<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03301623</url>
  </required_header>
  <id_info>
    <org_study_id>Pro00049085</org_study_id>
    <nct_id>NCT03301623</nct_id>
  </id_info>
  <brief_title>Comparative Effectiveness Trial of Communication Strategies in the Management of Chronic Pain</brief_title>
  <official_title>Integrating the Patient Voice Into Comparative Effectiveness Trial of Communication Strategies in the Management of Chronic Pain</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Cedars-Sinai Medical Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Patient-Centered Outcomes Research Institute</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Cedars-Sinai Medical Center</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Investigators will compare Clinical Decision Support (CDS) versus Patient Education and&#xD;
      Activation Tools (PEATs) in patients prescribed long-term or multiple opioids to measure&#xD;
      outcomes that are important to patients. Primary outcomes are pain interference, physical&#xD;
      function, and satisfaction with patient-physician communication. Secondary outcomes are&#xD;
      overall Health-Related Quality of Life and high-risk prescribing, including prescriptions&#xD;
      over 90 morphine milligram equivalents per day and co-prescribing of benzodiazepines and&#xD;
      opioids.&#xD;
&#xD;
      Patients in the PEAT arm will receive patient materials during the intervention, developed to&#xD;
      engage patients in chronic pain treatment, prior to Primary Care Physician office visits. In&#xD;
      the provider-facing CDS arm, PCPs will receive computerized reminders about appropriate&#xD;
      opioid use during office visits for enrolled patients. Patients in both groups will receive&#xD;
      questionnaires about pain interference, quality of life, and physician-patient communication&#xD;
      through the patient portal one month after each visit to their Primary Care Physician (PCP).&#xD;
      Investigators will use multi-level regression models to compare the effectiveness of these&#xD;
      two communication strategies.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Investigators will compare two strategies: (1) Engage PCPs with Clinical Decision Support at&#xD;
      the point of care, raising active alerts through the Electronic Health Record (EHR) when&#xD;
      there is risk of inappropriate opioid prescribing, thus leading to informed decision-making&#xD;
      with the patient about alternative treatments; versus (2) Engage patients prior to their PCP&#xD;
      visit using Patient Education and Activation Tools (PEATs) administered via REDCap, helping&#xD;
      patients to prepare for their visit and encouraging discussion about treatment preferences,&#xD;
      values and treatment goals at the time of the visit, thus leading to shared decision-making&#xD;
      with the provider. Our CDS intervention will use &quot;Choosing Wisely&quot; and Centers for Disease&#xD;
      Control and Prevention (CDC) guidelines, and our Patient Education and Activation Tool&#xD;
      intervention will use widely disseminated material developed by Consumer Reports and the&#xD;
      ACPA. Investigators will assess whether improved communication and patient activation through&#xD;
      these strategies improve patient-reported outcomes related to pain interference and HRQOL. To&#xD;
      assess these outcomes, investigators will use NIH Patient Reported Outcome Measurement&#xD;
      Information System (PROMIS®) questionnaires to capture health domains identified by our&#xD;
      patient partners as most important. Using PROs will also help capture whether the use of&#xD;
      either of these strategies leads to unintended consequences for patients when opioids are&#xD;
      reduced and other pain management strategies are not substituted.&#xD;
&#xD;
      Recruitment procedures: The study team mails study materials including an introductory&#xD;
      brochure, information sheet, and initial contact letter to eligible participants. Eligible&#xD;
      participants are then called and asked if they would like to enroll in the study, at which&#xD;
      point the study team obtains consent over the phone. Non-responders, eligible participants&#xD;
      who the study team has not been able to reach by phone and for whom a voicemail was left, are&#xD;
      automatically enrolled in an abbreviated arm of the study after two weeks of non-response.&#xD;
      Those enrolled in both the full study PEATs group and abbreviated PEATs group will be sent&#xD;
      the PEATs materials two days before an appointment with their primary care clinician.&#xD;
      Participants may choose to opt out of any arm of the study.&#xD;
&#xD;
      Data collection: Upon enrollment in the fully study, investigators will send patients an&#xD;
      enrollment questionnaire, which includes questions on education, language proficiency, and&#xD;
      health literacy. At this point, investigators will also send the two PROMIS questionnaires&#xD;
      (pain interference and physical function) via REDCap. The study team has programmed the&#xD;
      surveys to be sent via automatic email in REDCap. The email will contain a link where&#xD;
      participants can access the questionnaire and redeem their Amazon gift card instantly. The&#xD;
      total time to take this questionnaire is 2 minutes.&#xD;
&#xD;
      All enrolled participants will receive monthly PROMIS questionnaires during the 12-month&#xD;
      intervention period. Enrolled patients who have any follow-up visits during this intervention&#xD;
      period in both full study arms will be sent the Communication Questionnaire (COMRADE) via&#xD;
      REDCap one day after each office visit with their PCP.&#xD;
&#xD;
      For participants enrolled in the abbreviated arm of the study, the study team will have&#xD;
      access to medical records that will allow for a retrospective pull of relevant&#xD;
      patient-reported outcome measures and PCP satisfaction data collected by the health system.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 13, 2017</start_date>
  <completion_date type="Actual">December 31, 2019</completion_date>
  <primary_completion_date type="Actual">December 31, 2019</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <intervention_model_description>The study team will randomize the study on the provider level and use a random number generator to assign providers to study arms.&#xD;
Patients within the physicians randomized to the Informed Decision Making (IDM) arm will not receive the PEAT materials; their physicians will receive the CDS alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Patients within the physicians randomized to the Shared Decision Making (SDM) arm will receive the PEAT materials via REDCap two days before their PCP office visit. They will receive these materials every time they have an office visit with their PCP.</intervention_model_description>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>PROMIS - Pain Interference Short Form 8a</measure>
    <time_frame>Assessed at baseline at randomization, monthly up to 20 months after start of intervention (i.e. repeated measures).</time_frame>
    <description>PROMIS - Pain Interference instruments assess self-reported consequences of pain on relevant aspects of one's life. This includes the extent to which pain hinders engagement with social, cognitive, emotional, physical, and recreational activities. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Pain Interference, a T-score of 60 is one SD higher pain than average. A t-score of 50 represents the mean pain interference reported by a representative US population.&#xD;
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>CG-CAHPS</measure>
    <time_frame>1-year pre-intervention vs. 1-year post-intervention (i.e. repeated measures).</time_frame>
    <description>The Consumer Assessment of Healthcare Providers and System Clinician and Group Survey (CG-CAHPS) is a widely used PRO for collecting and reporting information from patients' about their experiences of care. We used the &quot;How well providers communicate with patients&quot; 6-item composite score. The response scale for these items was &quot;Yes, definitely&quot;, &quot;Yes, somewhat&quot;, and &quot;No&quot;. The composite score was represented as a binary value indicating whether a PCP received all &quot;top-box&quot; scores (represented by &quot;Yes, definitely&quot; responses) on the 6 items.&#xD;
We report the count of &quot;top box&quot; responses in the pre- and post-intervention periods by group. Analysis featured a mixed effects logistic regression model for repeated measures where the term of interest was an interaction term describing the change in the odds of a &quot;top box&quot; score in the PEAT group during the post-intervention period.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>PROMIS Physical Function 6b v1.2</measure>
    <time_frame>Assessed at baseline at randomization, monthly up to 20 months after start of intervention (i.e. repeated measures).</time_frame>
    <description>PROMIS Physical Function instruments measure self-reported capability rather than actual performance of physical activities. A single Physical Function capability score is obtained from a short form. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Physical Function, a T-score of 60 is one SD better than average. By comparison, a Physical Function T-score of 40 is one SD worse than average.&#xD;
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Number of Opioid Prescriptions Over 90 MME/Day Written by Physicians</measure>
    <time_frame>1-year pre-intervention vs. 1 year post-intervention</time_frame>
    <description>Physicians should avoid increasing dosage to ≥90 MME/day, and this measure compares odds of writing prescriptions over 90mme pre- vs. post-intervention</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Number of Opioid Co-prescription of Opioids and Benzodiazepines Written by Physicians</measure>
    <time_frame>1-year pre-intervention vs. 1-year post-intervention</time_frame>
    <description>Physicians should avoid co-prescribing of opioids and benzodiazepines. This binary outcome captures the presence (or lack) of a written prescriptions for opioids within a 24-hour window on either side of a prescription for benzodiazepines.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Patient Health Questionnaire-9 (PHQ-9)</measure>
    <time_frame>1-year pre-intervention vs. 1-year post-intervention at all appointments (i.e. repeated measures).</time_frame>
    <description>The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as &quot;0&quot; (not at all) to &quot;3&quot; (nearly every day). The raw score was categorized by severity according to the scoring guide and analyzed as such. Raw scores were assigned the following categories: 0-4, None; 5-9, Mild; 10-14, Moderate; 15-19, Moderately severe; and 20 or greater, Severe.&#xD;
