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. Author manuscript; available in PMC: 2018 May 1.
Published in final edited form as: J Opioid Manag. 2017 May-Jun;13(3):169–181. doi: 10.5055/jom.2017.0384

Cost of Opioid-Treated Chronic Low Back Pain: Findings from a Pilot Randomized Controlled Trial of Mindfulness Meditation-Based Intervention

Aleksandra E Zgierska 1,, James Ircink 2, Cindy A Burzinski 3, Marlon P Mundt 4
PMCID: PMC5836724  NIHMSID: NIHMS934607  PMID: 28829518

Abstract

Objective

Opioid-treated chronic low back pain (CLBP) is debilitating, costly and often refractory to existing treatments. This secondary analysis aims to pilot-test the hypothesis that mindfulness meditation (MM) can reduce economic burden related to opioid-treated CLBP.

Design

26-week unblinded pilot randomized controlled trial, comparing MM, adjunctive to usual-care, to usual care alone.

Setting

Outpatient

Participants

Thirty-five adults with opioid-treated CLBP (≥ 30 morphine-equivalent mg/day) for 3+ months enrolled; none withdrew.

Intervention

8 weekly therapist-led MM sessions and at-home practice.

Outcome Measures

Costs related to self-reported healthcare utilization, medication use (direct costs), lost productivity (indirect costs), and total costs (direct+indirect costs) were calculated for 6-month pre- and post-enrollment periods and compared within and between the groups.

Results

Participants (21 MM; 14 control) were 20% men, age 51.8 ± 9.7 years, with severe disability, opioid dose of 148.3 ± 129.2 morphine-equivalent mg/day, and individual annual income of $18,291 ± $19,345. At baseline, total costs were estimated at $15,497 ± 13,677 (direct: $10,635 ± 9,897; indirect: $4,862 ± 7,298) per participant. Although MM group participants, compared to controls, reduced their pain severity ratings and pain sensitivity to heat-stimuli (p<0.05), no statistically significant within-group changes or between-group differences in direct and indirect costs were noted.

Conclusions

Adults with opioid-treated CLBP experience a high burden of disability despite the high costs of treatment. Although this pilot study did not show a statistically significant impact of MM on costs related to opioid-treated CLBP, MM can improve clinical outcomes and should be assessed in a larger trial with long-term follow-up.

Keywords: mindfulness meditation, chronic low back pain, opioids, economic evaluation

INTRODUCTION

The U.S. Healthcare System is the most expensive in the world.1 Americans are also the highest consumers of prescription medications.2 Despite high spending, the U.S. was ranked last among 11 industrialized countries when comparing quality, access, efficiency of healthcare, and health indicators.1

Low back pain (LBP) affects 80% of U.S. adults in their lifetime.3 Chronic LBP (CLBP) affects 15-20% of LBP sufferers,4 yet it incurs 90% of total LBP-related costs estimated at $84.1-$624.8 billion annually.46 A 2008 analysis of a nationally-representative insurance claims database showed greater annual direct medical costs of patients with CLBP ($8,386) compared to non-CLBP controls ($3,607).3 Indirect costs due to lost productivity are estimated to be even more substantial.5,7

Severe refractory CLBP is the most common chronic non-cancer pain treated with long-term opioids.8 Opioid therapy is controversial in CLBP and associated with dose-dependent harms, including hyperalgesia, addiction, and overdose death.810 Providing patients with new, cost-effective and safe therapy options for opioid-treated CLBP could lead to an increase in value of medical spending that the U.S. desperately needs and decrease patients’ reliance on opioids.

Mindfulness meditation (MM) has been used to treat chronic pain for decades and recent studies support its potential for opioid-treated chronic pain.1116 Our 26-week pilot randomized-controlled trial (RCT, N=35) showed that MM was associated with reduced pain severity (p<0.05) and decreased sensitivity to heat-pain stimuli (p<0.05) among adults with disabling CLBP treated, on average, with a high-dose opioid therapy.15 In addition, the MM intervention was found to be safe, feasible, and highly acceptable.16

Little is known about MM’s effects on costs related to this health condition. Therefore, we performed a secondary cost-analysis of data from our pilot RCT, which focused on the acceptability, feasibility and efficacy assessment of the MM intervention.15,16 We hypothesized that MM, in addition to safely improving health outcomes, can also reduce costs in opioid-treated CLBP.

METHODS

Design

Data were derived from a 26-week pilot parallel-arm RCT of MM intervention, adjunctive to usual care (MM group, N=21), compared to usual care alone (wait-list control, N=14) among adults with opioid-treated CLBP. The study was approved by the Institutional Review Board and registered with ClinicalTrials.gov. Details of the methods, and efficacy and feasibility results were published elsewhere.1517 This paper focuses on secondary cost-analysis findings.

Participants

Potential participants were recruited from several local health systems. They were 21 years or older, diagnosed with CLBP and treated with opioids ≥30 mg/day of morphine-equivalent dosage (MED) for 3+ months.15,17 All 35 enrolled participants completed baseline and at least one follow-up assessment (34 completed an 8 week; 33 completed a 26-week follow-up), providing data for the analysis.15 No participant withdrew from the study. The CONSORT study flow diagram is presented elsewhere.15

As previously published, participants were 51.8±9.7 years old (20% male, 20% non-Caucasian) and reported severe disability (66.7±11.4%; Oswestry Disability Index1820), averaged pain severity of 5.8±1.4 (0-10 rating scale; Brief Pain Inventory21) and high daily opioid dose (148.3±129.2 mg/day MED).15,17 They earned $18,291± $19,345 annually, with 34% reporting an individual income greater than $15,000 and 77% receiving social security/disability benefits.17 Over the 26-week follow-up period, the MM group participants, compared to the controls, reported a reduction in pain severity ratings (p=0.045) and showed a decreased sensitivity to noxious heat stimuli (p<0.05).15

Setting and Procedures

Sample size for this pilot study was convenience-based. Participants were enrolled, completed baseline assessments, and then were randomized.15 Randomization envelopes were prepared by the study statistician to account for up to 50 enrolled participants (1:1 randomization ratio); since we enrolled 35 participants within a designated recruitment/enrollment period, this led to unequal group sizes. Follow-up assessments occurred at 8 weeks (post-intervention; F1) and 26-weeks (F2) post-entry.

