19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Risk Factors Associated With Transition From Acute to Chronic Low Back Pain in US Patients Seeking Primary Care

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Key Points

          Question

          Is the transition from acute to chronic low back pain (LBP) associated with risk strata, defined by a standardized prognostic tool, and/or with early exposure to guideline nonconcordant care?

          Findings

          In this cohort study of 5233 patients with acute LBP from 77 primary care practices, nearly half the patients were exposed to at least 1 guideline nonconcordant recommendation within the first 21 days after the index visit. Patients were significantly more likely to transition to chronic LBP as their risk on the prognostic tool increased and as they were exposed to more nonconcordant recommendations.

          Meaning

          In this study, the transition rate to chronic LBP was substantial and increased correspondingly with risk strata and early exposure to guideline nonconcordant care.

          Abstract

          This cohort study assesses the associations between the transition from acute to chronic lower back pain with risk strata from a standardized prognostic tool; demographic, clinical, and physician characteristics; and guideline nonconcordant processes of care.

          Abstract

          Importance

          Acute low back pain (LBP) is highly prevalent, with a presumed favorable prognosis; however, once chronic, LBP becomes a disabling and expensive condition. Acute to chronic LBP transition rates vary widely owing to absence of standardized operational definitions, and it is unknown whether a standardized prognostic tool (ie, Subgroups for Targeted Treatment Back tool [SBT]) can estimate this transition or whether early non–guideline concordant treatment is associated with the transition to chronic LBP.

          Objective

          To assess the associations between the transition from acute to chronic LBP with SBT risk strata; demographic, clinical, and practice characteristics; and guideline nonconcordant processes of care.

          Design, Setting, and Participants

          This inception cohort study was conducted alongside a multisite, pragmatic cluster randomized trial. Adult patients with acute LBP stratified by SBT risk were enrolled in 77 primary care practices in 4 regions across the United States between May 2016 and June 2018 and followed up for 6 months, with final follow-up completed by March 2019. Data analysis was conducted from January to March 2020.

          Exposures

          SBT risk strata and early LBP guideline nonconcordant processes of care (eg, receipt of opioids, imaging, and subspecialty referral).

          Main Outcomes and Measures

          Transition from acute to chronic LBP at 6 months using the National Institutes of Health Task Force on Research Standards consensus definition of chronic LBP. Patient demographic characteristics, clinical factors, and LBP process of care were obtained via electronic medical records.

          Results

          Overall, 5233 patients with acute LBP (3029 [58%] women; 4353 [83%] White individuals; mean [SD] age 50.6 [16.9] years; 1788 [34%] low risk; 2152 [41%] medium risk; and 1293 [25%] high risk) were included. Overall transition rate to chronic LBP at six months was 32% (1666 patients). In a multivariable model, SBT risk stratum was positively associated with transition to chronic LBP (eg, high-risk vs low-risk groups: adjusted odds ratio [aOR], 2.45; 95% CI, 2.00-2.98; P < .001). Patient and clinical characteristics associated with transition to chronic LBP included obesity (aOR, 1.52; 95% CI, 1.28-1.80; P < .001); smoking (aOR, 1.56; 95% CI, 1.29-1.89; P < .001); severe and very severe baseline disability (aOR, 1.82; 95% CI, 1.48-2.24; P < .001 and aOR, 2.08; 95% CI, 1.60-2.68; P < .001, respectively) and diagnosed depression/anxiety (aOR, 1.66; 95% CI, 1.28-2.15; P < .001). After controlling for all other variables, patients exposed to 1, 2, or 3 nonconcordant processes of care within the first 21 days were 1.39 (95% CI, 1.21-2.32), 1.88 (95% CI, 1.53-2.32), and 2.16 (95% CI, 1.10-4.25) times more likely to develop chronic LBP compared with those with no exposure ( P < .001).

          Conclusions and Relevance

          In this cohort study, the transition rate to chronic LBP was substantial and increased correspondingly with SBT stratum and early exposure to guideline nonconcordant care.

          Related collections

          Most cited references48

          • Record: found
          • Abstract: found
          • Article: not found

          The Oswestry Disability Index.

