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BackgroundMultiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients’ lives. ObjectiveThis study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. MethodsIn this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. ResultsRecruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. ConclusionsWith self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. Trial RegistrationClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. International Registered Report Identifier (IRRID)DERR1-10.2196/25175

Drug treatment courts (DTCs) provide substance abuse treatment and case management services to offenders with substance use disorders as an alternative to incarceration. Studies indicate that African Americans less frequently complete DTC programming. The current study analyzed data from the Dane County Drug Treatment Court (n = 573). The study ascertained factors associated with failure to complete treatment among African American DTC participants. Significant factors were unemployment (p = 0.011), previous criminal history (p = 0.013), and, possibly, the presence of a cocaine use disorder (p = 0.064). Treatment plans for DTC participants should incorporate services addressing needs specific to African Americans, who are over-represented in the U.S. correctional system. The current results indicate that employment, prior corrections involvement, and the presence of a cocaine use disorder may be specific issues to consider. (Contains 3 tables and 1 figure.)

Drug treatment courts (DTCs) provide substance abuse treatment and case management services to offenders with substance use disorders as an alternative to incarceration. Studies indicate that African Americans less frequently complete DTC programming. The current study analyzed data from the Dane County Drug Treatment Court (n = 573). The study ascertained factors associated with failure to complete treatment among African American DTC participants. Significant factors were unemployment (p = 0.011), previous criminal history (p = 0.013), and, possibly, the presence of a cocaine use disorder (p = 0.064). Treatment plans for DTC participants should incorporate services addressing needs specific to African Americans, who are over-represented in the U.S. correctional system. The current results indicate that employment, prior corrections involvement, and the presence of a cocaine use disorder may be specific issues to consider. KEYWORDS African Americans, drug court, drug offenders, health disparities, substance abuse

Background: Multiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients' lives. Objective: This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. Methods: In this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. Results: Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. Conclusions: With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. Trial Registration: ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. International Registered Report Identifier (IRRID): DERR1-10.2196/25175 JMIR Res Protoc 2021;10(2):e25175 doi:10.2196/25175 [ABSTRACT FROM AUTHOR]

AbstractBackgroundMethodsResultsConclusionsSocial support appears to play a pivotal role in the prevention, development, and remission of substance use disorders. Previous research suggests that interpersonal relationships moderate treatment outcomes for opioid use disorder based on the nature and quality of the relationship. However, the role of social support in the initiation of prescription opioid misuse (POM) is unclear.In a prospective cohort of 221 patients with traumatic injuries at a level 1 trauma center in Wisconsin, we used multiple linear regression analysis to examine the association between social support and POM at six months post-discharge. Covariates included morphine equivalent daily dose (MEDD) at baseline (24 h pre-discharge), opioid use at six months post-discharge, pre-injury depression and anxiety symptoms, and discharge pain intensity.In models adjusted for relevant demographic and clinical outcomes, social support scores (β = −3.898, p < 0.001; Bonferroni corrected) and depression and anxiety composite scores (β = 2.29, p < 0.023; uncorrected) significantly predict POM scores 6 months post-discharge. When controlling for pre-injury depression and anxiety, patients with positive POM scores had significantly lower baseline social support scores than patients with negative POM (M = 24.31 vs 30.05, p = 0.003).Findings suggest that the perceived presence and quality of social support within an individual’s life may influence the initiation of POM and should be considered in screening for risks related to potential POM. Providers may consider the use of social support when stratifying patients for risk of possible misuse. [ABSTRACT FROM AUTHOR]

The article reflects on prescription drug monitoring programs aimed at preventing drug misuse in the U.S. In New York and California, prescribers are required to track their prescription by creating three copies of prescription sent to drug stores and a central government-authorized location. It states that the programs impede drug access and misidentify high-frequency and high-volume use of prescriptions. It argues that such programs will not totally prevent patients from obtaining medication.

Background: Factors surrounding opioid overdose and naloxone use must be explored from the user perspective in order to more effectively combat the current opioid crisis., Methods: AIDS Resource Center of Wisconsin needle exchange clients were surveyed regarding overdose victim demographics, interventions, experience with naloxone, and overdose outcomes., Results: Most respondents (102/108, 94.4%) reported either experiencing or witnessing an overdose. While naloxone was often used (64/102, 62.7%), other recommended interventions, such as calling 911 (44/102, 43.1%) and rescue breathing (31/102, 30.4%) often were not. Potential legal consequences were cited as a major barrier for contacting emergency medical services (42.3%)., Discussion/conclusion: There appears to be a need for education and/or policy change to facilitate appropriate overdose prevention and use of emergency medical services in the setting of opioid overdose., (Copyright© Wisconsin Medical Society.)

