Detecting fraud, waste, and abuse in substance use disorder treatment.
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ABSTRACT:
SUBMITTER: Garrido MM
PROVIDER: S-EPMC9441269 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
Publications
Detecting fraud, waste, and abuse in substance use disorder treatment.
Garrido Melissa M MM Jones David K DK Woodruff Alexander A Strombotne Kiersten K Palani Sivagaminathan S Zahakos Sarah S Adelberg Michael M Pizer Steven D SD Frakt Austin B AB
Health services research 20220819 5
Similar Datasets
Project description:A substantial body of literature has found associations between interpersonal victimization, trauma symptoms, and substance use disorders (SUD) among adolescents. Secondary data analysis was conducted on structured interview data collected by treatment providers as 172 adolescents (ages 12-19) entered outpatient substance abuse treatment. Results indicate high prevalence rates of interpersonal trauma exposure: 71.5% self-reported trauma exposure, specifically direct physical abuse or assault, sexual abuse or assault, and/or witnessing intimate partner violence of a parent. Severity of SUD, as measured by number of DSM-5 criteria endorsed, was not only associated with the number of types of criterion A events for Posttraumatic Stress Disorder but also more self-reported internalizing problems. There was no significant relationship between the severity of SUD and the severity of trauma symptoms at treatment intake, gender, or attention problems. Ongoing assessment of possible trauma symptoms is recommended throughout substance abuse treatment with youth who have reported trauma exposure, as well as continued screening of trauma exposure.
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Project description:This study investigates the proteomic composition of extracellular vesicles (EVs) derived from postmortem prefrontal cortex brain tissues of individuals with substance use disorder (SUD) and matched controls.
2025-05-14 | PXD061471 | Pride
Project description:IntroductionThe majority of patients enrolled in treatment for substance use disorders (SUDs) also use tobacco. Many will continue to use tobacco even during abstinence from other drugs and alcohol, often leading to smoking-related illnesses. Despite this, little research has been conducted to assess the influence of being a smoker on SUD treatment outcomes and changes in smoking during a treatment episode.MethodsIn this secondary analysis, cigarette smoking was evaluated in participants completing outpatient SUD treatment as part of a multi-site study conducted by the National Drug Abuse Treatment Clinical Trials Network. Analyses included the assessment of changes in smoking and nicotine dependence via the Fagerström Test for Nicotine Dependence during the 12-week study among all smokers (aim #1), specifically among those in the experimental treatment group (aim #2), and the moderating effect of being a smoker on treatment outcomes (aim #3).ResultsParticipants generally did not reduce or quit smoking throughout the course of the study. Among a sub-set of participants with higher baseline nicotine dependence scores randomized to the control arm, scores at the end of treatment were lower compared to the experimental arm, though measures of smoking quantity did not appear to decrease. Further, being a smoker was associated with poorer treatment outcomes compared to non-smokers enrolled in the trial.ConclusionsThis study provides evidence that patients enrolled in community-based SUD treatment continue to smoke, even when abstaining from drugs and alcohol. These results add to the growing literature encouraging the implementation of targeted, evidence-based interventions to promote abstinence from tobacco among SUD treatment patients.
| S-EPMC4414703 | biostudies-literature
Project description:Exercise holds potential to reduce substance use, but engaging patients in exercise regimens is challenging. Contingency management (CM) interventions can directly address adherence by targeting initiation and maintenance of exercise behavior. This study evaluated the efficacy of a CM-reinforced exercise intervention as an adjunct to standard outpatient substance use disorder treatment. Participants were 120 patients with substance use disorders who were randomly assigned to standard care with CM for completing exercise goals or CM for completing general nonexercise goals weekly for a 4-month treatment period. Urine samples were tested for evidence of illicit substance use up to twice a week during treatment and at follow-ups through month 12. Results found that the CM-exercise condition demonstrated during-treatment improvements on several physical activity and relevant psychosocial functioning indices (e.g., self-efficacy for exercise). The CM-exercise condition had no advantage relative to the CM-general condition in decreasing substance use. Overall, this study adds to a small body of well-powered trials assessing effects of exercise interventions as adjunct treatment for substance use disorders and finds no benefit over an alternate CM approach in terms of drug abstinence. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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Project description:Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world, recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD
2020-04-01 | GSE112652 | GEO
Project description:BackgroundThe National Drug Abuse Treatment Clinical Trials Network (CTN) called for its national nodes to promote the translation of evidence-based interventions from substance use disorder (SUD) research into clinical practices. This collaborative demonstration project engaged CTN-affiliated practice-based research networks (PBRNs) in research that describes aspects of opioid prescribing in primary care.MethodsSix PBRNs queried electronic health records from a convenience sample of 134 practices (84 participants) to identify the percent of adult patients with an office visit who were prescribed an opioid medication from October 1, 2015, to September 30, 2016, and, of those, the percent also prescribed a sedative in that year. Seven PBRNs sent an e-mail survey to a convenience sample of 108 practices (58 participants) about their opioid management policies and procedures during the project year.ResultsOf 561,017 adult patients with a visit to one of the 84 clinics in the project year, 22.9% (PBRN range 3.1%-25.4%) were prescribed opioid medications, and 52.1% (PBRN range 8.5%-60.6%) of those were prescribed a sedative in the same year. Of the 58 practices returning a survey (45.3% response rate), 98.1% had formal written treatment agreements for chronic opioid therapy, 68.5% had written opioid prescribing policies, and 43.4% provided reports to providers with feedback on opioid management. Only 24.1% were providing buprenorphine for OUD.ConclusionCTN-affiliated PBRNs demonstrated their ability to collaborate on a project related to opioid management; results highlight the important role for PBRNs in OUD treatment, research, and the need for interventions and additional policies addressing opioid prescribing in primary care practice.