We report the count of categorized PHQ-9 responses in the pre- (baseline characteristics) and post-intervention periods by group. Analysis featured a mixed effects ordered logistic regression model for repeated measures where the term of interest was an interaction describing the change in the odds of a &quot;top box&quot; score in the PEAT group during the post-intervention period. Analysis did not require balanced data (i.e. any scores in any time period meant patient was included).</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">983</enrollment>
  <condition>Chronic Pain</condition>
  <arm_group>
    <arm_group_label>Clinical Decision Support</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Patient Education and Activation Tools</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Clinical Decision Support</intervention_name>
    <description>The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
    <arm_group_label>Clinical Decision Support</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Patient Education and Activation Tools</intervention_name>
    <description>The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
    <arm_group_label>Patient Education and Activation Tools</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        Within a 90-day period prior to the patient recruitment date:&#xD;
&#xD;
          -  ≥30 days of prescriptions for opioid medications; or&#xD;
&#xD;
          -  2 or more opioid prescriptions; or&#xD;
&#xD;
          -  a total amount of ≥700 Morphine Milligram Equivalents (MME) in a single opioid&#xD;
             prescription;&#xD;
&#xD;
        and&#xD;
&#xD;
          -  Patients who have had 1 or more Cedars-Sinai Medical Group primary care physician in&#xD;
             the year prior to the study start date; and&#xD;
&#xD;
          -  At least 1 visit during the follow-up year (the follow-up year will start after they&#xD;
             consent to be in the study).&#xD;
&#xD;
        Prescriptions in the inpatient setting will not make a patient eligible for this study.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Individuals less than 18 years of age; or&#xD;
&#xD;
          -  Individuals with any cancer treatment (chemotherapy or radiotherapy) administered 180&#xD;
             days or less prior to patient recruitment; or&#xD;
&#xD;
          -  Individuals with a cancer diagnosis in the Problem List 180 days or less prior to&#xD;
             patient recruitment (patients with cancer surveillance only will be included in the&#xD;
             study); or&#xD;
&#xD;
          -  Individuals with palliative care treatment administered 180 days or less prior to&#xD;
             patient recruitment; or&#xD;
&#xD;
          -  Individuals with any end-of-life treatment (comfort care) prior to patient&#xD;
             recruitment; or&#xD;
&#xD;
          -  Patients currently taking prescription medications (e.g. Suboxone, subutex, Buprenex,&#xD;
             Butrans, Probuphine, Belbuca, buprenorphine/naloxone, Zubsolv, and Bunavail) for&#xD;
             Opioid Use or other Substance Use Disorder treatment.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Brennan Spiegel, MD, MSHS</last_name>
    <role>Principal Investigator</role>
    <affiliation>Cedars-Sinai Medical Center</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Cedars-Sinai Medical Center</name>
      <address>
        <city>Los Angeles</city>
        <state>California</state>
        <zip>90048</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <reference>
    <citation>Ballantyne JC, Sullivan MD. Intensity of Chronic Pain--The Wrong Metric? N Engl J Med. 2015 Nov 26;373(22):2098-9. doi: 10.1056/NEJMp1507136. No abstract available.</citation>
    <PMID>26605926</PMID>
  </reference>
  <reference>
    <citation>Centers for Disease Control and Prevention (CDC). Vital signs: overdoses of prescription opioid pain relievers---United States, 1999--2008. MMWR Morb Mortal Wkly Rep. 2011 Nov 4;60(43):1487-92.</citation>
    <PMID>22048730</PMID>
  </reference>
  <reference>
    <citation>Daubresse M, Chang HY, Yu Y, Viswanathan S, Shah ND, Stafford RS, Kruszewski SP, Alexander GC. Ambulatory diagnosis and treatment of nonmalignant pain in the United States, 2000-2010. Med Care. 2013 Oct;51(10):870-8. doi: 10.1097/MLR.0b013e3182a95d86.</citation>
    <PMID>24025657</PMID>
  </reference>
  <reference>
    <citation>Dorn SD, Meek PD, Shah ND. Increasing frequency of opioid prescriptions for chronic abdominal pain in US outpatient clinics. Clin Gastroenterol Hepatol. 2011 Dec;9(12):1078-85.e1. doi: 10.1016/j.cgh.2011.08.008. Epub 2011 Aug 18. Erratum In: Clin Gastroenterol Hepatol. 2012 Mar;10(3):332.</citation>
    <PMID>21854735</PMID>
  </reference>
  <reference>
    <citation>Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain--United States, 2016. JAMA. 2016 Apr 19;315(15):1624-45. doi: 10.1001/jama.2016.1464.</citation>
    <PMID>26977696</PMID>
  </reference>
  <reference>
    <citation>Wilsey BL, Fishman SM, Crandall M, Casamalhuapa C, Bertakis KD. A qualitative study of the barriers to chronic pain management in the ED. Am J Emerg Med. 2008 Mar;26(3):255-63. doi: 10.1016/j.ajem.2007.05.005.</citation>
    <PMID>18358933</PMID>
  </reference>
  <reference>
    <citation>Bhamb B, Brown D, Hariharan J, Anderson J, Balousek S, Fleming MF. Survey of select practice behaviors by primary care physicians on the use of opioids for chronic pain. Curr Med Res Opin. 2006 Sep;22(9):1859-65. doi: 10.1185/030079906X132398.</citation>
    <PMID>16968589</PMID>
  </reference>
  <reference>
    <citation>Hooten WM, Bruce BK. Beliefs and attitudes about prescribing opioids among healthcare providers seeking continuing medical education. J Opioid Manag. 2011 Nov-Dec;7(6):417-24. doi: 10.5055/jom.2011.0082.</citation>
    <PMID>22320023</PMID>
  </reference>
  <reference>
    <citation>Kavukcu E, Akdeniz M, Avci HH, Altug M, Oner M. Chronic noncancer pain management in primary care: family medicine physicians' risk assessment of opioid misuse. Postgrad Med. 2015 Jan;127(1):22-6. doi: 10.1080/00325481.2015.993572. Epub 2014 Dec 25.</citation>
    <PMID>25539797</PMID>
  </reference>
  <reference>
    <citation>McCarthy DM, Cameron KA, Courtney DM, Adams JG, Engel KG. Communication about opioid versus nonopioid analgesics in the emergency department. J Opioid Manag. 2015 May-Jun;11(3):229-36. doi: 10.5055/jom.2015.0271.</citation>
    <PMID>25985807</PMID>
  </reference>
  <reference>
    <citation>Morse JS, Stockbridge H, Egan KB, Mai J, Wickizer T, Franklin GM. Primary care survey of the value and effectiveness of the Washington State Opioid Dosing Guideline. J Opioid Manag. 2011 Nov-Dec;7(6):427-33. doi: 10.5055/jom.2011.0083.</citation>
    <PMID>22320024</PMID>
  </reference>
  <reference>
    <citation>Manchikanti L, Manchikanti KN, Pampati V, Cash KA. Prevalence of side effects of prolonged low or moderate dose opioid therapy with concomitant benzodiazepine and/or antidepressant therapy in chronic non-cancer pain. Pain Physician. 2009 Jan-Feb;12(1):259-67.</citation>
    <PMID>19165308</PMID>
  </reference>
  <reference>
    <citation>Mahowald ML, Singh JA, Majeski P. Opioid use by patients in an orthopedics spine clinic. Arthritis Rheum. 2005 Jan;52(1):312-21. doi: 10.1002/art.20784.</citation>
    <PMID>15641058</PMID>
  </reference>
  <reference>
    <citation>Luo X, Pietrobon R, Hey L. Patterns and trends in opioid use among individuals with back pain in the United States. Spine (Phila Pa 1976). 2004 Apr 15;29(8):884-90; discussion 891. doi: 10.1097/00007632-200404150-00012.</citation>
    <PMID>15082989</PMID>
  </reference>
  <reference>
    <citation>Ives TJ, Chelminski PR, Hammett-Stabler CA, Malone RM, Perhac JS, Potisek NM, Shilliday BB, DeWalt DA, Pignone MP. Predictors of opioid misuse in patients with chronic pain: a prospective cohort study. BMC Health Serv Res. 2006 Apr 4;6:46. doi: 10.1186/1472-6963-6-46.</citation>
    <PMID>16595013</PMID>
  </reference>
  <reference>
    <citation>Fredheim OMS, Borchgrevink PC, Mahic M, Skurtveit S. A pharmacoepidemiological cohort study of subjects starting strong opioids for nonmalignant pain: a study from the Norwegian Prescription Database. Pain. 2013 Nov;154(11):2487-2493. doi: 10.1016/j.pain.2013.07.033. Epub 2013 Sep 24.</citation>
    <PMID>24075311</PMID>
  </reference>
  <reference>
    <citation>Burgess DJ, Crowley-Matoka M, Phelan S, Dovidio JF, Kerns R, Roth C, Saha S, van Ryn M. Patient race and physicians' decisions to prescribe opioids for chronic low back pain. Soc Sci Med. 2008 Dec;67(11):1852-60. doi: 10.1016/j.socscimed.2008.09.009. Epub 2008 Oct 15.</citation>
    <PMID>18926612</PMID>
  </reference>
  <reference>
    <citation>Adams NJ, Plane MB, Fleming MF, Mundt MP, Saunders LA, Stauffacher EA. Opioids and the treatment of chronic pain in a primary care sample. J Pain Symptom Manage. 2001 Sep;22(3):791-6. doi: 10.1016/s0885-3924(01)00320-7.</citation>
    <PMID>11532592</PMID>
  </reference>
  <reference>
    <citation>Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain. 2012 Aug;13(8):715-24. doi: 10.1016/j.jpain.2012.03.009. Epub 2012 May 16.</citation>
    <PMID>22607834</PMID>
  </reference>
  <reference>
    <citation>Chapman JB, Lehman CL, Elliott J, Clark JD. Sleep quality and the role of sleep medications for veterans with chronic pain. Pain Med. 2006 Mar-Apr;7(2):105-14. doi: 10.1111/j.1526-4637.2006.00110.x.</citation>
    <PMID>16634723</PMID>
  </reference>
  <reference>
    <citation>King SA, Strain JJ. Benzodiazepine use by chronic pain patients. Clin J Pain. 1990 Jun;6(2):143-7. doi: 10.1097/00002508-199006000-00013.</citation>
    <PMID>1983726</PMID>
  </reference>
  <reference>
    <citation>Menefee LA, Frank ED, Doghramji K, Picarello K, Park JJ, Jalali S, Perez-Schwartz L. Self-reported sleep quality and quality of life for individuals with chronic pain conditions. Clin J Pain. 2000 Dec;16(4):290-7. doi: 10.1097/00002508-200012000-00003.</citation>
    <PMID>11153783</PMID>
  </reference>
  <reference>
    <citation>Ritzwoller DP, Crounse L, Shetterly S, Rublee D. The association of comorbidities, utilization and costs for patients identified with low back pain. BMC Musculoskelet Disord. 2006 Sep 18;7:72. doi: 10.1186/1471-2474-7-72.</citation>
    <PMID>16982001</PMID>
  </reference>
  <reference>
    <citation>Friedman BW, Chilstrom M, Bijur PE, Gallagher EJ. Diagnostic testing and treatment of low back pain in United States emergency departments: a national perspective. Spine (Phila Pa 1976). 2010 Nov 15;35(24):E1406-11. doi: 10.1097/BRS.0b013e3181d952a5.</citation>
    <PMID>21030902</PMID>
  </reference>
  <reference>
