| Coverage Policy Manual | |
| Policy #: | 2020018 |
| Category: | Medicine |
| Initiated: | July 2020 |
| Last Review: | August 2023 |
|
|
|
|||||||||||
| Digital Health Therapies for Substance Abuse | |
|
|
|
| Description: |
The World Health Organization defines substance use disorder as “the harmful or hazardous use of psychoactive substances, including alcohol and illicit drugs”, which include alcohol, cocaine, marijuana, stimulants, benzodiazepines and opiates. The American Psychiatric Association, in the Diagnostic and Statistical Manual of Mental Disorders, details 11 problematic patterns of use that lead to clinically significant impairment or distress. Mild substance use disorder (SUD) is defined as meeting 2 to 3 criteria, moderate as 4 to 5 criteria, and severe as 6 or more criteria.
Treatments for substance use disorder include behavioral counseling, skills training, medication, treatment for withdrawal symptoms, treatment for co-occurring mental health issues, and long-term follow-up to prevent relapse. For patients with primary opioid use disorder (OUD), medication assisted treatment is the most common approach. U.S. Food and Drug Administration (FDA)-approved drugs for opioid use treatment include a full opioid agonist (methadone), a partial opioid agonist (buprenorphine), and an opioid antagonist (naltrexone). These are used to suppress withdrawal symptoms and reduce cravings and may be used in combination with counseling and behavioral therapies.
One common psychosocial intervention is cognitive-behavioral therapy (CBT). CBT is an established therapy based on social learning theory that addresses a patient’s thinking and behavior. CBT has proven positive effects for the treatment of SUD (McHugh, 2010). There are two main goals of CBT: first, recognize thoughts and behaviors that are associated with substance abuse, and second, expand the repertoire of effective coping responses. Specific goals for SUD and OUD include a better understanding of risk factors for use, more accurate attributions of cause and effect, increased belief in the ability to address problems, and coping skills. Specific skills may include motivation, drink/drug refusal skills, communication, coping with anger and depression, dealing with interpersonal problems, and managing stress.
The community reinforcement approach (CRA) is a form of CBT that has a goal of making abstinence more rewarding than continued use. CRA increases non-drug reinforcement by teaching skills and encouraging behaviors that help improve employment status, family/social relations and recreational activities. CRA was originally developed for alcohol dependence and cocaine use and has been shown to be more effective than usual care in reducing the number of substance use days.
Contingency management may also be a component of addiction treatment. Contingency management, also known as motivational incentives, provides immediate positive reinforcement to encourage abstinence and attendance. Positive reinforcement may range from a verbal/text acknowledgement of completion of a task to monetary payment for drug-negative urine specimens. Contingency management is based on the principles of operant conditioning as formulated by B.F. Skinner, which posits that rewarding a behavior will increase the frequency of that behavior. Contingency management is typically used to augment a psychosocial treatment such as CRA.
The combination of CRA plus contingency management was shown in a 2018 network meta-analysis of 50 RCTs to be the most efficacious and accepted intervention among 12 structured psychosocial interventions, including contingency management alone, in individuals with cocaine or amphetamine addiction (De Crescenzo, 2018). Positive reinforcement with voucher draws (eg, from a fishbowl) of variable worth that range from a congratulatory message to an occasional high dollar value are as effective as constant monetary vouchers. Studies conducted by the National Drug Abuse Treatment Clinical Trials Network have shown that intermittent reinforcement with incentives totaling $250 to $300 over 8 to 12 weeks both increases retention in a treatment program and reduces stimulant drug use during treatment (Stitzer, 2010)
Software as a Medical Device
The International Medical Device Regulators Forum, a consortium of medical device regulators from around the world which is led by the FDA, distinguishes between 1) software in a medical device and 2) software as a medical device (SaMD). The Forum defines SaMD as "software that is intended to be used for one or more medical purposes that perform those purposes without being part of a hardware medical device" (International Medical Device Regulators Forum, 2013).
FDA's Center for Devices and Radiological Health is taking a risk-based approach to regulating SaMD. Medical software that "supports administrative functions, encourages a healthy lifestyle, serves as electronic patient records, assists in displaying or storing data, or provides limited clinical decision support, is no longer considered to be and regulated as a medical device" (FDA, 2020).
Regulatory review will focus on mobile medical apps that present a higher risk to patients.
