principal Investigator or Designee will report to the IRB any of the following 
adverse events that occur: 1) during the conduct of the study, 2) after study completion (if 
study staff become aware), or 3) after participant withdrawal or completion (if study staff 
become aware).  
1. Unanticipated adverse effects that are serious and caused by, or associated with, the study 
treatments (ICE care or IPT care). 
2. Breach of confidentiality or violation of HIPAA (e.g., lost or stolen laptop). 
Reports will be submitted within 5 working days or 7 calendar days of the date the 
investigator first becomes aware of the problem.  In cases involving serious adverse events, 
reports will be submitted to IRB within 48 hours of the investigator becoming aware of the 
event.

24 
FINAL PROTOCOL (10-01-2021) 
12. Study Timeline 

 
25 
STATISTICAL ANALYSIS PLAN 
 
Outcomes 
1 Primary Outcomes  
The two primary outcomes for the trial will be: (a) spine-related cost of care at one year 
and (b) change in pain at three months as assessed by the Oswestry Disability Index (ODI, 
Appendix G).  Secondary outcomes will include pain at 12 months, quality of life at 12 months 
assessed using the EQ-5D, and self-efficacy at 12 months assessed using a scale developed by 
Lorig et al. (31).  
 
 
1.1 Spine-Related Cost of Care 
Spine-related cost of care will be estimated by applying unit costs incurred by subjects 
or third-party payers to estimates of resource utilization obtained from subject-reported 
utilization data (Appendix H).  Subject-reported utilization will be collected using monthly 
checklists for the first three months, then bimonthly for the following nine months, that are 
based upon the approach recently employed by Fritz et al. (15) and originally developed by 
Goosens et al. (33).  Subjects will be asked about all healthcare services used, including primary 
care visits, emergency room encounters, hospital admissions, imaging studies (including MR 
Table 1: Outcomes 
Primary 
Spine related cost of care at one year 
Change in pain (measured by ODI) at three months 
Secondary 
Change in pain (measured by ODI) at one year 
Quality of life (measured by EQ-5D) at one year 
Self-efficacy (measured by scale developed by Lorig et. al) at one year 

 
26 
and CT), prescriptions, and physical therapy services that pertain to spine-related healthcare 
(14,34).  
Data from the utilization checklists will be categorized using Current Procedural 
Terminology (CPT) and International Classification of Disease (ICD) codes. Medications will be 
characterized using the Unified Medical Language System® Master Drug Database, Medi-Span®. 
Unit cost of these different services will be estimated using publicly available data 
sources. In specific, for outpatient visits to PCPs, specialists, physical therapists and other 
providers and for tests and procedures, we will use the Centers for Medicare & Medicaid 
Services Physician Fee Schedule Look-Up Tool.1 For hospitalizations, we will use the hospital 
adjusted expenses per inpatient day value calculated by the Kaiser Family Foundation.2 For 
emergency department visits, we will use estimates from the Medical Expenditure Panel 
Survey.3 To calculate the average retail price of medications, we will use average retail prices 
from GoodRx.com.4,  
 
1.2 Pain 
The ODI is the most commonly used scale for low back pain (35). It is a self-administered 
questionnaire that has ten topics: intensity of pain, lifting, sexual function, social life, sleep, and 
ability to walk, sit, stand, care for oneself, and travel.  It has been recommended as one of the 
standardized metrics for research of low back pain based on its ability to quantify functional 
status in this population (36). The ODI typically takes three to five minutes to complete, and 
one minute to score (37).  Previous studies have evaluated the ODI in pain-free subjects and 
found that mean score to be 10.19 (35, 38, 39) and those with disability from low back pain is 

 
27 
22.07 (40).  Previous studies have indicated that a change in ODI by 6 points is clinically 
meaningful (41).   
 