          The Oswestry Disability Index (ODI) has become one of the principal condition-specific outcome measures used in the management of spinal disorders. This review is based on publications using the ODI identified from the authors' personal databases, the Science Citation Index, and hand searches of Spine and current textbooks of spinal disorders. To review the versions of this instrument, document methods by which it has been validated, collate data from scores found in normal and back pain populations, provide curves for power calculations in studies using the ODI, and maintain the ODI as a gold standard outcome measure. It has now been 20 years since its original publication. More than 200 citations exist in the Science Citation Index. The authors have a large correspondence file relating to the ODI, that is cited in most of the large textbooks related to spinal disorders. All the published versions of the questionnaire were identified. A systematic review of this literature was made. The various reports of validation were collated and related to a version. Four versions of the ODI are available in English and nine in other languages. Some published versions contain misprints, and many omit the scoring system. At least 114 studies contain usable data. These data provide both validation and standards for other users and indicate the power of the instrument for detecting change in sample populations. The ODI remains a valid and vigorous measure and has been a worthwhile outcome measure. The process of using the ODI is reviewed and should be the subject of further research. The receiver operating characteristics should be explored in a population with higher self-report disabilities. The behavior of the instrument is incompletely understood, particularly in sensitivity to real change.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults — United States, 2016

            Chronic pain, one of the most common reasons adults seek medical care ( 1 ), has been linked to restrictions in mobility and daily activities ( 2 , 3 ), dependence on opioids ( 4 ), anxiety and depression ( 2 ), and poor perceived health or reduced quality of life ( 2 , 3 ). Population-based estimates of chronic pain among U.S. adults range from 11% to 40% ( 5 ), with considerable population subgroup variation. As a result, the 2016 National Pain Strategy called for more precise prevalence estimates of chronic pain and high-impact chronic pain (i.e., chronic pain that frequently limits life or work activities) to reliably establish the prevalence of chronic pain and aid in the development and implementation of population-wide pain interventions ( 5 ). National estimates of high-impact chronic pain can help differentiate persons with limitations in major life domains, including work, social, recreational, and self-care activities from those who maintain normal life activities despite chronic pain, providing a better understanding of the population in need of pain services. To estimate the prevalence of chronic pain and high-impact chronic pain in the United States, CDC analyzed 2016 National Health Interview Survey (NHIS) data. An estimated 20.4% (50.0 million) of U.S. adults had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain, with higher prevalences of both chronic pain and high-impact chronic pain reported among women, older adults, previously but not currently employed adults, adults living in poverty, adults with public health insurance, and rural residents. These findings could be used to target pain management interventions. NHIS is a cross-sectional, in-person, household health survey of the civilian noninstitutionalized U.S. population, conducted by the National Center for Health Statistics (NCHS).* Data from the 2016 Sample Adult Core for adults aged ≥18 years (33,028; response rate = 54.3%) † were analyzed. Information about pain was collected through responses to the following questions: “In the past six months, how often did you have pain? Would you say never, some days, most days, or every day?” and “Over the past six months, how often did pain limit your life or work activities? Would you say never, some days, most days, or every day?” Chronic pain was defined as pain on most days or every day in the past 6 months, as recommended by the International Association for the Study of Pain, § modified to account for intermittent pain, and used in both the National Pain Strategy and National Institutes of Health Task Force on Chronic Back Pain ( 6 ). As suggested in the National Pain Strategy, high-impact chronic pain was defined as chronic pain that