The agency has launched a software pre-cert pilot program for SaMD that entered its test phase in 2019. Key features of the regulatory model include the approval of manufacturers prior to evaluation of a product, which is based on a standardized "Excellence Appraisal" of an organization, and its commitment to monitor product performance after introduction to the U.S. market. Criteria include excelling in software design, development, and validation. Companies that obtain pre-certification participate in a streamlined pre-market review of the SaMD. Pre-certified organizations might also be able to market lower-risk devices without additional review. In 2017, FDA selected 9 companies to participate in the pilot program, including Pear Therapeutics.
Regulatory Status
In 2017, reSET® (Pear Therapeutics), received de novo marketing clearance from the FDA to provide CBT as an adjunct to contingency management, for patients with substance use disorder who are enrolled in outpatient treatment under the supervision of a clinician (DEN160018). This is the first prescription digital therapeutic to be approved by the FDA. reSET is indicated as a 12-week (90 days) prescription-only treatment intended to increase abstinence from a patient's substances of abuse during treatment and increase retention in the outpatient treatment. FDA product code: PWE
In 2018, reSET-O® (Pear Therapeutics) was cleared for marketing by the FDA through the 510(k) pathway as a prescription-only digital therapeutic to “increase retention of patients with opioid use disorder (OUD) in outpatient treatment by providing cognitive behavioral therapy, as an adjunct to outpatient treatment that includes transmucosal buprenorphine and contingency management” K173681). FDA determined that this device was substantially equivalent to existing devices. The predicate device was reSET®.
Vorvida® and Modia® (Orexo) provide support for individuals with problematic drinking and OUD. These digital technologies have not received marketing clearance by U.S. Food and Drug Administration and are not reviewed here. They are currently available in the U.S. through the Enforcement Policy for Digital Health Devices for Treating Psychiatric Disorders During COVID-19 (FDA, 2020).
|
|
|
|
|
Policy/ Coverage: |
Effective July 2021
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Digital health therapies for patients with substance use disorders do not meet primary coverage criteria that there be scientific evidence of effectiveness.
For members with contracts without primary coverage criteria, digital health therapies for patients with substance use disorders are considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
Effective Prior to July 2021
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Prescription digital therapeutics for patients with substance use disorder does not meet primary coverage criteria that there be scientific evidence of effectiveness.
For members with contracts without primary coverage criteria, prescription digital therapeutics for patients with substance use disorder is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
|
|
|
|
| Rationale: |
This evidence review was created in July 2020 with a search of the PubMed database through May 6, 2020.
Prescription Digital Therapeutics for Substance Use Disorder
Substance abuse is a serious health problem in the U.S. A 2018 survey from the Substance Abuse and Mental Health Services Administration found that 21.2 million people age 12 or older in the U.S., or 7.8 percent of the U.S. population, needed substance use treatment (US DHHS, 2020). The most common substances reported in the survey are alcohol, followed by tobacco and marijuana. Illicit drug use and prescription drug misuse occur in a lower percentage of the population.
Significant barriers to treatment exist for patients with substance use disorder (SUD) and opioid use disorder (OUD). There are an insufficient number of clinicians who are trained for substance abuse treatment, particularly in rural areas, and access to outpatient programs may be difficult and time consuming. Patients typically present to their primary care provider, who may not have sufficient time or training to treat patients with substance abuse. In addition, the stigma of substance abuse may prevent individuals from seeking treatment. Digital technologies could potentially increase access to specialty care for patients who may not otherwise be able to attend a treatment program. Digital technologies might also reduce the need for attendance in a clinic for patients who avoid treatment due to stigma or other factors.
A computer-delivered cognitive-behavioral therapy (CBT) program named CBT4CBT (Computer-Based Training for Cognitive Behavioral Therapy) has been developed to provide therapy for patients with substance abuse. The program includes 7 core CBT skills delivered by on-screen narration, graphic animation, quizzes, and interactive exercises. In a 2018 randomized controlled trial (RCT), both clinician and computer delivery of CBT reduced the frequency of substance use more than treatment as usual (TAU) (Kiluk, 2018). In addition, patients who received the computer-based CBT with minimal monitoring had the best treatment retention, learning of CBT concepts, and 6 month outcomes compared to either clinician-delivered CBT or TAU. A computer-based community reinforcement approach (CRA) plus vouchers was reported in a 2008 study to lead to similar levels of abstinence as patients who received clinician-guided CRA plus vouchers (Bickel, 2008). These results suggest that computerized CRA (CCRA) could potentially substitute for clinician-guided therapy and increase access to treatment.