MM Intervention

All participants continued usual care for opioid-treated CLBP22 through their regular providers. In addition, the MM group received the MM intervention (eight weekly 2-hour group sessions, led by two trained and experienced therapists, and at-home MM practice at least 6 days/week during the whole study), described elsewhere.15,16 The MM intervention was patterned after established curricula2325 and tailored to meet the psychophysical needs of patients with opioid-treated CLBP.

Outcome Measures

All measures relied on self-report.

Healthcare utilization and productivity loss data were collected with a study team-developed survey based on expert recommendations.26 The survey inquired about the “past 6 months” at baseline, the “past 8 weeks” at F1, and the “past 18 weeks” at F2, yielding 6 months of pre-enrollment and 6 months of post-enrollment data. Healthcare utilization was measured by the number of visits, regardless of the reason, to the emergency department (ED), urgent care, primary care, and outpatient mental health care, and the number of days of hospitalization (overnight stay). Productivity loss was quantified as the number of missed work days and the number of missed school/housework days (missed household chores and responsibilities) due to being sick, injured or not feeling well.

Medication use (average daily use, past 30 days) was measured by the study team-developed medication survey, and verified against the medication bottle information.15,17 The Timeline Followback (TLFB) method27,28 was used to collect data on the daily use of prescription-based opioids for the “past 28 days” to enable calculation of a MED/day.

Total costs associated with opioid-treated CLBP were defined as a sum of direct costs (healthcare utilization, medications) and indirect costs (lost productivity from missed work and/or school/housework) in the prior 6 months.

Healthcare Utilization Costs

Hospitalization, ED, and urgent care visit costs were estimated using the state Price Point System-data for 2013.29 Average daily hospital inpatient charge ($1,722) was based on an “Other back/neck disorders, fractures, and injuries, no surgery” diagnosis.30 ED visit cost ($945) was based on “Neck/Back Sprains & Strains” and “Spinal Disorders” diagnoses.31 Hospital-based urgent care charge ($257) estimated the cost of using urgent care.31,32

Medication Costs

The average quantity of each medication taken by participants (past month) was estimated from the medication survey for non-opioid medications and the TLFB for opioids. Medication use and related costs were prorated from “past month” to “past 6 months” at baseline and proportionately during the follow-up to estimate medication costs for 6 months pre- and 6 months post-enrollment.

Medications were categorized as: A) opioids; B) non-opioid analgesics and medications with pain-modulating properties; C) bowel regimen medications; and D) other medications, including vitamins, herbal preparations and other supplements, and topicals (Table 1).

Table 1.

Baseline (6 months pre-enrollment) healthcare utilization, medication use and productivity loss reported by the study participants (N=35).

Variable (N=35)

Healthcare Utilization Number, # Cost, USD

Outpatient Visits
  Primary Care
    Mean (SD) 7.1 (9.1) $1,226 (1,572)
    Median (25–75%) 4.0 (2.0–6.0) $692 (346–1,038)
  Urgent Care
    Mean (SD) 0.2 (0.5) $59 (141)
    Median (25–75%) 0.0 (0.0-0.0) $0 (0-0)
  Mental Health
    Mean (SD) 2.9 (5.2) $391 (704)
    Median (25–75%) 0.0 (0.0–4.0) $0 (0–541)
Total Outpatient Visits
    Mean (SD) 10.2 (11.1) $1,675 (1,806)
    Median (25–75%) 6.0 (4.0–12.0) $1,122 (692–2,076)

Emergency Department Visits
    Mean (SD) 0.5 (1.1) $459 (1,060)
    Median (25–75%) 0.0 (0.0–1.0) $0 (0–945)

Days of Hospitalization
    Mean (SD) 1.2 (3.6) $2,075 (6,246)
    Median (25–75%) 0.0 (0.0-0.0) $0 (0-0)

Total Healthcare Utilization
    Mean (SD) ---- $4,211 (6,472)
    Median (25–75%) $1,640 (865–4,672)

Medication Use Number, # Cost, USD

Opioid Medications
    Mean (SD) 1.8 (0.7) $1,254 (1,492)
    Median (25–75%) 2.0 (1.0–2.0) $571 (338–2,012)

Non-Opioid Analgesicsa and Pain-Modulating Medicationsb
    Mean (SD) 2.9 (1.7) $1,859 (2,489)
    Median (25–75%) 3.0 (1.0–4.0) $373 (108–3,005)

Bowel Regimen Medications
    Mean (SD) 0.5 (0.8) $67 (180)
    Median (25–75%) 0.0 (0.0–1.0) $0 (0–35)

Other Medicationsc
    Mean (SD) 7.9 (5.1) $3,243 (5,284)
    Median (25–75%) 8.0 (4.0–12.0) $1,397 (338–3,436)

Total Medication Use
    Mean (SD) 13.1 (6.4) $6,423 (6,989)
    Median (25–75%) 12.0 (8.0–19.0) $4,199 (1,241–8,511)

Productivity Loss Number, # Cost, USD

Days of Missed Work
    Mean (SD) 12.3 (42.4) $1,994 (6,905)
    Median (25–75%) 0.0 (0.0-0.0) S0 (0-0)

Days of Missed School/Housework
    Mean (SD) 49.4 (64.8) $2,868 (3,761)
    Median (25–75%) 18.0 (0.0–90.0) $1,044 (0–5,220)