2 Other outcomes 
2.1 Quality of Life 
Quality of life will be assessed by the EQ-5D (Appendix I), which has been shown to be 
beneficial in describing and valuing health related quality of life (42, 43). It was developed for 
self-completion, and has been validated against other measures of quality of life, including SF-
12 (44).  The EQ-5D has been shown to correlate well with low back pain specific 
measurements, and also be responsive to change (45,46).  The instrument consists of a 
descriptive section and a visual analogue scale. The descriptive section measures 5 dimensions 
of health (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) with each 
dimension having 5 levels ranging from “no problem” to “extreme problem”. The visual 
analogue scale is a self-rated horizontal health scale with end points labelled as “the best health 
you can imagine” and “the worst health you can imagine”. The raw scores are converted into 
index scores based on US norms5. Previous studies identify a change in EQ-5D index of 0.08 as a 
minimal important clinical distance (47), and in a study evaluating the sensitivity to change of 
EQ-5D index with back pain it was seen that after two weeks there was a decrease of 0.21 after 
treatment; albeit this was in an interventional study that included steroid injections (46).  The 
EQ-5D is also helpful in converting to quality adjusted life years (QALY) to perform a cost utility 
analysis, and is the most common measure for conversion (37).   
 

 
28 
2.2 Self-Efficacy  
 
We will evaluate self-efficacy at baseline, six months, and one year.  As the focus of this 
trial is to support those with acute spine pain to prevent the development of chronic pain, 
measuring self-efficacy both as a predictor and outcome of the treatment arms will be 
necessary as a metric of self-management for future episodes.  We will use Lorig et al.’s self-
efficacy scale for individuals with musculoskeletal complaints, which has three subscales that 
focus on pain, functioning, and other symptoms (31).  Because spine-specific pain is already 
captured with ODI, we will use the “functioning” and “other symptoms” subscales in this trial to 
measure self-efficacy (Appendix J).  The “function” subscale produces an average of 73.27 (s.d. 
20.22), and the “other symptoms” subscale produces an average of 55.62 (s.d. 21.64). 
 
2.3 Productivity 
We will also evaluate the impact of spine pain on work-related activities by evaluating 
absenteeism and presenteeism.  Absenteeism will be assessed by subject self-report.  Time lost 
from work, or other usual activities, associated with spine pain and all other health problems 
will be collected and measured.  The total number of unplanned work absences will be 
multiplied by an average employee's daily wage to obtain the cost per participant of work 
absenteeism. Presenteeism will be assessed using the methods of van den Heuvel, et al (49). 
Three assertions will be ranked on a scale of 1-5: 1) I achieve all objectives of the job, 2) Job-
related tasks come easily to me, and 3) I perform well in my job.  The scores will be 
dichotomized using the median value from all respondents.  A study participant will be 
described as suffering from presenteeism if they are above the median value. 

 
29 
 
2.4 Other outcomes 
We will measure implementation-related outcomes to assess intervention fidelity. 
These will include the number of protocol-specified appointments (i.e., Spine Coach, physical 
therapist, or the Egoscue practitioner) scheduled and attended, the timing of visits and the 
length of the treatment course, which we originally expected to last 6 to 8 weeks. 
 
Data Collection 
 
Study data will be collected and managed using REDCap electronic data capture tools 
(50)  hosted at Brigham and Women’s Hospital.  Data will be collected based on the schedule in 
Table 3.  Study subjects will be contacted by email five business days prior to a survey being due 
for completion to be notified that the survey is available.  If the survey is not completed they 
will be notified again three and five business days after the due date.  Should the study subject 
still not complete the survey, they will have three phone attempts to be reached and guided 
through completion. 
Table 2: Subject Reported Outcome Administration Schedule 
 
Months After Enrollment 
Metric 
0 
1 
1.5 
2 
3 
4 
5 
6 
7 
8 
9 
10 
11 
12 
STarT Back Tool 
x 
 
 
 
 
 
 
 
 
 
 
 
 
 
Healthcare Utilization 
Checklist 
 
x 
 
x 
x 
 
x 
 
x 
 
x 
 
x 
x 
Oswestry Disability Index 
x 
 
x 
 
x 
 
 
x 
 
 
 
 
 
x 
EQ-5D 
x 
 
x 
 
 
 
 
x 
 
 
 
 
 
x 
Self-Efficacy 
Questionnaire 
x 
 
 
 
 
 
 
x 
 
 
 