In 2017 and 2018, the first prescription mobile apps (ie, reSET and reSET-O) were cleared for marketing by the U.S. Food and Drug Administration (FDA). These have the potential to increase access to substance abuse treatments in patients who have SUD or OUD. These 2 apps are intended to provide CCRA as an addition to traditional therapy in the context of an outpatient program.
Two pivotal RCTs for the prescription digital apps for SUD (reset) and OUD(reset-O) were identified. The technology was developed by the National Institute of Drug Abuse-funded Center for Technology and Behavioral Health as the Therapeutic Education System (TES), which subsequently submitted to the FDA for a mobile platform by Pear Therapeutics.
Campbell et al reported the pivotal multicenter trial for reSET, in which patients with SUD or OUD completed 20 to 30 min multimedia modules on a desktop while in the clinic or at home (Campbell, 2014; FDA, 2016). The active treatment was the TES, which combined CCRA plus contingency management, and was compared to TAU (therapy alone) at 10 community-based outpatient treatment programs as part of the National Drug Abuse Clinical Trials Network. Clinicians were able to access reports on computer activity and discussed module completion in the individual therapy sessions. Contingency management consisted of random selection of vouchers, which ranged from a congratulatory message to $100 cash, for module completion and negative urine drug results. The mean dollar earned was $277 (SD $226) over the 12 weeks. Although the study was intended to replace some of the hours of therapy, the TES group received the same number of therapy session as the control group, so the combined program was effectively in addition to counseling alone.
The co-primary outcomes were abstinence from drug/heavy alcohol use in the last 4 weeks of treatment and retention in the treatment program. In 2004, the analysis by Campbell et al, TES reduced drop-out from the treatment program (hazard ratio=.72 [95% CI: 0.57 to 0.92], P=.010), and the odds of achieving abstinence was 1.62 fold greater in the group with CCRA and contingency management group (p=.010) (Campbell, 2014). However, the beneficial effect of TES was observed only in patients who were not abstinent at baseline. For patients who were abstinent at baseline, TES did not increase abstinence, and at 3 and 6 month follow-up, the effect of TES was no longer significant. Subsequent analyses of the trial found that TES was not associated with improvements in social functioning compared to standard outpatient care (Marino, 2019).
In the FDA analyses of the tria;, results were analyzed for the entire cohort and for cohorts that excluded patients who reported opioid use (FDA, 2016). Abstinence during weeks 9-12 and total abstinence with CCRA plus contingency management was significantly greater in the cohort as a whole and more so in the analyses that excluded primary opioid users. For example, abstinence during weeks 9-12 was 40.3% in the SUD subgroup who received CCRA + vouchers compared to 17.6% in the group who received only therapy (P<.001). Total abstinence, defined as the number of half weeks with a negative urine drug test, was 11.9 half weeks in the SUD subgroup who received the experimental treatment and 8.8 half weeks in controls (p=.003).
In the pivotal study reported by Christensen et al, CCRA was added to TAU in patients who had opioids as the primary substance of abuse (Christensen, 2014; FDA, 2019). TAU in this second trial included clinic visits 3 times per week with a reward for a negative urine drug screen (maximum of $997.50), sublingual buprenorphine/naloxone, and a clinician visit every 2 weeks. Patients who did not show up for any of the thrice weekly clinic visits were considered to have a positive drug screen, and were considered drop-outs if they missed 3 visits in a row. The primary outcomes were the longest continuous abstinence and total abstinence. The study was powered to detect a 3 week difference between groups in mean weeks of continuous abstinence. In the 84 day treatment program there were 9.7 more days of abstinence in the CCRA group (67.1 days) than in the control group (57.4 days, P=.01), but the trial did not meet one of the primary outcomes of a significant difference between the two groups in the longest abstinence (5.5 days P=.214). The group using the computerized therapy had an increase in medication Addiction Severity Index scores (P=.04) , but did not show a significant improvement on the overall Addiction Severity Index (P>.16). The data on abstinence and Addiction Severity Index was not reported in the 510(K) Summary for the U.S. Food and Drug Administration (FDA, 2019).
Both trials reported a significant increase in retention during the 12 week programs. The SUD subgroup had a 23.8% drop out rate compared to 36.8% in the control group (P=.004). The addition of CCRA to TAU in patients with OUD also increased retention, with a hazard ratio for dropping out of treatment of 0.47 (0.26 to 0.85).
Both trials had a number of limitations in relevance and in design and conduct that preclude determination of the effect of the intervention on relevant health outcomes. These limitations are described below.
Given all of these limitations, further study in well designed trials is needed to determine the effects of the technology on addiction.