limited life or work activities on most days or every day during the past 6 months ( 5 ). The prevalence of chronic pain and high-impact chronic pain (both crude and age-adjusted, with 95% confidence intervals) were estimated for the U.S. adult population overall and by various sociodemographic characteristics. These characteristics, collected with the Family Core questionnaire, included age, sex, race/ethnicity, education level, current employment status, ¶ poverty status (calculated using NHIS imputed income files),** veteran status, health insurance coverage type (reported separately for adults aged <65 and ≥65 years), and urbanicity. All prevalence estimates met NCHS reliability standards. †† Because pain prevalence varies by age, age-adjusted estimates were used in comparisons of chronic pain and high-impact chronic pain between subgroups. Based on two-tailed Z-tests, all reported differences between subgroups are statistically significant (unless otherwise noted; p<0.05). Analyses were conducted using statistical software that accounts for the stratification and clustering of households in the NHIS sampling design. Estimates incorporated the final sample adult weights adjusted for nonresponse and calibrated to population control totals to enable generalization to the civilian noninstitutionalized population aged ≥18 years. In 2016, an estimated 20.4% of U.S. adults (50.0 million) had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain (Table), with higher prevalence associated with advancing age. Age-adjusted prevalences of both chronic pain and high-impact chronic pain were significantly higher among women, adults who had worked previously but were not currently employed, adults living in or near poverty, and rural residents. In addition, the age-adjusted prevalences of chronic pain and high-impact chronic pain were significantly lower among adults with at least a bachelor’s degree compared with all other education levels. TABLE Prevalence of chronic pain* and high impact chronic pain † among U.S. adults aged ≥18 years, by sociodemographic characteristics—National Health Interview Survey, 2016 Characteristic Chronic pain* High-impact chronic pain† Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Total 50,009,000 20.4 (19.7–21.0) 19.4 (18.7–20.0) 19,611,000 8.0 (7.6–8.4) 7.5 (7.1–7.9) Age group (yrs) 18–24 2,082,000 7.0 (5.8–8.5) —** 446,000 1.5 (0.9–2.3) —** 25–44 11,042,000 13.2 (12.3–14.1) —** 3,681,000 4.4 (3.9–5.0) —** 45–64 23,269,000 27.8 (26.6–29.0) —** 10,044,000 12.0 (11.2–12.9) —** 65–84 11,808,000 27.6 (26.4–29.0) —** 4,578,000 10.7 (9.9–11.6) —** ≥85 1,766,000 33.6 (30.1–37.3) —** 830,000 15.8 (13.2–18.9) —** Sex Male 21,989,000 18.6 (17.7–19.5) 17.8 (17.0–18.7) 8,276,000 7.0 (6.5–7.6) 6.7 (6.2–7.3) Female 28,049,000 22.1 (21.2–23.0) 20.8 (19.9–21.6) 11,296,000 8.9 (8.4–9.4) 8.2 (7.7–8.7) Race/Ethnicity Hispanic 5,856,000 15.1 (13.6–16.7) 16.7 (15.2–18.4) 2,754,000 7.1 (6.0–8.3) 7.9 (6.9–9.2) White, non-Hispanic 36,226,000 23.0 (22.2–23.8) 21.0 (20.3–21.8) 13,230,000 8.4 (7.9–8.9) 7.4 (7.0–7.9) Black, non-Hispanic 5,148,000 17.9 (16.4–19.6) 17.8 (16.3–19.4) 2,387,000 8.3 (7.2–9.4) 8.1 (7.1–9.2) Other, non-Hispanic†† 2,774,000 13.8 (12.1–15.7) 14.4 (12.7–16.3) 1,326,000 6.6 (5.3–8.1) 7.0 (5.7–8.5) Education Less than high school 7,809,000 26.1 (24.2–28.2) 23.7 (21.7–25.7) 4,069,000 13.6 (12.3–15.2) 12.1 (10.7–13.7) High school/GED 14,441,000 23.7 (22.5–25.0) 22.6 (21.2–23.9) 5,910,000 9.7 (9.0–10.6) 9.1 (8.4–10.0) Some college 17,129,000 22.6 (21.5–23.8) 22.9 (21.8–24.0) 6,518,000 8.6 (7.9–9.4) 8.7 (8.0–9.5) Bachelor's degree or higher 10,383,000 13.4 (12.6–14.3) 12.4 (11.7–13.3) 2,944,000 3.8 (3.4–4.3) 3.5 (3.1–4.0) Employment status Employed 22,085,000 14.7 (14.1–15.5) 14.5 (13.8–15.2) 5,108,000 3.4 (3.1–3.8) 3.2 (2.9–3.6) Not employed; worked previously 25,737,000 31.5 (30.3–32.7) 29.2 (27.8–30.6) 13,318,000 16.3 (15.4–17.2) 16.1 (15.0–17.3) Not employed; never worked 2,083,000 15.9 (13.8–18.2) 18.7 (16.1–21.6) 1,192,000 9.1 (7.6–10.9) 11.1 (9.1–13.4) Poverty status <100% FPL 8,017,000 25.8 (24.2–27.6) 29.6 (27.9–31.3) 4,630,000 14.9 (13.6–16.4) 17.5 (16.1–19.0) 100% ≤FPL<200% 11,357,000 26.2 (24.5–27.9) 25.9 (24.2–27.7) 5,375,000 12.4 (11.3–13.6) 12.3 (11.2–13.5) 200% ≤FPL<400% 14,181,000 20.3 (19.2–21.4) 19.3 (18.3–20.4) 5,100,000 7.3 (6.7–8.1) 6.9 (6.2–7.6) ≥400% FPL 16,441,000 16.3 (15.4–17.2) 14.6 (13.8–15.5) 4,438,000 4.4 (4.0–4.9) 3.9 (3.5–4.4) Veteran Yes 6,379,000 29.1 (27.1–31.2) 26.0 (23.5–28.7) 2,258,000 10.3 (9.1–11.8) 9.2 (7.7–11.1) No 43,519,000 19.5 (18.9–20.2) 19.0 (18.4–19.7) 17,407,000 7.8 (7.4–8.2) 