 
 
x 
 

 
30 
Statistical considerations 
1 Analysis plan 
All analyses will be performed using intention to treat principles based on study arm 
with which a subject is assigned at study enrollment and regardless of whether or not all 
protocol steps have been completed. We will report means and frequencies of pre-
randomization variables separately by study arm. Comparison of these values will be made with 
generalized estimating equations to adjust for the block and cluster randomized design.  
Because cost data in healthcare is not normally distributed (32) due to significant zero 
data representing subjects for whom there is little to no cost, we will have to model the data 
accordingly.  We will evaluate the two primary outcomes, total cost of care, using generalized 
estimating equations with Poisson distributed errors and a log link function which can account 
for a positively skewed distribution. Changes in ODI from baseline to three months will be 
compared for the treatment arms using generalized estimating with normally distributed errors 
and an identity link function.  All models will adjust for age and sex, account for the cluster and 
block randomized study design and include fixed effects for the 3 different delivery networks 
that were used for recruitment. In secondary analyses, we will repeat our models adjusting for 
unmatched confounders that remained despite randomization.  Our primary analyses will 
compare each of the two treatment arms separately with usual care (i.e., ICE compared with 
usual care and IPT with usual care). Because we are evaluating two primary outcomes, we will 
use a Bonferroni-corrected two-tailed type 1 error of 0.025. Analysis of secondary outcomes 
will also be performed using generalized estimating equations with error distributions and link 
functions appropriate to the outcomes being evaluated.  

 
31 
 
Missing data will be accounted for using multiple imputation (51), which has been 
determined an adequate strategy to minimize both false positive and false negatives in clinical 
trials.  We will perform 20 imputations using Proc MI in SAS with a fully conditional 
specification. The following variables will be used to perform the imputation: age, study arm, 
study site, clinic, sex, race/ethnicity, BMI, exercise frequency at baseline, education level, 
employment status, smoking status, other medical conditions at baseline, number of 
medications used for spine pain at baseline, length of pain at baseline, number of previous pain 
episodes, STarT back score, baseline ODI, baseline self-efficacy, baseline EQ-5D, and scores for 
patient-reported outcomes at every follow-up timepoints (ODI, cost, Lorig self-efficacy scale, 
and EQ-5D).  
 
As resource utilization and ODI were collected at multiple time points, we will also 
evaluate non-missing cost and ODI data from each time point using a repeated measures 
design. In specific, we will use generalized estimating equations, with link functions and error 
distributions appropriate to the study outcomes, to assess changes in outcomes over the 12 
months of follow-up, while accounting for correlations in the repeated measurements. For 
spine-related health spending, these analyses will be conducted using the time intervals at 
which raw data were collected as well as after converting estimates to evenly-spaced months. 
Because cost data in healthcare is not normally distributed with zero values for participants 
with no resource utilization during follow-up, we will winsorize estimated costs at the 95th 
percentile in secondary analyses. We will report relative spending differences with confidence 
intervals and a two-tailed p value. As a sensitivity analysis, we will conduct a complete-case 
analysis on all non-missing values. 

 
32 
Exploratory analyses will be performed evaluating the effect of the interventions on cost 
in various strata of clinical interest, including age, sex, STarT Back risk group, location of pain, 
and whether or not this was the subject’s first pain episode. We will also evaluate the 
percentage of subjects in each arm with a decrease in ODI of six points at three, six, and twelve 
months of follow-up. 
 
2 Sample size 
The ICE model was anticipated to reduce total cost of care by 25% compared to usual care (52–
54). Because of the lack of peer-reviewed literature evaluating the economic impact of IPT, an 
effect similar to ICE was assumed for the purpose of performing power calculations.  We will 
need to enroll a total of 3,096 patients (1,032 per arm) to conservatively detect a change in 
spending of 20% between either treatment arm and usual care with 80% power and an alpha of 
0.05, with 33 clusters, and 10% loss to follow-up over the 12-month study period. Our results 
are robust to a standard deviation of 1.25 times the mean and an ICC value of 0.01. Given the 
substantially larger sample size required for our economic analyses, we powered our trial on 
the basis of this outcome, which would also give us more than 98% power to detect a 6-point 
change in ODI between each intervention arm and the usual care arm. 
 

