Comparative Performance of Three Claims-Based Frailty Measures Among Medicare Beneficiaries.

Frailty is an important predictor of mortality, health care costs and utilization, and health outcomes. Validated measures of frailty are not consistently collected during clinical encounters, making comparisons across populations challenging. However, several claims-based algorithms have been developed to predict frailty and related concepts. This study compares performance of three such algorithms among Medicare beneficiaries. Claims data from 12-month continuous enrollment periods were selected during 2014-2016. Frailty scores, calculated using previously developed algorithms from Faurot, Kim, and RAND, were added to baseline regression models to predict claims-based outcomes measured in the following year. Root mean square error and area under the receiver operating characteristic curve were calculated for each model and outcome combination and tested in subpopulations of interest. Overall, Kim models performed best across most outcomes, metrics, and subpopulations. Kim frailty scores may be used by health systems and researchers for risk adjustment or targeting interventions.

Development and Validation of Algorithms to Predict Activity, Mobility, and Memory Limitations Using Medicare Claims and Post-Acute Care Assessments.

Functional impairment predicts mortality and health care utilization. However, validated measures of functional impairment are not routinely collected during clinical encounters and are impractical to use for large-scale risk-adjustment or targeting interventions. This study's purpose was to develop and validate claims-based algorithms to predict functional impairment using Medicare Fee-for-Service (FFS) 2014-2017 claims data linked with post-acute care (PAC) assessment data and weighted to better represent the overall Medicare FFS population. Using supervised machine learning, predictors were identified that best predicted two functional impairment outcomes measured in PAC data-any memory limitation and a count of 0-6 activity/mobility limitations. The memory limitation algorithm had moderately high sensitivity and specificity. The activity/mobility limitations algorithm performed well in identifying beneficiaries with five or more limitations, but overall accuracy was poor. This dataset shows promise for use in PAC populations, though generalizability to broader older adult populations remains a challenge.

Understanding the social risk factor adjustment's effect on Star Ratings.

OBJECTIVES: CMS implemented the Categorical Adjustment Index (CAI) to address measurement bias in the Medicare Advantage (MA) Star Ratings, as unadjusted scores may disadvantage MA contracts serving more enrollees at greater social risk. CAI values are added to a contract's Star Ratings to adjust for the mean within-contract performance disparity associated with its percentage of enrollees with low socioeconomic status (ie, receipt of a Part D low-income subsidy or dual eligibility for Medicare and Medicaid [LIS/DE]) and who are disabled. We examined the CAI's effect on Star Ratings and the type of contracts affected. STUDY DESIGN: Observational study of MA contracts with health and prescription drug coverage. METHODS: We compared adjusted and unadjusted 2017-2020 Star Ratings overall and by contracts' proportion of LIS/DE and disabled enrollees. We assessed the CAI's effect on qualifying for quality bonus payments (QBPs), eligibility for rebate payments, and high-performing and low-performing designations. RESULTS: The CAI's impact was modest overall (3.2%-14.9% of contracts experienced one-half Star Rating changes). Upward changes were concentrated among contracts with high percentages of LIS/DE or disabled enrollees (7.7%-32.3% of these contracts saw increased Star Ratings). In 2020, 26.0% of contracts with a high proportion of LIS/DE or disabled enrollees that qualified for a QBP did so because of the CAI. CONCLUSIONS: The CAI primarily affected contracts with high LIS/DE or disabled enrollment, which received higher Star Ratings because of the CAI. The adjustment helps ensure that such contracts' performance is not understated and reduces incentives for MA contracts to avoid patients at greater social risk.

Imputation of Race and Ethnicity in Health Insurance Marketplace Enrollment Data, 2015-2022 Open Enrollment Periods.

Information on the race and ethnicity of individuals enrolled through the HealthCare.gov Health Insurance Marketplace is critical for assessing past enrollment efforts and determining whether outreach campaigns should be modified or tailored moving forward. However, approximately one-third of insurance applicants do not complete the race and Hispanic ethnicity questions on the Marketplace application. When self-reported race and ethnicity information is missing, other information about an individual can be used to infer race and ethnicity, such as surnames, first names, and addresses, with each characteristic contributing meaningfully to the identification of six mutually exclusive racial and ethnic groups: American Indian (AI)/Alaskan Native (AN); Asian American, Native Hawaiian, and Pacific Islander (AANHPI); Black; Hispanic; Multiracial; and White. Surnames are particularly useful for distinguishing people who identify as Hispanic and AANHPI from other racial and ethnic groups. Geocoded address information is particularly useful in distinguishing Black and White individuals who frequently reside in racially segregated neighborhoods. This article presents the results of imputing race and ethnicity for Marketplace enrollees from 2015 through 2022 using the modified Bayesian Improved First Name Surname and Geocoding (BIFSG) method, developed by the RAND Corporation, which uses surnames, first names, and residential addresses to indirectly estimate race and ethnicity.