7.5 (7.1–7.9) Health insurance coverage§§ Age <65 yrs Private 20,539,000 15.1 (14.3–15.8) 14.0 (13.3–14.8) 5,713,000 4.2 (3.8–4.7) 3.8 (3.4–4.2) Medicaid and other public coverage 8,215,000 29.3 (27.3–31.5) 30.0 (28.0–32.2) 4,822,000 17.2 (15.6–19.0) 17.8 (16.2–19.6) Other 3,860,000 43.5 (40.0–47.2) 34.8 (31.2–38.7) 2,263,000 25.5 (22.5–28.8) 19.3 (16.4–22.5) Uninsured 3,683,000 16.2 (14.4–18.2) 17.0 (15.2–19.0) 1,319,000 5.8 (4.7–7.2) 6.2 (5.0–7.6) Age ≥65 yrs Private 5,606,000 28.0 (26.3–29.9) 28.1 (26.3–30.0) 1,842,000 9.2 (8.1–10.5) 9.3 (8.2–10.6) Medicare and Medicaid 1,428,000 42.5 (37.6–47.5) 42.5 (37.6–47.5) 816,000 24.3 (20.4–28.6) 24.3 (20.4–28.6) Medicare Advantage 3,094,000 25.5 (23.1–28.1) 25.8 (23.4–28.4) 1,226,000 10.1 (8.5–11.8) 10.3 (8.7–12.1) Medicare only, excluding Medicare Advantage 2,115,000 25.9 (23.1–28.9) 25.9 (23.1–28.9) 939,000 11.5 (9.5–13.7) 11.5 (9.5–13.7) Other 1,229,000 31.6 (27.2–36.3) 31.8 (27.4–36.5) 545,000 14.0 (11.3–17.3) 14.3 (11.5–17.7) Uninsured 106,000 —¶¶ —¶¶ 59,000 —¶¶ —¶¶ Urbanicity*** Urban 38,401,000 19.0 (18.3–19.7) 18.4 (17.7–19.0) 14,754,000 7.3 (6.9–7.8) 7.0 (6.6–7.4) Rural 11,575,000 26.9 (25.4–28.5) 24.0 (22.5–25.6) 4,776,000 11.1 (10.2–12.2) 9.8 (8.8–10.9) Abbreviations: CI = confidence interval; FPL = federal poverty level; GED = General Educational Development certification. * Pain on most days or every day in the past 6 months. † Chronic pain limiting life or work activities on most days or every day in the past 6 months. § The estimated numbers, rounded to 1,000s, were annualized based on the 2016 data. Counts for adults of unknown status (responses coded as “refused,” “don’t know,” or “not ascertained”) with respect to chronic pain and high-impact chronic pain are not shown separately in the table, nor are they included in the calculation of percentages (as part of either the denominator or the numerator), to provide a more straightforward presentation of the data. ¶ Estimates are age-adjusted using the projected 2000 U.S. population as the standard population and five age groups: 18–29, 30–39, 40–49, 50–59, and ≥60 years. ** Not applicable. †† Non-Hispanic other includes non-Hispanic American Indian and Alaska Native only, non-Hispanic Asian only, non-Hispanic Native Hawaiian and Pacific Islander only, and non-Hispanic multiple race. §§ Based on a hierarchy of mutually exclusive categories. Adults reporting both private and Medicare Advantage coverage were assigned to the Medicare Advantage category. “Uninsured” includes adults who had no coverage as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. “Other” comprises military health care including TRICARE, VA, and CHAMP-VA, and certain types of local and state governmental coverage, not including the Children’s Health Insurance Program. ¶¶ Estimates are considered unreliable according to the National Center for Health Statistics’ standards of reliability. *** Based on U.S. Census Bureau definitions of urban and rural areas (https://www2.census.gov/geo/pdfs/reference/ua/Defining_Rural.pdf). Whereas non-Hispanic white adults had a significantly higher age-adjusted prevalence of chronic pain than did all other racial and ethnic subgroups, no significant differences in high-impact chronic pain prevalence by race/ethnicity were observed. Similarly, the age-adjusted prevalence of chronic pain was significantly higher among veterans than among nonveterans, but no significant difference was observed in the prevalence of high-impact chronic pain. Among adults aged <65 years, the age-adjusted prevalences of chronic pain and high-impact chronic pain were higher among those with Medicaid and other public health care coverage or other insurance (e.g., Veteran’s Administration, certain local and state government) than among adults with private insurance or those who were uninsured. Among adults aged ≥65 years, those with both Medicare and Medicaid had higher age-adjusted prevalences of chronic pain and high-impact chronic pain than did adults with all other types of coverage. Discussion Pain is a component of many chronic conditions, and chronic pain is emerging as a health concern on its own, with negative consequences to individual persons, their families, and society as a whole ( 4 , 5 ). Healthy People 2020 (https://www.healthypeople.gov/), the nation’s science-based health objectives, has a developmental objective to “decrease the prevalence of adults having high-impact chronic pain.” This analysis extends previous national studies of chronic pain prevalence by identifying adults with high-impact chronic pain. In 2016, approximately 