    <citation>Gilbert FJ, Grant AM, Gillan MG, Vale LD, Campbell MK, Scott NW, Knight DJ, Wardlaw D; Scottish Back Trial Group. Low back pain: influence of early MR imaging or CT on treatment and outcome--multicenter randomized trial. Radiology. 2004 May;231(2):343-51. doi: 10.1148/radiol.2312030886. Epub 2004 Mar 18.</citation>
    <PMID>15031430</PMID>
  </reference>
  <reference>
    <citation>Kerry S, Hilton S, Patel S, Dundas D, Rink E, Lord J. Routine referral for radiography of patients presenting with low back pain: is patients' outcome influenced by GPs' referral for plain radiography? Health Technol Assess. 2000;4(20):i-iv, 1-119. No abstract available.</citation>
    <PMID>11044957</PMID>
  </reference>
  <verification_date>September 2021</verification_date>
  <study_first_submitted>September 27, 2017</study_first_submitted>
  <study_first_submitted_qc>September 29, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">October 4, 2017</study_first_posted>
  <results_first_submitted>September 1, 2020</results_first_submitted>
  <results_first_submitted_qc>September 17, 2021</results_first_submitted_qc>
  <results_first_posted type="Actual">October 13, 2021</results_first_posted>
  <last_update_submitted>September 17, 2021</last_update_submitted>
  <last_update_submitted_qc>September 17, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">October 13, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Cedars-Sinai Medical Center</investigator_affiliation>
    <investigator_full_name>Brennan Spiegel</investigator_full_name>
    <investigator_title>Principal Investigator</investigator_title>
  </responsible_party>
  <keyword>Clinical Decision Support</keyword>
  <keyword>Patient Education Materials</keyword>
  <keyword>Opioid Use</keyword>
  <keyword>Chronic Noncancer Pain</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Chronic Pain</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>April 20, 2018</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/23/NCT03301623/Prot_SAP_000.pdf</document_url>
    </provided_document>
  </provided_document_section>

  <clinical_results>

    <participant_flow>
      <group_list>
        <group group_id="P1">
          <title>Clinical Decision Support</title>
          <description>Patients within the physicians randomized to the Informed Decision Making (IDM) arm will receive the Clinical Decision Support alerts via the Electronic Health Record (EHR) when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
        </group>
        <group group_id="P2">
          <title>Patient Education and Activation Tools</title>
          <description>Patients within the physicians randomized to Shared Decision Making (SDM) will receive the PEAT materials via REDCap two days prior to their Primary Care Physician (PCP) office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="462"/>
                <participants group_id="P2" count="521"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="445"/>
                <participants group_id="P2" count="506"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="17"/>
                <participants group_id="P2" count="15"/>
              </participants_list>
            </milestone>
          </milestone_list>
          <drop_withdraw_reason_list>
            <drop_withdraw_reason>
              <title>Death</title>
              <participants_list>
                <participants group_id="P1" count="3"/>
                <participants group_id="P2" count="1"/>
              </participants_list>
            </drop_withdraw_reason>
            <drop_withdraw_reason>
              <title>Withdrawal by Subject</title>
              <participants_list>
                <participants group_id="P1" count="11"/>
                <participants group_id="P2" count="13"/>
              </participants_list>
            </drop_withdraw_reason>
            <drop_withdraw_reason>
              <title>Lost to Follow-up</title>
              <participants_list>
                <participants group_id="P1" count="3"/>
                <participants group_id="P2" count="1"/>
              </participants_list>
            </drop_withdraw_reason>
          </drop_withdraw_reason_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>Clinical Decision Support</title>
          <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
        </group>
        <group group_id="B2">
          <title>Patient Education and Activation Tools</title>
          <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
        </group>
        <group group_id="B3">
          <title>Total</title>
          <description>Total of all reporting groups</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="445"/>
            <count group_id="B2" value="506"/>
            <count group_id="B3" value="951"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <title>&lt;=18 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Between 18 and 65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="317"/>
                    <measurement group_id="B2" value="380"/>
                    <measurement group_id="B3" value="697"/>
                  </measurement_list>
                </category>
                <category>
                  <title>&gt;=65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="128"/>
                    <measurement group_id="B2" value="126"/>
                    <measurement group_id="B3" value="254"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Age</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="55.38" spread="16.01"/>
                    <measurement group_id="B2" value="53.57" spread="16.08"/>
                    <measurement group_id="B3" value="54.42" spread="16.07"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex: Female, Male</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="262"/>
                    <measurement group_id="B2" value="290"/>
                    <measurement group_id="B3" value="552"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="183"/>
                    <measurement group_id="B2" value="216"/>
                    <measurement group_id="B3" value="399"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Race (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <title>American Indian or Alaska Native</title>
                  <measurement_list>
                    <measurement group_id="B1" value="2"/>
                    <measurement group_id="B2" value="2"/>
                    <measurement group_id="B3" value="4"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Asian</title>
                  <measurement_list>
                    <measurement group_id="B1" value="26"/>
                    <measurement group_id="B2" value="29"/>
                    <measurement group_id="B3" value="55"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Native Hawaiian or Other Pacific Islander</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="3"/>
                    <measurement group_id="B3" value="3"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Black or African American</title>
                  <measurement_list>
                    <measurement group_id="B1" value="93"/>
                    <measurement group_id="B2" value="120"/>
                    <measurement group_id="B3" value="213"/>
                  </measurement_list>
                </category>
                <category>
                  <title>White</title>
                  <measurement_list>
                    <measurement group_id="B1" value="283"/>
                    <measurement group_id="B2" value="313"/>
                    <measurement group_id="B3" value="596"/>
                  </measurement_list>
                </category>
                <category>
                  <title>More than one race</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="41"/>
                    <measurement group_id="B2" value="39"/>
                    <measurement group_id="B3" value="80"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Region of Enrollment</title>
          <units>participants</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>United States</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="445"/>
                    <measurement group_id="B2" value="506"/>
                    <measurement group_id="B3" value="951"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>PROMIS - Pain Interference Short Form 8a</title>
          <description>PROMIS - Pain Interference instruments assess self-reported consequences of pain on relevant aspects of one's life. This includes the extent to which pain hinders engagement with social, cognitive, emotional, physical, and recreational activities. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Pain Interference, a T-score of 60 is one SD higher pain than average. A t-score of 50 represents the mean pain interference reported by a representative US population.</description>
          <population>Sample limited to survey respondents.</population>
          <units>t-score</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="89"/>
                    <count group_id="B2" value="73"/>
                    <count group_id="B3" value="162"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="62.18" spread="8.54"/>
                    <measurement group_id="B2" value="62.79" spread="6.85"/>
                    <measurement group_id="B3" value="62.46" spread="7.78"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>CAHPS® Clinician &amp; Group Survey (CG-CAHPS)</title>
          <description>The Consumer Assessment of Healthcare Providers and System Clinician and Group Survey (CG-CAHPS) is a widely used PRO for collecting and reporting information from patients' about their experiences of care. We used the &quot;How well providers communicate with patients&quot; 6-item composite score. The response scale for these items was &quot;Yes, definitely&quot;, &quot;Yes, somewhat&quot;, and &quot;No&quot;. The composite score was represented as a binary value indicating whether a PCP received all &quot;top-box&quot; scores (represented by &quot;Yes, definitely&quot; responses) on the 6 items.</description>
          <population>Analysis was limited to survey respondents. CG-CAHPS is an extant measure within the health system. All surveys for PCPs in the study were included in analysis. There was not a requirement for a patient to have balanced data (i.e. responses in both study periods) to be included in analysis.</population>
          <units>Responses</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>Top Box</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="170"/>
                    <count group_id="B2" value="187"/>
                    <count group_id="B3" value="357"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="108"/>
                    <measurement group_id="B2" value="79"/>