Total Direct (Healthcare Utilization, Medications) and Indirect (Productivity Loss) Costs

Total Direct Costs
    Mean (SD) $10,635 (9,897)
    Median (25–75%) $7,426 (3,350–13,421)

Total Indirect Costs
    Mean (SD) $4,862 (7,298)
    Median (25–75%) $1,740 (0–6,960)

Total Direct+Indirect Costs
    Mean (SD) $15,497 (13,677)
    Median (25–75%) $10,851 (5,128–24,349)

Abbreviations: USD, United States Dollar

a

acetaminophen, nonsteroidal anti-inflammatory drugs (NSAIDs).

b

GABA analogs, skeletal muscle relaxants, benzodiazepines, tricyclic antidepressants, serotonin and norepinephrine reuptake inhibitors (SNRIs), anti-epileptics and other medications reported for pain relief.

c

All other medications used for various medical conditions (e.g., hypertension, diabetes, depression), including over the counter ones (e.g., vitamins, supplements).

Price quotes for a monthly supply of each specific medication (brand-name versus generic) were obtained in July and August 2014 using the following sources and protocol: a) primary source: www.rxpricequotes.com; using the local zip code;33 b) secondary source: www.drugs.com;34 c) tertiary source: www.walgreens.com;35 d) quotes for medications with an unlisted price were obtained by calling the local Walgreens pharmacy. In addition, for non-prescription medications, the least expensive preparation was selected; when the exact pricing was not possible to calculate, a bottle size that best accommodated the participant’s monthly use was applied; the average of listed price ranges was used to estimate a monthly medication cost; and, if the calculation of the average monthly quantity yielded a fraction, this number was rounded up to the next whole number.

Productivity Loss

The cost associated with productivity loss was calculated by multiplying the number of missed work or school/housework days by the estimated cost of each lost-productivity day. Cost of a missed work day ($162.72) was based on a state-specific average daily wage, calculated by averaging the 2013 state-specific daily wages across all occupations listed by the U.S. Department of Labor Bureau of Labor Statistics.36 Cost of a missed school/housework day ($58) was estimated based on the assumption of an 8 hour day of productivity, valued at the 2013 federal minimum wage of $7.25/hour.37

Statistical Analyses

IBM SPSS statistics 22 software was used for analyses. The Related-Samples Wilcoxon Signed Rank Test evaluated within-group changes over time. The Independent Samples Mann-Whitney U Test evaluated between-group differences at each time point and differences in longitudinal change in a given variable. Cohen’s d effect size evaluated the magnitude of between-group differences in longitudinal change.38 Statistical significance was set at a two-tailed p<0.05. Results were presented as a mean (± standard deviation, SD) unless otherwise noted.

RESULTS

Baseline Characteristics

Direct and Indirect Costs (Table 1)

Pre-enrollment (past 6 months), participants reported 10.2±11.1 outpatient visits, missed 12.3±42.4 days of work and 49.4±64.8 days of school/housework. They used 1.8±0.7 different opioid and 2.9±1.7 non-opioid medications for pain relief, and 7.9±5.1 medications for conditions other than pain or constipation. The average direct and indirect costs totaled $15,497±13,677. Medication costs comprised 60% of direct costs, exceeding healthcare utilization cost, for which hospitalization yielded the highest cost. Primary care visits were the second most costly service ($1,226±1,572). Indirect costs comprised 31% of total costs. Participants were estimated to sustain a loss of $1,994±6,905 in work and $2,868±3,761 in school/housework related costs. No statistically significant between-group differences were noted in these baseline characteristics (p>0.05).

Longitudinal Change: from Baseline (6 Months Pre-enrollment) to Follow-up (6 Months Post-enrollment)

Direct and Indirect Costs

Compared to baseline, both groups increased the number of medications used for conditions other than pain or constipation, and the total number of medications (p<0.05; Table 2). Within-group changes in healthcare utilization and productivity were not statistically significant (p≥0.05; Table 2). However, the MM group trended (p=0.068) toward reduced number of missed work days (Table 2) and related cost (Table 3), and controls showed a tendency (p=0.083) toward increased number of prescribed opioid medications (Table 2).

Table 2.

Healthcare utilization, medication use and productivity loss among the study participants (N=35) by group status at baseline (6 months pre-enrollment) and 26 week follow-up (6 months post-enrollment).

MM group (N=21) Control group (N=14)

Variable Baseline 26 weeks p valuea Baseline 26 weeks p valuea p valueb Effect size Cohen’s d
(95% CI)c

Healthcare Utilization

Number of Outpatient Visits:
    Primary Care
      Mean (SD) 7.1 (9.9) 8.0 (7.1) 0.230 7.1 (8.1) 9.3 (13.2) 0.279 0.606 0.14
      Median (25–75%) 5.0 (3.5–5.5) 6.5 (2.9–10.4) 2.5 (2.0–11.3) 5.9 (1.5–10.8) (−0.54; 0.82)
    Urgent Care
      Mean (SD) 0.2 (0.5) 0.3 (0.6) 0.677 0.2 (0.6) 0.3 (0.6) 0.715 0.934 0.03
      Median (25–75%) 0.0 (0.0–0.0) 0.0 (0.0–0.4) 0.0 (0.0–0.0) 0.0 (0.0–0.2) (−0.65; 0.70)
    Mental Health
      Mean (SD) 2.3 (4.6) 2.1 (4.0) 0.612 3.8 (6.1) 2.7 (4.1) 0.779 0.654 0.19
      Median (25–75%) 0.0 (0.0–2.0) 0.0 (0.0–2.4) 1.0 (0.0–6.0) 0.0 (0.0–6.1) (−0.87; 0.49)
Total Number of Outpatient Visits:
      Mean (SD) 9.6 (12.5) 10.3 (10.2) 0.357 11.1 (8.8) 12.3 (14.0) 0.975 0.987 0.05
      Median (25–75%) 6.0 (3.5–11.5) 8.4 (2.9–13.4) 9.0 (3.8–19.5) 7.7 (2.1–19.2) (−0.63; 0.72)