Visit Frequency and Outcomes for Patients Using Ongoing Chiropractic Care for Chronic Low-Back and Neck Pain: An Observational Longitudinal Study.

BACKGROUND: Chronic spinal pain is prevalent and long-lasting. Although provider-based nonpharmacologic therapies, such as chiropractic care, have been recommended, healthcare and coverage policies provide little guidance or evidence regarding long-term use of this care. OBJECTIVE: To determine the relationships between visit frequency and outcomes for patients using ongoing chiropractic care for chronic spinal pain. STUDY DESIGN: Observational 3-month longitudinal study. SETTING: Data collected from patients of 124 chiropractic clinics in 6 United States regions. METHODS: We examined the impact of visit frequency and patient characteristics on pain (pain 0-10 numeric rating scale) and functional outcomes (Oswestry Disability Index [ODI] for low-back pain and Neck Disability Index [NDI] for neck pain, both 0-100 scale) using hierarchical linear modeling (HLM) in a large national sample of chiropractic patients with chronic low back pain (CLBP) and/or chronic neck pain (CNP). This study was approved by the RAND Human Subjects Protection Committee and registered under ClinicalTrials.gov Identifier: NCT03162952. RESULTS: One thousand, three hundred, sixty-two patients with CLBP and 1,214 with CNP were included in a series of HLM models. Unconditional (time-only) models showed patients on average had mild pain and function, and significant, but slight improvements in these over the 3-month observation period: back and neck pain decreased by 0.40 and 0.44 points, respectively; function improved by 2.7 (ODI) and 3.0 points (NDI) (all P < 0.001). Adding chiropractic visit frequency to the models revealed that those with worse baseline pain and function used more visits, but only visits more than once per week for those with CLBP were associated with significantly better improvement. These relationships remained when other types of visits and baseline patient characteristics were included. LIMITATIONS: This is an observational study based on self-reported data from a sample representative of chiropractic patients, but not all patients with CLBP or CNP. CONCLUSIONS: This 3-month window on chiropractic patients with CLBP and/or CNP revealed that they were improving, although slowly; may have reached maximum therapeutic improvement; and are possibly successfully managing their chronic pain using a variety of chiropractic visit frequencies. These results may inform payers when building coverage policies for ongoing chiropractic care for patients with chronic pain.

Health Care Costs and Opioid Use Associated With High-impact Chronic Spinal Pain in the United States.

STUDY DESIGN: A descriptive analysis of secondary data. OBJECTIVE: The aim of this study was to estimate health care costs and opioid use for those with high-impact chronic spinal (back and neck) pain. SUMMARY OF BACKGROUND DATA: The US National Pain Strategy introduced a focus on high-impact chronic pain-that is, chronic pain associated with work, social, and self-care restrictions. Chronic neck and low-back pain are common, costly, and associated with long-term opioid use. Although chronic pain is not homogenous, most estimates of its costs are averages that ignore severity (impact). METHODS: We used 2003 to 2015 Medical Expenditures Panel Survey (MEPS) data to identify individuals with chronic spinal pain, their health care expenditures, and use of opioids. We developed prediction models to identify those with high- versus moderate- and low-impact chronic spinal pain based on the variables available in MEPS. RESULTS: We found that overall and spine-related health care costs, and the use and dosage of opioids increased significantly with chronic pain impact levels. Overall and spine-related annual per person health care costs for those with high-impact chronic pain ($14,661 SE: $814; and $5979 SE: $471, respectively) were more than double that of those with low-impact, but still clinically significant, chronic pain ($6371 SE: $557; and $2300 SE: $328). Those with high-impact chronic spinal pain also use spine-related opioids at a rate almost four times that of those with low-impact pain (48.4% vs. 12.4%), and on average use over five times the morphine equivalent daily dose (MEDD) in mg (15.3 SE: 1.4 vs. 2.7 SE: 0.6). Opioid use and dosing increased significantly across years, but the increase in inflation-adjusted health care costs was not statistically significant. CONCLUSION: Although most studies of chronic spinal pain do not differentiate participants by the impact of their chronic pain, these estimates highlight the importance of identifying chronic pain levels and focusing on those with high-impact chronic pain. LEVEL OF EVIDENCE: 3.