                    <measurement group_id="B3" value="188"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Not Top Box</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="170"/>
                    <count group_id="B2" value="187"/>
                    <count group_id="B3" value="357"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="14"/>
                    <measurement group_id="B2" value="24"/>
                    <measurement group_id="B3" value="38"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>PROMIS Physical Function 6b v1.2</title>
          <description>PROMIS Physical Function instruments measure self-reported capability rather than actual performance of physical activities. A single Physical Function capability score is obtained from a short form. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Physical Function, a T-score of 60 is one SD better than average. By comparison, a Physical Function T-score of 40 is one SD worse than average.</description>
          <population>Sample limited to survey respondents.</population>
          <units>t-score</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="88"/>
                    <count group_id="B2" value="72"/>
                    <count group_id="B3" value="160"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="38.82" spread="9.24"/>
                    <measurement group_id="B2" value="38.32" spread="7.39"/>
                    <measurement group_id="B3" value="38.59" spread="8.41"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Opioid Prescription Over 90 Morphine Milligram Equivalents (MME) (Dichotomous)</title>
          <description>Physicians should avoid increasing dosage to ≥90 MME/day, and this measure compares odds of writing prescriptions over 90mme pre- vs. post-intervention</description>
          <population>Limited to participants with at least one prescription during the post-intervention period. Multiple prescriptions are possible within patient.</population>
          <units>prescriptions</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>Rx Over 90</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="68"/>
                    <measurement group_id="B2" value="210"/>
                    <measurement group_id="B3" value="278"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Rx Not Over 90</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="737"/>
                    <measurement group_id="B2" value="1212"/>
                    <measurement group_id="B3" value="1949"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Co-prescription of Opioids and Benzodiazepines</title>
          <description>Physicians should avoid co-prescribing of opioids and benzodiazepines. This binary outcome captures the presence (or lack) of a written prescriptions for opioids within a 24-hour window on either side of a prescription for benzodiazepines.</description>
          <population>Sample limited to participants who had a prescription for benzodiazepines during the study period. There was not a requirement for a patient to have balanced data (i.e. prescriptions in both study periods) to be included in analysis.</population>
          <units>prescriptions</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>Co-Prescriptions</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="40"/>
                    <measurement group_id="B2" value="30"/>
                    <measurement group_id="B3" value="70"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Not Co-Prescriptions</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="20"/>
                    <measurement group_id="B2" value="86"/>
                    <measurement group_id="B3" value="106"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Patient Health Questionnaire-9 (PHQ-9)</title>
          <description>The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria as &quot;0&quot; (not at all) to &quot;3&quot; (nearly every day). The raw score was categorized by depression severity according to the scoring guide and analyzed as such.</description>
          <population>Because the instrument can be collected at each appointment, participants could contribute multiple responses.</population>
          <units>Responses</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>None</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="633"/>
                    <measurement group_id="B2" value="678"/>
                    <measurement group_id="B3" value="1311"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Mild</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="20"/>
                    <measurement group_id="B2" value="21"/>
                    <measurement group_id="B3" value="41"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Moderate</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="34"/>
                    <measurement group_id="B2" value="28"/>
                    <measurement group_id="B3" value="62"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Moderately Severe</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="32"/>
                    <measurement group_id="B2" value="31"/>
                    <measurement group_id="B3" value="63"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Severe</title>
              <analyzed_list>
                <analyzed>
                  <units>Participants</units>
                  <scope>Class</scope>
                  <count_list>
                    <count group_id="B1" value="445"/>
                    <count group_id="B2" value="506"/>
                    <count group_id="B3" value="951"/>
                  </count_list>
                </analyzed>
              </analyzed_list>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="23"/>
                    <measurement group_id="B2" value="26"/>
                    <measurement group_id="B3" value="49"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>PROMIS - Pain Interference Short Form 8a</title>
        <description>PROMIS - Pain Interference instruments assess self-reported consequences of pain on relevant aspects of one's life. This includes the extent to which pain hinders engagement with social, cognitive, emotional, physical, and recreational activities. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Pain Interference, a T-score of 60 is one SD higher pain than average. A t-score of 50 represents the mean pain interference reported by a representative US population.&#xD;
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.</description>
        <time_frame>Assessed at baseline at randomization, monthly up to 20 months after start of intervention (i.e. repeated measures).</time_frame>
        <population>Consists of all participants who contributed at least one response to the PROMIS-PI survey.</population>
        <group_list>
          <group group_id="O1">
            <title>Clinical Decision Support</title>
            <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
          </group>
          <group group_id="O2">
            <title>Patient Education and Activation Tools</title>
            <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
          </group>
        </group_list>
        <measure>
          <title>PROMIS - Pain Interference Short Form 8a</title>
          <description>PROMIS - Pain Interference instruments assess self-reported consequences of pain on relevant aspects of one's life. This includes the extent to which pain hinders engagement with social, cognitive, emotional, physical, and recreational activities. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Pain Interference, a T-score of 60 is one SD higher pain than average. A t-score of 50 represents the mean pain interference reported by a representative US population.&#xD;
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.</description>
          <population>Consists of all participants who contributed at least one response to the PROMIS-PI survey.</population>
          <units>score on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="89"/>
                <count group_id="O2" value="73"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="61.68" spread="9.22"/>
                    <measurement group_id="O2" value="60.26" spread="9.51"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Question: Which communication strategy used during the clinical encounter is more effective in reducing pain interference over time for patients with chronic pain who were taking opioids at baseline?&#xD;
Regression model includes a fixed effect for time and an interaction effect between pre/post intervention and intervention arm dummy variables. Analysis is clustered at the participant level.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.541</p_value>
            <method>Mixed Models Analysis</method>
            <method_desc>Test is on interaction term between time (pre/post intervention) and treatment group (CDSvsPEAT) dummy variables in the regression model.</method_desc>
            <param_type>Mean Difference (Net)</param_type>
            <param_value>-.69</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-2.9</ci_lower_limit>
            <ci_upper_limit>1.52</ci_upper_limit>
            <estimate_desc>The interaction term describes the effect of PEAT in the post period.</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>CG-CAHPS</title>
        <description>The Consumer Assessment of Healthcare Providers and System Clinician and Group Survey (CG-CAHPS) is a widely used PRO for collecting and reporting information from patients' about their experiences of care. We used the &quot;How well providers communicate with patients&quot; 6-item composite score. The response scale for these items was &quot;Yes, definitely&quot;, &quot;Yes, somewhat&quot;, and &quot;No&quot;. The composite score was represented as a binary value indicating whether a PCP received all &quot;top-box&quot; scores (represented by &quot;Yes, definitely&quot; responses) on the 6 items.&#xD;
We report the count of &quot;top box&quot; responses in the pre- and post-intervention periods by group. Analysis featured a mixed effects logistic regression model for repeated measures where the term of interest was an interaction term describing the change in the odds of a &quot;top box&quot; score in the PEAT group during the post-intervention period.</description>
        <time_frame>1-year pre-intervention vs. 1-year post-intervention (i.e. repeated measures).</time_frame>
        <population>Sample is limited to patients who returned a CG-CAHPS survey following a visit to their PCP.</population>
        <group_list>
          <group group_id="O1">
            <title>Clinical Decision Support</title>
            <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
          </group>
          <group group_id="O2">