 
33 
References 
1.  Maetzel A, Li L. The economic burden of low back pain: a review of studies published between 1996 
and 2001. Best Pract Res Clin Rheumatol. 2002 Jan;16(1):23–30.  
2.  Jarvik JG, Hollingworth W, Heagerty PJ, Haynor DR, Boyko EJ, Deyo RA. Three-year incidence of low 
back pain in an initially asymptomatic cohort: clinical and imaging risk factors. Spine. 2005 Jul 
1;30(13):1541–8; discussion 1549.  
3.  Borghouts JA, Koes BW, Bouter LM. The clinical course and prognostic factors of non-specific neck 
pain: a systematic review. Pain. 1998 Jul;77(1):1–13.  
4.  Hoving JL, Gross AR, Gasner D, Kay T, Kennedy C, Hondras MA, et al. A critical appraisal of review 
articles on the effectiveness of conservative treatment for neck pain. Spine. 2001 Jan 15;26(2):196–
205.  
5.  Weiner DK, Kim Y-S, Bonino P, Wang T. Low back pain in older adults: are we utilizing healthcare 
resources wisely? Pain Med Malden Mass. 2006 Apr;7(2):143–50.  
6.  Martin BI, Deyo RA, Mirza SK, et al. EXpenditures and health status among adults with back and 
neck problems. JAMA. 2008 Feb 13;299(6):656–64.  
7.  Bovim G, Schrader H, Sand T. Neck pain in the general population. Spine. 1994 Jun 15;19(12):1307–
9.  
8.  Brattberg G, Thorslund M, Wikman A. The prevalence of pain in a general population. The results of 
a postal survey in a county of Sweden. Pain. 1989 May;37(2):215–22.  
9.  Kelsey JL, White AA. Epidemiology and impact of low-back pain. Spine. 1980 Apr;5(2):133–42.  
10.  Côté P, Cassidy JD, Carroll LJ, Kristman V. The annual incidence and course of neck pain in the 
general population: a population-based cohort study. Pain. 2004 Dec;112(3):267–73.  
11.  Andersson GB. Epidemiological features of chronic low-back pain. Lancet Lond Engl. 1999 Aug 
14;354(9178):581–5.  
12.  Picavet HSJ, Schouten JS a. G. Musculoskeletal pain in the Netherlands: prevalences, consequences 
and risk groups, the DMC(3)-study. Pain. 2003 Mar;102(1-2):167–78.  
13.  Bouwmeester W, van Enst A, van Tulder M. Quality of low back pain guidelines improved. Spine. 
2009 Nov 1;34(23):2562–7.  
14.  Ivanova JI, Birnbaum HG, Schiller M, Kantor E, Johnstone BM, Swindle RW. Real-world practice 
patterns, health-care utilization, and costs in patients with low back pain: the long road to guideline-
concordant care. Spine J. 2011 Jul;11(7):622–32.  
15.  Sears ED, Caverly TJ, Kullgren JT, Fagerlin A, Zikmund-Fisher BJ, Prenovost K, et al. Clinicians’ 
Perceptions of Barriers to Avoiding Inappropriate Imaging for Low Back Pain—Knowing Is Not 
Enough. JAMA Intern Med [Internet]. 2016 Oct 17 [cited 2016 Oct 18]; Available from: 
http://archinte.jamanetwork.com/article.aspx?doi=10.1001/jamainternmed.2016.6364 