Perspectives on Opportunities and Challenges for Medicare Advantage Plans to Address Social Determinants of Health via the CHRONIC Care Act.

There is increasing recognition of the role of social determinants of health (SDOH) in the ability of Medicare Advantage (MA) enrollees to obtain needed care. The 2018 CHRONIC Care Act established Special Supplemental Benefits for the Chronically Ill (SSBCI), which for the first time gives MA plans the flexibility to provide supplemental benefits to enrollees to address SDOH. Given the role of SDOH in chronic disease, this represents an opportunity for MA plans to address underlying issues not strictly health care related with which MA enrollees struggle and that affect their overall health. MA plans have experimented with different approaches to address SDOH but have been limited by the lack of ability to offer services as part of covered benefits and reliance on partnerships, grants, and other funding sources to support the provision of these services. The effect of this policy and how it may evolve before implementation begins in 2020 remains uncertain as we wait to see how MA plans will interpret eligibility criteria and services offered without any additional allotted funding.

Are Nonpharmacologic Interventions for Chronic Low Back Pain More Cost Effective Than Usual Care? Proof of Concept Results From a Markov Model.

STUDY DESIGN: Markov model. OBJECTIVE: Examine the 1-year effectiveness and cost-effectiveness (societal and payer perspectives) of adding nonpharmacologic interventions for chronic low back pain (CLBP) to usual care using a decision analytic model-based approach. SUMMARY OF BACKGROUND DATA: Treatment guidelines now recommend many safe and effective nonpharmacologic interventions for CLBP. However, little is known regarding their effectiveness in subpopulations (e.g., high-impact chronic pain patients), nor about their cost-effectiveness. METHODS: The model included four health states: high-impact chronic pain (substantial activity limitations); no pain; and two others without activity limitations, but with higher (moderate-impact) or lower (low-impact) pain. We estimated intervention-specific transition probabilities for these health states using individual patient-level data from 10 large randomized trials covering 17 nonpharmacologic therapies. The model was run for nine 6-week cycles to approximate a 1-year time horizon. Quality-adjusted life-year weights were based on six-dimensional health state short form scores; healthcare costs were based on 2003 to 2015 Medical Expenditure Panel Survey data; and lost productivity costs used in the societal perspective were based on reported absenteeism. Results were generated for two target populations: (1) a typical baseline mix of patients with CLBP (25% low-impact, 35% moderate-impact, and 40% high-impact chronic pain) and (2) high-impact chronic pain patients. RESULTS: From the societal perspective, all but two of the therapies were cost effective (<$50,000/quality-adjusted life-year) for a typical patient mix and most were cost saving. From the payer perspective fewer were cost saving, but the same number was cost-effective. Assuming all patients in the model have high-impact chronic pain increases the effectiveness and cost-effectiveness of most, but not all, therapies indicating that substantial benefits are possible in this subpopulation. CONCLUSION: Modeling leverages the evidence produced from clinical trials to provide more information than is available in the published studies. We recommend modeling for all existing studies of nonpharmacologic interventions for CLBP. LEVEL OF EVIDENCE: 4.

Patient Willingness to Pay for Reductions in Chronic Low Back Pain and Chronic Neck Pain.

Many recommended nonpharmacologic therapies for patients with chronic spinal pain require visits to providers such as acupuncturists and chiropractors. Little information is available to inform third-party payers' coverage policies regarding ongoing use of these therapies. This study offers contingent valuation-based estimates of patient willingness to pay (WTP) for pain reductions from a large (n = 1,583) sample of patients using ongoing chiropractic care to manage their chronic low back and neck pain. Average WTP estimates were $45.98 (45.8) per month per 1-point reduction in current pain for chronic low back pain and $37.32 (38.0) for chronic neck pain. These estimates met a variety of validity checks including that individuals' values define a downward-sloping demand curve for these services. Comparing these WTP estimates with patients' actual use of chiropractic care over the next 3 months indicates that these patients are likely "buying" perceived pain reductions from what they believe their pain would have been if they didn't see their chiropractor-that is, they value maintenance of their current mild pain levels. These results provide some evidence for copay levels and their relationship to patient demand, but call into question ongoing coverage policies that require the documentation of continued improvement or of experienced clinical deterioration with treatment withdrawal. PERSPECTIVE: This study provides estimates of reported WTP for pain reduction from a large sample of patients using chiropractic care to manage their chronic spinal pain and compares these estimates to what these patients do for care over the next 3 months, to inform coverage policies for ongoing care.