Number of ED Visits
  Mean (SD) 0.7 (1.4) 0.7 (1.1) 0.381 0.2 (0.6) 0.4 (1.0) 0.686 0.342 0.23
  Median (25–75%) 0.0 (0.0–1.0) 0.0 (0.0–0.9) 0.0 (0.0–0.0) 0.0 (0.0–0.2) (−0.45; 0.91)

Number of Days of Hospitalization
  Mean (SD) 1.6 (4.5) 0.6 (1.4) 0.463 0.6 (1.6) 0.1 (0.2) 0.285 0.538 0.11
  Median (25–75%) 0.0 (0.0–0.0) 0.0 (0.0–0.0) 0.0 (0.0–0.0) 0.0 (0.0–0.0) (−0.56; 0.79)

Medication Use

Number of Opioid Medications
  Mean (SD) 1.9 (0.7) 2.0 (0.9) 0.414 1.6 (0.7) 1.9 (0.9) 0.083 0.702 0.24
  Median (25–75%) 2.0 (1.0–2.0) 2.0 (1.0–2.5) 1.5 (1.0–2.0) 2.0 (1.0–2.3) (−0.44; 0.92)

Number of Non-Opioid Analgesicsd and Pain-Modulating Medicationse
  Mean (SD) 3.0 (1.6) 3.3 (1.7) 0.163 2.8 (1.8) 2.9 (1.9) 0.366 0.454 0.18
  Median (25–75%) 3.0 (2.0–4.0) 3.0 (2.0–4.5) 2.5 (1.0–5.0) 2.5 (1.0–5.0) (−0.85; 0.50)

Number of Bowel Regimen Medications
  Mean (SD) 0.5 (0.8) 0.6 (1.0) 0.083 0.6 (0.9) 0.5 (0.9) 0.157 0.727 0.79
  Median (25–75%) 0.0 (0.0–1.0) 0.0 (0.0–1.0) 0.0 (0.0–1.0) 0.0 (0.0–1.0) (−1.49; −0.09)

Number of Other Medicationsf
  Mean (SD) 8.1 (5.3) 10.3 (6.7) 0.009 7.4 (4.9) 9.9 (7.4) 0.008 0.881 0.10
  Median (25–75%) 8.0 (4.5–12.0) 11.0 (4.0–15.0) 7.0 (2.8–12.3) 9.0 (2.8–16.3) (−0.58; 0.78)

Total Number of All Medications
  Mean (SD) 13.5 (6.5) 16.2 (8.2) 0.006 12.5 (6.3) 15.2 (8.9) 0.004 0.654 0.00
  Median (25%–75%) 12.0 (8.5–18.5) 16.0 (9.5–22.0) 13.0 (5.8–19.0) 15.5 (8.3–20.3) (−0.68; 0.68)

Productivity Loss

Days of Missed Work
  Mean (SD) 19.6 (53.9) 0.5 (1.3) 0.068 1.3 (4.8) 0.3 (0.6) 1.000 0.987 0.43
  Median (25–75%) 0.0 (0.0–3.5) 0.0 (0.0–0.0) 0.0 (0.0–0.0) 0.0 (0.0–0.2) (−0.26; 1.11)

Days of Missed School/Housework
  Mean (SD) 39.6 (57.7) 28.1 (37.6) 0.654 64.2 (74.1) 34.9 (43.8) 0.152 0.829 0.25
  Median (25–75%) 14.0 (0.0–61.0) 8.3 (2.5–48.2) 25.0 (0.0–135.0) 14.0 (1.5–67.8) (−0.93; 0.43)

Abbreviations: ED: Emergency Department

a

Within group comparison (post-enrollment versus pre-enrollment): Related-Samples Wilcoxon Signed Rank Test

b

Between group comparison at the 26 week follow-up: Independent Samples Mann-Whitney U Test

c

Between group comparison of difference scores (post-enrollment versus pre-enrollment): Cohen’s d, 95% Confidence Interval

d

acetaminophen, nonsteroidal anti-inflammatory drugs (NSAIDs)

e

GABA analogs, skeletal muscle relaxants, benzodiazepines, tricyclic antidepressants, serotonin and norepinephrine reuptake inhibitors (SNRIs), anti-epileptics, and other medications reported for pain relief

f

Other medications used for various medical conditions (e.g., hypertension, diabetes, depression), including over the counter ones (e.g., vitamins, supplements)

Table 3.

Costs (USD) related to healthcare utilization, medication use and productivity loss among the study participants by the group status at baseline (6 months pre-enrollment) and 26 week follow-up (6 months post-enrollment).

MM group (N=21) Control group (N=14)

Variable Baseline 26 weeks p
valuea
Baseline 26 weeks p
valuea
p
valueb
Effect size Cohen's d
(95% CI)c

Costs Related to Healthcare Utilization

Outpatient Visits
    Primary Care
      Mean (SD) 1,228 (1,706) 1,377 (1,220) 0.230 1,223 (1,410) 1,616 (2,286) 0.279 0.606 0.14
      Median (25–75%) 865 (606–952) 1,130 (509–1,799) 433 (346–1,946) 1,022 (264–1,862) (−0.54; 0.82)
    Urgent Care
      Mean (SD) 61 (139) 71 (155) 0.677 55 (149) 70 (150) 0.715 0.934 0.03
      Median (25–75%) 0 (0-0) 0 (0–94) 0 (0-0) 0 (0–43) (−0.65; 0.70)
    Mental Health
      Mean (SD) 309 (618) 283 (535) 0.612 512 (826) 362 (559) 0.779 0.654 0.20
      Median (25–75%) 0.0 (0.0–271) 0 (0–320) 135 (0–812) 0 (0–824) (−0.88; 0.48)
Total Costs Related to Outpatient Visits:
      Mean (SD) 1,598 (2,048) 1,730 (1,695) 0.375 1,791 (1,435) 2,049 (2,424) 0.975 1.000 0.07
      Median (25–75%) 963 (606–1,859) 1,418 (509–2,251) 1,256 (694–3,231) 1,238 (369–2,957) (−0.61; 0.74)