 
34 
16.  Risha Gidwani D, Patricia Sinnott P, Tigran Avoundjian MPH, Jeanie Lo MPH, Asch SM, Mph M, et al. 
Inappropriate Ordering of Lumbar Spine Magnetic Resonance Imaging: Are Providers Choosing 
Wisely? Am J Manag Care [Internet]. 2016 Feb 2 [cited 2016 Oct 18];22(February 2016 2). Available 
from: http://www.ajmc.com/journals/issue/2016/2016-vol22-n2/Inappropriate-Ordering-of-
Lumbar-Spine-Magnetic-Resonance-Imaging-Are-Providers-Choosing-Wisely/ 
17.  Jarvik JG, Gold LS, Comstock BA, Heagerty PJ, Rundell SD, Turner JA, et al. Association of early 
imaging for back pain with clinical outcomes in older adults. JAMA. 2015 Mar 17;313(11):1143–53.  
18.  Chou R, Fu R, Carrino JA, Deyo RA. Imaging strategies for low-back pain: systematic review and 
meta-analysis. Lancet Lond Engl. 2009 Feb 7;373(9662):463–72.  
19.  Jou J, Johnson PJ. Nondisclosure of Complementary and Alternative Medicine Use to Primary Care 
Physicians: Findings From the 2012 National Health Interview Survey. JAMA Intern Med [Internet]. 
2016 Mar 21 [cited 2016 Mar 28]; Available from: 
http://archinte.jamanetwork.com/article.aspx?doi=10.1001/jamainternmed.2015.8593 
20.  Hayden JA, Van Tulder MW, Malmivaara AV, Koes BW. Meta-analysis: exercise therapy for 
nonspecific low back pain. Ann Intern Med. 2005;142(9):765–75.  
21.  Van Tulder M, Malmivaara A, Esmail R, Koes B. Exercise therapy for low back pain: a systematic 
review within the framework of the cochrane collaboration back review group. Spine. 
2000;25(21):2784–96.  
22.  Rencher NR. The Acute Effects of Whole-Body Corrective Exercise on Postural Alignment. 2014 
[cited 2016 Mar 28]; Available from: http://scholarsarchive.byu.edu/etd/4379/ 
23.  Abenhaim L, Rossignol M, Valat JP, Nordin M, Avouac B, Blotman F, et al. The role of activity in the 
therapeutic management of back pain. Report of the International Paris Task Force on Back Pain. 
Spine. 2000 Feb 15;25(4 Suppl):1S – 33S.  
24.  Hay EM, Dunn KM, Hill JC, Lewis M, Mason EE, Konstantinou K, et al. A randomised clinical trial of 
subgrouping and targeted treatment for low back pain compared with best current care. The STarT 
Back Trial Study Protocol. BMC Musculoskelet Disord. 2008;9(1):58.  
25.  Foster NE, Mullis R, Young J, Doyle C, Lewis M, Whitehurst D, et al. IMPaCT Back study protocol. 
Implementation of subgrouping for targeted treatment systems for low back pain patients in 
primary care: a prospective population-based sequential comparison. BMC Musculoskelet Disord. 
2010 Aug 20;11:186.  
26.  Hill JC, Whitehurst DG, Lewis M, Bryan S, Dunn KM, Foster NE, et al. Comparison of stratified 
primary care management for low back pain with current best practice (STarT Back): a randomised 
controlled trial. The Lancet. 2011 Oct;378(9802):1560–71.  
27.  Sanders T, Foster NE, Ong BN. Perceptions of general practitioners towards the use of a new system 
for treating back pain: a qualitative interview study. BMC Med. 2011 May 9;9:49.  
28.  Beneciuk JM, Bishop MD, Fritz JM, Robinson ME, Asal NR, Nisenzon AN, et al. The STarT back 
screening tool and individual psychological measures: evaluation of prognostic capabilities for low 

 
35 
back pain clinical outcomes in outpatient physical therapy settings. Phys Ther. 2013 Mar;93(3):321–
33.  
29.  The Back Book. TSO; 2002. 21 p.  
30.  Egoscue - Stop Chronic Pain [Internet]. [cited 2016 Nov 16]. Available from: 
http://www.egoscue.com/ 
31.  Lorig K, Chastain RL, Ung E, Shoor S, Holman HR. Development and evaluation of a scale to measure 
perceived self-efficacy in people with arthritis. Arthritis Rheum. 1989;32(1):37–44.  
32.  Fritz JM, Kim M, Magel JS, Asche CV. Cost-Effectiveness of Primary Care Management with or 
Without Early Physical Therapy for Acute Low Back Pain: Economic Evaluation of a Randomized 
Clinical Trial. Spine. 2016 Jun 6;  
33.  Goossens ME, Rutten-van Mölken MP, Vlaeyen JW, van der Linden SM. The cost diary: a method to 
measure direct and indirect costs in cost-effectiveness research. J Clin Epidemiol. 2000 
Jul;53(7):688–95.  
34.  Chou R, Huffman LH. Medications for acute and chronic low back pain: a review of the evidence for 
an American Pain Society/American College of Physicians clinical practice guideline. Ann Intern Med. 
2007;147(7):505–14.  
35.  Fairbank JC, Pynsent PB. The Oswestry Disability Index. Spine. 2000 Nov 15;25(22):2940–52; 
discussion 2952.  
36.  Deyo RA, Battie M, Beurskens AJ, Bombardier C, Croft P, Koes B, et al. Outcome measures for low 
back pain research. A proposal for standardized use. Spine. 1998 Sep 15;23(18):2003–13.  
37.  Mehra A, Baker D, Disney S, Pynsent P. Oswestry Disability Index Scoring Made Easy. Ann R Coll Surg 
Engl. 2008 Sep;90(6):497–9.  
38.  Kankaanpää M, Taimela S, Webber CL, Airaksinen O, Hänninen O. Lumbar paraspinal muscle 
fatigability in repetitive isoinertial loading: EMG spectral indices, Borg scale and endurance time. Eur 
J Appl Physiol. 1997;76(3):236–42.  
39.  Kankaanpää M, Taimela S, Laaksonen D, Hänninen O, Airaksinen O. Back and hip extensor 
fatigability in chronic low back pain patients and controls. Arch Phys Med Rehabil. 1998 
Apr;79(4):412–7.  
40.  Tonosu J, Takeshita K, Hara N, Matsudaira K, Kato S, Masuda K, et al. The normative score and the 
cut-off value of the Oswestry Disability Index (ODI). Eur Spine J. 2012 Aug;21(8):1596–602.  
41.  Fritz JM, Magel JS, McFadden M, Asche C, Thackeray A, Meier W, et al. Early Physical Therapy vs 
Usual Care in Patients With Recent-Onset Low Back Pain: A Randomized Clinical Trial. JAMA. 2015 
Oct 13;314(14):1459.  
42.  Group TE. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy. 
1990;16(3):199–208.  