Practice Guidelines and Position Statements
The 2018 Principles of Drug Addiction and Treatment from the National Institute on Drug Abuse describes evidence-based approaches to drug addiction treatment (National Institute on Drug Abuse, 2018). Behavioral therapies include cognitive-behavioral therapy (alcohol, marijuana, cocaine, methamphetamine, nicotine), contingency management (alcohol, stimulants, opioids, marijuana, nicotine), community reinforcement approach plus vouchers (alcohol, cocaine, opioids), motivational enhancement therapy (alcohol, marijuana, nicotine), the matrix model (stimulants), 12-step facilitation therapy (alcohol, stimulants, opiates) and family behavior therapy.
Ongoing and Unpublished Clinical Trials
Some currently unpublished trials that might influence this review are listed below.
NCT04129580a A Randomized Clinical Trial of Comprehensive Cognitive Behavioral Therapy (CBT) Via
reSET-O for a Hub and Spoke Medication Assisted Treatment (MAT) System of Care
Planned enrollment: 200 Completion Date: September 2021
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through June 2021. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Marichich et al performed an industry-funded analysis of reSET-O data from 3,144 patients with OUD who had filled a 12 week prescription of the software (Marichich, 2021). Participants were instructed to complete at least 4 modules per week with a total possible of 31 core modules and 36 supplemental modules. Analysis of the software's data showed that about half of the patients completed all 31 modules, 66% completed half of the modules, and 74% of patients actively participated through 12 weeks. Use decreased from 100% in the first week to 55% of individuals completing 4 modules in week 12. (Retention in the pivotal study by Christensen was 80% for the software compared to 64% for contingency management alone) (Christensen, 2014; U.S. FDA, 2019). Abstinence during the last 4 weeks of treatment was determined by either urine drug screening or self-report recorded on reSET-O. With a conservative estimate of missing data considered to be a positive drug screen, 66% of patients were estimated to be abstinent during the last 4 weeks of the prescription. For patients who completed 3 to 5 modules in the first week, abstinence in the final 4 weeks ranged from 83% to 89%. A limitation of this study is that patients who completed more modules in the first week may have been more motivated to remain abstinent, and cause and effect cannot be determined from this non-comparative observational study.
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through June 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Maricich et al published a post hoc secondary analysis of data from the trial, excluding participants with OUD (n=399 individuals with SUD related to alcohol, cannabis, cocaine, or other stimulants). Abstinence was significantly higher than treatment as usual in the reSET group (40.3% vs. 17.6%; p<.001) as was retention in therapy (76.2% vs. 63.2%; p=.004) (Maricich, 2022).
In a retrospective analyses of data from the pivotal trial, Luderer et al found an association between engagement with the app (ie, total number of modules completed) and abstinence during weeks 9 to 12 (Luderer, 2022).
Marichich et al also published data from a subset of 643 individuals from the above cohort who completed the 12-week prescription and were then prescribed a second 12-week refill prescription (Marichich, 2021). At the end of the second prescription period, 86.0% of the cohort were abstinent and 91.4% were retained in treatment through 24 weeks.
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through July 2023. No new literature was identified that would prompt a change in the coverage statement.
|
|
|
|
| CPT/HCPCS: | |
|
|
|
| References: |
Bickel WK, Marsch LA, Buchhalter AR, et al.(2008) Computerized behavior therapy for opioid-dependent outpatients: a randomized controlled trial. Exp Clin Psychopharmacol. Apr 2008; 16(2): 132-43. PMID 18489017 Campbell AN, Nunes EV, Matthews AG, et al.(2014) Internet-delivered treatment for substance abuse: a multisite randomized controlled trial. Am J Psychiatry. Jun 2014; 171(6): 683-90. PMID 24700332 Christensen DR, Landes RD, Jackson L, et al.(2014) Adding an Internet-delivered treatment to an efficacious treatment package for opioid dependence. J Consult Clin Psychol. Dec 2014; 82(6): 964-72. PMID 25090043 DATOS(2008) Drug Abuse Treatment Outcome Studies (DATOS) Treatment retention findings. 