            <title>Patient Education and Activation Tools</title>
            <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
          </group>
        </group_list>
        <measure>
          <title>CG-CAHPS</title>
          <description>The Consumer Assessment of Healthcare Providers and System Clinician and Group Survey (CG-CAHPS) is a widely used PRO for collecting and reporting information from patients' about their experiences of care. We used the &quot;How well providers communicate with patients&quot; 6-item composite score. The response scale for these items was &quot;Yes, definitely&quot;, &quot;Yes, somewhat&quot;, and &quot;No&quot;. The composite score was represented as a binary value indicating whether a PCP received all &quot;top-box&quot; scores (represented by &quot;Yes, definitely&quot; responses) on the 6 items.&#xD;
We report the count of &quot;top box&quot; responses in the pre- and post-intervention periods by group. Analysis featured a mixed effects logistic regression model for repeated measures where the term of interest was an interaction term describing the change in the odds of a &quot;top box&quot; score in the PEAT group during the post-intervention period.</description>
          <population>Sample is limited to patients who returned a CG-CAHPS survey following a visit to their PCP.</population>
          <units>Responses</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="170"/>
                <count group_id="O2" value="187"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Post-intervention : Top Box</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="188"/>
                    <measurement group_id="O2" value="194"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Post-intervention : Not Top Box</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="34"/>
                    <measurement group_id="O2" value="27"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Question: Which communication strategy used during the clinical encounter is more effective in improving how satisfied patients feel over time after communicating with their physician about chronic pain treatment risks and benefits?&#xD;
Regression model includes a fixed effect for time and an interaction effect between pre/post intervention and intervention arm dummy variables. Analysis is clustered at the PCP level.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.019</p_value>
            <method>Regression, Logistic</method>
            <method_desc>There were 69 providers with at least one CG-CAHPS response.</method_desc>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>2.96</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.20</ci_lower_limit>
            <ci_upper_limit>7.31</ci_upper_limit>
            <estimate_desc>The interaction term describes the change in the PEAT group's scores in the post period.</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>PROMIS Physical Function 6b v1.2</title>
        <description>PROMIS Physical Function instruments measure self-reported capability rather than actual performance of physical activities. A single Physical Function capability score is obtained from a short form. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Physical Function, a T-score of 60 is one SD better than average. By comparison, a Physical Function T-score of 40 is one SD worse than average.&#xD;
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.</description>
        <time_frame>Assessed at baseline at randomization, monthly up to 20 months after start of intervention (i.e. repeated measures).</time_frame>
        <population>Consists of all participants who contributed at least one response to the PROMIS-Physical Function survey.</population>
        <group_list>
          <group group_id="O1">
            <title>Clinical Decision Support</title>
            <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
          </group>
          <group group_id="O2">
            <title>Patient Education and Activation Tools</title>
            <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
          </group>
        </group_list>
        <measure>
          <title>PROMIS Physical Function 6b v1.2</title>
          <description>PROMIS Physical Function instruments measure self-reported capability rather than actual performance of physical activities. A single Physical Function capability score is obtained from a short form. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Physical Function, a T-score of 60 is one SD better than average. By comparison, a Physical Function T-score of 40 is one SD worse than average.&#xD;
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.</description>
          <population>Consists of all participants who contributed at least one response to the PROMIS-Physical Function survey.</population>
          <units>score on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="88"/>
                <count group_id="O2" value="72"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="38.26" spread="9.38"/>
                    <measurement group_id="O2" value="39.35" spread="9.29"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Question: Which communication strategy used during the clinical encounter is more effective in improving physical function over time for patients with chronic pain who were taking opioids at baseline?&#xD;
Regression model includes a fixed effect for time and an interaction effect between pre/post intervention and intervention arm dummy variables. Analysis is clustered at the participant level.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.719</p_value>
            <method>Mixed Models Analysis</method>
            <param_type>Mean Difference (Final Values)</param_type>
            <param_value>-.42</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-2.73</ci_lower_limit>
            <ci_upper_limit>1.88</ci_upper_limit>
            <estimate_desc>The interaction term describes the effect of PEAT in the post period.</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Number of Opioid Prescriptions Over 90 MME/Day Written by Physicians</title>
        <description>Physicians should avoid increasing dosage to ≥90 MME/day, and this measure compares odds of writing prescriptions over 90mme pre- vs. post-intervention</description>
        <time_frame>1-year pre-intervention vs. 1 year post-intervention</time_frame>
        <population>Includes patients with at least one Rx for opioids written by PCPs randomized in the study (i.e. does not include patients who had opioids written by physicians not included in the study).</population>
        <group_list>
          <group group_id="O1">
            <title>Clinical Decision Support</title>
            <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
          </group>
          <group group_id="O2">
            <title>Patient Education and Activation Tools</title>
            <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
          </group>
        </group_list>
        <measure>
          <title>Number of Opioid Prescriptions Over 90 MME/Day Written by Physicians</title>
          <description>Physicians should avoid increasing dosage to ≥90 MME/day, and this measure compares odds of writing prescriptions over 90mme pre- vs. post-intervention</description>
          <population>Includes patients with at least one Rx for opioids written by PCPs randomized in the study (i.e. does not include patients who had opioids written by physicians not included in the study).</population>
          <units>prescriptions</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="426"/>
                <count group_id="O2" value="483"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Post-intervention Rx Over 90</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="208"/>
                    <measurement group_id="O2" value="679"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Post-intervention Rx Not Over 90</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="3278"/>
                    <measurement group_id="O2" value="3625"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Question: Which communication strategy used during the clinical encounter is more effective in reducing opioid prescriptions of more than 90 morphine milligrams equivalent (MME) over time for patients with chronic pain who were taking opioids at baseline?&#xD;
Regression model includes a fixed effect for time and an interaction effect between pre/post intervention and intervention arm dummy variables. Analysis is clustered at the PCP level.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.010</p_value>
            <method>Mixed Models Analysis</method>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.63</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>1.13</ci_lower_limit>
            <ci_upper_limit>2.36</ci_upper_limit>
            <estimate_desc>The interaction term describes the effect of PEAT in the post period.</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Number of Opioid Co-prescription of Opioids and Benzodiazepines Written by Physicians</title>
        <description>Physicians should avoid co-prescribing of opioids and benzodiazepines. This binary outcome captures the presence (or lack) of a written prescriptions for opioids within a 24-hour window on either side of a prescription for benzodiazepines.</description>
        <time_frame>1-year pre-intervention vs. 1-year post-intervention</time_frame>
        <population>These are patients who had at least one prescription for benzodiazepines as written by their PCP, and where PCP was included in the study.</population>
        <group_list>
          <group group_id="O1">
            <title>Clinical Decision Support</title>
            <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
          </group>
          <group group_id="O2">
            <title>Patient Education and Activation Tools</title>
            <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
          </group>
        </group_list>
        <measure>
          <title>Number of Opioid Co-prescription of Opioids and Benzodiazepines Written by Physicians</title>
          <description>Physicians should avoid co-prescribing of opioids and benzodiazepines. This binary outcome captures the presence (or lack) of a written prescriptions for opioids within a 24-hour window on either side of a prescription for benzodiazepines.</description>
          <population>These are patients who had at least one prescription for benzodiazepines as written by their PCP, and where PCP was included in the study.</population>
          <units>prescriptions</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="113"/>
                <count group_id="O2" value="144"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>Co-Prescription</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="196"/>