ED Visits
  Mean (SD) 630 (1,280) 615 (1,074) 0.381 203 (547) 415 (988) 0.686 0.342 0.23
  Median (25–75%) 0 (0–945) 0 (0–831) 0 (0-0) 0 (0–186) (−0.45; 0.91)

Hospitalization
  Mean (SD) 2,717 (7,744) 973 (2,392) 0.463 1,112 (2,846) 97 (364) 0.285 0.538 0.11
  Median (25–75%) 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-0) (−0.56; 0.79)

Total Healthcare Utilization
  Mean (SD) 4,945 (7,880) 3,318 (3,446) 0.639 3,110 (3,441) 2,562 (3,176) 0.875 0.474 0.16
  Median (25–75%) 1,640 (994–4,737) 1,968 (509–5,059) 1,654 (775–4,755) 1,637 (369–2,957) (−0.52; 0.83)

Costs Related to Medication Use

Opioid Medications
  Mean (SD) 1,356 (1,545) 1,253 (1,558) 0.149 1,102 (1,451) 1,487 (1,987) 0.510 0.727 0.69
  Median (25–75%) 579 (366–2,129) 585 (278–1,870) 499 (196–1,194) 517 (194–2,572) (−0.00; 1.39)

Non-Opioid Analgesicsd and Pain-Modulating Medicationse
  Mean (SD) 1,711 (1,794) 1,878 (1,923) 0.614 2,079 (3,342) 1,500 (2,207) 0.140 0.175 0.64
  Median (25–75%) 614 (160–3149) 658 (150–3,412) 308 (59–3,212) 241 (60–2,518) (−1.34; 0.05)

Bowel Regimen Medications
  Mean (SD) 89 (223) 104 (291) 0.678 34 (74) 26 (67) 0.753 0.474 0.35
  Median (25–75%) 0 (0–84) 0 (0–60) 0 (0–21) 0 (0–21) (−1.03; 0.34)

Other Medicationsf
  Mean (SD) 2,806 (4,501) 3,006 (4,888) 0.421 3,900 (6,409) 4,136 (6,544) 0.470 0.702 0.03
  Median (25–75%) 932 (321–3,412) 1,025 (277–4,088) 1,985 (311–3,991) 2,072 (342–4,466) (−0.65; 0.70)

Total Medication Use Costs
  Mean (SD) 5,962 (6,365) 6,241 (6,844) 0.794 7,115 (8,036) 7,149 (7,710) 0.826 0.960 0.12
  Median (25–75%) 4,056 (2,030–7,348) 4,732 (2,293–6,572) 4,342 (964–12,249) 4,155 (925–10,849) (−0.80; 0.56)

Costs Related to Productivity Loss

Days of Missed Work
  Mean (SD) 3,185 (8,772) 84 (210) 0.068 209 (783) 48 (99) 1.000 0.987 0.43
  Median (25–75%) 0 (0–570) 0 (0-0) 0 (0-0) 0 (0–34) (−0.26; 1.11)

Days of Missed School/Housework
  Mean (SD) 2,297 (3,344) 1,628 (2,183) 0.654 3,724 (4,297) 2,026 (2,541) 0.152 0.829 0.25
  Median (25–75%) 812 (0–3,538) 482 (146–2,797) 1,450 (0–7,830) 814 (85–3,932) (−0.93; 0.43)

Total Direct (Healthcare Utilization, Medications) and Indirect (Productivity Loss) Costs

Total Direct Costs
  Mean (SD) 10,907 (10,581) 9,559 (7,998) 0.986 10,226 (9,145) 9,711 (9,426) 0.594 0.678 0.12
  Median (25–75%) 6,868 (4,859–11,846) 8294 (3,148–13,517) 8,997 (1,908–17,148) 6,314 (1,130–20,459) (−0.80; 0.56)

Total Indirect Costs
  Mean (SD) 5,481 (8,826) 1,712 (2,140) 0.117 3,934 (4,234) 2,074 (2,511) 0.198 0.778 0.25
  Median (25–75%) 1,369 (0–7,453) 836 (148–2,797) 2,914 (0–7,830) 940 (200–3,932) (−0.43; 0.93)

Total Direct+Indirect Costs
  Mean (SD) 16,389 (15,459) 11,271 (8,368) 0.375 14,159 (10,880) 11,785 (9,960) 0.177 0.960 0.26
  Median (25–75%) 10,271 (5,880–28,919) 10,111 (5,655–14,871) 14,287 (3,229–24,847) 10,266 (1,699–23,563) (−0.94; 0.42)

Abbreviations: ED: Emergency Department; USD, United States Dollar

a

Within group comparison (post-enrollment versus pre-enrollment): Related-Samples Wilcoxon Signed Rank Test

b

Between group comparison at the 26 week follow-up: Independent Samples Mann-Whitney U Test

c

Between group comparison of difference scores (post-enrollment versus pre-enrollment): Cohen's d, 95% Confidence Interval

d

acetaminophen, nonsteroidal anti-inflammatory drugs (NSAIDs)

e

GABA analogs, skeletal muscle relaxants, benzodiazepines, tricyclic antidepressants, serotonin and norepinephrine reuptake inhibitors (SNRIs), anti-epileptics, and other medications reported for pain relief

f

Other medications used for various medical conditions (e.g., hypertension, diabetes, depression), including over the counter ones (e.g., vitamins, supplements)

Between-group comparison of longitudinal changes did not show statistically significant differences in healthcare utilization, medication use and productivity loss (Table 2), and the related costs (Table 3). Evaluation of the Cohen’s d effect size for between-group differences showed a promising yet statistically insignificant trend favoring the MM group over the control group at follow-up (Tables 2 & 3).