20% of U.S. adults had chronic pain (approximately 50 million), and 8% of U.S. adults (approximately 20 million) had high-impact chronic pain. This estimate of high-impact chronic pain is similar to or slightly lower than estimates reported in the few studies that have looked at pain using a similar construct. For example, a recent study that used a measure of high-impact chronic pain similar to the one used in this study reported an estimate of 13.7% among a sample of U.S. adult health plan enrollees ( 7 ). Similarly, a 2001 study of adults from a region in Scotland found that 14.1% of survey participants reported significant chronic pain, and 6.3% reported severe chronic pain, and a 2001 study of Australian adults reported that 11.0% of men and 13.5% of women reported chronic pain that interfered, to some degree, with daily life activities ( 3 , 8 ). The results of subgroup analyses in the current study were consistent with findings in these studies ( 3 , 8 ) insofar as the prevalence of high-impact chronic pain was higher among women, adults who had achieved lower levels of education, and those who were not employed at the time of the survey, and was lower among adults with private health insurance compared with public and other types of coverage. In addition, high-impact chronic pain was also found to be higher among adults living in poverty and among rural residents. Socioeconomic status appears to be a common factor in many of the subgroup differences in high-impact chronic pain prevalence reported here. Indicators of socioeconomic status such as education, poverty, and health insurance coverage have been determined to be associated with both general health status and the presence of specific health conditions ( 9 ) as well as with patients’ success in navigating the health care system ( 9 ). Identifying populations at risk is necessary to inform efforts for developing and targeting quality pain services. The findings in this report are subject to at least five limitations. First, data are self-reported and subject to recall bias. Second, data are cross-sectional, precluding drawing causal inferences. This might be particularly relevant for socioeconomic status, which can be both a risk factor for and a consequence of chronic pain or high-impact chronic pain, or both. Third, no information is available on treatment for chronic pain to assess the prevalence of chronic pain and high-impact chronic pain among those with and without treatment. Fourth, NHIS excludes important populations, such as active duty military and residents of long-term care facilities or prisons. And finally, NHIS does not collect data on chronic pain or high-impact chronic pain in children. Despite these limitations, three strengths of this study are that it used a large, nationally representative data source to produce estimates of chronic pain and high-impact chronic pain across many demographic subgroups, it used standard broad definitions of pain that were not limited to one or more specific health conditions (e.g., headache or arthritis), and it used the standard case definition for high-impact chronic pain proposed by the National Pain Strategy. Chronic pain contributes to an estimated $560 billion each year in direct medical costs, lost productivity, and disability programs ( 4 ). The National Pain Strategy, which is the first national effort to transform how the population burden of pain is perceived, assessed, and treated, recognizes the need for better data to inform action and calls for estimates of chronic pain and high-impact chronic pain in the general population ( 5 ). This report helps fulfill this objective and provides data to inform policymakers, clinicians, and researchers focused on pain care and prevention. Summary What is already known about this topic? Chronic pain has been linked to numerous physical and mental conditions and contributes to high health care costs and lost productivity. A limited number of studies estimate that the prevalence of chronic pain ranges from 11% to 40%. What is added by this report? In 2016, an estimated 20.4% of U.S. adults had chronic pain and 8.0% of U.S. adults had high-impact chronic pain. Both were more prevalent among adults living in poverty, adults with less than a high school education, and adults with public health insurance. What are the implications for public health practice? This report helps fulfill a National Pain Strategy objective of producing more precise estimates of chronic pain and high-impact chronic pain.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found
              Is Open Access