                    <measurement group_id="O2" value="264"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Not Co-Prescription</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="139"/>
                    <measurement group_id="O2" value="168"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Question: Which communication strategy used during the clinical encounter is more effective in reducing co-prescription of opioids and benzodiazepines over time for patients with chronic pain who were taking opioids at baseline?</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.510</p_value>
            <method>Mixed Models Analysis</method>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>.76</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>.34</ci_lower_limit>
            <ci_upper_limit>1.71</ci_upper_limit>
            <estimate_desc>The interaction term describes the effect of PEAT in the post period.</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Patient Health Questionnaire-9 (PHQ-9)</title>
        <description>The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as &quot;0&quot; (not at all) to &quot;3&quot; (nearly every day). The raw score was categorized by severity according to the scoring guide and analyzed as such. Raw scores were assigned the following categories: 0-4, None; 5-9, Mild; 10-14, Moderate; 15-19, Moderately severe; and 20 or greater, Severe.&#xD;
We report the count of categorized PHQ-9 responses in the pre- (baseline characteristics) and post-intervention periods by group. Analysis featured a mixed effects ordered logistic regression model for repeated measures where the term of interest was an interaction describing the change in the odds of a &quot;top box&quot; score in the PEAT group during the post-intervention period. Analysis did not require balanced data (i.e. any scores in any time period meant patient was included).</description>
        <time_frame>1-year pre-intervention vs. 1-year post-intervention at all appointments (i.e. repeated measures).</time_frame>
        <population>Includes all subjects who had at least one PHQ-9 score in the medical record during the study period.</population>
        <group_list>
          <group group_id="O1">
            <title>Clinical Decision Support</title>
            <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
          </group>
          <group group_id="O2">
            <title>Patient Education and Activation Tools</title>
            <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
          </group>
        </group_list>
        <measure>
          <title>Patient Health Questionnaire-9 (PHQ-9)</title>
          <description>The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as &quot;0&quot; (not at all) to &quot;3&quot; (nearly every day). The raw score was categorized by severity according to the scoring guide and analyzed as such. Raw scores were assigned the following categories: 0-4, None; 5-9, Mild; 10-14, Moderate; 15-19, Moderately severe; and 20 or greater, Severe.&#xD;
We report the count of categorized PHQ-9 responses in the pre- (baseline characteristics) and post-intervention periods by group. Analysis featured a mixed effects ordered logistic regression model for repeated measures where the term of interest was an interaction describing the change in the odds of a &quot;top box&quot; score in the PEAT group during the post-intervention period. Analysis did not require balanced data (i.e. any scores in any time period meant patient was included).</description>
          <population>Includes all subjects who had at least one PHQ-9 score in the medical record during the study period.</population>
          <units>participants</units>
          <param>Number</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="445"/>
                <count group_id="O2" value="506"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <title>None</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="220"/>
                    <measurement group_id="O2" value="270"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Mild</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="9"/>
                    <measurement group_id="O2" value="16"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Moderate</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="17"/>
                    <measurement group_id="O2" value="23"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Moderately Severe</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="14"/>
                    <measurement group_id="O2" value="15"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Severe</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="4"/>
                    <measurement group_id="O2" value="11"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>PHQ-9 was categorized by assigning scores of 0, 1, 2, and 3 to the response categories (not at all: several days, more than half the days, nearly every day, respectively) and then summing. Scores of 5, 10, 15, and 20 represent cutpoints for mild, moderate, moderately severe and severe depression, respectively. The analysis was conducted as a multilevel ordered logistic regression.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.260</p_value>
            <method>Regression, Logistic</method>
            <method_desc>We employed robust standard errors clustered at the participant level. Time was controlled for using a fixed effect.</method_desc>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.34</param_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>.76</ci_lower_limit>
            <ci_upper_limit>2.34</ci_upper_limit>
            <estimate_desc>The interaction term describes the effect of PEAT in the post period.</estimate_desc>
          </analysis>
        </analysis_list>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>1 year</time_frame>
      <desc>As the interventions in this trial are not greater than minimal risk, our study was monitored by the Cedars-Sinai Medical Center's Institutional Review Board (IRB), which operates under a Federal-wide Assurance (FWA) approved by the Office of Human Research Protections of the U.S. Department of Health and Human Services. All adverse events were required to be reported to the IRB within 48 hours. Throughout the study period, we did not receive any reports of adverse events.</desc>
      <group_list>
        <group group_id="E1">
          <title>Clinical Decision Support</title>
          <description>Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.&#xD;
Clinical Decision Support: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.</description>
        </group>
        <group group_id="E2">
          <title>Patient Education and Activation Tools</title>
          <description>Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.&#xD;
Patient Education and Activation Tools: The patient education materials selected for this study: &quot;Pain Management: Which Treatment is Right for You,&quot; &quot;Preparing for Your Health Care Visit,&quot; and a video from the American Chronic Pain Association (ACPA) named &quot;A Car with Four Flat Tires,&quot; which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).</description>
        </group>
      </group_list>
      <serious_events>
        <default_assessment>Non-systematic Assessment</default_assessment>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, all-cause mortality</sub_title>
                <counts group_id="E1" subjects_affected="1" subjects_at_risk="445"/>
                <counts group_id="E2" subjects_affected="3" subjects_at_risk="506"/>
              </event>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="1" subjects_at_risk="445"/>
                <counts group_id="E2" subjects_affected="3" subjects_at_risk="506"/>
              </event>
            </event_list>
          </category>
          <category>
            <title>General disorders</title>
            <event_list>
              <event>
                <sub_title>Death</sub_title>
                <description>Death due to unrelated reasons.</description>
                <counts group_id="E1" events="1" subjects_affected="1" subjects_at_risk="445"/>
                <counts group_id="E2" events="3" subjects_affected="3" subjects_at_risk="506"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="445"/>
                <counts group_id="E2" subjects_affected="0" subjects_at_risk="506"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>Principal Investigators are NOT employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <limitations_and_caveats>Sample sizes for a number of outcomes (i.e. CG-CAHPS, PROMIS-PI, PROMIS-PF) were a fraction of the proposed targets due to low response rates associated with the survey phase of the study, threatening generalizability. Differences in satisfaction and prescribing rates between the two arms in the pre-intervention period pose challenges to interpreting difference in outcomes between arms. The presence of multiple interventions meant they may have been applied unevenly between the two arms.</limitations_and_caveats>
    <point_of_contact>
      <name_or_title>Brennan Spiegel</name_or_title>
      <organization>Cedars-Sinai Medical Center</organization>
      <phone>310-423-6467</phone>
      <email>brennan.spiegel@cshs.org</email>
    </point_of_contact>
  </clinical_results>
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03301623
org study id: Pro00049085
nct id: NCT03301623
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Investigators will compare Clinical Decision Support (CDS) versus Patient Education and
      Activation Tools (PEATs) in patients prescribed long-term or multiple opioids to measure
      outcomes that are important to patients. Primary outcomes are pain interference, physical
      function, and satisfaction with patient-physician communication. Secondary outcomes are
      overall Health-Related Quality of Life and high-risk prescribing, including prescriptions
      over 90 morphine milligram equivalents per day and co-prescribing of benzodiazepines and
      opioids.

      Patients in the PEAT arm will receive patient materials during the intervention, developed to
      engage patients in chronic pain treatment, prior to Primary Care Physician office visits. In
      the provider-facing CDS arm, PCPs will receive computerized reminders about appropriate
      opioid use during office visits for enrolled patients. Patients in both groups will receive
      questionnaires about pain interference, quality of life, and physician-patient communication
      through the patient portal one month after each visit to their Primary Care Physician (PCP).
      Investigators will use multi-level regression models to compare the effectiveness of these
      two communication strategies.