2008 http://www.datos.org/adults/adultsretention. html. Accessed May 28, 2020 De Crescenzo F, Ciabattini M, D'Alo GL, et al.(2018) Comparative efficacy and acceptability of psychosocial interventions for individuals with cocaine and amphetamine addiction: A systematic review and network meta-analysis. PLoS Med. Dec 2018; 15(12):e1002715. PMID 30586362 Denis CM, Cacciola JS, Alterman AI.(2013) Addiction Severity Index (ASI) summary scores: comparison of the Recent Status Scores of the ASI-6 and the Composite Scores of the ASI-5. J Subst Abuse Treat. Nov-Dec 2013; 45(5): 444-50. PMID 23886822 Dennis BB, Sanger N, Bawor M, et al.(2020) A call for consensus in defining efficacy in clinical trials for opioid addiction: combined results from a systematic review and qualitative study in patients receiving pharmacological assisted therapy for opioid use disorder. Trials. Jan 06 2020; 21(1): 30. PMID 31907000 International Medical Device Regulators Forum.(2013) Software as a Medical Device (SaMD): Key Definitions. 2013. http://www.imdrf.org/docs/imdrf/final/technical/imdrf-tech-131209-samd-key-definitions-140901.pdf Accessed May 5, 2020. Kiluk BD, Nich C, Buck MB, et al.(2018) Randomized Clinical Trial of Computerized and Clinician-Delivered CBT in Comparison With Standard Outpatient Treatment for Substance Use Disorders: Primary Within-Treatment and Follow-Up Outcomes. Am J Psychiatry. Sep 01 2018; 175(9): 853-863. PMID 29792052 Luderer HF, Campbell ANC, Nunes EV, et al.(2022) Engagement patterns with a digital therapeutic for substance use disorders: Correlations with abstinence outcomes. J Subst Abuse Treat. Jan 2022; 132: 108585. PMID 34366201 Maricich YA, Gerwien R, Kuo A, et al.(2021) Real-world use and clinical outcomes after 24 weeks of treatment with a prescription digital therapeutic for opioid use disorder. Hosp Pract (1995). Dec 2021; 49(5): 348-355. PMID 34461801 Maricich YA, Nunes EV, Campbell ANC, et al.(2022) Safety and efficacy of a digital therapeutic for substance use disorder: Secondary analysis of data from a NIDA clinical trials network study. Subst Abus. 2022; 43(1): 937-942. PMID 35420979 Maricich YA, Xiong X, Gerwien R, et al.(2021) Real-world evidence for a prescription digital therapeutic to treat opioid use disorder. Curr Med Res Opin. Feb 2021; 37(2): 175-183. PMID 33140981 Marino LA, Campbell ANC, Pavlicova M, et al.(2019) Social functioning outcomes among individuals with substance use disorders receiving internet-delivered community reinforcement approach. Subst Use Misuse. 2019; 54(7): 1067-1074. PMID 30849925 Marsden J, Gossop M, Stewart D, et al.(1998) The Maudsley Addiction Profile (MAP): a brief instrument for assessing treatment outcome. Addiction. Dec 1998; 93(12): 1857-67. PMID 9926574 McHugh RK, Hearon BA, Otto MW.(2010) Cognitive behavioral therapy for substance use disorders. Psychiatr Clin North Am. Sep 2010;33(3): 511-25. PMID 20599130 National Institute on Drug Abuse.(2018) Principles of Drug Addiction Treatment: A Research-Based Guide (Third Edition). 2018. https://www.drugabuse.gov/publications/principles-drug-addiction-treatment-research-based-guide-third-edition/principleseffective-treatment. Accessed May 28, 2020 Stitzer ML, Petry NM, Peirce J.(2010) Motivational incentives research in the National Drug Abuse Treatment Clinical Trials Network. J Subst Abuse Treat. Jun 2010; 38 Suppl 1: S61-9. PMID 20307797 U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration.(2020) Data and Dissemination. https://www.samhsa.gov/data. Accessed May 5, 2020 U.S. Food and Drug Administration (FDA).(2020) Enforcement policy for digital health devices for treating psychiatric disorders during the coronovirus disease 2019 (COVID-19) public health emergency. Guidance for industry and Food and Drug Administration Staff. April 2020. https://www.fda.gov/media/136939/download. Accessed June 9, 2022. U.S. Food and Drug Administration.(2019) 510K Summary. 2019. https://www.accessdata.fda.gov/cdrh_docs/pdf17/K173681.pdf Accessed June 7, 2021 U.S. Food and Drug Administration.(2020) De Novo Classification Request for reSET. https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN160018.pdf. May 16, 2016. Accessed May 5, 2020. U.S. Food and Drug Administration.(2020) Digital health innovation action plan. https://www.fda.gov/media/106331/download |
|
|
|
|
Group specific policy will supersede this policy when applicable. This policy does not apply to the Wal-Mart Associates Group Health Plan participants or to the Tyson Group Health Plan participants.
CPT Codes Copyright © 2024 American Medical Association. |
|