              Clinical practice guidelines for the management of non-specific low back pain in primary care: an updated overview

                Bookmark

                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                16 February 2021
                February 2021
                16 February 2021
                : 4
                : 2
                : e2037371
                Affiliations
                [1 ]School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania
                [2 ]Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
                [3 ]Physician Network and Quality, St Clair Hospital, Pittsburgh, Pennsylvania
                [4 ]Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania
                [5 ]Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
                [6 ]Intermountain Healthcare Rehabilitation Services, Murray, Utah
                [7 ]Johns Hopkins University School of Medicine, Baltimore, Maryland
                [8 ]Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                [9 ]Johns Hopkins Hospital, Baltimore, Maryland
                [10 ]Department of Physical Therapy, University of Florida College of Public Health and Health Professions, Gainesville
                [11 ]Duke Clinical Research Institute, Department of Orthopedic Surgery, Duke University, Durham, North Carolina
                [12 ]Department of Family Medicine, Boston Medical Center, Boston, Massachusetts
                Author notes
                Article Information
                Accepted for Publication: December 24, 2020.
                Published: February 16, 2021. doi:10.1001/jamanetworkopen.2020.37371
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Stevans JM et al. JAMA Network Open.
                Corresponding Author: Joel M. Stevans, DC, PhD, School of Health and Rehabilitation Sciences, University of Pittsburgh, 100 Technology Dr, Bridgeside Point 1, Ste 488, Pittsburgh, PA 15219 ( jms363@ 123456pitt.edu ).
                Author Contributions: Dr Stevans had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Delitto, Schneider, Greco, Freel, Sowa, Wasan, Brennan, Hunter, Wegener, Ephraim, Friedman, George, Saper.
                Acquisition, analysis, or interpretation of data: Stevans, Delitto, Khoja, Patterson, Smith, Freburger, Greco, Sowa, Wasan, Brennan, Minick, Wegener, Ephraim, Beneciuk, George, Saper.
                Drafting of the manuscript: Stevans, Delitto, Khoja, Schneider, Freburger, Freel, Brennan, Beneciuk, George, Saper.
                Critical revision of the manuscript for important intellectual content: Stevans, Delitto, Khoja, Patterson, Smith, Schneider, Freburger, Greco, Sowa, Wasan, Brennan, Hunter, Minick, Wegener, Ephraim, Friedman, Beneciuk, George, Saper.
                Statistical analysis: Stevans, Patterson, Smith, Schneider, Wasan.
                Obtained funding: Delitto, Wasan, Brennan, Ephraim, Saper.
                Administrative, technical, or material support: Stevans, Delitto, Khoja, Schneider, Freburger, Greco, Freel, Sowa, Wasan, Brennan, Hunter, Minick, Wegener, Ephraim, Friedman, George.
                Supervision: Stevans, Delitto, Sowa, Wasan, Brennan, Ephraim, George, Saper.
                Conflict of Interest Disclosures: Dr Delitto reported receiving grants from the National Institutes of Health outside the submitted work. Dr Sowa reported receiving grants from the National Institutes of Health outside the submitted work. Dr George reported receiving grants from the National Institutes of Health and receiving personal fees from Rehab Essentials and MedRisk outside the submitted work. No other disclosures were reported.