Exploring the prevalence and construct validity of high-impact chronic pain across chronic low-back pain study samples.

BACKGROUND CONTEXT: The US National Pain Strategy focused attention on high-impact chronic pain and its restrictions. Although many interventions have been studied for chronic low-back pain, results are typically reported for heterogeneous samples. To better understand chronic pain and target interventions to those who most need care, more granular classifications recognizing chronic pain's impact are needed. PURPOSE: To test whether chronic pain impact levels can be identified in chronic low-back pain clinical trial samples, examine the baseline patient mix across studies, and evaluate the construct validity of high-impact chronic pain. STUDY DESIGN/SETTING: Descriptive analyses using 12 large study datasets. PATIENT SAMPLES: Chronic low-back pain patients in nonsurgical, nonpharmacologic trials in the US, Canada, and UK. OUTCOME MEASURES: Preference-based health utilities from the SF-6D and EQ-5D, employment status and absenteeism. METHODS: We used two logistic regression models to predict whether patients had high-impact chronic pain and whether the remainder had low- or moderate-impact chronic pain. We developed these models using two datasets. Models with the best predictive power were used to impute impact levels for six other datasets. Stratified by these estimated chronic pain impact levels, we characterized the case mix of patients at baseline in each dataset, and summarized their health-utilities and work productivity. This study was funded by a National Center for Complementary and Integrative Medicine grant. The authors have no potential conflicts of interest. RESULTS: The logistic models had excellent predictive power to identify those with high-impact chronic pain. Although studies were all of chronic low-back pain patients, the baseline mix of patients varied widely. Across all datasets, utilities, and productivity were similar for those with high-impact chronic pain and worsened as chronic pain impact increased. CONCLUSIONS: There is a need to better categorize chronic pain patients to allow the targeting of optimal interventions for those with each level of chronic pain impact.

The expansion of National Healthcare Safety Network enrollment and reporting in nursing homes: Lessons learned from a national qualitative study.

BACKGROUND: This study explored nursing home (NH) personnel perceptions of the National Healthcare Safety Network (NHSN). METHODS: NHs were purposively sampled based on NHSN enrollment and reporting status, and other facility characteristics. We recruited NH personnel knowledgeable about the facility's decision-making processes and infection prevention program. Interviews were conducted over-the-phone and audio-recorded; transcripts were analyzed using conventional content analysis. RESULTS: We enrolled 14 NHs across the United States and interviewed 42 personnel. Six themes emerged: Benefits of NHSN, External Support and Motivation, Need for a Champion, Barriers, Risk Adjustment, and Data Integrity. We did not find substantive differences in perceptions of NHSN value related to participants' professional roles or enrollment category. Some participants from newly enrolled NHs felt well supported through the NHSN enrollment process, while participants from earlier enrolled NHs perceived the process to be burdensome. Among participants from non-enrolled NHs, as well as some from enrolled NHs, there was a lack of knowledge of NHSN. CONCLUSIONS: This qualitative study helps fill a gap in our understanding of barriers and facilitators to NHSN enrollment and reporting in NHs. Improved understanding of factors influencing decision-making processes to enroll in and maintain reporting to NHSN is an important first step towards strengthening infection surveillance in NHs.

Reducing disparities requires multiple strategies.

Disparities in care are a complex issue requiring multiple strategies to solve, including approaches to improve the measurement of quality and reporting stratified performance estimates.

Adjusting Medicare Advantage star ratings for socioeconomic status and disability.