Investigators will compare two strategies: (1) Engage PCPs with Clinical Decision Support at
      the point of care, raising active alerts through the Electronic Health Record (EHR) when
      there is risk of inappropriate opioid prescribing, thus leading to informed decision-making
      with the patient about alternative treatments; versus (2) Engage patients prior to their PCP
      visit using Patient Education and Activation Tools (PEATs) administered via REDCap, helping
      patients to prepare for their visit and encouraging discussion about treatment preferences,
      values and treatment goals at the time of the visit, thus leading to shared decision-making
      with the provider. Our CDS intervention will use "Choosing Wisely" and Centers for Disease
      Control and Prevention (CDC) guidelines, and our Patient Education and Activation Tool
      intervention will use widely disseminated material developed by Consumer Reports and the
      ACPA. Investigators will assess whether improved communication and patient activation through
      these strategies improve patient-reported outcomes related to pain interference and HRQOL. To
      assess these outcomes, investigators will use NIH Patient Reported Outcome Measurement
      Information System (PROMIS®) questionnaires to capture health domains identified by our
      patient partners as most important. Using PROs will also help capture whether the use of
      either of these strategies leads to unintended consequences for patients when opioids are
      reduced and other pain management strategies are not substituted.

      Recruitment procedures: The study team mails study materials including an introductory
      brochure, information sheet, and initial contact letter to eligible participants. Eligible
      participants are then called and asked if they would like to enroll in the study, at which
      point the study team obtains consent over the phone. Non-responders, eligible participants
      who the study team has not been able to reach by phone and for whom a voicemail was left, are
      automatically enrolled in an abbreviated arm of the study after two weeks of non-response.
      Those enrolled in both the full study PEATs group and abbreviated PEATs group will be sent
      the PEATs materials two days before an appointment with their primary care clinician.
      Participants may choose to opt out of any arm of the study.

      Data collection: Upon enrollment in the fully study, investigators will send patients an
      enrollment questionnaire, which includes questions on education, language proficiency, and
      health literacy. At this point, investigators will also send the two PROMIS questionnaires
      (pain interference and physical function) via REDCap. The study team has programmed the
      surveys to be sent via automatic email in REDCap. The email will contain a link where
      participants can access the questionnaire and redeem their Amazon gift card instantly. The
      total time to take this questionnaire is 2 minutes.

      All enrolled participants will receive monthly PROMIS questionnaires during the 12-month
      intervention period. Enrolled patients who have any follow-up visits during this intervention
      period in both full study arms will be sent the Communication Questionnaire (COMRADE) via
      REDCap one day after each office visit with their PCP.

      For participants enrolled in the abbreviated arm of the study, the study team will have
      access to medical records that will allow for a retrospective pull of relevant
      patient-reported outcome measures and PCP satisfaction data collected by the health system.
allocation: Randomized
intervention model: Parallel Assignment
intervention model description: The study team will randomize the study on the provider level and use a random number generator to assign providers to study arms.
Patients within the physicians randomized to the Informed Decision Making (IDM) arm will not receive the PEAT materials; their physicians will receive the CDS alerts via the EHR when certain order criteria are triggered appropriately.
Patients within the physicians randomized to the Shared Decision Making (SDM) arm will receive the PEAT materials via REDCap two days before their PCP office visit. They will receive these materials every time they have an office visit with their PCP.
primary purpose: Health Services Research
masking: None (Open Label)
measure: PROMIS - Pain Interference Short Form 8a
time frame: Assessed at baseline at randomization, monthly up to 20 months after start of intervention (i.e. repeated measures).
description: PROMIS - Pain Interference instruments assess self-reported consequences of pain on relevant aspects of one's life. This includes the extent to which pain hinders engagement with social, cognitive, emotional, physical, and recreational activities. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Pain Interference, a T-score of 60 is one SD higher pain than average. A t-score of 50 represents the mean pain interference reported by a representative US population.
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.
measure: CG-CAHPS
time frame: 1-year pre-intervention vs. 1-year post-intervention (i.e. repeated measures).
description: The Consumer Assessment of Healthcare Providers and System Clinician and Group Survey (CG-CAHPS) is a widely used PRO for collecting and reporting information from patients' about their experiences of care. We used the "How well providers communicate with patients" 6-item composite score. The response scale for these items was "Yes, definitely", "Yes, somewhat", and "No". The composite score was represented as a binary value indicating whether a PCP received all "top-box" scores (represented by "Yes, definitely" responses) on the 6 items.
We report the count of "top box" responses in the pre- and post-intervention periods by group. Analysis featured a mixed effects logistic regression model for repeated measures where the term of interest was an interaction term describing the change in the odds of a "top box" score in the PEAT group during the post-intervention period.
measure: PROMIS Physical Function 6b v1.2
time frame: Assessed at baseline at randomization, monthly up to 20 months after start of intervention (i.e. repeated measures).
description: PROMIS Physical Function instruments measure self-reported capability rather than actual performance of physical activities. A single Physical Function capability score is obtained from a short form. The forms are universal rather than disease-specific. A higher PROMIS T-score represents more of the concept. For Physical Function, a T-score of 60 is one SD better than average. By comparison, a Physical Function T-score of 40 is one SD worse than average.
We report pre- and post-intervention means. Analysis featured a linear mixed model for repeated measures where the term of interest was an interaction term describing the change in the PEAT group during the post-intervention period.
measure: Number of Opioid Prescriptions Over 90 MME/Day Written by Physicians
time frame: 1-year pre-intervention vs. 1 year post-intervention
description: Physicians should avoid increasing dosage to ≥90 MME/day, and this measure compares odds of writing prescriptions over 90mme pre- vs. post-intervention
measure: Number of Opioid Co-prescription of Opioids and Benzodiazepines Written by Physicians
time frame: 1-year pre-intervention vs. 1-year post-intervention
description: Physicians should avoid co-prescribing of opioids and benzodiazepines. This binary outcome captures the presence (or lack) of a written prescriptions for opioids within a 24-hour window on either side of a prescription for benzodiazepines.
measure: Patient Health Questionnaire-9 (PHQ-9)
time frame: 1-year pre-intervention vs. 1-year post-intervention at all appointments (i.e. repeated measures).
description: The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The raw score was categorized by severity according to the scoring guide and analyzed as such. Raw scores were assigned the following categories: 0-4, None; 5-9, Mild; 10-14, Moderate; 15-19, Moderately severe; and 20 or greater, Severe.
We report the count of categorized PHQ-9 responses in the pre- (baseline characteristics) and post-intervention periods by group. Analysis featured a mixed effects ordered logistic regression model for repeated measures where the term of interest was an interaction describing the change in the odds of a "top box" score in the PEAT group during the post-intervention period. Analysis did not require balanced data (i.e. any scores in any time period meant patient was included).
arm group label: Clinical Decision Support
arm group type: Experimental
description: Patients within the physicians randomized to the IDM arm will receive the Clinical Decision Support alerts via the EHR when certain order criteria are triggered appropriately.
arm group label: Patient Education and Activation Tools
arm group type: Experimental
description: Patients within the physicians randomized to SDM will receive the PEAT materials via REDCap two days prior to their PCP office visit. They will receive these materials every time they have an office visit with their PCP.
intervention type: Other
intervention name: Clinical Decision Support
description: The CDS intervention will test the use of existing guideline-based EHR alerts related to the prescription of opioids. CDS alerts employ computer algorithms that account for patient characteristics and diagnoses to deliver reminders of appropriate use when a provider enters an order for a medication.
arm group label: Clinical Decision Support
intervention type: Other
intervention name: Patient Education and Activation Tools
description: The patient education materials selected for this study: "Pain Management: Which Treatment is Right for You," "Preparing for Your Health Care Visit," and a video from the American Chronic Pain Association (ACPA) named "A Car with Four Flat Tires," which helps to give patients a better understanding of how multi-modal treatment can be more effective than relying on one source of treatment (e.g., pain medication).
arm group label: Patient Education and Activation Tools
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Brennan Spiegel, MD, MSHS
role: Principal Investigator
affiliation: Cedars-Sinai Medical Center
facility: 
country: United States
citation: Ballantyne JC, Sullivan MD. Intensity of Chronic Pain--The Wrong Metric? N Engl J Med. 2015 Nov 26;373(22):2098-9. doi: 10.1056/NEJMp1507136. No abstract available.