DISCUSSION

This secondary analysis showed that opioid-treated CLBP is associated with high direct and indirect costs, comprising 69% and 31% of total costs, respectively. Direct costs related to medications were high, constituting approximately 41% of all costs. Although our pilot RCT indicated that MM can reduce pain severity ratings and sensitivity to heat-pain stimuli,15 this analysis did not show a statistically significant impact of MM on direct or indirect costs.

A 2008 nationally-representative sample of patients with CLBP, the minority (37%) of whom were treated with any opioids, estimated total direct medical costs, including medications, to be $8,386±17,507 annually, a figure that included CLBP-related surgeries, other procedures, and imaging,3 not accounted for in the current RCT. If our estimated 6-month healthcare utilization cost of $4,211±6,472 was extrapolated to an annual figure, it would be comparable to that found in the above study;3 adding the cost of procedures and imaging to our calculations would likely result in costs surpassing the above estimates. The costs of medication and healthcare utilization are likely higher in opioid-treated populations with severe disability, such as the sample in the current study. Therefore, our study likely underestimates medical costs related to opioid-treated CLBP. In our study, the conservatively-estimated high cost related to opioid-treated CLBP is especially concerning because it was borne by a cohort whose income was, on average, low.

Although indirect costs were lower than direct costs in the current study, they were substantial and likely underestimated. Participants reported four times as many missed school/housework days than work days. The impact of school/housework loss likely translates to missed opportunities to engage in personal growth and positive activities with family or friends, and maintaining the household. The profound disease impact on work and school/housework was likely due to the severe level of disability reported by our participants, with only one-third (N=15) reporting paid employment.17 Since a missed day of work is cost-valued almost three times more than a missed day of school/housework, indirect costs depend heavily on employment characteristics; if more participants reported “being employed” but “unable to work,” costs related to productivity loss would have increased. Restricting the sample to only those who reported paid work, the number of missed work days and related cost would double in this subsample to 28.6±62.2.

Despite high healthcare utilization and medication use at baseline, participant disability was high, indicating a reduced health-related quality of life. During 26-week follow-up, the MM group, compared to controls, decreased their pain severity ratings (large effect size, d=0.86, p=0.045) and pain sensitivity to heat-pain stimuli (p<0.05),15 without increasing costs. Several trends may even suggest positive effects of the MM intervention on costs both for within-group changes (as suggested by p<0.1) and between-group differences (as suggested by effect size, Cohen’s d > 0.2).

Limitations

This analysis was based on self-reported data, as opposed to claims or health system-based utilization data, thus introducing a possibility of reporting bias. Further, parameters used to calculate healthcare utilization costs were based on combined back, neck or spinal disorder diagnoses that may or may not have included individuals with opioid-treated CLBP. In addition, medication costs were extrapolated from a single month of data at baseline and two months of data post-entry, so they may not represent actual 6-month medication costs. Furthermore, our results were derived from a severely-disabled sample, so they may not extend to a less-affected population. Finally, because data on SSDI-based income were not collected, the effects of the MM intervention on SSDI-related costs are unclear. We elected not to include costs of the MM intervention delivery in our analysis. The benefits of sustained MM practice can persist well beyond the duration of the initial training,39,40 thus off-setting over a longer period the single-fee associated with the MM course.

Small sample size and short follow-up duration could have impacted the findings of this pilot study, which was likely underpowered for the conducted cost analysis. An adequately-powered trial, with sample size calculation enabled by the current pilot, is needed to determine the long-term effects of MM in this population. Incorporation of claims data and collection of detailed information on income and wages would enable a more conclusive evaluation of MM’s impact on health-related cost in this patient population.

Conclusions

This study confirmed that adults with opioid-treated CLBP experience a high burden of disability despite high healthcare utilization, medication use and productivity loss related costs. Although MM shows promise for safely and effectively improving clinical outcomes in this population, this 26-week pilot RCT did not show a statistically significant impact of MM on costs related to opioid-treated CLBP, calling for further research in this area.

Acknowledgments

This work was supported by the K23AA017508 grant from the National Institutes of Health (NIH) National Institute on Alcohol Abuse and Alcoholism (NIAAA) and funds from the University of Wisconsin-Madison, awarded to AEZ, and the K01AA018410 from the NIH AAA awarded to MPM. The project was also supported by the University of Wisconsin-Madison School of Medicine and Public Health Shapiro Summer Research Program, with funding for JI from the Herman and Gwendolyn Shapiro Foundation, and by the Clinical and Translational Science Award (CTSA) program through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR000427. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Aleksandra Zgierska is engaged in research related to improving opioid prescribing, funded by the National Institutes of Health National Institute on Drug Abuse (1R34 DA036720-01A1) and by Pfizer (researcher-initiated unrestricted grants: 16213567, WI200706); these funding sources were not associated with the current study conduct or result write-up.

Footnotes

Conflict of Interest

Otherwise, the authors have no ownership interest or affiliation with any commercial or for-profit company or program that would create a conflict of interest.

The abbreviated findings described in this manuscript were presented as a poster and a brief oral presentation at the Wisconsin Research and Education Network (WREN) Annual Conference, Wisconsin Dells, WI, in November 2014.

Contributor Information

Aleksandra E. Zgierska, University of Wisconsin-Madison, School of Medicine and Public Health, Department of Family, Medicine and Community Health, 1100 Delaplaine Court, Madison, WI 53715, Aleksandra.Zgierska@fammed.wisc.edu, Office: 608 263 7882; Fax: 608 263 5813.