OBJECTIVES: Studies have identified potential unintended effects of not adjusting clinical performance measures in value-based purchasing programs for socioeconomic status (SES) factors. We examine the impact of SES and disability adjustments on Medicare Advantage (MA) plans' and prescription drug plans' (PDPs') contract star ratings. These analyses informed the development of the Categorical Adjustment Index (CAI), which CMS implemented with the 2017 star ratings. STUDY DESIGN: Retrospective analyses of MA and PDP performance using 2012 Medicare beneficiary-level characteristics and performance data from the Star Rating Program. METHODS: We modeled within-contract associations of beneficiary SES (Medicaid and Medicare dual eligibility [DE] or receipt of a low-income subsidy [LIS]) and disability with performance on 16 clinical measures. We estimated variability in contract-level DE/LIS and disability disparities using mixed-effects regression models. We simulated the impact of applying the CAI to adjust star ratings for DE/LIS and disability to construct the 2017 star ratings. RESULTS: DE/LIS was negatively associated with performance for 12 of 16 measures and positively associated for 2 of 16 measures. Disability was negatively associated with performance for 11 of 15 measures and positively associated for 3 of 15 measures. Adjusting star ratings using the CAI resulted in half-star rating increases for 8.5% of MA and 33.3% of PDP contracts that exceeded 50% DE/LIS beneficiaries. CONCLUSIONS: Increases in star ratings following adjustment of clinical performance for SES and disability using the CAI focused on contracts with higher percentages of DE/LIS beneficiaries. Adjustment for enrollee characteristics may improve the accuracy of quality measurement and remove incentives for providers to avoid caring for more challenging patient populations.

Characteristics of Chiropractic Patients Being Treated for Chronic Low Back and Neck Pain.

OBJECTIVES: Chronic low back pain (CLBP) and chronic neck pain (CNP) are the most common types of chronic pain, and chiropractic spinal manipulation is a common nonpharmacologic treatment. This study presents the characteristics of a large United States sample of chiropractic patients with CLBP and CNP. METHODS: Data were collected from chiropractic patients using multistage systematic stratified sampling with 4 sampling levels: regions and states, sites (ie, metropolitan areas), providers and clinics, and patients. The sites and regions were San Diego, California; Tampa, Florida; Minneapolis, Minnesota; Seneca Falls and Upstate New York; Portland, Oregon; and Dallas, Texas. Data were collected from patients through an iPad-based prescreening questionnaire in the clinic and emailed links to full screening and baseline online questionnaires. The goal was 20 providers or clinics and 7 patients with CLBP and 7 with CNP from each clinic. RESULTS: We had 6342 patients at 125 clinics complete the prescreening questionnaire, 3333 patients start the full screening questionnaire, and 2024 eligible patients completed the baseline questionnaire: 518 with CLBP only, 347 with CNP only, and 1159 with both. In general, most of this sample were highly-educated, non-Hispanic, white females with at least partial insurance coverage for chiropractic care who have been in pain and using chiropractic care for years. Over 90% reported high satisfaction with their care, few used narcotics, and avoiding surgery was the most important reason they chose chiropractic care. CONCLUSIONS: Given the prevalence of CLBP and CNP, the need to find effective nonpharmacologic alternatives for chronic pain, and the satisfaction these patients found with their care, further study of these patients is worthwhile.

Acupuncture for the Treatment of Adults with Posttraumatic Stress Disorder: A Systematic Review and Meta-Analysis.

Acupuncture has been suggested as a treatment for posttraumatic stress disorder (PTSD), yet its clinical effects are unclear. This review aims to estimate effects of acupuncture on PTSD symptoms, depressive symptoms, anxiety symptoms, and sleep quality for adults with PTSD. We searched 10 databases in January 2016 to identify eligible randomized controlled trials (RCTs). We performed random effects meta-analyses and examined quality of the body of evidence (QoE) using the GRADE approach to rate confidence in meta-analytic effect estimates. Seven RCTs with 709 participants met inclusion criteria. We identified very low QoE indicating significant differences favoring acupuncture (versus any comparator) at post-intervention on PTSD symptoms (standardized mean difference [SMD] = -0.80, 95% confidence interval [CI] [-1.59, -0.01], 6 RCTs), and low QoE at longer follow-up on PTSD (SMD = -0.46, 95% CI [-0.85, -0.06], 4 RCTs) and depressive symptoms (SMD = -0.56; 95% CI [-0.88, -0.23], 4 RCTs). No significant differences were observed between acupuncture and comparators at post-intervention for depressive symptoms (SMD = -0.58, 95% CI [-1.18, 0.01], 6 RCTs, very low QoE), anxiety symptoms (SMD = -0.82, 95% CI [-2.16, 0.53], 4 RCTs, very low QoE), and sleep quality (SMD = -0.46, 95% CI [-3.95, 3.03], 2 RCTs, low QoE). Safety data (7 RCTs) suggest little risk of serious adverse events, though some participants experienced minor/moderate pain, superficial bleeding, and hematoma at needle insertion sites. To increase confidence in findings, sufficiently powered replication trials are needed that measure all relevant clinical outcomes and dedicate study resources to minimizing participant attrition.