Objective: To examine associations between Pain Catastrophizing Scale (PCS) scores and daily opioid dosage in traumatic injury patients., Design: This was a prospective cohort study with patient assessments at baseline and 1-month following discharge., Setting: Study visits were conducted at a Regional Level I Trauma Center and by phone at follow-up., Patients: Forty-nine injured inpatients completed baseline PCS. A subsample of 23 patients continued to take prescribed opioid medication at 1-month postdischarge and were included in the current analyses., Main Outcome Measured: Associations between baseline PCS and morphine equivalent daily dose (MEDD) at 1-month follow-up., Results: Controlling for baseline MEDD, baseline PCS score was positively associated with MEDD at 1-month postdischarge (β= 0.577 [0.399, 1.535]; p = 0.002; R 2 of PCS = 0.395)., Conclusions: In the current sample of traumatic injury inpatients, findings indicated that a baseline measure of pain catastrophizing predicts ongoing opioid medication use and dosage at 1-month postdischarge from an inpatient trauma unit.

Objective: Sleep problems are common among patients with chronic pain (CP). Information on sleep problems and associated covariates in opioid-treated patients with CP is limited. The aim of this study was to assess the prevalence, characteristics, and risk factors of sleep and daytime sleepiness problems in this specific population., Design: Cross-sectional., Setting: Primary care outpatient clinics., Participants: Eight hundred and seventy six patients with CP treated with long-term opioids., Main Outcome Measures: Prestudy selected questionnaires: six questions from the Medical Outcomes Study Sleep Scale, Pain Inventory Survey, Pain Patient Profile, Substance Dependence Severity Scale, and medication log., Results: Insomnia-type sleep problems and combined sleep and sleepiness problems were reported by 87 percent and 49 percent of the sample, respectively. Logistic regression analysis showed that depression (adjusted OR, aOR 2.8, 95% CI2.1-3.7) and pain severity (aOR 1.4, 95% CI 1.1-1.7) were the strongest independent predictors of sleep problems; only depression severity predicted daytime sleepiness (aOR 1.9, 95% CI 1.6-2.2) or combined sleep/sleepiness problems (aOR 2.2, 95% CI 1.8-2.5). Opioid dose was associated with a slight tendency toward unrefreshing sleep (aOR 1.2, 95% CI 1.0-1.4) and worse sleep maintenance (aOR 1.2, 95% CI 1.0-1.4), while use of long-acting opioids was associated with a trend toward increased napping (aOR 1.3, 95% CI 1.0-1.8)., Conclusions: Sleep and daytime sleepiness problems are common among opioid-treated primary care patients with CP and seem to be related mainly to depression and pain severity. Physicians caring for opioid-treated patients with CP may want to assess them for sleep disorders as a part of routine CP care.

Chronic opioid therapy is commonly prescribed for chronic nonmalignant pain. Few published data describe the adverse effects experienced by patients with chronic nonmalignant pain being treated by primary care physicians. A prevalence study was conducted on a sample of 1,009 patients (889 receiving chronic opioids) being treated by 235 primary care physicians. Standardized questionnaires and medical record reviews were used to assess rates of addiction, pain diagnosis and severity, opioid adverse effects, and mental health. The mean daily dose of opioids was 92 mg using a morphine-equivalent conversion. Side effects included constipation (40 percent), sleeping problems (25 percent), loss of appetite (23 percent), and sexual dysfunction (18 percent), with patients on daily opioids experiencing more side effects than subjects on intermittent medication. The Medical Outcomes Study Mental Health Inventory (MOS-MHI) cognitive functioning scale indicated poorer cognitive function in the overall sample of chronic pain patients as compared to a general clinical sample (delta x 95 percent CI = 9.28, 13.76). However, there were limited differences in MOS scores between chronic pain subjects on daily opioids vs. intermittent opioids vs. no prescription opioids. A regression model suggests that psychological measures and pain severity are more predictive of decrements in cognitive function than specific opioid preparations or daily opioid dose. Physicians should closely monitor patients for adverse effects and adequacy of pain control when using chronic opioid therapy for chronic pain treatment. Psychological health, an important predictor of cognitive dysfunction, is a particularly important measure to actively monitor and manage.