James Ircink, University of Wisconsin-Madison, School of Medicine and Public Health, Department of Family, Medicine and Community Health.

Cindy A. Burzinski, University of Wisconsin-Madison, School of Medicine and Public Health, Department of Family, Medicine and Community Health.

Marlon P. Mundt, University of Wisconsin-Madison, School of Medicine and Public Health, Department of Family, Medicine and Community Health, Department of Population Health Sciences.

References

  • 1.Davis K, Stremikis C, Schoen C, Squires D. Mirror, Mirror on the Wall, 2014 Update: How the U.S. Health Care System Compares Internationally. The Commonwealth Fund; Jun, 2014. [Accessed on Feb 23, 2016]. Available at: http://www.commonwealthfund.org/~/media/files/publications/fund-report/2014/jun/1755_davis_mirror_mirror_2014.pdf. [Google Scholar]
  • 2.Squires D, Anderson C. U.S. Health Care from a Global Perspective: Spending, Use of Services, Prices, and Health in 13 Countries. The Commonwealth Fund; Oct, 2015. [Accessed on Feb 23, 2016]. Available at: http://www.commonwealthfund.org/publications/issue-briefs/2015/oct/us-health-care-from-a-global-perspective. [PubMed] [Google Scholar]
  • 3.Gore M, Sadosky A, Stacey BR, Tai KS, Leslie D. The burden of chronic low back pain: clinical comorbidities, treatment patterns, and health care costs in usual care settings. Spine (Phila Pa 1976) 2012 May;37(11):E668–677. doi: 10.1097/BRS.0b013e318241e5de. [DOI] [PubMed] [Google Scholar]
  • 4.US Department of Health and Human Services. [Accessed on Oct 16, 2016];Healthy People 2020, 2020 Topics and Objectives: Arthritis, Osteoporosis, and Chronic Back Conditions. Updated 2016. Available at: http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=3.
  • 5.Dagenais S, Caro J, Haldeman S. A systematic review of low back pain cost of illness studies in the United States and internationally. Spine Journal. 2008 Jan-Feb;8(1):8–20. doi: 10.1016/j.spinee.2007.10.005. [DOI] [PubMed] [Google Scholar]
  • 6.Manek NJ, MacGregor AJ. Epidemiology of back disorders: prevalence, risk factors, and prognosis. Curr Opin Rheumatol. 2005 Mar;17(2):134–140. doi: 10.1097/01.bor.0000154215.08986.06. [DOI] [PubMed] [Google Scholar]
  • 7.Ricci JA, Stewart WF, Chee E, Leotta C, Foley K, Hochberg MC. Back pain exacerbations and lost productive time costs in United States workers. Spine. 2006 Dec 15;31(26):3052–3060. doi: 10.1097/01.brs.0000249521.61813.aa. [DOI] [PubMed] [Google Scholar]
  • 8.Dillie KS, Fleming MF, Mundt MP, French MT. Quality of life associated with daily opioid therapy in a primary care chronic pain sample. J Am Board Fam Med. 2008 Mar-Apr;21(2):108–117. doi: 10.3122/jabfm.2008.02.070144. [DOI] [PubMed] [Google Scholar]
  • 9.Dunn KM, Saunders KW, Rutter CM, et al. Opioid prescriptions for chronic pain and overdose: a cohort study. Ann Intern Med. 2010 Jan;152(2):85–92. doi: 10.1059/0003-4819-152-2-201001190-00006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Gomes T, Mamdani MM, Dhalla IA, Paterson JM, Juurlink DN. Opioid dose and drug-related mortality in patients with nonmalignant pain. Arch Intern Med. 2011 Apr 11;171(7):686–691. doi: 10.1001/archinternmed.2011.117. [DOI] [PubMed] [Google Scholar]
  • 11.Kabat-Zinn J. An outpatient program in behavioral medicine for chronic pain patients based on the practice of mindfulness meditation: theoretical considerations and preliminary results. Gen Hosp Psychiatry. 1982;4(1):33–47. doi: 10.1016/0163-8343(82)90026-3. [DOI] [PubMed] [Google Scholar]
  • 12.Patil SG. Effectiveness of mindfulness meditation (Vipassana) in the management of chronic low back pain. Indian J Anaesth. 2009 Apr;53(2):158–163. [PMC free article] [PubMed] [Google Scholar]
  • 13.Cramer H, Haller H, Lauche R, Dobos G. Mindfulness-based stress reduction for low back pain. A systematic review. BMC Complement Altern Med. 2012;12:162. doi: 10.1186/1472-6882-12-162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Garland EL, Manusov EG, Froeliger B, Kelly A, Williams JM, Howard MO. Mindfulness-Oriented Recovery Enhancement for Chronic Pain and Prescription Opioid Misuse: Results From an Early-Stage Randomized Controlled Trial. J Consult Clin Psychol. 2014;82(3):448–459. doi: 10.1037/a0035798. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zgierska AE, Burzinski CA, Cox J, et al. Mindfulness Meditation and Cognitive Behavioral Therapy Intervention Reduces Pain Severity and Sensitivity in Opioid-Treated Chronic Low Back Pain: Pilot Findings from a Randomized Controlled Trial. Pain Med. 2016 Mar 10; doi: 10.1093/pm/pnw006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Zgierska AE, Burzinski CA, Cox J, et al. Mindfulness Meditation-Based Intervention Is Feasible, Acceptable, and Safe for Chronic Low Back Pain Requiring Long-Term Daily Opioid Therapy. J Altern Complement Med. 2016;22(8):610–20. doi: 10.1089/acm.2015.0314. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Zgierska A, Wallace ML, Burzinski CA, Cox J, Backonja M. Pharmacological and toxicological profile of opioid-treated, chronic low back pain patients entering a mindfulness intervention randomized controlled trial. J Opioid Manag. 2014 Sep-Oct;10(5):323–335. doi: 10.5055/jom.2014.0222. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Fairbank JC, Couper J, Davies JB, O'Brien JP. The Oswestry low back pain disability questionnaire. Physiotherapy. 1980 Aug;66(8):271–273. [PubMed] [Google Scholar]