Complementary and Alternative Medicine Services in the Military Health System.

OBJECTIVES: Surveys of military personnel indicate substantial use of complementary and alternative medicine (CAM) that possibly exceeds use in the general U.S. POPULATION: Although military treatment facilities (MTFs) are known to offer CAM, surveys do not indicate where service members receive this care. This study offers a comprehensive system-wide accounting of the types of CAM offered across the military health system (MHS), the conditions for which it is used, and its level of use. These data will help MHS policymakers better support their population's healthcare needs. DESIGN: A census survey of MTFs across the MHS on all CAM use, supplemented where possible by MHS utilization data. OUTCOME MEASURES: Types of CAM offered by each MTF, reasons given for offering CAM, health conditions for which CAM is used, and number of patient visits for each CAM type. RESULTS: Of the 142 MTFs in the MHS, 133 (94%) responded. Of these, 110 (83%) offer at least one type of CAM and 5 more plan to offer CAM services in the future. Larger MTFs (those reporting ≥25,000 beneficiaries enrolled) are both more likely to offer CAM services (p < 0.001) and a larger number (>10) of different types of CAM (p = 0.010) than smaller MTFs. Three-fourths of MTFs offering CAM provide stress management/relaxation therapy, two-thirds provide acupuncture, and at least half provide progressive muscle relaxation, guided imagery, chiropractic, and mindfulness meditation. MTFs most commonly report CAM use for pain and mental health conditions. Acupuncture and chiropractic are most commonly used for pain, and stress management/relaxation therapy and mind-body medicine combinations are most often used for mental health-related conditions. We estimate 76,000 CAM patient encounters per month across the MHS. CONCLUSIONS: The availability of CAM services in the MHS is widespread and is being used to address a range of challenging pain and mental health conditions.

Introducing Value-Based Purchasing into TRICARE Reform.

TRICARE, the health benefits program created for beneficiaries of the U.S. Department of Defense, covers health care provided in military treatment facilities and by civilian providers. Congress is now considering how to update TRICARE, which was first developed in the 1980s drawing on managed care concepts from civilian health plans. This article places TRICARE's current managed care strategy in historical context and describes recent innovations by private insurers and Medicare intended to enhance the value---cost and quality---of the care they purchase for their members. With this movement toward value-based purchasing as background, the authors evaluate two existing proposals for reform and describe an alternative approach that blends the existing proposals.

Mindfulness-based Relapse Prevention for Substance Use Disorders: A Systematic Review and Meta-analysis.

OBJECTIVES: Substance use disorder (SUD) is a prevalent health issue with serious personal and societal consequences. This review aims to estimate the effects and safety of Mindfulness-based Relapse Prevention (MBRP) for SUDs. METHODS: We searched electronic databases for randomized controlled trials evaluating MBRP for adult patients diagnosed with SUDs. Two reviewers independently assessed citations, extracted trial data, and assessed risks of bias. We conducted random-effects meta-analyses and assessed quality of the body of evidence (QoE) using the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: We identified 9 randomized controlled trials comprising 901 participants. We did not detect statistically significant differences between MBRP and comparators on relapse (odds ratio [OR] 0.72, 95% confidence interval [CI] 0.46-1.13, low QoE), frequency of use (standardized mean difference [SMD] 0.02, 95% CI -0.40 to 0.44, low QoE), treatment dropout (OR 0.81, 95% CI 0.40 to 1.62, very low QoE), depressive symptoms (SMD -0.09, 95% CI -0.39 to 0.21, low QoE), anxiety symptoms (SMD -0.32, 95% CI -1.16 to 0.52, very low QoE), and mindfulness (SMD -0.28, 95% CI -0.72 to 0.16, very low QoE). We identified significant differences in favor of MBRP on withdrawal/craving symptoms (SMD -0.13, 95% CI -0.19 to -0.08, I = 0%, low QoE) and negative consequences of substance use (SMD -0.23, 95% CI -0.39 to -0.07, I = 0%, low QoE). We found negligible evidence of adverse events. CONCLUSIONS: We have limited confidence in estimates suggesting MBRP yields small effects on withdrawal/craving and negative consequences versus comparator interventions. We did not detect differences for any other outcome. Future trials should aim to minimize participant attrition to improve confidence in effect estimates.