                Funding/Support: This research work was funded by award PCS-1402-10867 from the Patient-Centered Outcomes Research Institute.
                Role of the Funder/Sponsor: The funder was not involved in decisions related to the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Additional Contributions: The TARGET trial investigative team would like to acknowledge the leadership teams at UPMC; Chief Medical and Scientific Officer, Steven Shapiro, MD; the President of Community Medicine Incorporated, Fran Solano, MD; and Chief Quality Officer, Tami Minnier, MSN, for their support throughout all phases of the TARGET trial. We would also like to acknowledge our patient and payer stakeholders for their valuable input in the design and interpretation of the TARGET trial. Patient stakeholders included Marie Tamasy (Pittsburgh), Jewel Cash (Boston), Scott Lake (Salt Lake City), Penny Cohen (American Chronic Pain Society), and Beth E. Brown (Arthritis Foundation). Payer stakeholders included Pamela Peele, PhD, and Michael Parkinson, MD (UPMC-Health Plan), and David Elton, DC (OPTUM Health). Provider stakeholders included Russell Phillips, MD (Harvard Medical School Center for Primary Care), and William Boissonnault, DPT (American Physical Therapy Association). We would also like to acknowledge the team members from Boston Medical Center, including clinic site champions Laura Goldman, MD, Stephanie Charles, MD, Jonathan Berz, MD, Stephen Tringale, MD, Jennifer Lo, MD, and Katherine Gergen Barnett, MD. We are grateful to those who designed and executed data extraction, including Associate Chief Medical Information Officer Rebecca Mishuris, MD, Director of Clinical Research Informatics for Boston University William Adams, MD, Medical Director of the Boston HealthNet Charles Williams, MD, and Clinical Data Warehouse Research Manager Linda Rosen. We wish to also thank Karen Mattie, PT, DPT, MS, Director of Rehabilitation Services, and Christopher Joyce, DPT, PhD, who provided physical therapy leadership. Lastly, we appreciate the hard work of our research staff at Boston Medical Center who collected baseline and 6-month survey data, including Chelsey Lemaster, MD, MPH, Dorothy Plumb, MA, Salvatore D’Amico, BS, Jessica Howard, MA, MPH, Alex Femia, Samia Jaffar, MPH, Iniya Rajendran, MD, Bhumi Patel, MPH, Kristin Mikhail, MS, MPH, Frank Liu, Shweta Palakkode, Sumedha Javalikar, MPH, and Kimberly Prescod. Mss Tamasy and Cash and Mr Lake received consulting fees and travel reimbursement; Ms Cohen and Drs Phillips and Boissonnault received honoraria and travel reimbursement; Dr Parkinson received honoraria; and Dr Elton received travel reimbursement.
                Additional Information: Access to deidentified data will be made available by by Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan by no later than July 01, 2021. Requests for access to the data can be made at https://www.icpsr.umich.edu/web/pages/.
                Article
                zoi201119
                10.1001/jamanetworkopen.2020.37371
                7887659
                33591367
                49d9e3eb-f0b5-45df-8468-e92066a901e0
                Copyright 2021 Stevans JM et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 9 November 2020
                : 24 December 2020
                Categories
                Research
                Original Investigation
                Online Only
                Health Policy

                Comments

                Comment on this article