PMID: 26605926
citation: Centers for Disease Control and Prevention (CDC). Vital signs: overdoses of prescription opioid pain relievers---United States, 1999--2008. MMWR Morb Mortal Wkly Rep. 2011 Nov 4;60(43):1487-92.
PMID: 22048730
citation: Daubresse M, Chang HY, Yu Y, Viswanathan S, Shah ND, Stafford RS, Kruszewski SP, Alexander GC. Ambulatory diagnosis and treatment of nonmalignant pain in the United States, 2000-2010. Med Care. 2013 Oct;51(10):870-8. doi: 10.1097/MLR.0b013e3182a95d86.
PMID: 24025657
citation: Dorn SD, Meek PD, Shah ND. Increasing frequency of opioid prescriptions for chronic abdominal pain in US outpatient clinics. Clin Gastroenterol Hepatol. 2011 Dec;9(12):1078-85.e1. doi: 10.1016/j.cgh.2011.08.008. Epub 2011 Aug 18. Erratum In: Clin Gastroenterol Hepatol. 2012 Mar;10(3):332.
PMID: 21854735
citation: Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain--United States, 2016. JAMA. 2016 Apr 19;315(15):1624-45. doi: 10.1001/jama.2016.1464.
PMID: 26977696
citation: Wilsey BL, Fishman SM, Crandall M, Casamalhuapa C, Bertakis KD. A qualitative study of the barriers to chronic pain management in the ED. Am J Emerg Med. 2008 Mar;26(3):255-63. doi: 10.1016/j.ajem.2007.05.005.
PMID: 18358933
citation: Bhamb B, Brown D, Hariharan J, Anderson J, Balousek S, Fleming MF. Survey of select practice behaviors by primary care physicians on the use of opioids for chronic pain. Curr Med Res Opin. 2006 Sep;22(9):1859-65. doi: 10.1185/030079906X132398.
PMID: 16968589
citation: Hooten WM, Bruce BK. Beliefs and attitudes about prescribing opioids among healthcare providers seeking continuing medical education. J Opioid Manag. 2011 Nov-Dec;7(6):417-24. doi: 10.5055/jom.2011.0082.
PMID: 22320023
citation: Kavukcu E, Akdeniz M, Avci HH, Altug M, Oner M. Chronic noncancer pain management in primary care: family medicine physicians' risk assessment of opioid misuse. Postgrad Med. 2015 Jan;127(1):22-6. doi: 10.1080/00325481.2015.993572. Epub 2014 Dec 25.
PMID: 25539797
citation: McCarthy DM, Cameron KA, Courtney DM, Adams JG, Engel KG. Communication about opioid versus nonopioid analgesics in the emergency department. J Opioid Manag. 2015 May-Jun;11(3):229-36. doi: 10.5055/jom.2015.0271.
PMID: 25985807
citation: Morse JS, Stockbridge H, Egan KB, Mai J, Wickizer T, Franklin GM. Primary care survey of the value and effectiveness of the Washington State Opioid Dosing Guideline. J Opioid Manag. 2011 Nov-Dec;7(6):427-33. doi: 10.5055/jom.2011.0083.
PMID: 22320024
citation: Manchikanti L, Manchikanti KN, Pampati V, Cash KA. Prevalence of side effects of prolonged low or moderate dose opioid therapy with concomitant benzodiazepine and/or antidepressant therapy in chronic non-cancer pain. Pain Physician. 2009 Jan-Feb;12(1):259-67.
PMID: 19165308
citation: Mahowald ML, Singh JA, Majeski P. Opioid use by patients in an orthopedics spine clinic. Arthritis Rheum. 2005 Jan;52(1):312-21. doi: 10.1002/art.20784.
PMID: 15641058
citation: Luo X, Pietrobon R, Hey L. Patterns and trends in opioid use among individuals with back pain in the United States. Spine (Phila Pa 1976). 2004 Apr 15;29(8):884-90; discussion 891. doi: 10.1097/00007632-200404150-00012.
PMID: 15082989
citation: Ives TJ, Chelminski PR, Hammett-Stabler CA, Malone RM, Perhac JS, Potisek NM, Shilliday BB, DeWalt DA, Pignone MP. Predictors of opioid misuse in patients with chronic pain: a prospective cohort study. BMC Health Serv Res. 2006 Apr 4;6:46. doi: 10.1186/1472-6963-6-46.
PMID: 16595013
citation: Fredheim OMS, Borchgrevink PC, Mahic M, Skurtveit S. A pharmacoepidemiological cohort study of subjects starting strong opioids for nonmalignant pain: a study from the Norwegian Prescription Database. Pain. 2013 Nov;154(11):2487-2493. doi: 10.1016/j.pain.2013.07.033. Epub 2013 Sep 24.
PMID: 24075311
citation: Burgess DJ, Crowley-Matoka M, Phelan S, Dovidio JF, Kerns R, Roth C, Saha S, van Ryn M. Patient race and physicians' decisions to prescribe opioids for chronic low back pain. Soc Sci Med. 2008 Dec;67(11):1852-60. doi: 10.1016/j.socscimed.2008.09.009. Epub 2008 Oct 15.
PMID: 18926612
citation: Adams NJ, Plane MB, Fleming MF, Mundt MP, Saunders LA, Stauffacher EA. Opioids and the treatment of chronic pain in a primary care sample. J Pain Symptom Manage. 2001 Sep;22(3):791-6. doi: 10.1016/s0885-3924(01)00320-7.
PMID: 11532592
citation: Gaskin DJ, Richard P. The economic costs of pain in the United States. J Pain. 2012 Aug;13(8):715-24. doi: 10.1016/j.jpain.2012.03.009. Epub 2012 May 16.
PMID: 22607834
citation: Chapman JB, Lehman CL, Elliott J, Clark JD. Sleep quality and the role of sleep medications for veterans with chronic pain. Pain Med. 2006 Mar-Apr;7(2):105-14. doi: 10.1111/j.1526-4637.2006.00110.x.
PMID: 16634723
citation: King SA, Strain JJ. Benzodiazepine use by chronic pain patients. Clin J Pain. 1990 Jun;6(2):143-7. doi: 10.1097/00002508-199006000-00013.
PMID: 1983726
citation: Menefee LA, Frank ED, Doghramji K, Picarello K, Park JJ, Jalali S, Perez-Schwartz L. Self-reported sleep quality and quality of life for individuals with chronic pain conditions. Clin J Pain. 2000 Dec;16(4):290-7. doi: 10.1097/00002508-200012000-00003.
PMID: 11153783
citation: Ritzwoller DP, Crounse L, Shetterly S, Rublee D. The association of comorbidities, utilization and costs for patients identified with low back pain. BMC Musculoskelet Disord. 2006 Sep 18;7:72. doi: 10.1186/1471-2474-7-72.
PMID: 16982001
citation: Friedman BW, Chilstrom M, Bijur PE, Gallagher EJ. Diagnostic testing and treatment of low back pain in United States emergency departments: a national perspective. Spine (Phila Pa 1976). 2010 Nov 15;35(24):E1406-11. doi: 10.1097/BRS.0b013e3181d952a5.
PMID: 21030902
citation: Gilbert FJ, Grant AM, Gillan MG, Vale LD, Campbell MK, Scott NW, Knight DJ, Wardlaw D; Scottish Back Trial Group. Low back pain: influence of early MR imaging or CT on treatment and outcome--multicenter randomized trial. Radiology. 2004 May;231(2):343-51. doi: 10.1148/radiol.2312030886. Epub 2004 Mar 18.
PMID: 15031430
citation: Kerry S, Hilton S, Patel S, Dundas D, Rink E, Lord J. Routine referral for radiography of patients presenting with low back pain: is patients' outcome influenced by GPs' referral for plain radiography? Health Technol Assess. 2000;4(20):i-iv, 1-119. No abstract available.
PMID: 11044957
responsible party type: Principal Investigator
investigator affiliation: Cedars-Sinai Medical Center
investigator full name: Brennan Spiegel
investigator title: Principal Investigator
mesh term: Chronic Pain
sharing ipd: No
provided document: 
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
limitations and caveats: Sample sizes for a number of outcomes (i.e. CG-CAHPS, PROMIS-PI, PROMIS-PF) were a fraction of the proposed targets due to low response rates associated with the survey phase of the study, threatening generalizability. Differences in satisfaction and prescribing rates between the two arms in the pre-intervention period pose challenges to interpreting difference in outcomes between arms. The presence of multiple interventions meant they may have been applied unevenly between the two arms.
point of contact: 