 
36 
43.  Brooks R. EuroQol: the current state of play. Health Policy Amst Neth. 1996 Jul;37(1):53–72.  
44.  Johnson JA, Pickard AS. Comparison of the EQ-5D and SF-12 health surveys in a general population 
survey in Alberta, Canada. Med Care. 2000 Jan;38(1):115–21.  
45.  Soer R, Reneman MF, Speijer BLGN, Coppes MH, Vroomen PCAJ. Clinimetric properties of the 
EuroQol-5D in patients with chronic low back pain. Spine J. 2012 Nov;12(11):1035–9.  
46.  Whynes DK, McCahon RA, Ravenscroft A, Hodgkinson V, Evley R, Hardman JG. Responsiveness of the 
EQ-5D Health-Related Quality-of-Life Instrument in Assessing Low Back Pain. Value Health. 2013 
Jan;16(1):124–32.  
47.  Walters SJ, Brazier JE. Comparison of the minimally important difference for two health state utility 
measures: EQ-5D and SF-6D. Qual Life Res Int J Qual Life Asp Treat Care Rehabil. 2005 
Aug;14(6):1523–32.  
48.  Richardson G, Manca A. Calculation of quality adjusted life years in the published literature: a 
review of methodology and transparency. Health Econ. 2004 Dec;13(12):1203–10.  
49.  van den Heuvel SG, Geuskens GA, Hooftman WE, Koppes LLJ, van den Bossche SNJ. Productivity loss 
at work; health-related and work-related factors. J Occup Rehabil. 2010 Sep;20(3):331–9.  
50.  Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research Electronic Data Capture 
(REDCap) - A metadata-driven methodology and workflow process for providing translational 
research informatics support. J Biomed Inform. 2009 Apr;42(2):377–81.  
51.  Li P, Stuart EA, Allison DB. Multiple imputation: A flexible tool for handling missing data. JAMA. 2015 
Nov 10;314(18):1966–7.  
52.  Luo X, Pietrobon R, Sun SX, Liu GG, Hey L. Estimates and patterns of direct health care expenditures 
among individuals with back pain in the United States. Spine. 2004 Jan 1;29(1):79–86.  
53.  Veroff DR, Ochoa-Arvelo T, Venator B. A randomized study of telephonic care support in populations 
at risk for musculoskeletal preference-sensitive surgeries. BMC Med Inform Decis Mak. 2013;13:21.  
54.  Dagenais S, Caro J, Haldeman S. A systematic review of low back pain cost of illness studies in the 
United States and internationally. Spine J Off J North Am Spine Soc. 2008 Feb;8(1):8–20.  
Additional References 
1. Centers for Medicare & Medicaid Services - Physician Fee Schedule Look-Up Tool. 
2. Kaiser Family Foundation: Hospital Adjusted Expenses per Inpatient Day. 
3. Mirel LB and Carper K. Trends in Health Care Expenditures for the Elderly, Age 65 and Older: 2001, 
2006, and 2011 Statistical Brief (Medical Expenditure Panel Survey (US)) Rockville (MD): Agency for 
Healthcare Research and Quality (US); 2001. 
4. GoodRx. 
5.van Hout B, Janssen MF, Feng YS, Kohlmann T, Busschbach J, Golicki D, Lloyd A, Scalone L, Kind P and 
Pickard AS. Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets. Value in 
health : the journal of the International Society for Pharmacoeconomics and Outcomes Research. 
2012;15:708-15. 

 
37