  • 19.Podichetty VK, Varley ES, Secic M. Role of patient-based health status outcome measurements in opioid management for low back pain. J Opioid Manag. 2008 May-Jun;4(3):153–162. doi: 10.5055/jom.2008.0020. [DOI] [PubMed] [Google Scholar]
  • 20.Walsh TL, Hanscom B, Lurie JD, Weinstein JN. Is a condition-specific instrument for patients with low back pain/leg symptoms really necessary? The responsiveness of the Oswestry Disability Index, MODEMS, and the SF-36. Spine (Phila Pa 1976) 2003 Mar 15;28(6):607–615. doi: 10.1097/01.BRS.0000050654.97387.DF. [DOI] [PubMed] [Google Scholar]
  • 21.Von Korff M, Jensen MP, Karoly P. Assessing global pain severity by self-report in clinical and health services research. Spine (Phila Pa 1976) 2000 Dec 15;25(24):3140–3151. doi: 10.1097/00007632-200012150-00009. [DOI] [PubMed] [Google Scholar]
  • 22.Manchikanti L, Abdi S, Atluri S, et al. American Society of Interventional Pain Physicians (ASIPP) guidelines for responsible opioid prescribing in chronic non-cancer pain: Part I--evidence assessment. Pain Physician. 2012 Jul;15(3 Suppl):S1–65. [PubMed] [Google Scholar]
  • 23.Kabat-Zinn J. Full Catastrophe Living: Using the Wisdom of Your Body and Mind to Face Stress, Pain, and Illness. New York: Delta; 1990. [Google Scholar]
  • 24.Segal ZV, Williams JM, Teasdale JD. Mindfulness-Based Cognitive Therapy for Depression. Second. New York: Guilford Press; 2013. [Google Scholar]
  • 25.Bowen S, Chawla N, Marlatt A. Mindfulness-Based Relapse Prevention for Addictive Behaviors: A Clinician's Guide. New York: Guilford Press; 2010. [Google Scholar]
  • 26.Mattke S, Balakrishnan A, Bergamo G, Newberry SJ. A review of methods to measure health-related productivity loss. Am J Manag Care. 2007 Apr;13(4):211–217. [PubMed] [Google Scholar]
  • 27.Sobell LC, Sobell MB. Timeline Followback: a technique for assessing self-reported alcohol consumption. In: Litten RZ, Allen J, editors. Measuring Alcohol Consumption: Psychosocial and Biological Methods. New Jersey: Humana Press; 1992. [Google Scholar]
  • 28.Fals-Stewart W, O'Farrell TJ, Freitas TT, McFarlin SK, Rutigliano P. The timeline followback reports of psychoactive substance use by drug-abusing patients: psychometric properties. J Consult Clin Psychol. 2000;68(1):134–144. doi: 10.1037//0022-006x.68.1.134. [DOI] [PubMed] [Google Scholar]
  • 29.Wisconsin Hospital Association Information Center. [Accessed July 1, 2014];Wisconsin PricePoint System. Available at: http://www.wipricepoint.org.
  • 30.Wisconsin Hospital Association Information Center. Hospital Inpatient Charges for Other Back/Neck Disorders/Fractures, Injuries, No Surgery: Wisconsin Hospitals, 2013. Generated interactively. 2014 Jul 1; [Google Scholar]
  • 31.Wisconsin Hospital Association Information Center. Emergency Department Charges for Neck/Back Sprains & Strains and Spinal Disorders: Wisconsin Hospitals, 2013. Generated interactively. 2014 Jul 1; [Google Scholar]
  • 32.Wisconsin Hospital Association Information Center. Hospital-Based Urgent Care Charges for Neck/Back Sprains & Strains and Spinal Disorders: Wisconsin Hospitals, 2013. Generated interactively. 2014 Jul 1; [Google Scholar]
  • 33.New Benefits, Ltd. [Accessed July–August 2014];Drug Price Search. Available at: www.rxpricequotes.com.
  • 34.Drugs.com. [Accessed July–August 2014];Drug Price Guide. Available at: http://www.drugs.com/price-guide.
  • 35.Walgreens Co. [Accessed July–August 2014]; Available at: http://www.walgreens.com/
  • 36.United States Department of Labor. Occupational Employment Statistics. State Occupational Employment and Wage Estimates; Wisconsin: May, 2013. [Accessed on July 1, 2014]. Bureau of Labor Statistics. Available at: http://www.bls.gov/oes/current/oes_wi.htm. [Google Scholar]
  • 37.United States Department of Labor. [Accessed on July 1, 2014];Wages, Minimum Wage. Available at: http://www.dol.gov/dol/topic/wages/minimumwage.htm.
  • 38.Cohen J. A power primer. Psychological bulletin. 1992 Jul;112(1):155–159. doi: 10.1037//0033-2909.112.1.155. [DOI] [PubMed] [Google Scholar]
  • 39.Miller JJ, Fletcher K, Kabat-Zinn J. Three-year follow-up and clinical implications of a mindfulness meditation-based stress reduction intervention in the treatment of anxiety disorders. Gen Hosp Psychiatry. 1995;17(3):192–200. doi: 10.1016/0163-8343(95)00025-m. [DOI] [PubMed] [Google Scholar]
  • 40.Herron RE. Changes in physician costs among high-cost transcendental meditation practitioners compared with high-cost nonpractitioners over 5 years. Am J Health Promot. 2011 Sep-Oct;26(1):56–60. doi: 10.4278/ajhp.100729-ARB-258. [DOI] [PubMed] [Google Scholar]

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