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Project description:ObjectiveTo provide evidence on the effects of expansions to private and public insurance programs on adolescent specialty substance use disorder (SUD) treatment use.Data source/study settingThe Treatment Episodes Data Set (TEDS), 1996 to 2017.Study designA quasi-experimental difference-in-differences design using observational data.Data collectionThe TEDS provides administrative data on admissions to specialty SUD treatment.Principal findingsExpansions of laws that compel private insurers to cover SUD treatment services at parity with general health care increase adolescent admissions by 26% (P < .05). These increases are driven by nonintensive outpatient admissions, the most common treatment episodes, which rise by 30% (P < .05) postparity law. In contrast, increases in income eligibility for public insurance targeting those 6-18 years old are not statistically associated with SUD treatment.ConclusionsPrivate insurance expansions allow more adolescents to receive SUD treatment, while public insurance income eligibility expansions do not appear to influence adolescent SUD treatment.
| S-EPMC7969204 | biostudies-literature
Project description:Ex vivo large-scale proteomic analysis using LC-MS/MS in postmortem brains of patients with substance use disorder and controls. Brain tissue was collected postmortem after consent from the next of kin. As part of the clinical information, medical records were obtained and a detailed psychological autopsy was performed on all participants by interviewing the next-of-kin. Information regarding the psychiatric clinical phenotypes (evidence of depression, mania, and psychosis) stressful life events, age of drug use onset, types of drugs used, smoking and drinking history, and any co-morbidities, was obtained. A diagnosis of substance use disorder was confirmed based on the psychological autopsy, detailed medical records, and review of all relevant case information by three psychiatrists at a consensus meeting. The cause of death was obtained from the medical examiner’s report and toxicological findings after death.
2021-09-10 | PXD025269 | Pride
Project description:IntroductionThis study aims to assess the trends in the number and characteristics of substance use disorder (SUD) treatment facilities within the county of residence of adults aged 50+ years over time.MethodsUsing retrospective longitudinal data from the 1992-2018 Health and Retirement Study merged with the county-level data on all licensed treatment facilities in the country, linear mixed models were estimated to calculate geographic accessibility to SUD treatment, adjusted for person-level demographics, state-level controls, and calendar year-fixed effects. Analysis was conducted in 2022.ResultsOverall, older adults experienced a decline in the average number of SUD treatment facilities within their counties of residence from 4.80 per 100,000 residents (95% CI=4.69, 4.92) in 1992 to 4.50 (95% CI=4.35, 4.64) in 2018. However, the number accepting Medicare increased from 0.26 (95% CI=0.21, 0.30) in 1992 to 1.88 (95% CI=1.80, 1.96) facilities per 100,000 (42% of facilities); Medicaid increased from 0.20 (95% CI=0.13, 0.26) in 1992 to 3.50 (95% CI=3.39, 3.62) facilities per 100,000 (78% of facilities) in 2018. Older adults living in more rural areas experienced the most growth in SUD treatment facilities per capita in their counties but with less significant growth in facilities offering medication for opioid use disorder than those living in more urban areas.ConclusionsDespite increases in the number of SUD treatment facilities in rural areas, there has been less growth in nearby facilities offering evidence-based medication treatment for opioid use disorder.
| S-EPMC10524906 | biostudies-literature
Project description:BACKGROUND:Fraud, Waste, and Abuse (FWA) detection is a significant yet challenging problem in the health insurance industry. An essential step in FWA detection is to check whether the medication is clinically reasonable with respect to the diagnosis. Currently, human experts with sufficient medical knowledge are required to perform this task. To reduce the cost, insurance inspectors tend to build an intelligent system to detect suspicious claims with inappropriate diagnoses/medications automatically. OBJECTIVE:The aim of this study was to develop an automated method for making use of a medical knowledge graph to identify clinically suspected claims for FWA detection. METHODS:First, we identified the medical knowledge that is required to assess the clinical rationality of the claims. We then searched for data sources that contain information to build such knowledge. In this study, we focused on Chinese medical knowledge. Second, we constructed a medical knowledge graph using unstructured knowledge. We used a deep learning-based method to extract the entities and relationships from the knowledge sources and developed a multilevel similarity matching approach to conduct the entity linking. To guarantee the quality of the medical knowledge graph, we involved human experts to review the entity and relationships with lower confidence. These reviewed results could be used to further improve the machine-learning models. Finally, we developed the rules to identify the suspected claims by reasoning according to the medical knowledge graph. RESULTS:We collected 185,796 drug labels from the China Food and Drug Administration, 3390 types of disease information from medical textbooks (eg, symptoms, diagnosis, treatment, and prognosis), and information from 5272 examinations as the knowledge sources. The final medical knowledge graph includes 1,616,549 nodes and 5,963,444 edges. We designed three knowledge graph reasoning rules to identify three kinds of inappropriate diagnosis/medications. The experimental results showed that the medical knowledge graph helps to detect 70% of the suspected claims. CONCLUSIONS:The medical knowledge graph-based method successfully identified suspected cases of FWA (such as fraud diagnosis, excess prescription, and irrational prescription) from the claim documents, which helped to improve the efficiency of claim processing.
| S-EPMC7413281 | biostudies-literature